Predictors of dropout from maternal continuum of care in Ethiopia: evidence from the 2016 population-based health survey
Bibliographic record
Abstract
Abstract IntroductionIntegrated primary health care service provided by skilled birth attendants is linked to safe childbirth and postnatal care, vitally improves maternal, newborn, and child health outcomes. Despite a significant reduction in maternal and neonatal mortality in Ethiopia, low maternal service utilization, and dropout from the maternal continuum of care continues to be a major challenge. Therefore, this study aimed to investigate the individual and community predictors of dropout from the maternal continuum of care in Ethiopia.MethodsWe used data from the 2016 Ethiopian demographic and health survey (EDHS). Women who had a birth in the 5 years preceding the survey were included. Dropout from the maternal continuum of care was the outcome of this study. This includes, attending less than four antenatal care visits (<4 ANC), a dropout from skilled birth attendance (SBA) after having 4 or more ANC, and dropout from postnatal care (PNC) after having SBA. Multilevel logistic regression analysis was employed. The mixed effect and variation in the outcome were expressed by the intracluster correlation coefficient (ICC).ResultsHigher dropouts from SBA to PNC (85%) and from ≥4 ANC to SBA (43.4%) in the maternal continuum of care were observed. Women from the poorest wealth quantile (AOR=2.31,95% CI 1.69,3.16), not covered by health insurance (AOR=1.44, 95% CI, 1.01,2.06), and residing in a community with high poverty (AOR=1.28,95% CI, 1.01,1.63) were more likely to attend inadequate ANC. On the other side, distance from a health facility (AOR=1.45, 95% CI, 1.12,1.88), lower community media exposure (AOR=1.6, 95% CI, 1.14,2.23) and rural residency (AOR=3.03, 95% CI, 1.75,5.26) were associated with dropout from SBA after attending ANC visits. Living in Somali, Harari, and Dire Dawa significantly associated with drop out from the PNC after SBA.ConclusionThe pattern of dropout from the maternal continuum of care was higher in Ethiopia. Maternal education, wealth index, community media exposure, and distance from a health facility were the factors associated with dropouts from the maternal continuum of care. Home care strategies and contextual understanding of the barriers to the PNC service is needed.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".