RELATIONSHIP BETWEEN PHYSICAL ACTIVITY AND AEROBIC FITNESS IN CHILDREN
Bibliographic record
Abstract
Accelerometers and/or heart rate monitors have been used to evaluate physical activities in children, using sampling periods of 1-min or longer. However, children's activities are often characterized by very short bursts (3–6 sec). Sampling of longer duration may, therefore, underestimate activities of a short-intense nature. This may be one of the reasons that the relationships between physical activity and aerobic fitness are not clear. PURPOSE To assess the relationship between physical activity and aerobic fitness in children, based on analysis of short-duration accelerometry sampling. METHODS Subjects were 57 boys and 55 girls aged 10 to 11 years. A multistage 20-metre shuttle run test (20-MST) was carried out according to a previously reported method. The total laps of running back and forth were taken as an index of aerobic fitness. Using a single axis accelerometer (Lifecoder, Suzuken), the physical activities were evaluated every 4 seconds on three weekdays. Levels 8 and 9 of accelerometer output, as recorded by this apparatus, were considered a “vigorous” activity, which corresponded to at least 30 ml¥kg-1¥min-1 of oxygen uptake, based on previous determination on a treadmill. Time spent on vigorous activities was accumulated each day. RESULTS Mean values and standard deviations of the laps in the 20-MST were 60.8 ± 20.6 and 43.7 ± 14.4 in boys and girls, respectively. Accumulated daily vigorous activities were 13.6 ± 6.2 min in boys and 8.6 ± 5.6 min in girls. These gender differences are significant. The vigorous activities significantly correlated with the total laps in the 20-MST (r = 0.51 and 0.52 in boys and girls, respectively). CONCLUSION Short-term vigorous physical activities moderately relate to aerobic fitness in both boys and girls.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".