Potentials, Experiences and Outcomes of a Comprehensive Community Based Programme to Address Malnutrition in Tribal India
Bibliographic record
Abstract
This paper demonstrates the effect of an innovative community-based management programme on acute malnutrition among children under three years of age, through an observational longitudinal cohort study in tribal blocks in central-eastern India. The key components of the programme include child care through crèches, community mobilisation and systems strengthening to ensure better child feeding and caring practices and delivery of public health and nutrition services. For a cohort of 587 children, the increase in children in the non-wasting category is from 72% to 80% (p<0.001) and the reduction in Severe Acute Malnutrition (SAM) from 8% to 4% (p<0.005), a reduction of 46.6%. Normalcy is fairly well maintained at 89%. Among the severely wasted, 16% show no improvement, 49% moved into a moderate wasting category and 36% to normalcy over 4-6 months. Among the moderately wasted, 26% showed no improvement and 7% declined to a severely wasted category, and 67% moved to normalcy. The average Weight for Height Z-score (WHZ) for the cohort improved from -1.41 in the initial period to -1.13 in November (p<0.0001). This study suggests that this medium term strategy using a rights-based participatory approach for community based management of malnutrition may be comparatively effective by current WHO guidelines and other known community based interventions in terms of mortality, cost, degree and pace of improvements.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.004 |
| 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".