Prevalence Estimates of Overweight and Obesity in Cree Preschool Children in Northern Quebec According to International and US Reference Criteria
Bibliographic record
Abstract
OBJECTIVES: We estimated the prevalence of overweight and obesity in Cree Canadian children aged 5 years (n=1044) using international and US growth references and examined the longitudinal tracking of weight categories between ages 2 and 5 years (n=562). METHODS: Weight categories based on body mass index (calculated from measured heights and weights) were derived from the International Obesity Task Force (IOTF) and the Centers for Disease Control and Prevention (CDC) references. RESULTS: According to the IOTF reference, 52.9% of children were overweight (31.6%) or obese (21.3%) whereas with the CDC reference, 64.9% were overweight (27.5%) or obese (37.4%). The IOTF and CDC references provided dissimilar tracking of weight categories. Based on the IOTF reference, 4.9% of the children who were normal weight at age 2 years were obese at age 5 years. Based on the CDC reference, 14.9% of children categorized as normal weight at age 2 years were obese at age 5 years. CONCLUSIONS: The IOTF reference provided more conservative estimates of obesity than the CDC reference, and longitudinal analyses showed dissimilar tracking of weight categories with the 2 references. Public health responses to obesity prevalence estimates should be made with awareness of methodological limitations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".