Monday, May 25, 2026

Age differences in factors associated with pulmonary tuberculosis [TBN 078]

1. Who

  • Population: 715,394 Indonesian participants aged ≥16 years from RISKESDAS 2018.
  • Age groups:
    • 16–45 years: 469,517 participants
    • 46–64 years: 191,732 participants
    • ≥65 years: 54,145 participants
  • Key conditions assessed: Pulmonary tuberculosis (PTB), diabetes mellitus (DM), heart disease, smoking status, BMI, education, employment, sex, residence, and family size.

2. What

  • Study focus: Prevalence of PTB and factors associated with PTB across different age groups in Indonesia.
  • PTB prevalence:
    • 16–45 years: 3.5‰
    • 46–64 years: 6.8‰
    • ≥65 years: 9.6‰
  • Independent factors associated with PTB:
    • Age 16–45: education ≤6 years, former smoking, underweight, DM, heart disease.
    • Age 46–64: male sex, large family size, education ≤6 years, unemployment, former smoking, underweight, DM, heart disease.
    • Age ≥65: male sex, education ≤6 years, former smoking, underweight, DM, heart disease.
  • Strongest associations:
    • DM in age 16–45: aOR 6.23, 95% CI 4.37–8.89.
    • Underweight in age 46–64: aOR 3.64, 95% CI 3.02–4.39.
    • Underweight in age ≥65: aOR 2.72, 95% CI 2.09–3.55.
  • Interaction findings: Associations between PTB and former smoking, DM, and heart disease differed significantly by age group.

3. When

  • Survey year: 2018.
  • PTB definition timeframe: Diagnosed by a healthcare professional within the past year.
  • Survey frequency: RISKESDAS is conducted every five years.

4. Where

  • Location: Indonesia.
  • Coverage: All 34 provinces, 416 districts, and 98 cities.
  • Data source: Nationally representative RISKESDAS 2018 survey.

5. Why

  • Rationale: TB-DM comorbidity is linked to treatment failure, recurrence, and drug resistance.
  • Knowledge gap: Indonesia’s national TB program does not currently integrate age-specific grouping in diagnosis and treatment strategies.
  • Objective: To investigate PTB prevalence and age-specific factors associated with PTB.

6. How

  • Study design: Cross-sectional analysis of nationally representative survey data.
  • Level of evidence: Observational, cross-sectional evidence.
  • Sampling: Two-stage sampling using probability proportional to size and systematic household selection.
  • Data collection: Face-to-face interviews, structured questionnaires, visual aids, anthropometric measurements, and blood glucose testing.
  • Statistical methods:
    • Rao-Scott Chi-square tests
    • Univariable and multivariable binary logistic regression
    • Adjusted odds ratios with 95% confidence intervals
    • Interaction analysis by age group
Source: Susanti EW, Wiratama BS, Hsieh FI. Age differences in factors associated with pulmonary tuberculosis: a cross-sectional study of Indonesian Basic Health Research (RISKESDAS) 2018. Infectious Diseases. 2026 Feb 1;58(2):221-32. https://benangmerah.net/record/97/age-differences-in

Association between iron deficiency anemia and the risk of new-onset TB infection [TBN 077]

1. Who

  • Population: Adult patients aged ≥18 years from the TriNetX Research Network.
  • Sample size:
    • Initial cohorts: 177,846 patients with iron deficiency anemia (IDA) and 309,662 control patients with dermatitis.
    • Final matched cohort after 1:1 propensity score matching: 160,928 patients.
  • Demographics:
    • Mean age after matching: ~51 years.
    • Male proportion: ~27–29%.
    • Predominantly White participants (46–48%), with smaller Black/African American (~12–15%) and Asian (~5%) populations.
  • Inclusion criteria:
    • Adults with IDA (ICD-10 D50) and at least one additional IDA diagnosis within 2 years.
  • Exclusion criteria:
    • Prior tuberculosis (TB), latent TB, TB exposure, anti-TB medication use, HIV infection, organ transplantation, immunosuppressive therapy, glucocorticoid use, antineoplastic use, and other anemias.
  • Subgroups analyzed:
    • Sex (male vs female).
    • Age (18–50 years vs >50 years).

