Assessing the utility of cardiorespiratory fitness, visceral fat, and liver fat in predicting changes in insulin sensitivity beyond simple changes in body weight after exercise training in adolescents
Bibliographic record
Abstract
To examine the utility of changes in cardiorespiratory fitness (CRF) and body composition in response to exercise training in adolescents with obesity beyond simple measures of body weight change. This is a secondary analysis of our previously published randomized trials of aerobic, resistance, and combined training. We included 104 adolescents (body mass index (BMI) ≥85th percentile) who had complete baseline and post-intervention data for CRF, regional body fat, insulin sensitivity, and oral glucose tolerance. Associations between changes in body composition and CRF with cardiometabolic variables were examined adjusted for age, sex, Tanner stage, race, exercise group, and weight loss. At baseline, CRF, visceral fat and liver fat were correlated with insulin sensitivity with and without adjustment for BMI percentile. Training-associated changes in CRF, visceral fat, and liver fat were also correlated with insulin sensitivity changes, but not independent of body weight change. After accounting for body weight change, none of the body composition or CRF were associated with changes in insulin sensitivity, glucose tolerance, systolic blood pressure, or high-density lipoprotein cholesterol. Although CRF and body composition were strong independent correlates of insulin sensitivity at baseline, changes in CRF and visceral fat were not associated with changes in insulin sensitivity after accounting for body weight change. Clinicaltrials.gov registration nos.: NCT00739180, NCT01323088, NCT01938950. Novelty With exercise training, changes in body weight, CRF, visceral fat, and liver fat were correlated with changes in insulin sensitivity. Changes in body composition or CRF generally did not remain significant correlates of changes in insulin sensitivity after adjusting for body weight changes.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".