Modeling Time to First Birth among Reproductive-Age Women in Zimbabwe Using Accelerated Failure Time and Frailty Models

Modeling Time to First Birth among Reproductive-Age Women in Zimbabwe Using Accelerated Failure Time and Frailty Models | 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 Modeling Time to First Birth among Reproductive-Age Women in Zimbabwe Using Accelerated Failure Time and Frailty Models Hilary Takunda Takawira This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7884921/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 Background Early adolescent childbearing is associated with adverse maternal and neonatal, highlighting the importance of understanding determinants for public health and policy interventions. This study examined the timing of first birth and its socio-demographic, reproductive, and behavioral determinants among Zimbabwean women using accelerated failure time and frailty models. Methods This study conducted a secondary analysis of 9,955 women aged 15–49 years from the 2015 Zimbabwe DHS. Socio-demographic, reproductive, and behavioral factors were evaluated as predictors of time to first birth. Kaplan–Meier survival curves and log-rank tests were used for preliminary comparisons. Due to violations of the Cox proportional hazards assumption, several parametric models including exponential, Weibull, log-normal, and log-logistic, with and without gamma-shared frailty were compared. The log-logistic AFT model with gamma frailty provided the best fit, allowing estimation of time ratios (TRs) while accounting for regional-level heterogeneity (p < 0.05) Results Among 9,955 women, 73.4% had experienced their first birth, with a median age of 19 years (IQR: 17–21). Later sexual debut (≥ 18 years; TR = 1.08, 95% CI: 1.07–1.09) and older age at first cohabitation (15–17 years: TR = 1.15, 95% CI: 1.13–1.16; ≥18 years: TR = 1.25, 95% CI: 1.23–1.27) were associated with longer time to first birth. Higher education delayed first birth (secondary: TR = 1.03, 95% CI: 1.01–1.06; higher: TR = 1.11, 95% CI: 1.08–1.14), whereas being married (TR = 0.98, 95% CI: 0.98–0.99), contraceptive use (TR = 0.97, 95% CI: 0.96–0.97), and spousal age gap ≥ 5 years (TR = 0.98, 95% CI: 0.97–0.99) shortened it. Media exposure, wealth, residence, religion, and ovulation knowledge were not significant. Frailty variance (θ = 0.671, p < 0.001) indicated substantial regional heterogeneity. Conclusion Early age at first sex and cohabitation, marriage, low education, contraceptive non-use, and high spousal age gap accelerated first birth, while secondary/higher education and delayed cohabitation delayed it. Promoting women’s education and preventing early marriage are key to optimizing first birth timing. Interventions targeting early sexual debut, delayed marriage, and education may help delay first birth and improve reproductive health outcomes. The contextual differences in time to first birth are an important finding, which requires more study and interventions. Biostatistics Time to first birth accelerated failure time frailty model socio-demographic determinants Full Text Additional Declarations The authors declare no competing interests. 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. 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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-7884921","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":531119042,"identity":"28af1c7e-e75c-4ec3-8e02-857109c3b4c0","order_by":0,"name":"Hilary Takunda 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Models\u003c/strong\u003e\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"1.\tZvitambo Institute of Maternal and Child Health Research, Harare, Zimbabwe","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":"Time to first birth, accelerated failure time, frailty model, socio-demographic determinants","lastPublishedDoi":"10.21203/rs.3.rs-7884921/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7884921/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eEarly adolescent childbearing is associated with adverse maternal and neonatal, highlighting the importance of understanding determinants for public health and policy interventions. This study examined the timing of first birth and its socio-demographic, reproductive, and behavioral determinants among Zimbabwean women using accelerated failure time and frailty models.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis study conducted a secondary analysis of 9,955 women aged 15\u0026ndash;49 years from the 2015 Zimbabwe DHS. Socio-demographic, reproductive, and behavioral factors were evaluated as predictors of time to first birth. Kaplan\u0026ndash;Meier survival curves and log-rank tests were used for preliminary comparisons. Due to violations of the Cox proportional hazards assumption, several parametric models including exponential, Weibull, log-normal, and log-logistic, with and without gamma-shared frailty were compared. The log-logistic AFT model with gamma frailty provided the best fit, allowing estimation of time ratios (TRs) while accounting for regional-level heterogeneity (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eAmong 9,955 women, 73.4% had experienced their first birth, with a median age of 19 years (IQR: 17\u0026ndash;21). Later sexual debut (\u0026ge;\u0026thinsp;18 years; TR\u0026thinsp;=\u0026thinsp;1.08, 95% CI: 1.07\u0026ndash;1.09) and older age at first cohabitation (15\u0026ndash;17 years: TR\u0026thinsp;=\u0026thinsp;1.15, 95% CI: 1.13\u0026ndash;1.16; \u0026ge;18 years: TR\u0026thinsp;=\u0026thinsp;1.25, 95% CI: 1.23\u0026ndash;1.27) were associated with longer time to first birth. Higher education delayed first birth (secondary: TR\u0026thinsp;=\u0026thinsp;1.03, 95% CI: 1.01\u0026ndash;1.06; higher: TR\u0026thinsp;=\u0026thinsp;1.11, 95% CI: 1.08\u0026ndash;1.14), whereas being married (TR\u0026thinsp;=\u0026thinsp;0.98, 95% CI: 0.98\u0026ndash;0.99), contraceptive use (TR\u0026thinsp;=\u0026thinsp;0.97, 95% CI: 0.96\u0026ndash;0.97), and spousal age gap\u0026thinsp;\u0026ge;\u0026thinsp;5 years (TR\u0026thinsp;=\u0026thinsp;0.98, 95% CI: 0.97\u0026ndash;0.99) shortened it. Media exposure, wealth, residence, religion, and ovulation knowledge were not significant. Frailty variance (θ\u0026thinsp;=\u0026thinsp;0.671, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) indicated substantial regional heterogeneity.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eEarly age at first sex and cohabitation, marriage, low education, contraceptive non-use, and high spousal age gap accelerated first birth, while secondary/higher education and delayed cohabitation delayed it. Promoting women\u0026rsquo;s education and preventing early marriage are key to optimizing first birth timing. Interventions targeting early sexual debut, delayed marriage, and education may help delay first birth and improve reproductive health outcomes. The contextual differences in time to first birth are an important finding, which requires more study and interventions.\u003c/p\u003e","manuscriptTitle":"Modeling Time to First Birth among Reproductive-Age Women in Zimbabwe Using Accelerated Failure Time and Frailty Models","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-20 11:11:37","doi":"10.21203/rs.3.rs-7884921/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"4e8690af-8b35-4560-8330-a0a1e02f2d46","owner":[],"postedDate":"October 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56464463,"name":"Biostatistics"}],"tags":[],"updatedAt":"2025-10-20T11:11:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-20 11:11:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7884921","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7884921","identity":"rs-7884921","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}