Home birth and associated factors in Nigeria: a comparative study of rural and urban settings based on the analysis of national population-based data
Bibliographic record
Abstract
Abstract Introduction Despite global efforts to reduce maternal and neonatal mortality, Nigeria continues to report disproportionately high rates. Home birth, childbirth occurring outside health facilities and without timely access to emergency obstetric care, remains a significant public health concern. National estimates can obscure stark sub-national disparities. This study estimated the prevalence of home birth and identified associated factors, comparing national, rural, and urban contexts. Methods We analysed data from 21,512 mothers using the 2018 Nigeria Demographic and Health Survey, guided by Andersen’s Behavioural Model. Logistic regression was used to examine associations between home birth and a range of individual, household, and contextual factors. Results Nationally, 58.1% (95% CI: 56.5, 59.7) of mothers gave birth at home, with prevalence nearly twice as high in rural areas (72.4%) compared to urban areas (36.1%). The North-West region reported the highest prevalence nationally (83.6%), in rural (89.4%) and urban (66.6%) areas. The South-East had the lowest prevalence in rural areas (16.2%), and the South-West in urban areas (16.7%). Nationally and across settings, lower maternal and partner education, poor household wealth, fewer than eight antenatal contacts, higher birth order, Hausa-Fulani ethnicity, and limited exposure to media and the internet were associated with increased odds of home birth. In rural areas, additional predictors included greater difficulty obtaining permission to seek care, distance to facilities, limited maternal decision-making autonomy, and pronounced regional disparities across all northern and the South-South regions. In urban areas, younger maternal age, Islamic religion, and financial barriers to accessing healthcare were uniquely associated. Conclusion Home birth remains common in Nigeria, particularly in rural areas and in northern and South-South regions, reflecting persistent structural, socioeconomic, and informational inequities. Addressing home birth requires setting-specific, equity-oriented strategies. In rural areas, policies should prioritise women’s autonomy, reduce geographic and regional barriers, and expand healthcare access. In urban areas, targeted interventions should focus on supporting younger mothers, mitigating financial barriers, and providing culturally and religiously responsive care. Nationally, investments in education, antenatal care utilisation, and access to health information through media and the internet are critical to promoting facility-based childbirth and improving maternal and neonatal outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".