The association between physical fitness and health in a nationally representative sample of Canadian children and youth aged 6 to 17 years
Bibliographic record
Abstract
INTRODUCTION: This study explored the relationship between physical fitness and indicators of physical and psychosocial health in a nationally representative sample of Canadian children and youth aged 6-17 years. METHODS: We conducted a secondary data analysis of Canadian Health Measures Survey (Cycles 1 and 2; 2007-2011) data. The physical fitness measures included cardiorespiratory fitness (CRF; modified Canadian Aerobic Fitness Test), strength (handgrip strength), flexibility (sit-and-reach), and muscular endurance (partial curl-ups). The physical health indicators included directly measured biomarkers (total and HDL [high-density lipoprotein] cholesterol, C-reactive protein, glucose, and HbA1c [glycohaemoglobin]) and measures of adiposity, resting heart rate, and blood pressure. Psychosocial health was assessed using the Strengths and Difficulties Questionnaire. Multiple linear regressions were used to determine the association between variables, stratified by age groups and sex. RESULTS: 3,800 (48.9% female) children and youth were retained for this analysis. CRF displayed significant favourable associations with most physical health indicators in male and female participants. There were less significant favourable associations with flexibility and muscular endurance compared with CRF across age and sex groups. Strength was associated with higher adiposity in males and females, and lower heart rate in male children (β = -1.9; 95% CI: -2.9, -1.0) and female youth (β = -2.0; 95% CI: -2.7, -1.2). There were few significant favourable associations between measures of physical fitness and psychosocial health in this sample of children and youth. CONCLUSION: These findings suggest that physical fitness, and especially CRF, is a significant indicator of physical health among Canadian children and youth aged 6-17 years.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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".