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Record W2787193025 · doi:10.1111/mcn.12557

Nutritional status, food insecurity, and biodiversity among the<scp>K</scp>hasi in<scp>M</scp>eghalaya,<scp>N</scp>orth‐East<scp>I</scp>ndia

2017· article· en· W2787193025 on OpenAlexaff
Daniella Anne L. Chyne, Indrapal I. Meshram, Ananthan Rajendran, Venkaiah Kodali, Neeraja Getti, Phrang Roy, Harriet V. Kuhnlein, T. Longvah

Bibliographic record

VenueMaternal and Child Nutrition · 2017
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsMedicineWastingUnderweightMalnutritionEnvironmental healthAnthropometrySocioeconomic statusFood securityPopulationPublic healthAgricultureObesityGeographyOverweight

Abstract

fetched live from OpenAlex

A community-based cross-sectional study was carried out with 603 children ages 5 and under and 500 of their mothers from 510 households to examine the prevalence of undernutrition and chronic diseases among the Khasis of North-East India. Anthropometric measurements including Mid-Upper Arm Circumference, height, and weight were taken. Dry blood spots to estimate haemoglobin and vitamin A were collected from children and women separately by finger prick. Mothers provided data about household socio-demographic particulars and infant and young child feeding practices. The prevalence in children of underweight was 31%, stunting was 57%, and wasting was 10%. Undernutrition was higher among boys as compared to girls. Nutrient intakes were below recommended levels. The prevalence of anaemia among children ages 1 to 5 years old was 68%, and vitamin A deficiency was 59%, and they were 83% and 48%, respectively, among women. Hypertension was observed in 15% of women, whereas diabetes was less than 1%. Only about 20% of households were food secure, and this was associated with parental literacy, per capita income, and family size. Undernutrition was unacceptably high among the Khasis despite rich food biodiversity. Proper implementation of nutritional intervention programs such as Integrated Child Development Services, Mid Day Meal, and the Public Distribution System will improve the nutrient intake and nutritional status of the population. Additionally, preservation of forest lands and products paired with judicious use of the rich food biodiversity available will promote dietary diversity and ultimately better nutrition and health.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.013
GPT teacher head0.222
Teacher spread0.209 · 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.

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

Citations48
Published2017
Admission routes1
Has abstractyes

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