Association of cardiorespiratory fitness levels with dietary habits and lifestyle factors in schoolchildren
Bibliographic record
Abstract
This study examined the association between cardiorespiratory fitness (CRF) levels and lifestyle factors in a representative sample of Greek schoolchildren. In 2015, a health survey was carried out in 177 091 participants 8-17 years of age. Dietary habits, sleeping hours, physical activity (PA), and sedentary activities were assessed through self-completed questionnaires. CRF was evaluated with a 20-m shuttle run test. Insufficient dietary habits were greater in boys and girls classified as having low CRF than in their peers with healthy CRF. Skipping breakfast (odds ratio (OR), 0.82; 95% confidence interval (CI) 0.79-0.85), fast food consumption (OR, 0.70; 95% CI 0.68-0.72), and regular sweet intake (OR, 0.79; 95% CI 0.76-0.82) decreased the odds of having a healthy CRF level. An increase in age by 1 year (OR, 0.71; 95% CI, 0.70-0.72), overweight/obesity (OR, 0.30; 95% CI 0.29-0.31), and insufficient sleep duration (OR, 0.74; 95% CI 0.72-0.76) decreased the odds of a healthy CRF level, whereas sufficient dietary habits and adequate PA levels increased a participant's odds of having a healthy CRF level, by 48% and 40%, respectively. Although the mechanisms via which CRF may be influenced by dietary habits remain unclear, health policy-makers should consider opportunities for improving both CRF and dietary habits.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".