Impact of milk consumption on cardiometabolic risk in postmenopausal women with abdominal obesity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 it