Fat oxidation over a range of exercise intensities: fitness versus fatness
Bibliographic record
Abstract
Maximal fat oxidation (MFO), as well as the exercise intensity at which it occurs (Fatmax), have been reported as lower in sedentary overweight individuals but have not been studied in trained overweight individuals. The aim of this study was to compare Fatmax and MFO in lean and overweight recreationally trained males matched for cardiorespiratory fitness (CRF) and to study the relationships between these variables, anthropometric characteristics, and CRF. Twelve recreationally trained overweight (high fatness (HiFat) group, 30.0% ± 5.3% body fat) and 12 lean males (low fatness (LoFat), 17.2% ± 5.7% body fat) matched for CRF (maximal oxygen consumption (V̇O2max) 39.0 ± 5.5 vs. 41.4 ± 7.6 mL·kg(-1)·min(-1), p = 0.31) and age (p = 0.93) performed a graded exercise test on a cycle ergometer. V̇O2max and fat and carbohydrate oxidation rates were determined using indirect calorimetry; Fatmax and MFO were determined with a mathematical model (SIN); and % body fat was assessed by air displacement plethysmography. MFO (0.38 ± 0.19 vs. 0.42 ± 0.16 g·min(-1), p = 0.58), Fatmax (46.7% ± 8.6% vs. 45.4% ± 7.2% V̇O2max, p = 0.71), and fat oxidation rates over a wide range of exercise intensities were not significantly different (p > 0.05) between HiFat and LoFat groups. In the overall cohort (n = 24), MFO and Fatmax were correlated with V̇O2max (r = 0.46, p = 0.02; r = 0.61, p = 0.002) but not with % body fat or body mass index (p > 0.05). Fat oxidation during exercise was similar in recreationally trained overweight and lean males matched for CRF. Consistently, substrate oxidation rates during exercise were not related to adiposity (% body fat) but were related to CRF. The benefits of high CRF independent of body weight and % body fat should be further highlighted in the management of 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) | 0.000 | 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".