Cardiometabolic risk improvement in response to a 3-yr lifestyle modification program in men: contribution of improved cardiorespiratory fitness vs. weight loss
Bibliographic record
Abstract
Our objective was to examine the respective contributions of changes in visceral adiposity, subcutaneous adiposity, liver fat, and cardiorespiratory fitness (CRF) to the improvements in cardiometabolic risk markers in response to a 3-yr healthy eating/physical activity lifestyle intervention. Ninety-four out of 144 viscerally obese healthy men completed a 3-yr lifestyle intervention. Body weight, body composition, and fat distribution were assessed by anthropometry and DEXA/computed tomography. CRF, adipokines, lipoprotein/lipid profile, and 75 g of oral glucose tolerance were assessed. CRF and visceral and subcutaneous adiposity significantly improved over the 3-yr intervention, with a nadir in year 1 and a partial regain in year 3. Liver fat (estimated by insulin hepatic extraction) stabilized from year 1 to year 3, whereas HOMA-IR, ISI-Matsuda index, and adiponectin continued to improve. Multivariate analysis revealed that both visceral adiposity and estimated liver fat reductions contributed to the improved ISI-Matsuda index observed over 3 yr ( r2= 0.28, P < 0.001). Three-year changes in fat mass and CRF were independently associated with changes in visceral fat (adjusted r2= 0.40, P < 0.001), whereas only changes in CRF were associated with changes in estimated liver fat (adjusted r2= 0.18, P < 0.001). A long-term (3 yr) healthy eating/physical activity intervention in men improves several cardiometabolic risk markers over the long term (3 yr) despite a partial body weight regain observed between year 1 and year 3. The improvement in CRF contributes to visceral and estimated liver fat losses over the long term, which in turn explain the benefits of the lifestyle intervention on cardiometabolic risk profile.
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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 | 0.001 |
| 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 | 0.000 | 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".