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Potentials, Experiences and Outcomes of a Comprehensive Community Based Programme to Address Malnutrition in Tribal India

2015· article· en· W1776133934 on OpenAlexvenueno aff
Vandana Prasad, Dipa Sinha

Bibliographic record

VenueInternational Journal of Child Health and Nutrition · 2015
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
FundersTata Trusts
KeywordsMedicineMalnutritionEnvironmental healthPathology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.054
GPT teacher head0.363
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2015
Admission routes1
Has abstractyes

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