Evidence map›Paper›PMID 42318607›Full record

ArticleBioMed research international2026

Geospatial Variation and Determinants of Time to Pregnancy Loss Among Reproductive-Aged Women in East Africa: Bayesian Spatial Frailty Model.

Solomon Keflie Assefa, Meron Asmamaw Alemayehu, Tadesse Awoke Ayele

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Article in BioMed research international, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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5 · Who and what money

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3 authors.

Solomon Keflie AssefaDepartment of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia, uog.edu.et.ORCID https://orcid.org/0009-0005-6988-9471
Meron Asmamaw AlemayehuDepartment of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia, uog.edu.et.
Tadesse Awoke AyeleDepartment of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia, uog.edu.et.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPregnancy loss is the terminated pregnancy before the completed pregnancy time. Spatial location can significantly influence pregnancy outcomes, yet geographic disparities in the risk of pregnancy loss remain poorly studied in East Africa. This study is aimed at examining the spatial variation and determinants of time to pregnancy loss among women of reproductive age in the region.

methodsA Bayesian spatial survival model with an intrinsic conditional autoregressive approach was utilized to identify factors related to time to pregnancy loss across 169 regions in 9 East African countries using secondary data from recent demographic and health surveys (2015-2023). A spike-and-slab prior was used for variable selection. Model comparison utilized deviance information criteria, Watanabe-Akaike information criterion, and log pseudo marginal likelihood, with diagnostics from Cox and Snell residuals.

resultsPregnancy loss showed significant spatial clustering. Earlier occurrence was observed among women aged 25-34 years (ϕ = 0.712; 95% CrI: 0.680-0.744) and ≥ 35 years (ϕ = 0.326; 95% CrI: 0.307-0.344), those living with their husbands (ϕ = 0.893; 95% CrI: 0.856-0.932), with primary education (ϕ = 0.939; 95% CrI: 0.892-0.987), regular media exposure (ϕ = 0.854; 95% CrI: 0.819-0.889), employed (ϕ = 0.818; 95% CrI: 0.788-0.850), and attending antenatal care (ϕ = 0.964; 95% CrI: 0.933-0.996). In contrast, college-educated women (ϕ = 1.109; 95% CrI: 1.024-1.203), rural residents (ϕ = 1.144; 95% CrI: 1.102-1.190), low parity (ϕ = 14.93; 95% CrI: 13.853-16.132), and grand multiparity (ϕ = 22.088; 95% CrI: 20.131-24.247) were associated with longer time to pregnancy loss. After adjusting for individual-level factors, residual variation in the hazard of pregnancy loss remained.

conclusionsPregnancy loss remains a significant public health challenge in East Africa, with significant geographic variation. Spatial analysis can guide region-specific healthcare strategies and targeted interventions.

Indexed as

Abortion, SpontaneousAdultAfrica, EasternBayes TheoremEast African PeopleFemaleHumansPregnancyPregnancy OutcomeYoung AdultBayesian spatialBayesian survivalEast Africafrailtypregnancy lossspatial survival

Identifiers

PMID42318607
PMCPMC13280569

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.