Determinants of Skilled Birth Attendance in Nigeria: A Population-Based Analysis of the 2018 Demographic and Health Survey

Abstract

Background: Nigeria bears one of the highest maternal mortality burdens globally, with skilled birth attendance (SBA) remaining critically low in many regions. Understanding the independent determinants of SBA is essential for designing targeted interventions. Methods: This cross sectional study analyzed 21,465 births from the 2018 Nigeria Demographic and Health Survey (NDHS), a nationally representative household survey using stratified two stage cluster sampling. SBA was defined as delivery attended by a doctor, nurse, midwife, or auxiliary midwife. Multivariable logistic regression was used to estimate adjusted odds ratios (aOR) with 95% confidence intervals for the associations between SBA and maternal education, household wealth, place of residence, geopolitical region, maternal age, parity, and antenatal care (ANC) utilization, after accounting for confounding. Results: The overall prevalence of SBA was 44.9%. In the fully adjusted model, higher education (aOR = 7.01, 95% CI: 5.68-8.67), richest wealth quintile (aOR = 6.27, 95% CI: 5.27-7.46), and attending ≥4 ANC visits (aOR = 3.80, 95% CI: 3.51-4.11) were the strongest independent predictors of SBA. Regional inequalities were pronounced, with SBA prevalence ranging from 17.7% in the North West to 85.6% in the South West. Crude effect estimates for education and wealth were substantially attenuated after adjustment, indicating large confounding by correlated socioeconomic factors. Conclusions: Maternal education, household wealth, ANC utilization, and geopolitical region are independent determinants of SBA in Nigeria. Scaling up ANC programs represents the most immediately actionable intervention, while long term gains require investment in girls' education and wealth equity. Targeted strategies for the northern regions are urgently needed. Keywords: skilled birth attendance, maternal mortality, Nigeria, DHS, antenatal care, logistic regression, health equity

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This study did not receive any funding.

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

This study used only openly available human data from the 2018 Nigeria Demographic and Health Survey (NDHS), conducted by the National Population Commission and ICF. The dataset was publicly available prior to the initiation of this study and can be accessed at: https://dhsprogram.com/data/dataset/Nigeria_Standard-DHS_2018.cfm

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

Comments (0)

No login
gif