MétaCan
Menu
← Back to cohort
Record W2275235033

Parent and child factors associated with youth obesity.

2003· article· en· W2275235033 on OpenAlexaffabout
Gisèle Carrière

Bibliographic record

VenuePubMed · 2003
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsAboriginal Affairs Northern Dev CanadaStatistics Canada
Fundersnot available
KeywordsOddsObesityBody mass indexLogistic regressionOdds ratioDemographyMedicineCommunity healthChildhood obesityCross-sectional studyGerontologyPsychologyPublic healthOverweightEndocrinologySociology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVES: This article examines relationships between parent and adolescent weight, as well as other selected characteristics and health behaviours of both, and then explores which factors are associated with youth obesity. DATA SOURCE: The analysis is based on cross-sectional household data from cycle 1.1 of the 2000/01 Canadian Community Health Survey (CCHS), conducted by Statistics Canada. The sample comprises 4,803 girls and 4,982 boys who were aged 12 to 19 in 2000/01. ANALYTICAL TECHNIQUES: Estimates of body mass index (BMI) were calculated and selected health behaviours were evaluated for adolescents and a parent who lived in the same household. Multiple logistic regression was used to identify factors associated with youth obesity while controlling for age of the youth and the sex of the reporting parent. MAIN RESULTS: For both sexes, having an obese parent greatly increased the odds for youth obesity. Among girls, former smokers had higher odds for obesity, but smoking behaviour was not associated with obesity for boys. For boys, being physically inactive or even moderately active increased the odds of obesity. And if the responding parent smoked daily, this increased the odds of obesity for boys.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.017
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.032
GPT teacher head0.221
Teacher spread0.189 · 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

Citations32
Published2003
Admission routes2
Has abstractyes

Explore more

Same venuePubMed→Same topicObesity, Physical Activity, Diet→French-language works237,207→