Effect of a Child-Owned Poultry Intervention Providing Eggs on Nutrition Status and Motor Skills of Young Children in Southern Ethiopia: A Cluster Randomized and Controlled Community Trial
Bibliographic record
Abstract
Eggs are highly nutritious foods, yet intake by children in Ethiopia is low. We hypothesized that a nutrition-sensitive poultry intervention improves nutritional status of children 6–18 months using a 6-month cluster randomized controlled community trial. Intervention group (IG) children received a gift of two egg-laying hens in a ceremony where children’s ownership of the chickens was declared by community leaders. Parents promised to add more hens and feed the owner-child one-egg-a-day. Trained community workers reinforced egg feeding, environmental sanitation and poultry husbandry. Control group (CG) mothers received usual nutrition education on child feeding. At baseline 29.6% of children were stunted, 19.4% underweight and 8.6% wasted. Egg consumption significantly increased only in IG, at 6 months. The intervention increased weight-for-age and weight-for-height z-scores by 0.38 (95% CI = 0.13–0.63) and 0.43 (95% CI = 0.21–0.64), respectively. Binary logit model indicated IG children were 54% (Odds ratio [OR] = 0.46; 95% CI = 0.26–0.84) and 42% (OR = 0.58; 95% CI = 0.37–0.91) less likely to be underweight and stunted, respectively, compared to CG. IG children attained the milestone of running (p = 0.022; AHR = 1.43; 95% CI = 1.05–1.95), kicking a ball (p = 0.027; AHR = 1.39; 95% CI = 1.04–1.87) and throwing a ball (p = 0.045; AHR = 1.37; 95% CI = 1.01–1.86) earlier than CG. This nutrition-sensitive child-owned poultry approach should be implemented where animal-source food intake is low.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".