Association Between Exercise, Cardiorespiratory Fitness and Change in Insulin
Bibliographic record
Abstract
BACKGROUND: Cardiorespiratory fitness (CRF) is an established predictor of insulin sensitivity. Whether this association persists following control for exercise is unclear. PURPOSE: The primary objective of this study was to investigate the associations between changes in exercise, CRF and insulin sensitivity. METHODS: Participants were 140 middle aged [mean (standard deviation), 52.6 (7.7) yrs], abdominally obese (WC: 110.2 (11.5) cm), inactive adults that participated in a 24-week exercise trial. Exercise was performed 5 times per week for the duration of the trial. Exercise-induced energy expenditure (exercise EE) was determined using an individually adjusted heart rate to energy expenditure relationship for each exercise session. CRF was measured using a maximal treadmill test. Waist circumference (WC) was measured at the level of the iliac crest. Daily physical activity performed outside of the exercise sessions was measured by accelerometry. Caloric intake and diet composition was monitored using daily diet records. A 75-gram, 2-hour oral glucose tolerance test was used to determine insulin area under the curve (IAUC). RESULTS: Change in IAUC was associated (p 0.05). After further adjustment for change in WC, neither exercise EE (r = -0.16, p = 0.07) nor change in CRF (r = 0.03, p >0.10) were associated with change in IAUC. Change in WC was associated with IAUC (r = 0.35, p <0.001) independent of exercise EE and CRF. CONCLUSIONS: Exercise was associated with improvement in insulin sensitivity independent of change in CRF, whereas the opposite was not true.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".