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Record W1994573867 · doi:10.1017/s1368980010000406

Emerging obesity and dietary habits among James Bay Cree youth

2010· article· en· W1994573867 on OpenAlexafffundabout
Cynthia Bou Khalil, Louise Johnson‐Down, Grace M. Egeland

Bibliographic record

VenuePublic Health Nutrition · 2010
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsMcGill University
FundersNiskamoon Corporation
KeywordsOverweightObesityEnvironmental healthAdded sugarMedicineSugarPopulationConsumption (sociology)Food scienceFood frequency questionnaireRefined grainsGerontologyWhole grainsBiologyEndocrinology

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe dietary habits and extent of overweight and obesity among Cree youth. DESIGN: Dietary intake and habits were assessed by a 24 h recall and FFQ as part of a cross-sectional survey. SETTING: Three Cree communities in northern Québec, Canada. SUBJECTS: A total of 125 youth aged 9-18 years. RESULTS: Overall 67·6 % of the study population was either at risk of overweight or overweight. Over 98 % had a usual saturated fat intake over 10 % of energy while 65 % had a lower consumption of fruit/vegetables and 95 % had a lower consumption of milk and milk products than recommended by Canada's Food Guide. The majority (96·8 %) consumed high-fat foods (>40 % of total energy as fat), which accounted for 39 % of total energy intake (EI). Similarly, 92·8 % consumed high-sugar food and beverages (>25 % of total energy as sugar), which accounted for 12·8 % of total EI. Furthermore, 95 % of the youth had a Healthy Eating Index (HEI) below the recommended score of 80 or above. Certain measures of diet quality (traditional food (TF) consumption, HEI and vegetables and fruit consumption) were significantly correlated with adiposity measures. CONCLUSIONS: A high prevalence of low-diet quality was found with a high degree of sugar and fat intake and a low consumption of vegetables/fruit and milk/milk alternates and any weekly TF. Dietary interventions are sorely needed.

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 score0.029
Threshold uncertainty score0.752

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.294
Teacher spread0.262 · 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

Citations35
Published2010
Admission routes3
Has abstractyes

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