Obesity in a provincial population of Canadian preschool children: Differences between 1984 and 1997 birth cohorts
Bibliographic record
Abstract
OBJECTIVE: To determine whether trends of increasing overweight and obesity reported for older children and adults are evident in Canadian preschoolers. METHODS: A sample of 3857 preschool-aged children (51.1% boys) in the Province of Newfoundland and Labrador, born in 1984 and measured in 1987-1989, was selected from government archival records. The sample of 4161 children (50.1% boys), born in 1997 and measured in 2000-2002, was obtained from regional health authority records. Body mass index (BMI) was calculated using heights and weights measured by nurses. Overweight and obesity prevalence was estimated according to the International Obesity Task Force (IOTF) and the Centres for Disease Control (CDC) methods. RESULTS: Combined rates of overweight and obesity were significantly higher in preschoolers born in 1997 (25.6% IOTF and 36.0% CDC) than in 1984 (16.9% IOTF and 25.1% CDC), when levels were already high. There were some differences between sexes and classification systems. CONCLUSION: The relatively rapid rise in overweight and obesity in children as young as 3.5 years, in little more than a decade, underscores the immediate need for monitoring, and implementation of effective interventions. Overweight and obesity in preschool children is not new, but has become increasingly prevalent, and requires population-based strategies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".