Bayesian Spatio-Temporal Modelling of Reported Terminated Pregnancy Across Nigerian States (2013-2024)

Bayesian Spatio-Temporal Modelling of Reported Terminated Pregnancy Across Nigerian States (2013-2024) | 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 Bayesian Spatio-Temporal Modelling of Reported Terminated Pregnancy Across Nigerian States (2013-2024) Taiwo Oyewale Asifat, Oluwafemi Lawal Bisiriyu, Abolaji Moses Ogunetimoju This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8872479/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The long- standing disconnection of abortion legislation in Nigeria with the estimated incidence of 1.8 million terminations a year has contributed to systematic gaps in reliable abortion data for health policy. Any subnational monitoring under conditions of legal restraint tends to remain hidden beneath under-reporting and spatial instability such that policy makers are not left with a clear picture of where and why these decisions are being made. To address this ambiguity, this paper traces the path of state-level evolution of reproductive choices within the 2013, 2018 and 2024 NDHS. We detected the latent socio-demographic causes of terminated pregnancy using a Bayesian spatio-temporal framework, such as wealth, education, literacy, and contraceptive prevalence. The rates were highly spatio-temporally intense and polarized in the region, with probabilistic evidence to justify state-specific reproductive health interventions between 2013 and 2024. Southern and coastal states (e.g., Lagos, Bayelsa) demonstrated sustained increases in prevalence in line with a high fertility transition, termination is more reproductive agency, access to services and reporting. Conversely, the unmet contraceptive need and structural vulnerability were the major causes of increased rates in the northern states (e.g., Yobe, Kano). Patterns of determinants also changed with time: in previous surveys, household wealth turned out to be a protective factor, as of 2024, education and literacy had become the strongest predictors. Such findings affirm a dual reproductive regime in Nigeria—choice based in the South and vulnerability based in the North necessitating a shift from homogenous national approaches to state-specific reproductive health policies. Bayesian spatio-temporal modelling Terminated pregnancy Reproductive health inequality Nigeria Demographic and Health Survey (NDHS) Fertility transition Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8872479","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":607633060,"identity":"aef37566-4f57-4c3c-9723-2985f76bfc1e","order_by":0,"name":"Taiwo Oyewale Asifat","email":"","orcid":"","institution":"University of Ibadan","correspondingAuthor":false,"prefix":"","firstName":"Taiwo","middleName":"Oyewale","lastName":"Asifat","suffix":""},{"id":607633061,"identity":"a7f9336b-18af-4d9d-a5f5-56a2c8b98380","order_by":1,"name":"Oluwafemi Lawal Bisiriyu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABB0lEQVRIiWNgGAWjYDACdh6GAwwGDDwMDMwHgFwJfpCgBF4tzHAtbAkgxZINxGiBAh4DEElYCz8z78GDPwruyRjcyPn44GebBdBlzAdv8zDcsWvAoUWymS/hMI9BMY/BjdzNhr1tEkCXsSVb8zA8S8alxQCo/jCDQQJIyzYJ3jaJOoMDPGbSPAyHk3E5DKTl4A+wlpxnkn+Bttgf4P9GUMsBHogWNmmgLRLA0GMDabHDpQXqlwQeyTPPjI1lzklISBxmM7acY3A4AZcWfvbewx9//Emw5zue/PDhm7I6Cf725oc33lQctselBQ4UDsBYzGAHMyQ2ENIij66CsC2jYBSMglEwUgAA/dVPmBiN7J4AAAAASUVORK5CYII=","orcid":"","institution":"Obafemi Awolowo University","correspondingAuthor":true,"prefix":"","firstName":"Oluwafemi","middleName":"Lawal","lastName":"Bisiriyu","suffix":""},{"id":607633062,"identity":"29b70796-5e0d-4cc5-a2f1-7caeb7284fce","order_by":2,"name":"Abolaji Moses Ogunetimoju","email":"","orcid":"","institution":"Obafemi Awolowo University","correspondingAuthor":false,"prefix":"","firstName":"Abolaji","middleName":"Moses","lastName":"Ogunetimoju","suffix":""}],"badges":[],"createdAt":"2026-02-13 13:38:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8872479/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8872479/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105727699,"identity":"214bf123-6538-49b4-a9a1-7b9e14e9398f","added_by":"auto","created_at":"2026-03-30 11:00:29","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":733277,"visible":true,"origin":"","legend":"","description":"","filename":"BayesianSpatioTemporalModellingofReportedTerminatedPregnancyAcrossNigerianStates20132024.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8872479/v1_covered_385e3e29-79c5-4961-90df-0a55875dedae.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Bayesian Spatio-Temporal Modelling of Reported Terminated Pregnancy Across Nigerian States (2013-2024)","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Bayesian spatio-temporal modelling, Terminated pregnancy, Reproductive health inequality, Nigeria Demographic and Health Survey (NDHS), Fertility transition","lastPublishedDoi":"10.21203/rs.3.rs-8872479/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8872479/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe long- standing disconnection of abortion legislation in Nigeria with the estimated incidence of 1.8\u0026nbsp;million terminations a year has contributed to systematic gaps in reliable abortion data for health policy. Any subnational monitoring under conditions of legal restraint tends to remain hidden beneath under-reporting and spatial instability such that policy makers are not left with a clear picture of where and why these decisions are being made. To address this ambiguity, this paper traces the path of state-level evolution of reproductive choices within the 2013, 2018 and 2024 NDHS. We detected the latent socio-demographic causes of terminated pregnancy using a Bayesian spatio-temporal framework, such as wealth, education, literacy, and contraceptive prevalence. The rates were highly spatio-temporally intense and polarized in the region, with probabilistic evidence to justify state-specific reproductive health interventions between 2013 and 2024. Southern and coastal states (e.g., Lagos, Bayelsa) demonstrated sustained increases in prevalence in line with a high fertility transition, termination is more reproductive agency, access to services and reporting. Conversely, the unmet contraceptive need and structural vulnerability were the major causes of increased rates in the northern states (e.g., Yobe, Kano). Patterns of determinants also changed with time: in previous surveys, household wealth turned out to be a protective factor, as of 2024, education and literacy had become the strongest predictors. 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