Infant nutritional outcomes in an integrated agriculture, health and nutrition program in Western Kenya
Bibliographic record
Abstract
The Mama SASHA project integrated an orange‐fleshed sweetpotato (OFSP)‐focused, agricultural‐nutrition education intervention into delivery of routine health services and pregnant women's clubs. It aimed to improve diets, nutrition and health of pregnant /lactating women and their infants. We enrolled 505 women from intervention and control facilities during first antenatal care visit in early pregnancy. Infant anthropometry, vitamin A and iron status were assessed at 4 and 9 mos of age and anemia at 9 mos. There were no significant socioeconomic differences at enrollment. OFSP consumption was significantly higher and maternal MUAC significantly lower in intervention mothers at enrollment and throughout the follow up period. Mean birth weight was 3.27±0.5 kg and did not differ between groups. At 9 mos household food security and coverage with VA supplementation were significantly higher in controls; consumption of OFSP was significantly higher in intervention infants. From 4 to 9 mos postpartum, stunting increased significantly in controls (6.9% to 10.6%, p<0.05); stunting decreased nonsignificantly in the intervention group (11.5% to 10.3%, p>0.05). There was no change in either underweight from 4 to 9 mos (intervention: 3.1% to 3.3%; controls: 3.9% to 4.3%) or wasting (intervention: 2.1% to 1.6%; controls: 2.9% to 2.7%). There were no significant group differences in infant micronutrient status or anemia at 4 or 9 months. Further analysis will evaluate impact using mixed models that control for clustering, repeated measures and confounding.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".