Food and Nutritional Security of Children of Urban Farmers in Kampala, Uganda
Bibliographic record
Abstract
BACKGROUND: Urban agriculture is an important livelihood strategy to increase access to and availability of food in urban settings. OBJECTIVE: We examined the impact of sociodemographic and farming variables on the household food security and nutritional security of an index child aged 2 to 5 years. Our hypothesis was that dietary quality (percentage of energy from animal-source foods [%ASF] and dietary diversity) would have an impact on infection (as measured by C-reactive protein [CRP]), which in turn would have an impact on biochemical indices (hemoglobin and retinol) and anthropometric indices (weight-for-age z-score [WAZ] and body mass index z-score [ZBMI]). We examined the relationships among urban agricultural activities, household food security, and child nutritional security. METHODS: We conducted a cross-sectional survey of 296 households within each randomly selected study zone in Kampala, Uganda. Correlations were calculated and bivariate and exploratory path analysis was conducted to explore relationships. RESULTS: Household food security score was significantly positively correlated with the number of tropical livestock units (r = 0.142, p = .017), dietary diversity (r = 0.230, p < .001), %ASF (r = 0.185, p = .002), and WAZ (r = 0.149, p = .017). Exploratory path analysis demonstrated a significant positive relationship between household food security and %ASF, which in turn was positively associated with retinol. Consumption of animal-source food was significantly negatively associated with C-reactive protein level, which in turn was significantly negatively associated with hemoglobin level, and hemoglobin was significantly positively associated with WAZ. CONCLUSIONS: Our findings are supportive of efforts to enhance access to land for urban farming and engagement in activities aimed at improving the quality of dietary intake of urban residents, in particular by increasing consumption of animal-source foods.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".