Baseline Household Agriculture and Child Nutrition Linkages in the Nutrition Links Project
Bibliographic record
Abstract
The Nutrition Links Project is testing effect of integrated agriculture and nutrition strategies on livelihoods, nutrition, and health status of infants in Ghana's Eastern Region. Logistic regression were used to determine relationships between infant nutrition (EBF, diet diversity, Hb <11 g/dl, anthropometry), and household agriculture resource ownership (land, livestock) and practices (farming, home gardening) in the last year, with baseline data. Only 57% of 1081 households owned agricultural land but 77% cultivated food, 40% had a home garden, and 79% owned livestock. Mean child age was 5.8 + 3.5 months. Wasting, underweight and stunting rates were 6%, 11%, and 12%, respectively. Exclusive breastfeeding in past 24 hr was 86% and 52% among infants <3 months and 3‐6 mo, respectively. Only 24% of infants > 6 months were fed diets with 4+ food groups in past 24 hr. Infants in households with home gardens were less likely to exclusively breastfeed (OR=0.65; p=0.04) but also less at risk of underweight (OR=0.53; p=0.01). Land ownership was associated with lower risk of wasting (OR=0.59; p=0.04). We conclude that although agricultural activities are associated with better infant nutritional indicators, interventions are needed to improve infant and young child feeding practices in the Eastern Region.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".