Maternity waiting home Utilization and associated factors among women who gave birth in the Digelu and Tijo district of the Arsi Zone, Oromia, Ethiopia
Bibliographic record
Abstract
Abstract Background Maternity Waiting Homes (MWHs) is an intervention designed to reduce maternal and perinatal mortality. Ethiopia has introduced the intervention before three decades however; its utilization is very low. Therefore, this study is aimed to assess MWH utilization and associated factors among women who gave birth in the last 12 months in Digelu and Tijo district Arsi Zone Oromia Region, Ethiopia. Methods Community-based cross-sectional study was conducted in April 2019 on 530 randomly selected women. Data were collected by face-to-face interview using structured questionnaire. Descriptive statistics and logistics regressions were used to analyze the results. Adjusted odds ratio and 95% confidence interval were respectively calculated to measure strength of association and its statistical significance.The confidence interval was used to declare statistical significance in the final model. Results One hundred twenty-five (23.6%) of the respondents used maternity waiting home. Traveling time less than and equals to 60 minutes from a nearby health facility (AOR=0.16, 95% CI: 0.09, 0.27), women’s decision power (AOR=1.81, 95% CI: 1.10, 2.96), not utilizing antenatal care (AOR=0.6, 95% CI: 0.37, 0.97) and delivering more than three children (AOR=0.56, 95% CI: 0.34, 0.90) were independently associated with utilizing the maternity waiting home. Conclusion Even though the MWH was designed to reduce maternal and perinatal mortality, less than a quarter (23.6%) of women delivered in the last 12 months before the study in the Digelu and Tijo District had utilized the services. Increasing availability of the service, promoting antenatal care utilization, empowering women and evolving policy makers are recommended to enhance the current low utilization of the MWH.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".