2. What

  • Research focus:
    To determine whether iron deficiency anemia is associated with an increased risk of incident tuberculosis, including pulmonary and extrapulmonary TB.
  • Primary outcome:
    Incident tuberculosis within 5 years after index diagnosis.
  • Secondary outcomes:
    • TB incidence during years 5–10.
    • Positive control outcomes: pneumonia and reactive thrombocytosis.
  • Key findings:
    • IDA was associated with higher TB risk within 5 years:
      • HR 1.48 (95% CI 1.10–2.00, p=0.010).
    • No significant association during 5–10 years:
      • HR 1.17 (95% CI 0.63–2.17, p=0.627).
    • Pulmonary TB:
      • HR 1.71 (95% CI 1.30–2.24, p<0.001).
    • Extrapulmonary TB:
      • HR 3.01 (95% CI 1.73–5.22, p<0.001).
    • Stronger associations were observed in:
      • Men: HR 2.06.
      • Younger adults (18–50 years): HR 2.42.
    • Positive controls confirmed expected associations:
      • Pneumonia HR 1.87.
      • Reactive thrombocytosis HR 3.68.
  • Authors’ conclusions:
    IDA was independently associated with increased short-term TB risk, particularly extrapulmonary TB, suggesting that iron metabolism and nutritional status may influence susceptibility to mycobacterial infection.
  • Practical implications:
    Patients with IDA may warrant closer monitoring for TB symptoms, especially in high-risk settings or populations.

3. When

  • Study period: January 1, 2010 to December 31, 2020.
  • Follow-up duration:
    • Primary analysis: within 5 years after index date.
    • Secondary analysis: 5–10 years post-index.

4. Where

  • Data source: TriNetX Research Network.
  • Geographic coverage: Multinational healthcare organizations from:
    • United States
    • Australia
    • Belgium
    • Brazil
    • Bulgaria
    • Estonia
    • France
    • Germany
    • Ghana
    • Israel
    • Italy
    • Japan
    • Lithuania
    • Malaysia
    • Poland
    • Singapore
    • Spain
    • Taiwan
    • UAE
    • United Kingdom
    • and others.
  • Institutional oversight:
    Approved by Chi Mei Medical Center IRB (Taiwan).

5. Why

  • Rationale:
    Prior evidence linking IDA with TB susceptibility was limited by small sample sizes, restricted populations, and insufficient subtype analyses.
  • Knowledge gap addressed:
    Whether IDA independently increases TB risk across diverse multinational populations and whether associations differ by TB subtype.
  • Objective:
    To evaluate the association between IDA and incident TB using a large multinational electronic health record database with robust matching and subtype analysis.

6. How

  • Study design:
    Retrospective matched cohort study (observational).
  • Data source:
    Federated electronic health records from TriNetX.
  • Comparator group:
    Patients with unspecified dermatitis (ICD-10 L30).
  • Matching method:
    1:1 propensity score matching using greedy nearest-neighbor algorithm.
  • Covariates included:
    • Age
    • Sex
    • Race
    • BMI
    • Comorbidities
    • Laboratory values
    • Diabetes medications
  • Statistical analyses:
    • Kaplan–Meier survival analysis
    • Cox proportional hazards regression
    • Schoenfeld residual testing
    • Subgroup analyses
  • Positive controls:
    Pneumonia and reactive thrombocytosis.
  • Major limitations:
    • Residual confounding cannot be excluded.
    • Lack of race-stratified subgroup analysis due to low event counts.
    • Reliance on ICD-10 coding may introduce misclassification.
    • Observational design cannot establish causality.
    • TB incidence remained relatively low despite large sample size.
  • Level of evidence:
    Moderate observational evidence (retrospective propensity-matched cohort study).
  • Funding/conflict of interest:
    Not specified in the provided text.
Source: Chen IW, Chang LC, Chang YJ, Lai YC, Hung KC. Association between iron deficiency anemia and the risk of new-onset tuberculosis infection: a matched cohort analysis. Frontiers in Nutrition. 2026 Jan 20;13:1727992. https://benangmerah.net/record/96/association-between-iron

Risk of TB in individuals with type 2 DM based on the TPI score [TBN 076]

Who

Adult patients >18 years with type 2 diabetes mellitus, with or without pulmonary TB, attending the Internal Medicine Outpatient Department at Fatmawati General Hospital. Final sample: 109 participants, comprising 39 cases with diabetes and TB and 70 controls with diabetes only. Patients with immunocompromised conditions, autoimmune disease receiving major immunosuppressive care, or incomplete records were excluded.

