Vigorous intensity physical activity is related to the metabolic syndrome independent of the physical activity dose
Bibliographic record
Abstract
BACKGROUND: Current physical activity guidelines imply that, by comparison with moderate physical activity (MPA), the benefits of engaging in vigorous physical activity (VPA) are attributed to the greater energy expenditure dose per unit of time and do not relate to intensity per se. The purpose of this study was to determine whether VPA influences the metabolic syndrome (MetS) independent of its influence on the energy expenditure dose of moderate-to-vigorous physical activity (MVPA). METHODS: Participants consisted of 1841 adults from the 2003-06 National Health and Nutrition Examination Survey, a representative cross-sectional study. MPA and VPA were measured objectively over 7 days using Actigraph accelerometers. MetS was determined using an established clinical definition. Associations between physical activity and the MetS were determined using logistic regression and controlled for relevant covariates. RESULTS: Analyses revealed that VPA remained a meaningful predictor of the MetS after controlling for the total energy expenditure dose of MVPA such that the relative odds of the MetS was 0.28 (95% confidence interval 0.17-0.46) in the group with the highest VPA compared with the group with no VPA. VPA had a greater influence on the MetS than an equivalent energy expenditure dose of MPA. For instance, between 0 and 500 MET min/week of MPA the adjusted prevalence of the MetS decreased by 15.5%, whereas between 0 and 500 MET min/week of VPA the prevalence decreased by 37.1%. CONCLUSION: These cross-sectional findings suggest that VPA per se has an important role in cardiometabolic disease prevention.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".