Sprint interval and moderate-intensity cycling training differentially affect adiposity and aerobic capacity in overweight young-adult women
Bibliographic record
Abstract
The purpose of the study was to examine the effects of sprint interval training (SIT) and moderate-intensity continuous cycle training (MICT), with equal estimated energy expenditure during training on body composition and aerobic capacity. Body composition measured via dual-energy X-ray absorptiometry and aerobic capacity were assessed following 6 weeks of training in previously inactive overweight/obese young women (n = 52; age, 20.4 ± 1.5 years; body mass index, 30.3 ± 4.5 kg·m−2, 67.3% white). Training was performed in a group-exercise format that mimicked cycling classes offered by commercial fitness facilities, and included 3 weekly sessions of either 30-s “all-out” sprints followed by 4 min of active recovery (SIT), or continuous cycling at 60%–70% heart rate reserve to expend a similar amount of energy. Participants were randomized to SIT or MICT, attended a similar number of sessions (15.0 ± 1.5 sessions vs. 15.8 ± 1.9 sessions, P = 0.097) and expended a similar amount of energy (541.8 ± 104.6 kJ·session−1 vs. 553.5 ± 138.1 kJ·session−1, P = 0.250). Without significant changes in body mass (P > 0.05), greater relative reductions occurred in SIT than in MICT in total fat mass (3.6% ± 5.6% vs. 0.6% ± 3.9%, P = 0.007), and android fat mass (6.6% ± 6.9% vs. 0.7% ± 6.5%, P = 0.002). Aerobic capacity (mL·kg−1·min−1) increased significantly following both interventions (P < 0.05), but the relative increase was 2-fold greater in SIT than in MICT (14.09% ± 10.31% vs. 7.06% ± 7.81%, P < 0.001). In conclusion, sprint-interval cycling reduces adiposity and increases aerobic capacity more than continuous moderate-intensity cycling of equal estimated energy expenditure in overweight/obese young women.
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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) | 0.000 | 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".