What

The study evaluated the tuberculosis predictive index (TPI) score for identifying TB risk among patients with diabetes. High TPI score was significantly associated with TB: 82.1% of diabetes-TB patients had high TPI scores versus 40.0% of diabetes-only patients. The association was significant, with OR 6.8, 95% CI 2.6–17.6, p<0.001.

Among individual factors, TB-like symptoms showed the strongest association with TB risk: OR 13.3, 95% CI 5.1–34.3, p<0.001. Low BMI <18.5 kg/m² was also associated with TB risk: OR 3.3, 95% CI 1.0–11.0, p=0.039. Poor housing ventilation ≤10% of floor area was associated with increased TB risk: OR 3.2, 95% CI 1.4–9.8, p=0.008.

When

Medical records from 2021–2024 were reviewed. Data collection occurred from May to August 2024, with questionnaires during July–August 2024.

Where

Fatmawati General Hospital, Internal Medicine Outpatient Clinic, Indonesia.

Why

The study addressed limitations of conventional TB screening among patients with diabetes, especially atypical presentation, latent or early TB detection difficulties, and the added complexity of poor glycemic control. The objective was to assess whether the TPI score could improve TB risk stratification in patients with diabetes.

How

Observational case-control study using consecutive sampling. Data came from medical records and patient questionnaires. The TPI score included age, sex, TB contact history, HbA1c, TB-like symptoms, BMI, diabetes duration, house ventilation, and psychological well-being. TB-like symptoms required ≥3 symptoms such as prolonged cough, hemoptysis, fever, night sweats, weight loss, or reduced appetite.

Level of evidence: observational analytic case-control evidence; useful for association and risk stratification, but not causal inference.

Major limitations: potential recall bias for subjective symptoms, reliance on medical records, single-center setting, and case-control design limiting causal conclusions.

Source: Audina DP, Aritonang RS, Mokoagow MI. Risk of tuberculosis in individuals with type 2 diabetes mellitus based on the tuberculosis predictive index score: a case-control study in Indonesia. Osong Public Health and Research Perspectives. 2025 Jun 11;16(4):406. https://benangmerah.net/record/95/risk-of-tuberculosis

Monday, May 11, 2026

Factors Associated with the Incidence of Pulmonary TB in Patients with Type 2 DM [TBN 075]

Who

The study included 110 adult patients with type 2 diabetes mellitus (T2DM) treated at Adam Malik Hospital, Medan, consisting of:

  • 55 cases: T2DM patients with pulmonary TB
  • 55 controls: T2DM patients without pulmonary TB

Eligibility criteria:

  • age ≥18 years
  • physician-diagnosed type 2 DM
  • complete medical record data

Exclusion criteria:

  • extrapulmonary TB
  • incomplete clinical documentation

Case definition:

  • pulmonary TB confirmed by GeneXpert MTB/RIF

Control definition:

  • T2DM patients with no history of pulmonary TB, based on medical records

Reported characteristics:

  • In cases, the largest subgroup was age 45–54 years (50.9%), male (62.1%), senior high school educated (54.0%), unemployed (59.6%), smokers (69.0%), and underweight (56.4%)
  • In controls, the largest subgroup was age 45–54 years (38.2%), female (68.2%), junior high school educated (66.7%), employed (60.4%), smokers (84.6%), and underweight (34.5%)

Important caution: the case and control groups appear imbalanced on several baseline characteristics, which complicates interpretation of reported odds ratios.

What

The study aimed to identify factors associated with pulmonary TB among patients with type 2 DM.

