Geospatial Codistribution of Tuberculosis and Diabetes Mellitus in Indonesia

Geospatial Codistribution of Tuberculosis and Diabetes Mellitus in Indonesia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Geospatial Codistribution of Tuberculosis and Diabetes Mellitus in Indonesia Indra Dwinata, Tsheten Tsheten, Ansariadi Ansariadi, Fasil Wagnew, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7296473/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Mar, 2026 Read the published version in Infectious Diseases of Poverty → Version 1 posted 5 You are reading this latest preprint version Abstract Background Tuberculosis (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 targetting of screening programs. Methods Using data from the 2023 Indonesian Health Survey (SKI), we applied a Bayesian geostatistical model to estimate disease prevalence and assess associations with key sociodemographic factors. Results 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. Conclusion Spatial 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. 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 TB and DM in Indonesia. Tuberculosis Diabetes Mellitus Geospatial analysis Indonesia Full Text Cite Share Download PDF Status: Published Journal Publication published 30 Mar, 2026 Read the published version in Infectious Diseases of Poverty → Version 1 posted Editorial decision: Major revision 07 Sep, 2025 Reviewers agreed at journal 14 Aug, 2025 Reviewers invited by journal 13 Aug, 2025 Editor assigned by journal 07 Aug, 2025 First submitted to journal 06 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7296473","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":500223176,"identity":"4c2c73f8-0780-4655-b6c7-d9e36cc78a09","order_by":0,"name":"Indra 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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 targetting of screening programs.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eUsing data from the 2023 Indonesian Health Survey (SKI), we applied a Bayesian geostatistical model to estimate disease prevalence and assess associations with key sociodemographic factors.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe 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.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eSpatial 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. 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 TB and DM in Indonesia.\u003c/p\u003e","manuscriptTitle":"Geospatial Codistribution of Tuberculosis and Diabetes Mellitus in Indonesia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-21 12:11:06","doi":"10.21203/rs.3.rs-7296473/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2025-09-07T10:07:14+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-08-14T08:01:10+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-14T01:29:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-08T03:23:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"Infectious Diseases of Poverty","date":"2025-08-07T01:54:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"infectious-diseases-of-poverty","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"idop","sideBox":"Learn more about [Infectious Diseases of Poverty](http://idpjournal.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/idop/default.aspx","title":"Infectious Diseases of Poverty","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a4549d80-7984-418b-b540-c9f786386a67","owner":[],"postedDate":"August 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-07T16:03:08+00:00","versionOfRecord":{"articleIdentity":"rs-7296473","link":"https://doi.org/10.1186/s40249-026-01432-x","journal":{"identity":"infectious-diseases-of-poverty","isVorOnly":false,"title":"Infectious Diseases of Poverty"},"publishedOn":"2026-03-30 15:59:34","publishedOnDateReadable":"March 30th, 2026"},"versionCreatedAt":"2025-08-21 12:11:06","video":"","vorDoi":"10.1186/s40249-026-01432-x","vorDoiUrl":"https://doi.org/10.1186/s40249-026-01432-x","workflowStages":[]},"version":"v1","identity":"rs-7296473","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7296473","identity":"rs-7296473","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}