Feeding style and toddlers' dietary intake in two agro‐ecological zones of Ghana
Bibliographic record
Abstract
In sub‐Saharan Africa, childhood malnutrition can be attributed in part to sub‐optimal feeding practices. Study objectives were to (1) examine caregivers' feeding behaviors in two agro‐ecological zones of Ghana and (2) determine the association between caregiver feeding style and child dietary intake. Events during one meal for children 1–3 y of age were observed in households in the Forest‐Savanna Transitional (n=60) and Guinea Savanna zones (n=71). A multi‐item feeding behavior instrument was used to code caregivers' actions. All served foods and all food left on the child's plate were weighed. Anthropometric measures were taken. The prevalence of stunting among all children was 21%. There was a significant difference in the median energy intake of children who refused at least one mouthful (24%) versus children who did not refuse any mouthfuls (115 vs 214 kcal, respectively; p<0.05). Caregivers in the Transitional zone were more likely to remove the child's food following a refusal than caregivers in the Guinea Savanna (p< 0.05). However, there was no significant difference in child median energy intake between zones (204 vs 173 kcal, respectively; p=0.27). Practical, hands‐on interventions are needed to help caregivers learn to respond effectively to food refusals by young children. Funded by Jim Ellis Mentorship Program and GL‐CRSP/USAID #PCE‐G‐00‐98‐00036‐00. Grant Funding Source : US‐AID
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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 | 0.001 |
| 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".