Framingham 10-year Risk Score, Energy Expenditure And The Metabolic Profile In Inactive Obese Postmenopausal Women.
Bibliographic record
Abstract
PURPOSE: To compare inactive obese postmenopausal women displaying lower vs higher Framingham 10-Year Risk Score for body composition, metabolic profile, inflammatory markers and daily energy expenditure. METHODS: 132 postmenopausal women (age: 57.6 ± 4.8 yrs; BMI: 32.3 ± 4.6 kg/m2) were studied. Subjects were first divided into tertiles based on the Framingham 10-Year Risk Score. Subjects in the second tertile (3.2% to 5%) were combined with those in the third one (> 5%), and then compared with those in the first tertile (< 3.2%). Variables of interest were: body composition (DXA), body fat distribution (CT scan), glucose homeostasis (fasting state and euglycemic/hyperinsulinemic clamp), fasting lipids, resting blood pressure, inflammatory markers, resting metabolic rate (indirect calorimetry), and energy expenditure (DLW). RESULTS: A significant difference was found between groups for age. No significant difference was observed between groups for body composition, body fat distribution and glucose homeostasis measures and inflammatory markers. Compared to women with the higher score, those in the first tertile showed significant higher values for physical activity levels (2.01 ± 0.28 vs 1.84 ± 0.25; p= 0.005), daily physical activity energy expenditure (1027 ± 281 vs 864 ± 283 kcal/d; p= 0.03) and resting metabolic rate (1284 ± 173 vs 1335 ± 189 kcal/d; p= 0.03). Also, women in the first tertile had lower values for plasma triglycerides (1.39 ± 0.49 vs 1.79 ± 0.80 mmol/L; p< 0.001), total cholesterol/HDL-cholesterol ratio (3.52 ± 0.70 vs 3.95 ± 0.88; p< 0.001), and triglycerides/HDL-cholesterol ratio (0.93 ± 0.43 vs 1.37 ± 0.76; p< 0.001). These differences were still significant after controlling for age. CONCLUSIONS: The present study showed that, even in women displaying an overall low Framingham Score, those with the lowest score also displayed higher physical activity levels and daily physical activity energy expenditure, as well as a better lipid profile.
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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) | 0.000 | 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) | 0.001 | 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".