Maternal healthcare utilsation and complete childhood vaccination in sub-Saharan Africa: a cross-sectional study of 29 nationally representative surveys
Bibliographic record
Abstract
OBJECTIVE: The objective of the study was to examine the association between maternal healthcare utilisation and complete childhood vaccination in sub-Saharan Africa. DESIGN: Our study was a cross-sectional study that used pooled data from 29 countries in sub-Saharan Africa. PARTICIPANTS: A total of 60 964 mothers of children aged 11-23 months were included in the study. OUTCOME VARIABLES: The main outcome variable was complete childhood vaccination. The explanatory variables were number of antenatal care (ANC) visits, assistance during delivery and postnatal care (PNC). RESULTS: The average prevalence of complete childhood vaccination was 85.6%, ranging from 67.0% in Ethiopia to 98.5% in Namibia. Our adjusted model, children whose mothers had a maximum of three ANC visits were 56% less likely to have complete vaccination, compared with those who had at least four ANC visits (adjusted OR (aOR)=0.44, 95% CI 0.42 to 0.46). Children whose mothers were assisted by traditional birth attendant/other (aOR=0.43, 95% CI 0.41 to 0.56) had lower odds of complete vaccination. The odds of complete vaccination were lower among children whose mothers did not attend PNC clinics (aOR=0.26, 95% CI 0.24 to 0.29) as against those whose mothers attended. CONCLUSION: The study found significant variations in complete childhood vaccination across countries in sub-Saharan Africa. Maternal healthcare utilisation (ANC visits, skilled birth delivery, PNC attendance) had significant association with complete childhood vaccination. These findings suggest that programmes, interventions and strategies aimed at improving vaccination should incorporate interventions that can enhance maternal healthcare utilisation. Such interventions can include education and sensitisation, reducing cost of maternal healthcare and encouraging male involvement in maternal healthcare service utilisation.
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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 | 0.002 | 0.004 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".