Outcome variable

  • Presence or absence of pulmonary TB

Independent variables

  • age
  • sex
  • education level
  • employment status
  • body mass index (BMI)
  • smoking history
  • HbA1c level

HbA1c classification

  • controlled: <7.0%
  • uncontrolled: ≥7.0%

Main findings

Bivariate analysis showed significant associations between pulmonary TB and:

  • age <55 years: OR 4.741; 95% CI 2.099–10.710
  • male sex: OR 3.514; 95% CI 1.569–7.869
  • unemployment: OR 2.253; 95% CI 1.050–4.834
  • smoking: OR 12.250; 95% CI 4.485–33.460
  • abnormal BMI: OR 4.225; 95% CI 1.905–9.371
  • low education: OR 3.148; 95% CI 1.430–6.931

A separate table reportedly showed that:

  • HbA1c >7% was associated with an approximately 11-fold higher risk of pulmonary TB compared with HbA1c ≤7%

In multivariable logistic regression:

  • smoking remained a significant factor and had the strongest adjusted association with pulmonary TB among T2DM patients (p < 0.001)

Authors’ interpretation: smoking was the dominant risk factor for pulmonary TB in patients with T2DM.

Careful interpretation: this study supports an association, not causation. The very large ORs for smoking and HbA1c should be interpreted cautiously given the apparent imbalance between groups and incomplete reporting of the adjusted model.

When

The study was conducted from January to June 2024.

Where

The study took place at Adam Malik Hospital, Medan, Indonesia, using hospital medical record data.

Why

The study sought to address which patient-related factors are associated with the occurrence of pulmonary TB in people with type 2 DM, a clinically important question because diabetes may increase TB susceptibility and worsen outcomes.

How

This was an observational analytical study using a case-control design.

Methods:

  • 1:1 case-control ratio
  • non-probability consecutive sampling
  • hospital-based recruitment from medical records
  • pulmonary TB diagnosis confirmed with GeneXpert MTB/RIF
  • factors assessed from clinical and demographic data

Statistical approach:

  • chi-square test for bivariate analysis
  • logistic regression for multivariable analysis

Strength of evidence

This is a hospital-based case-control study, which provides moderate observational evidence for association but is limited for causal inference. It is stronger than a purely descriptive study, but still vulnerable to selection bias, confounding, and measurement limitations.

Major limitations and interpretation issues

  1. Case and control groups may not be comparable
    The groups appear substantially different by sex, employment, education, BMI, and possibly smoking distribution. This raises concern for confounding and unstable effect estimates.
  2. Very large odds ratios need caution
    The reported ORs for smoking and HbA1c >7% are large and may partly reflect residual confounding, selection issues, or model instability.
  3. Sampling method may introduce bias
    Consecutive non-probability sampling limits representativeness and may affect internal validity.
  4. Hospital-based design
    Findings may not generalize well to all T2DM patients in the community.
  5. Control selection details are limited
    Controls were defined by absence of pulmonary TB history in records, but the text does not clarify whether they were systematically screened to exclude undiagnosed TB.
  6. Inconsistency in table presentation
    Table 1 reportedly mixes column percentages and row percentages, making interpretation less transparent.

Overall concise interpretation

This case-control study of 110 T2DM patients at Adam Malik Hospital found that younger age (<55 years), male sex, unemployment, low education, abnormal BMI, smoking, and HbA1c >7% were associated with pulmonary TB in bivariate analyses. In multivariable analysis, smoking remained the most important associated factor. However, the findings should be interpreted carefully because the case and control groups appear imbalanced, some reported effect sizes are very large, and the adjusted model is not fully presented.

Source: Harahap K, Sinaga BY, Syarani F, Eyanoer PC. Factors Associated with the Incidence of Pulmonary Tuberculosis in Patients with Type 2 Diabetes Mellitus. Mutiara Medika: Jurnal Kedokteran dan Kesehatan. 2025 Jul 31;25(2):123-31.

