Moderate-Intensity Exercise and High-Intensity Interval Training Affect Insulin Sensitivity Similarly in Obese Adults
Bibliographic record
Abstract
OBJECTIVE: We compared the effects of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on insulin sensitivity and other important metabolic adaptations in adults with obesity. METHODS: Thirty-one inactive adults with obesity (age: 31 ± 6 years; body mass index: 33 ± 3 kg/m2) completed 12 weeks (4 sessions/week) of either HIIT (10 × 1-minute at 90%HRmax, 1-minute active recovery; n = 16) or MICT (45 minutes at 70%HRmax; n = 15). To assess the direct effects of exercise independent of weight/fat loss, participants were required to maintain body mass. RESULTS: Training increased peak oxygen uptake by ~10% in both HIIT and MICT (P < 0.0001), and body weight/fat mass were unchanged. Peripheral insulin sensitivity (hyperinsulinemic-euglycemic clamp) was ~20% greater the day after the final exercise session compared to pretraining (P < 0.01), with no difference between HIIT and MICT. When trained participants abstained from exercise for 4 days, insulin sensitivity returned to pretraining levels in both groups. HIIT and MICT also induced similar increases in abundance of many skeletal muscle proteins involved in mitochondrial respiration and lipid and carbohydrate metabolism. Training-induced alterations in muscle lipid profile were also similar between groups. CONCLUSION: Despite large differences in training intensity and exercise time, 12 weeks of HIIT and MICT induce similar acute improvements in peripheral insulin sensitivity the day after exercise, and similar longer term metabolic adaptations in skeletal muscle in adults with obesity. These findings support the notion that the insulin-sensitizing effects of both HIIT and MICT are mediated by factors stemming from the most recent exercise session(s) rather than adaptations that accrue with training.
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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) | 0.000 | 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) | 0.002 | 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".