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Record W2054597671 · doi:10.3148/71.3.2010.115

Weight Status and Determinants of Health: In Manitoba Children and Youth

2010· article· en· W2054597671 on OpenAlexaffvenueabout
Bo Nancy Yu, Jennifer L. P. Protudjer, Kristin Anderson, Paul Fieldhouse

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2010
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of ManitobaManitoba Health
Fundersnot available
KeywordsOverweightObesityMedicineLogistic regressionEnvironmental healthGerontologyDemographyChildhood obesityScreen time

Abstract

fetched live from OpenAlex

PURPOSE: Because of the tremendous increase in overweight and obesity in Canadian children and youth in recent decades, we examined associations among health determinants, healthy living characteristics, and overweight and obesity in Manitoba children and youth. METHODS: Using descriptive statistics and logistic regression, we identified factors associated with measured overweight and obesity in a sample of 1651 Manitoba children and youth aged two to 17 years from the 2004 Canadian Community Health Survey 2.2-Nutrition. RESULTS: Thirty-one percent of the children and youth were overweight or obese. Males aged 12 to 17 or from food-insecure homes were more likely to be overweight or obese than were younger males or males from food-secure households. Females from households with higher parental education were less likely to be overweight or obese than were those from households with lower parental education. Female youth who were sedentary for at least three hours daily were more likely to be overweight or obese than were less sedentary female youth. A trend toward significance with overweight or obesity in youth was noted with levels of daily fruit and vegetable consumption and regular physical activity. CONCLUSIONS: Overweight and obesity in Manitoba children and youth are associated with socio-economic and demographic characteristics, and with food and activity behaviours. These findings can inform health and nutrition policy and practice by indicating health inequities that require particular attention.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.045
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.369
Teacher spread0.316 · 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 source (direct Gemma or distilled Codex), 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

Citations17
Published2010
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Dietetic Practice and ResearchSame topicObesity, Physical Activity, DietFrench-language works237,207