Determination of the exercise intensity that elicits maximal fat oxidation in individuals with obesity
Bibliographic record
Abstract
Maximal fat oxidation (MFO) and the exercise intensity that elicits MFO (FatMax) are commonly determined by indirect calorimetry during graded exercise tests in both obese and normal-weight individuals. However, no protocol has been validated in individuals with obesity. Thus, the aims were to develop a graded exercise protocol for determination of FatMax in individuals with obesity, and to test validity and inter-method reliability. Fat oxidation was assessed over a range of exercise intensities in 16 individuals (age: 28 (26–29) years; body mass index: 36 (35–38) kg·m−2; 95% confidence interval) on a cycle ergometer. The graded exercise protocol was validated against a short continuous exercise (SCE) protocol, in which FatMax was determined from fat oxidation at rest and during 10 min of continuous exercise at 35%, 50%, and 65% of maximal oxygen uptake. Intraclass and Pearson correlation coefficients between the protocols were 0.75 and 0.72 and within-subject coefficient of variation (CV) was 5 (3–7)%. A Bland−Altman plot revealed a bias of –3% points of maximal oxygen uptake (limits of agreement: –12 to 7). A tendency towards a systematic difference (p = 0.06) was observed, where FatMax occurred at 42 (40–44)% and 45 (43–47)% of maximal oxygen uptake with the graded and the SCE protocol, respectively. In conclusion, there was a high−excellent correlation and a low CV between the 2 protocols, suggesting that the graded exercise protocol has a high inter-method reliability. However, considerable intra-individual variation and a trend towards systematic difference between the protocols reveal that further optimization of the graded exercise protocol is needed to improve validity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| 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) | 0.000 | 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".