Evidence map›Paper›PMID 41906164›Full record

ArticleInfectious diseases of poverty2026

Geospatial codistribution of tuberculosis and diabetes mellitus in Indonesia.

Indra Dwinata, Tsheten Tsheten, Ansariadi Ansariadi, Fasil Wagnew, Kefyalew Addis Alene, I Nyoman Sutarsa, Paula Moraga, I Wayan Gede Artawan Eka Putra, Matthew Kelly

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Article in Infectious diseases of poverty, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Indra DwinataDepartment of Epidemiology, Faculty of Public Health, Hasanuddin University, Jln Perintis Kemerdekaan Km.10, Makassar, South Sulawesi, 90242, Indonesia. indra@unhas.ac.id.ORCID http://orcid.org/0000-0001-9279-7755
Tsheten TshetenNational Centre for Epidemiology and Population Health, College of Law, Governance and Policy, Australian National University, Canberra, Australia.
Ansariadi AnsariadiDepartment of Epidemiology, Faculty of Public Health, Hasanuddin University, Jln Perintis Kemerdekaan Km.10, Makassar, South Sulawesi, 90242, Indonesia.
Fasil WagnewPopulation Health Program, QIMR Berghofer, Medical Research Institute, Brisbane, QLD, Australia.
Kefyalew Addis AleneSchool of Population Health, Faculty of Health Sciences, Curtin University, Bentley, WA, Australia.
I Nyoman SutarsaSchool of Medicine and Psychology, College of Science and Medicine, Australian National University, Canberra, Australia.
Paula MoragaComputer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, 23955-6900, Thuwal, Saudi Arabia.
I Wayan Gede Artawan Eka PutraSchool of Public Health, Faculty of Medicine, Udayana University, Bali, Indonesia.
Matthew KellyNational Centre for Epidemiology and Population Health, College of Law, Governance and Policy, Australian National University, Canberra, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTuberculosis (TB) and diabetes mellitus (DM) co-morbidity is a growing public health challenge, particularly in Indonesia, where TB incidence remains high and DM prevalence is increasing. DM co-morbidity is known to increase the risk of TB incidence and have negative effects on TB treatment outcomes. This study aims to analyze the geographical co-distribution of TB and DM and their sociodemographic determinants in Indonesia, to help inform public health response and targeting of screening programs.

methodsUsing data from the 2023 Indonesian Health Survey (SKI), a nationally representative, population-based survey, we applied a Bayesian geostatistical model to estimate disease prevalence and assess associations with key sociodemographic factors.

resultsThe predicted TB prevalence varied from 0.1% to 3.0%, highest in eastern Indonesia, particularly Papua, while DM prevalence ranged from 0.6% to 6.2%, concentrated in Java and Sumatra. Approximately 62 districts showed more than a 50% posterior probability that both TB and DM prevalences simultaneously exceed their respective national thresholds. The proportion of the poor population is significantly associated with higher TB prevalence (0.106; 95% CrI: 0.039, 0.174), while population density has a strong positive correlation with DM prevalence (0.198; 95% CrI: 0.156, 0.241). Proportion of the poor population (- 0.053; 95% CrI: - 0.096, - 0.009) and hospital services (- 0.071; 95% CrI: - 0.116, - 0.027) show a negative association with DM prevalence.

conclusionSpatial analysis revealed significant regional variations, with high TB-DM co-distribution observed in rapidly urbanizing and high-poverty districts, including parts of West Java, East Java, Sumatra, and Kalimantan in Indonesia. These findings emphasize the need for strengthened TB-DM integration in healthcare services, especially in areas that have a high prevalence of both diseases. Strengthening integrated disease management strategies in local areas can help mitigate the burden of both TB and DM in Indonesia, particularly given likely low case detection and health care access in lower income regions.

Indexed as

Diabetes MellitusTuberculosisBayes TheoremComorbidityHealth SurveysHumansIndonesiaPrevalenceSpatial AnalysisDiabetes mellitusGeospatial analysisIndonesiaTuberculosis

Identifiers

PMID41906164
PMCPMC13034603

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