Determinants of undernutrition in rural communities of a protected area in Gabon
Bibliographic record
Abstract
OBJECTIVE: To understand how access to natural resources may contribute to nutrition. DESIGN: In each of the two major seasons, data were collected during a 7 d period using observations, semi-structured interviews, anthropometric measures and a weighed food consumption survey. SETTING: Four rural communities selected to represent inland and coastal areas of the Gamba Complex in Gabon. SUBJECTS: In each community, all individuals from groups vulnerable to malnutrition, i.e. children aged 0-23 months (n 41) and 24-59 months (n 63) and the elderly (n 101), as well as women caregivers (n 96). RESULTS: In most groups, household access to natural resources was associated with household access to food but not with individual nutritional status. In children aged 0-23 months, access to care and to health services and a healthy environment were the best predictors of length-for-age (adjusted R2: 14%). Health status was the only predictor of weight-for-height in children aged 24-59 months (adjusted R2: 14%). In women caregivers, household food security was negatively associated with nutritional status, as was being younger than 20 years (adjusted R2: 16%). Among the elderly, only nutrient adequacy predicted nutritional status (adjusted R2: 5%). CONCLUSION: Improving access to care and health for young children would help reverse the process of undernutrition. Reaching a better understanding of how the access of individuals to both food and other resources relate to household access could further our appreciation of the constraints to good nutrition. This is particularly relevant in women to ensure that their possibly important contribution to the household is not at their own expense.
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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) | 0.001 | 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".