Comparison of a Low-Fat Diet to a Low-Carbohydrate Diet on Weight Loss, Body Composition, and Risk Factors for Diabetes and Cardiovascular Disease in Free-Living, Overweight Men and Women
Bibliographic record
Abstract
Overweight and obese men and women (24-61 yr of age) were recruited into a randomized trial to compare the effects of a low-fat (LF) vs. a low-carbohydrate (LC) diet on weight loss. Thirty-one subjects completed all 10 wk of the diet intervention (retention, 78%). Subjects on the LF diet consumed an average of 17.8% of energy from fat, compared with their habitual intake of 36.4%, and had a resulting energy restriction of 2540 kJ/d. Subjects on the LC diet consumed an average of 15.4% carbohydrate, compared with habitual intakes of about 50% carbohydrate, and had a resulting energy restriction of 3195 kJ/d. Both groups of subjects had significant weight loss over the 10 wk of diet intervention and nearly identical improvements in body weight and fat mass. LF subjects lost an average of 6.8 kg and had a decrease in body mass index of 2.2 kg/m2, compared with a loss of 7.0 kg and decrease in body mass index of 2.1 kg/m2 in the LC subjects. The LF group better preserved lean body mass when compared with the LC group; however, only the LC group had a significant decrease in circulating insulin concentrations. Group results indicated that the diets were equally effective in reducing systolic blood pressure by about 10 mm Hg and diastolic pressure by 5 mm Hg and decreasing plasminogen activator inhibitor-1 bioactivity. Blood beta-hydroxybutyrate concentrations were increased in the LC only, at the 2- and 4-wk time points. These data suggest that energy restriction achieved by a very LC diet is equally effective as a LF diet strategy for weight loss and decreasing body fat in overweight and obese adults.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".