Determinants of successful vitamin A supplementation coverage among children aged 6–59 months in thirteen sub-Saharan African countries
Bibliographic record
Abstract
OBJECTIVE: Vitamin A supplementation (VAS) for children aged 6-59 months occurs regularly in most sub-Saharan African countries. The present study aimed to explore child, household and delivery platform factors associated with VAS coverage and identify barriers to compliance in thirteen African countries. DESIGN: We pooled data (n ~60 000) from forty-four household coverage surveys and used bivariate and multivariable regression analyses to assess the effects of supplementation strategy, rural v. urban residence, child sex, child age, caregiver education and campaign awareness on child VAS status. Setting/Subjects Primary caregivers of children aged 6-59 months in thirteen countries. RESULTS: Door-to-door distribution resulted in higher VAS coverage than fixed-site plus outreach approaches (91 v. 63 %) and was a significant predictor of supplementation in the adjusted model (OR=19·0; 95 % CI 17·2, 21·1; P<0·001). Having been informed about the campaign was the main predictor of VAS in the door-to-door (OR=6·8; 95 % CI 5·8, 7·9; P<0·001) and fixed-site plus outreach (OR=72·5; 95 % CI 66·6, 78·8; P<0·001) groups. CONCLUSIONS: Door-to-door provision of VAS may achieve higher coverage than fixed-site models in the African context. However, the phase-out of door-to-door polio immunization campaigns in most sub-Saharan African countries threatens the main distribution vehicle for VAS. Our findings suggest well-informed communities are key to attaining higher coverage using fixed-site delivery alternatives.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".