Environmental housing conditions of TB patients in a tidal-flooded area [TBN 074]

Who

The study included 25 households of registered pulmonary tuberculosis (TB) patients living in tidal-flood–affected coastal areas of Pekalongan, Indonesia. These households were selected from the service areas of Tirto II, Kramat Sari, and Dukuh primary health centers using total sampling from the eligible population. Of 52 registered TB cases, only 25 households met inclusion criteria.

Inclusion criteria were:

  • confirmed active pulmonary TB,
  • residence in tidal-flood–affected zones,
  • willingness to participate.

Exclusion criteria were:

  • untraceable address,
  • duplicate residence,
  • relocation,
  • death.

Respondent characteristics reported were:

  • age range 8–70 years, mean 46.12 ± 17.78 years,
  • 56% male and 44% female,
  • 80% married,
  • 84% had education at elementary level or lower,
  • 52% laborers, 32% housewives,
  • 84% earned < IDR 1,000,000/month,
  • 16% had BCG immunization history,
  • mean TB illness duration 3.64 ± 2.29 months,
  • mean residence duration 33.24 ± 21.38 years,
  • 12% reported household transmission.

Important ambiguity: the report describes “respondents” as TB patients, but the actual unit of analysis appears to be the household/house, not the individual patient. The presence of respondents aged 8 years is also insufficiently explained in the methods.

What

The study examined the physical environmental characteristics of houses occupied by TB patients, focusing on housing conditions as a composite variable with six indicators:

  1. occupancy density,
  2. ventilation area,
  3. indoor humidity,
  4. indoor temperature,
  5. lighting intensity,
  6. floor type.

Key findings:

  • 20% of households had occupancy density below the standard of 9 m²/person.
  • 92% failed to meet the ventilation standard of ≥10% of floor area.
  • Mean household humidity was 78.31% RH, above the recommended 40–60% RH.
  • 84% of houses exceeded the recommended temperature limit of 30°C, with room temperatures around 32°C.
  • 64% of households had inadequate lighting below 60 lux.
  • 92% had waterproof flooring; 8% did not.
  • Overall, only 1 household (4%) had adequate housing conditions, while 96% were classified as inadequate.

Authors’ apparent conclusion: most houses of TB patients in these tidal-flood–affected areas had poor environmental housing conditions, especially ventilation, humidity, temperature, and lighting.

Interpretation that is justified: the study shows a high prevalence of substandard housing conditions among households with TB patients.

Interpretation that is not justified: the study does not establish that these housing conditions caused TB, because there was no comparison group and the design was purely descriptive.

When

Data were collected between October 2023 and August 2024.

Where

The study was conducted in tidal-flood–affected coastal areas of Pekalongan, Indonesia, specifically in the service areas of:

  • Tirto II Primary Health Center,
  • Kramat Sari Primary Health Center,
  • Dukuh Primary Health Center.

The setting was household-based, with direct observation and environmental measurement in:

  • bedrooms,
  • living rooms,
  • kitchens,
  • bathrooms.

Why

The study aimed to describe whether the homes of TB patients in flood-affected coastal areas met healthy housing standards. The implied rationale is that poor housing environments may facilitate TB transmission or persistence, especially in settings affected by chronic tidal flooding, dampness, heat, and poor ventilation.

The knowledge gap addressed appears to be the limited description of housing environmental conditions among TB-affected households in a coastal tidal-flood context.

How

This was a descriptive quantitative study. The single main variable was housing condition, measured using six environmental indicators.

Data collection methods:

  • structured environmental assessment questionnaire adapted from prior validated instruments,
  • dichotomous scoring for each indicator,
  • classification into good, moderate, or poor housing condition categories,
  • direct measurements in all major rooms.

Tools used:

  • digital thermohygrometer for temperature and humidity,
  • Smart Sensor AS803 lux meter for lighting intensity,
  • measuring tape for room dimensions and ventilation area.

Environmental standards used:

  • occupancy density: ≥9 m²/person,
  • ventilation: ≥10% of floor area,
  • humidity: 40–60% RH,
  • temperature: 18–30°C,
  • lighting: ≥60 lux,
  • waterproof flooring as acceptable.

