Predictors of Antenatal Care Service Utilization Among Women of Reproductive Age in Ethiopia: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Previous primary studies reported controversial findings on the association between predictors and antenatal care (ANC) service use. Therefore, we aimed to provide pooled predictors of ANC service use among women of reproductive age in Ethiopia.Methods: All observational studies done in Ethiopia between 2002 and 2022 were included in this review. Studies were systematically searched from PubMed, Medline, CINAHL, EMBASE, Google Scholar, and Google. We conducted a database search from June 1-31, 2023. The Newcastle-Ottawa scale (NOS) tool was utilized for quality assessment (risk of bias). The review was registered in the PROSPERO register with the registration number CRD42022322940. All data analyses were conducted by utilizing Stata version 17. A random-effects model was used to get the pooled predictors of ANC use. The publication bias was checked using a funnel plot and Egger's regression test. Results: A total of twenty-two studies with a total sample size of 25,671 were comprised for this review. Based on the NOS checklist assessment, we classified eight studies as low quality. The identified predictors of ANC use were highest wealth rank (AOR 1.92 [95% CI: 1.53 - 2.31]), formal women education (AOR 2.40 [95% CI: 1.75 - 3.06]), formal husband education (AOR 1.49 [95% CI: 1.36 - 1.66]), women age > 20 (AOR 1.75 [95% CI: 1.47 - 2.17]), mass media exposure (AOR 1.44 [95% CI: 1.21 - 1.66]), good maternal knowledge about the pregnancy complication (AOR 1.49 [95% CI: 1.11 - 1.88]), planned pregnancy (AOR 1.59 [95% CI: 1.28 - 1.91]), women autonomy (AOR 1.42 [95% CI: 1.23 - 1.62]), and positive husband attitude about the ANC service use (AOR 2.63 [95% CI: 1.47 - 3.79]). Conclusions: Several predictors have increased the ANC utilization, like wealth status, women's and their husbands' education, older/increasing women's age, media exposure, maternal knowledge about the pregnancy complications, planned pregnancy, women's autonomy to decide on household health care, and positive husband attitude about the ANC service utilization. Thus, the government and stakeholders should create women-focused economic reforms such as encouraging women's involvement in rural saving and credit cooperative organizations and productive safety net programs to increase their income, advocate ANC in mass media, and increase the mechanism of ANC service messages to reach the largest women of reproductive age groups.
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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 | 0.014 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.030 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".