Impact of milk consumption on cardiometabolic risk in postmenopausal women with abdominal obesity
Bibliographic record
Abstract
BACKGROUND: The impact of dairy intake on cardiometabolic risk factors associated with metabolic syndrome (MetS) needs further research. OBJECTIVE: To investigate the impact of milk consumption on a wide array of cardiometabolic risk factors associated with MetS (blood lipids, cholesterol homeostasis, glucose homeostasis, systemic inflammation, blood pressure, endothelial function) in postmenopausal women with abdominal obesity. METHODS: In this randomized, crossover study, 27 women with abdominal obesity consumed two 6-week diets based on the National Cholesterol Education Program (NCEP), one with 3.2 servings/d of 2% fat milk per 2000 kcal (MILK) and one without milk or other dairy (NCEP). The macronutrient composition of both diets was comparable (55% carbohydrates, 15% proteins, 30% fat and 10% saturated fat). RESULTS: The MILK diet had no significant effect on LDL-C, triglycerides, LDL size, CRP and cell adhesion molecule concentrations and on indicators of insulin sensitivity. The MILK diet reduced HDL-C, adiponectin, endothelin and fasting glucose levels as well blood pressure (all P ≤ 0.01), but those changes were comparable to those seen with the NCEP milk-free diet (all between-diet P ≥ 0.07). Finally, the MILK diet was associated with lower VLDL apolipoprotein B fractional catabolic rate (-13.4%; P = 0.04) and plasma sterol concentrations (-12.0%; P = 0.04) compared with the control NCEP milk-free diet. CONCLUSIONS: These data suggest that short-term consumption of low fat milk in the context of a prudent NCEP diet has no favorable nor deleterious effect on cardiometabolic risk factors associated with MetS in postmenopausal women with abdominal obesity.
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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 | 0.000 |
| 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".