Quality procedures:

  • instrument calibration against hospital-standard instruments,
  • trained researchers,
  • standardized protocols,
  • informed consent and administrative authorization.

Strength of evidence

This is a descriptive cross-sectional household environmental assessment, which is a low level of evidence for causality. It is useful for describing conditions but not for determining whether poor housing conditions increase TB risk.


Overall concise interpretation

Among 25 TB-affected households in tidal-flood–affected Pekalongan, 96% were classified as having inadequate housing conditions. The most prominent deficits were poor ventilation, high humidity, high indoor temperature, and insufficient lighting. However, because the study was small, descriptive, and lacked a non-TB comparison group, it supports only a description of housing conditions, not a conclusion that these conditions caused TB.

Source: Irnawati, I., Wulan, D. R., Rahmatullah, R., Kartikasari, D., Permadi, Y. W., & Arifin, M. (2026). Environmental housing conditions of tuberculosis patients in a tidal-flooded area: Evidence from one of the world’s second-highest tb-burden countries. BIS Health and Environmental Science, 3, V326012.

Saturday, May 9, 2026

Linking Vulnerability, Adherence, and Outcomes in TB

(Yoseph Samodra)

Unequal TB burden shaped by demography, comorbidity, and place

  • Tuberculosis burden is strongly patterned by age, with consistently higher prevalence among older adults, particularly those aged 55 years and above, as shown in national Indonesian survey data and hospital based cohorts.
  • Men experience substantially higher TB prevalence than women in Indonesia, aligning with both population level epidemiology and clinic based samples of drug resistant and pulmonary TB patients.
  • Socioeconomic vulnerability is a recurrent determinant, with higher TB prevalence among individuals with low educational attainment, informal or physically demanding occupations, and lower economic status.
  • Occupational risk is pronounced in livelihoods tied to physical strain and environmental exposure, such as fishermen, farmers, agricultural laborers, drivers, and domestic workers.
  • Urban settings, especially dense and informal settlements, show higher TB prevalence than rural areas, reflecting crowding, mobility, and health system fragmentation.
  • Spatial analyses demonstrate that TB cases are not randomly distributed but clustered, with strong spatial autocorrelation and concentration in western Indonesia, particularly on Java Island.
  • Comorbid conditions significantly amplify TB risk, most notably diabetes mellitus, where TB prevalence among diabetic patients is many times higher than in the general population.
  • Among diabetic populations, younger age, smoking, HIV infection, poor glycemic control, insulin only treatment, and longer duration of diabetes independently increase TB risk.
  • Environmental vulnerability in coastal urban areas, including flooding, tidal intrusion, and erosion, normalizes chronic illness and weakens perceived urgency for TB diagnosis and prevention.

See also: https://lintblab.weebly.com/research-topics.html


Treatment adherence as a social and relational process

  • Medication adherence varies widely across TB populations, with drug resistant TB patients showing particularly low adherence, where only a very small minority achieve high adherence.
  • Female patients and those in productive adult age groups tend to show better adherence, suggesting gendered and life course influences on treatment behavior.
  • Educational level, occupation, and physical distance to health facilities do not consistently predict adherence, challenging assumptions that structural access alone determines compliance.
  • The presence of a treatment supporter or PMO is one of the most consistent positive determinants of adherence in pulmonary TB patients.
  • Patient motivation to recover is strongly associated with adherence, underscoring the importance of psychosocial and behavioral dimensions of TB care.
  • Long and complex treatment regimens, especially for drug resistant TB, erode adherence over time and require sustained support beyond initial treatment phases.
  • In coastal urban communities, irregular livelihoods and daily survival priorities disrupt routine medication intake and clinic attendance.
  • Communication failures within health systems, including euphemistic language and avoidance of explicitly naming TB, weaken understanding of treatment necessity and infectious risk.
  • Stigma drives concealment of illness and resistance to screening, indirectly undermining adherence and continuity of care.


