Energy Expenditure from Physical Activity and the Metabolic Risk Profile at Menopause
Bibliographic record
Abstract
PURPOSE: A sedentary lifestyle and visceral obesity are important risk factors for Type 2 diabetes and the development of cardiovascular disease, two conditions that are prevalent in women after menopause. The aim of this study was to assess the relationship between daily energy expenditure from moderate to intense physical activity and several metabolic parameters in postmenopausal women not receiving hormone therapy (HT) and to verify whether these associations are independent of the accumulation of visceral adipose tissue (AT). METHODS: Daily energy expenditure and frequency of participation in physical activity (kcal.kg(-1).15 min(-1)) were measured from a 3-d activity diary in 118 postmenopausal women (56 +/- 4 yr; 29 +/- 6 kg.m(-2)). Daily activities for each 15-min period during 24 h were categorized according to their intensity on a 1-9 scale. Category 1 indicated very low energy expenditure such as sleeping, and category 9 indicated very high energy expenditure such as running. Energy expenditure corresponding to categories 6-9 (EE6-9) was examined in relation to the metabolic risk profile. RESULTS: EE6-9 was negatively and significantly associated with body mass index (BMI) (r = -0.22, P < 0.05) and visceral AT accumulation (r = -0.18, P < 0.05). Partial correlation analyses adjusted for visceral AT showed that EE6-9 was significantly associated with systolic blood pressure (r = -0.22, P < 0.05), plasma concentrations of HDL-cholesterol (chol) (r = 0.23, P < 0.05), HDL2-chol (r = 0.22, P < 0.05), fasting glucose (r = -0.24, P < 0.05), and fasting C-peptide (r = -0.24, P = or <0.05). EE6-9 was also associated with insulin sensitivity as measured by the hyperinsulinemic-euglycemic clamp (r = 0.27, P < 0.01). CONCLUSIONS: Higher engagement in physical activity (EE6-9) is associated with a lower BMI and visceral AT accumulation and with a healthier metabolic profile in postmenopausal women. Furthermore, the associations between EE6-9 and some metabolic parameters appear to be independent of visceral AT accumulation.
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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".