Influence of Movement Intensity and Physical Activity on Adiposity in Youth
Bibliographic record
Abstract
BACKGROUND: Despite the plethora of research examining the physical activity-adiposity relation in youth, questions remain regarding the ideal intensity. Therefore, the purpose of this study was to explore the independent effects of physical activity intensity and incidental movement on total and trunk adiposity. METHODS: The sample consisted of 1165 youth aged 8 to 17 years from the 2003-04 U.S. National Health and Nutrition Examination Survey. Physical activity (low, moderate, vigorous intensity) and incidental movement (activity level when not physically active) were measured using Actigraph accelerometers over 7 days. Total body and trunk fat were measured using dual-energy X-ray absorptiometry; age- and sex-specific percentile scores were calculated. RESULTS: Bivariate analyses revealed an inverse relation between total, low, moderate and vigorous intensity physical activity with total body and trunk fat. After consideration of the total volume of physical activity in the multivariate analyses, moderate-to-vigorous intensity physical activity remained significantly related to total and trunk fat. Participants with the highest (top 12.5%) moderate-to-vigorous intensity activity values had total fat percentile scores that were 34 points lower than participants with the lowest (bottom 25%) values. CONCLUSION: These results are consistent with public health guidelines which recommend that children and youth participate in moderate-to-vigorous intensity physical activity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".