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Record W2246717248 · doi:10.1177/0973174115588841

Individual and Ecological Variation in Child Undernutrition in India

2015· article· en· W2246717248 on OpenAlex
Iván Mejía‐Guevara, Aditi Krishna, Daniel J. Corsi, S. V. Subramanian

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of South Asian Development · 2015
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsAnthropometryUnderweightMalnutritionWastingMedicineDemographyStandard scoreBody mass indexEnvironmental healthPediatricsOverweightStatisticsMathematics

Abstract

fetched live from OpenAlex

Despite the substantial burden of child undernutrition in South Asia, little is known on the relative importance and contribution of individual and micro/macro environments in shaping variation in child undernutrition. Using measures of anthropometry, we decompose the variation in child undernutrition in India to the levels of child, communities and states, quantifying the extent to which variation at each of these levels can be explained by known proximal and distal risk factors, measured at the individual (child/household) level. Data are from under-five singleton children participating in the 2005–2006 National Family Health Survey (NFHS-3). The outcome variables were: height-for-age z-score (HAZ), weight-for-age z-score (WAZ) and weight-for-height z-score (WHZ), as well as their associated measures of anthropometric failure: stunting, underweight and wasting, defined as more than two standard deviations below the median of the referred z-scores, respectively. We also considered the composite index of anthropometric failure (CIAF), defined by combinations of child anthropometric failure. After accounting for risk factors, of the total variation in HAZ, 93.2 per cent, 4.9 per cent and 1.9 per cent were attributable to the individual, community and state levels, respectively. The observed risk factors explained 6.3 per cent and 46.9 per cent of the variation at the individual and community level, respectively; however, between-state variation was not explained by these risk factors. Variability in other measures of anthropometry and anthropometric failure largely followed this pattern. Additionally, there were also considerable differences in the amount of variation at the individual and community levels among different states. Hence, there is a substantial variability at the community level compared to the state level, suggesting the presence of micro-geographies of undernutrition. Additionally, while a substantial majority of the variation in child undernutrition is at the individual level, our ability to explain variability in undernutrition at the individual-level risk factors is extremely limited. Further research is needed to explore community level or environmental factors affecting child undernutrition, generating evidence for policies to target these determinants.

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.

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 score0.065
Threshold uncertainty score0.330

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 head0.027
GPT teacher head0.256
Teacher spread0.228 · 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