Alternating high-intensity interval training and continuous training is efficacious in improving cardiometabolic health in obese middle-aged men
Bibliographic record
Abstract
High-intensity interval training (HIIT) or moderate-intensity continuous training (MICT) alone has been shown to improve metabolic health, but the effects of alternating the two training approaches as often practiced in real life remained unclear. The purpose of the current study was to examine the effects of HIIT or MICT alone or alternating HIIT-MICT on cardiometabolic responses in inactive obese middle-aged men. Forty-two participants (age: 42 ± 5 y; BMI: 26.3 ± 2.1 kg m−2) were randomly assigned to four groups: HIIT (12 x 1-min running bouts at 80–90% HRmax interspersed with 1-min active recovery at 50% HRmax), MICT (40-min brisk walk at 65–70% HRmax), alternating HIIT-MICT or a non-exercise control group (CON). Exercise sessions were conducted three times per week for 16 weeks. Maximal oxygen uptake (VO2max), body composition (by bioelectrical impedance analysis), blood pressure, fasting blood glucose, insulin resistance (HOMA-IR) and lipid profile were assessed at baseline and after the 16-week intervention. Enjoyment and self-efficacy were also assessed at the end of intervention. All exercise groups showed a similar VO2max increase of ∼15% (HIIT: 34.3 ± 4.4 vs 39.1 ± 5.4; MICT: 34.9 ± 5.0 vs 39.4 ± 7.2; and alternating HIIT-MICT: 34.4 ± 5.0 vs 40.3 ± 4.6 mL kg−1min−1) compared to baseline and CON (all p < 0.05). Weight, BMI, % fat and waist circumference also showed similar reductions in all exercise groups compared to baseline and CON (all p < 0.05). No significant group difference was observed for all blood markers. Compared to baseline, total cholesterol decreased after HIIT-MICT, while HIIT significantly decreased fasting insulin level and improved insulin resistance (p < 0.05). Enjoyment, self-efficacy and adherence were similar among all exercise groups. HIIT or MICT alone or alternating HIIT-MICT similarly improve cardiovascular fitness and body composition in obese middle-aged men despite differences in total training volume and time commitment.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".