Low-Fat Versus Low-Carbohydrate Weight Reduction Diets
Bibliographic record
Abstract
OBJECTIVE: Low-fat hypocaloric diets reduce insulin resistance and prevent type 2 diabetes in those at risk. Low-carbohydrate, high-fat diets are advocated as an alternative, but reciprocal increases in dietary fat may have detrimental effects on insulin resistance and offset the benefits of weight reduction. RESEARCH DESIGN AND METHODS: We investigated a low-fat (20% fat, 60% carbohydrate) versus a low-carbohydrate (60% fat, 20% carbohydrate) weight reduction diet in 24 overweight/obese subjects ([mean +/- SD] BMI 33.6 +/- 3.7 kg/m(2), aged 39 +/- 10 years) in an 8-week randomized controlled trial. All food was weighed and distributed, and intake was calculated to produce a 500 kcal/day energy deficit. Insulin action was assessed by the euglycemic clamp and insulin secretion by meal tolerance test. Body composition, adipokine levels, and vascular compliance by pulse-wave analysis were also measured. RESULTS: Significant weight loss occurred in both groups (P < 0.01), with no difference between groups (P = 0.40). Peripheral glucose uptake increased, but there was no difference between groups (P = 0.28), and suppression of endogenous glucose production was also similar between groups. Meal tolerance-related insulin secretion decreased with weight loss with no difference between groups (P = 0.71). The change in overall systemic arterial stiffness was, however, significantly different between diets (P = 0.04); this reflected a significant decrease in augmentation index following the low-fat diet, compared with a nonsignificant increase within the low-carbohydrate group. CONCLUSIONS: This study demonstrates comparable effects on insulin resistance of low-fat and low-carbohydrate diets independent of macronutrient content. The difference in augmentation index may imply a negative effect of low-carbohydrate diets on vascular risk.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".