Association between cardiorespiratory fitness and metabolic risk factors in a population with mild to severe obesity
Bibliographic record
Abstract
Previous literature suggests the beneficial effects of fitness on abdominal obesity may be attenuated in obesity and abolished in severe obesity. It is unclear whether the beneficial association between fitness and health is similarly present in those with mild and severe obesity. Patients from the Wharton Medical Clinic ( n = 853) completed a clinical examination and maximal treadmill test. Patients were categorized into fit and unfit based on age- and sex-categories and body mass index (BMI) class (mild: ≤ 34.9 kg/m 2 , moderate: 35–39.9 kg/m 2 or severe obesity: ≥ 40 kg/m 2 ). Within the sample, 41% of participants with mild obesity had high fitness whereas only 25% and 11% of the participants with moderate and severe obesity, respectively, had high fitness. BMI category was independently associated with most of the metabolic risk factors, while fitness was only independently associated with systolic blood pressure and triglycerides ( P < 0.05). The prevalent relative risk for pre-clinical hypertension, hypertriglyceridemia and hypoalphalipoproteinemia and pre-diabetes was only elevated in the unfit moderate and severe obesity groups ( P < 0.05), and fitness groups were only significantly different in their relative risk for prevalent pre-clinical hypertension within the severe obesity group ( p = 0.03). High fitness was associated with smaller waist circumferences, with differences between high and low fitness being larger in those with severe obesity than mild obesity (Men: P = 0.06, Women: P = 0.0005). Thus, in contrast to previous observations, the favourable associations of having high fitness and health may be similar if not augmented in individuals with severe compared to mild 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".