Trajectories of cardiorespiratory fitness from childhood to adolescence: Findings from the QUALITY cohort
Bibliographic record
Abstract
Estimate the shape and number of cardiorespiratory fitness (CRF) trajectories from childhood to adolescence; and verify whether CRF trajectory membership can be predicted by sex, biological maturation, body weight, body composition and physical activity (PA) in childhood. Data from QUALITY were used. Participants attended baseline (8–10 y old, n = 630) and follow-ups 2 years (n = 564) and 7 years (n = 359) after baseline. Group-based trajectory analysis for relative peak oxygen consumption (VO2peak, ml·kg−1·min−1) was performed. A multinomial logistic regression model was used to estimate the associations between baseline predictors and trajectory membership. Mean age of the 454 participants was 9.7 ± 0.9 years at baseline. Three distinct VO2peak trajectories were identified and all tended to decrease. They were labelled according to the starting point and slope. High-Decreasers were mostly boys, had lower body weight and fat-free mass index and higher PA levels at baseline (p < 0.05). Female sex and higher weight were associated with higher odds of being classified in the Low-Decreaser trajectory (OR = 74.03, 95%CI = 27.06–202.54; OR = 1.48, 95%CI = 1.36–1.60). Those with higher PA were less likely to be Low-Decreasers (OR = 0.96, 95%CI = 0.94–0.97). Sex, body weight and PA in childhood are important influencing factors of VO2peak (ml·kg−1·min−1) trajectories across adolescence.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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".