A Canadian longitudinal study of the associations between weight control status and lifestyle behaviors during adolescence
Bibliographic record
Abstract
This study aimed to estimate associations between weight control status (trying to lose, gain or maintain weight) and lifestyle behaviors (moderate-to-vigorous physical activity (MVPA), screen time, and the consumption of breakfast, fast food, fruits and vegetables, and sugar-sweetened beverages (SSB)) in adolescents. Data from 919 adolescents in the MATCH study, in New Brunswick, Canada, who self-reported their weight control status at least once within 24 data collection cycles over 8 years (from 2011 to 2019) and from 812 who provided data at least once over the 7 cycles on eating behaviors were used. Generalized estimating equations were used. At the first cycle, mean age was 11.3 (SD = 1.2) years old and 56% were girls. Trying to gain (β = 0.47, CI = [0.15, 0.79]) and maintain weight (β = 0.35, CI = [0.12, 0.57]) were positively associated with MVPA. Trying to lose weight was negatively associated with breakfast (IRR = 0.90, CI = [0.85, 0.94]) and positively associated with screen time (β = 0.62, CI = [0.15, 1.10]), fruit and vegetable (IRR = 1.12, CI = [1.01, 1.25]) and SSB (IRR = 1.42, CI = [1.10, 1.84]). Changes from one weight control status to trying to lose weight were associated with increases in fast food consumption (β = 0.49, CI = [0.15, 0.84]). Weight control status was associated with healthy and unhealthy behaviors in adolescents. Trying to gain or maintain weight was generally associated with more favorable health-related behaviors. Education on healthy weight management behaviors is needed to improve adolescents' health.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".