Effects of an Energy-Restrictive Diet With or Without Exercise on Abdominal Fat, Intermuscular Fat, and Metabolic Risk Factors in Obese Women
Bibliographic record
Abstract
OBJECTIVE: The primary objective was to examine whether the combination of diet and aerobic exercise (DA) or diet and resistance exercise (DR) is associated with greater improvements in metabolic risk factors by comparison to diet only (DO) in obese women. A second objective considered whether reductions in metabolic risk factors are related to concurrent changes in abdominal and/or intermuscular fat distribution. RESEARCH DESIGN AND METHODS: A total of 38 premenopausal obese women were randomly assigned to one of three 16-week treatments: DO (n=13), DA (n=11), or DR (n=14). Plasma glucose, insulin, and lipid levels were measured in a fasting state and after a 75-g oral glucose challenge (oral glucose tolerance test [OGTT]). Total, abdominal subcutaneous, visceral, and intermuscular fat were measured by magnetic resonance imaging. RESULTS: Significant reductions (P < 0.02) in body weight (approximately 10 kg or 10%) and in total, abdominal subcutaneous, visceral, and intermuscular fat were observed within each group. Fasting and OGTT insulin, total cholesterol, LDL cholesterol, and apolipoprotein B also decreased within each group (P < or = 0.02). The changes in the body fat and metabolic variables were not different across treatment (P > 0.05). Visceral fat alone was related to the metabolic risk factors both before and after the treatment. CONCLUSIONS: Weight loss was associated with reductions in metabolic risk factors in obese women. The improvement in the metabolic profile was not enhanced by the addition of aerobic or resistance exercise. The findings reinforce the importance of diminished visceral fat in the treatment of insulin resistance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".