Preference in the use of full childhood immunizations in Ethiopia: the role of maternal health services
Bibliographic record
Abstract
Background: Immunizations represent a successful and cost-effective public health strategy in preventing common childhood diseases. Ethiopia has made remarkable progress in increasing its full immunization coverage, but significant gaps remain. This study aims to measure the preference in the use of full immunizations for children aged 12–23 months in Ethiopia and examine the role of key maternal health services. Methods: This is a cross-sectional study and uses data from a nationally generalizable survey, the Ethiopian Demographic and Health Survey, 2016. It includes a representative sample of 2,168 children aged 12–23 months. The main outcome was full immunization, measured based on the WHO guidelines (Bacillus Calmette–Guérin [BCG], diphtheria, tetanus, and pertussis [DPT], polio, and measles vaccines). The main exposure variables were provision of three key maternal health services (antenatal care, delivery services, and tetanus vaccine) as well as other sociodemographic factors. Descriptive statistics and multivariate logistic regression analyses were conducted. Results: This study found the overall full immunization coverage in Ethiopia to be much lower (39%) than the WHO-recommended rate (≥90%). There were distinctive differences in the preference in the use of full immunization coverage for various vaccines (BCG 70.0%, polio 56.5%, measles 55.3%, and DPT 53.9%). The maternal health service variables (antenatal care, delivery services, and tetanus vaccine) were significantly associated with the full immunization of children aged 12–23 months ( P <0.001). In the full model, the maternal health service variables remained significant, along with other socioeconomic predictors of full immunization, including sex of the household head ( P <0.001), maternal education ( P <0.05), wealth index ( P <0.01), and religion ( P <0.001). Conclusion: Full immunization coverage has been identified as a critical factor in the prevention of morbidity and mortality from childhood diseases. Future progress in the provision of key maternal health services can have a positive impact in narrowing the gap in immunization coverage. Keywords: Africa, Ethiopia, childhood immunizations, maternal health services
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".