A comparison of the energy expenditure between weight supported and unsupported exercise in obesity
Bibliographic record
Abstract
Background Weight loss is better achieved by a combination of diet and exercise. We hypothesised that obese individuals may be able to endure cycling (weight supported) for longer than walking (weight unsupported). We therefore investigated whether weight supported or unsupported exercise was associated with greater energy expenditure in obese individuals. Methods Individuals were recruited from a sleep clinic with a BMI > 30 kg/m2 and treated obstructive sleep apnoea. Patients with pulmonary or cardiac disease were excluded. On separate days in a randomised order, participants performed an incremental cardiopulmonary exercise test on a cycle ergometer (CE) and a treadmill (TM) with expired gas analysis to determine the peak oxygen uptake (VO2pk). Two endurance tests were performed on each modality matched at 80% and 60% of the highest VO2 pk determined by the incremental tests. The total energy expenditure during each endurance test was calculated from the total oxygen uptake. Results 12 participants completed all six tests: 7 male, mean [SD] age 57 [14] y, BMI 34.5 [7.1] kg/m2. The peak VO2 on the TM vs CE was 2275 [522] vs 1791 [390] ml/min, respectively. Table one shows the duration (tlimit) and energy expenditure at 80 and 60% VO2 pk on the TM and CE. View this table: Table 1 Conclusion In obese individuals, treadmill walking (weight unsupported) at a matched metabolic intensity led to significantly higher total energy expenditure than cycling.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".