Evidence map›Paper›PMID 41270096›Full record

ArticlePloS one2025

Home birth and associated factors in Nigeria: A comparative study of rural and urban settings-Analysis of national population-based data.

Emmanuel O Adewuyi, Asa Auta, Olumuyiwa Omonaiye, Mary I Adewuyi, Victory Olutuase, Kazeem Adefemi, Olumide A Odeyemi, Yun Zhao, Gizachew A Tessema, Gavin Pereira

Abstract readComparative Study
In one paragraph

Article in PloS one, 2025. 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Emmanuel O AdewuyiCurtin School of Population Health, Faculty of Health Sciences, Curtin University, Perth, Western Australia, Australia.ORCID https://orcid.org/0000-0002-4533-0340
Asa AutaFaculty of Health, Social Care and Medicine, Edge Hill University, Ormskirk, United Kingdom.
Olumuyiwa OmonaiyeSchool of Nursing and Midwifery and Centre for Quality and Patient Safety Research in the Institute for Health Transformation, Deakin University, Geelong, Australia.
Mary I AdewuyiFaculty of Health, Department of Social Work, Charles Darwin University, Darwin, Northern Territory, Australia.
Victory OlutuaseNational Institute for Health Research, Clinical Research Network: East Midlands, Research and Development, Leicestershire Partnership National Health Service Trust, Leicester, United Kingdom.
Kazeem AdefemiNewfoundland & Labrador Centre for Applied Health Research, Faculty of Medicine, Memorial University of Newfoundland, St John's, Newfoundland and Labrador, Canada.ORCID https://orcid.org/0000-0002-4333-7848
Olumide A OdeyemiAnchor University Centre for Global Health (AUCGH), Anchor University, Lagos, Nigeria.
Yun ZhaoCurtin School of Population Health, Faculty of Health Sciences, Curtin University, Perth, Western Australia, Australia.
Gizachew A TessemaCurtin School of Population Health, Faculty of Health Sciences, Curtin University, Perth, Western Australia, Australia.
Gavin PereiraCurtin School of Population Health, Faculty of Health Sciences, Curtin University, Perth, Western Australia, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionNigeria currently has the highest maternal mortality ratio and one of the highest neonatal mortality rates worldwide. Home birth-childbirth outside health facilities, often without skilled attendance or timely access to emergency obstetric care-may contribute to these disproportionate and avoidable adverse maternal and neonatal outcomes. National estimates often mask substantial sub-national disparities. This study examines the prevalence of home birth and associated factors across national, rural, and urban settings in Nigeria.

methodsWe analysed data from the nationally representative cross-sectional Nigeria Demographic and Health Survey 2018, guided by Andersen's Behavioural Model. Multivariable logistic regression was used to examine the associations between home birth and various predictor variables at the national level, as well as separately for rural and urban areas in Nigeria.

resultsNationally, 58.1% (95% CI: 56.5, 59.7) of mothers gave birth at home, with prevalence twice as high in rural areas (72.4%, 95% CI: 70.7, 74.0) compared to urban areas (36.1%, 95% CI: 33.6, 38.7) (p < 0.001). The North-West region had the highest home birth prevalence both nationally (83.6%, 95% CI: 81.5, 85.6) and in rural (89.4%, 95% CI: 87.6, 91.0), and urban (66.6%, 95% CI: 60.5, 72.2) areas (p < 0.001). The South-East recorded the lowest prevalence in rural areas (16.2%, 95% CI: 11.0, 23.3), while the South-West had the lowest in urban areas (16.7%, 95% CI: 14.1, 19.7) (p < 0.001). At the national level and across all settings, factors such as low maternal and husband's education, poor household wealth, fewer than eight antenatal contacts, higher birth order, Hausa-Fulani ethnicity, and limited exposure to media (radio and television) and the internet were associated with higher odds of home birth. In rural areas, additional predictors included difficulty obtaining permission, distance to health facilities, limited decision-making autonomy, and significant regional disparities, especially in the North and South-South regions. In urban areas, young maternal age, Islamic religion, financial barriers, and poor or middle household wealth were uniquely associated with higher odds of home birth.

conclusionHome birth remains highly prevalent in Nigeria, particularly in rural settings and in the northern and South-South regions, where prevalence is disproportionately high. Reducing home births requires a comprehensive approach that addresses the interplay of factors identified in this study. From a social justice and health determinants perspective, these factors are interconnected and can influence both access to and use of services. In rural areas, policies should enhance women's decision-making autonomy, reduce distance barriers, and address region-specific challenges (e.g., insecurity in northern regions). In urban areas, it is essential to address financial barriers, support young mothers, and provide culturally and religiously sensitive care. Nationally, efforts should focus on improving education, expanding and strengthening antenatal care, and increasing access to media and the internet. From an equity perspective, interventions must be tailored to specific contexts to reduce unsafe home births and ensure that all mothers, regardless of location, have equitable access to skilled, respectful, and high-quality childbirth care.

Indexed as

Home ChildbirthRural PopulationUrban PopulationAdolescentAdultCross-Sectional StudiesFemaleHumansInfant, NewbornMaternal MortalityMiddle AgedNigeriaPregnancyYoung Adult

Identifiers

PMID41270096
PMCPMC12637914

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LicenceCC BY
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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.