Trends and disparities in antenatal care utilization: A multilevel analysis of four-plus and eight-plus ANC visits among urban women in Ethiopia
Bibliographic record
Abstract
INTRODUCTION: Antenatal care(ANC) is the gateway of the continuum of reproductive health care, offering a framework for complication prevention, screening, diagnosis, and health promotion. OBJECTIVE: This study examined trends, disparities and associated factors of ANC utilization (ANC4+ and ANC8+) among urban women in Ethiopia between 2000 and 2019. METHODS: We analyzed five rounds of Ethiopian Demographic and Health Surveys (2000-2019) data, disaggregated by wealth, education, and region using Stata version 16.1. Multilevel logistic regression model was used to identify factors associated with four-plus and eight-plus ANC utilization. Adjusted odds ratios (AORs) with 95% confidence intervals were reported, with statistical significance set at p < 0.05. RESULTS: ANC4 + utilization increased from 43.1% in 2000 to 58.7% in 2019. while, ANC8 + utilization declined from 11.4% to 3.6%. Among the urban non-poor, ANC4 + rose from 60.5% to 81.8% compared to 37.8% to 48.7% among the urban poor. Regional disparities were pronounced: Addis Ababa showed the highest ANC4 + use (72% to 82%), but a decline in ANC8+ (38% to 10%). Somali region had the lowest ANC4+ (9% to 24%) utilization, though it increased from 9% in 2000 to 24% in 2019 and Gambella had the lowest ANC8 + utilization. Wealth disparities were strong, with non-poor women more likely to utilize ANC4+ (AOR= 2.43; 95% CI: 2.12-2.78) and ANC8+ (AOR= 3.02; 95% CI: 2.49-3.65) than poor women. Education also significantly associated: women with secondary or higher education had greater odds of ANC4+ (AOR= 3.02; 95% CI: 2.54-3.59) and ANC8+ (AOR= 2.13; 95% CI: 1.63-2.78). Women aged 30-34 years had higher odds of utilizing ANC4+ (AOR= 2.89; 95% CI: 2.10-3.98) and ANC8+ (AOR= 2.22; 95% CI: 1.37-3.59). Weekly media exposure was positively associated with ANC4+ (AOR= 1.53; 95% CI: 1.28-1.83). CONCLUSION: Significant disparities in ANC (ANC4+ and ANC8+) utilization persist across wealth, education and regions in urban Ethiopia. Wealth status was the strongest predictor, with non-poor women steadily advantaged. Maternal education, age, media exposure, and marital status also showed positive associations, while regional disparities persisted, with Addis Ababa outperforming other urban areas. Improving ANC uptake requires targeted interventions for urban poor women, alongside media-based awareness and educational initiatives.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".