Metabolic Effect of Breaking Up Prolonged Sitting with Stair Climbing Exercise Snacks
Bibliographic record
Abstract
PURPOSE: Prolonged sitting is associated with cardiometabolic complications. The study purpose was to investigate whether breaking up prolonged sitting with brief stair climbing exercise "snacks" could lower postprandial insulin, glucose, and free fatty acids responses. METHODS: In two separate randomized crossover studies, 12 young healthy-weight men (study 1) and 11 adults with overweight/obesity (OW; study 2) completed two experimental conditions: i) sedentary (SED; 9-h sitting) and ii) stair climbing snacks (SS; 8 × 15-30 s once per hour). The same high-glycemic index meals were consumed at 0, 3, and 6 h at each condition. The primary outcome was total insulin area under the curve (AUC) across 9 h. RESULTS: In healthy-weight men, there were no significant differences between SS and SED for total (9-h) insulin AUC (P = 0.24, d = 0.4), total glucose AUC (P = 0.17, d = 0.48), total nonesterified fatty acid (NEFA) AUC (P = 0.22, d = 0.4), or total triglyceride AUC (P = 0.72). In adults with OW, total insulin AUC (-16.5%, P = 0.036, d = 0.94) and total NEFA AUC (-21%, P = 0.016, d = 1.2) were significantly lower in SS versus SED. No differences were found for total glucose and triglyceride AUC (all, P > 0.31) in participants with OW. CONCLUSIONS: Breaking up 9 h of prolonged sitting with hourly brief stair climbing exercise snacks lowered postprandial insulin and NEFA levels in adults with overweight/obesity.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".