Prognosis, mortality, and the importance of holistic clinical assessment

  • Older adults with TB experience high mortality, even when respiratory function appears relatively preserved at admission.
  • Functional status, measured by performance status, is the strongest predictor of TB related death, outweighing chronological age alone.
  • Corticosteroid use is independently associated with both TB related and TB unrelated mortality, reflecting the impact of immune suppression.
  • Hypoalbuminemia emerges as a powerful marker of poor prognosis, highlighting the central role of nutritional status in TB outcomes.
  • Mortality risk increases stepwise as multiple risk factors accumulate, supporting the use of simple composite risk stratification in clinical practice.
  • TB unrelated deaths in older patients are strongly influenced by age, comorbidities, and systemic frailty, reinforcing the need for integrated geriatric care.
  • In diabetic patients, poor metabolic control not only increases TB risk but likely worsens disease course and recovery.
  • Fragmented care pathways and delayed diagnosis, particularly in socially marginalized settings, contribute indirectly to worse outcomes by prolonging infectious periods and disease severity.
  • Comprehensive TB management requires attention to daily functioning, nutrition, immune status, and comorbid disease alongside microbiological cure.


Practical actions to strengthen TB disease management

  • Integrate routine TB screening into diabetes care, with emphasis on glycemic control and smoking cessation.
  • Prioritize treatment supporter programs, especially for drug resistant TB and socially vulnerable patients.
  • Incorporate simple functional and nutritional assessments, such as performance status and serum albumin, into routine TB care for older adults.
  • Design patient centered adherence strategies that align treatment schedules with local livelihoods and daily realities.
  • Address stigma directly through clear, explicit, and culturally sensitive communication that names TB and explains transmission.
  • Use spatial analysis to target high burden clusters with intensified case finding and resource allocation.
  • Strengthen coordination between clinical services, community health workers, and social support systems to reduce fragmentation.

References:

  1. Harahap, D.W.S., Andrajati, R., Sari, S.P. and Handayani, D., 2024. Medication Adherence among Drug-Resistant Tuberculosis (DR-TB) Patients at Universitas Indonesia Hospital. Jurnal Respirologi Indonesia, 44(3), pp.196-200.
  2. Handayani, L., 2024. Studi Epidemiologi Tuberkulosis Paru (TB) di Indonesia: Temuan Survey Kesehatan Indonesia (SKI) 2023. Jurnal Kendari Kesehatan Masyarakat, 4(1), pp.59-67.
  3. Kusmiyani, O.T., Hermanto, H. and Rosela, K., 2024. Analisis faktor yang berhubungan dengan kepatuhan minum obat anti tuberkulosis pada pasien TB paru di Puskesmas Samuda dan Bapinang Kotawaringin Timur. Jurnal Surya Medika, 10(1), pp.139-151.
  4. Alemu, A., Seid, G., Diriba, G., Hailu, M., Dange, B., Moga, S., Melese, D., Tadesse, G., Mariam, S.H., Berhe, N. and Gumi, B., 2025. Prevalence and associated factors of tuberculosis among diabetic patients attending public health facilities in Ethiopia: a multicenter study. Archives of Public Health, 83(1), pp.1-15.
  5. Rahmawati, Y., Jamil, I.R., Hidayah, I., Kusumawardani, D. and Wibowo, W., 2026. Spatial Econometric Analysis of the Impact of Health Infrastructure on TBC Patients Study Case in Indonesia Provinces Level. International Review for Spatial Planning and Sustainable Development, 14(1), pp.96-117.
  6. Miyoshi, S., Semba, M., Tanabe, M., Sato, C., Watanabe, A., Ito, R., Kubota, M. and Abe, M., 2025. Assessment of Risk Factors for Death in Older Adult Patients With TB in Japan. CHEST Pulmonary, 3(2).
  7. Shaluhiyah, Z., Handayani, S., Sriatmi, A., Agushybana, F. and Rimawati, E., 2025. Understanding tuberculosis as a wicked problem: a qualitative study in coastal urban settlements of Semarang, Indonesia. Frontiers in Communication, 10, p.1719819.
TBN 008

Age differences in factors associated with pulmonary tuberculosis [TBN 078]

1. Who Population: 715,394 Indonesian participants aged ≥16 years from RISKESDAS 2018. Age groups: 16–45 years: 469,517 participants...