Updating normative cross-sectional values and secular trends in body mass, body height and body mass index among Québec children and adolescents
Bibliographic record
Abstract
OBJECTIVE: The main objective of this study was to examine secular trends in body mass, body height and body mass index (BMI) from measured rather than self-reported values between 1972 and 2017. METHODS: A total of 4500 students (males = 51%) were selected from a stratified sampling. The age range varied between 6.0 and 17.9 years. The sample came from 24 elementary schools and 12 high schools located in six urban cities from the province of Québec. All the tests selected were based on standardized procedures that are recognized as valid and reliable. Standardization and modeling of smoothed percentile curves for each variable for both sexes were produced. RESULTS: , i.e. 19.9%) with minor change in body height (~ 1.8 cm, i.e. 3.9%). Youth from low-income backgrounds (p = 0.001) as well as those living in large urban cities (p = 0.002) see their probability of developing overweight or obesity greatly increase (low-income = 2.1 times; large urban cities = 1.3 times). However, overweight and obesity rates seem to have stabilized at around 21% since 2004. CONCLUSION: This study provides up-to-date data on factors that contribute to the prevalence of overweight and obesity in youth in urban settings of Québec, and will be instrumental in guiding public health strategies designed to optimize growth outcomes.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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".