Functional capacity depends on lower limb muscle strength rather than on abdominal obesity in active postmenopausal women
Bibliographic record
Abstract
OBJECTIVE: An association has been found between abdominal obesity and functional capacity (FC) in the literature where waist circumference has been used to infer abdominal obesity. However, most studies focused on evaluating predictors of FC and functional disabilities only in sedentary people. This study aimed to examine whether abdominal obesity is associated with FC in physically active postmenopausal women. METHODS: Forty-four active (>7,500 steps/d) postmenopausal women were recruited. Body composition and distribution (DXA), FC (chair-stand/alternate-step/one-leg-stance), handgrip strength and knee extensor strength (dynamometry), steps/d (accelerometer), and cardiorespiratory function (spirometry/VO2max) were measured. The cohort was divided into groups based on a FC score (1-4 scale using quartiles). Pearson's correlation, t test, and linear regression were applied using SPSS (17.0). RESULTS: There was no correlation for body composition or BMI with FC score. However, waist circumference (r = -0.34, P = 0.024), handgrip (r = 0.32, P = 0.036), knee extensor strength (r = 0.43, P = 0.003), and VO2max (r = 0.41, P = 0.006) were significantly correlated with FC score. In addition, when the highest quartile group was compared with the lowest one, a significant difference was observed for knee extensor strength (P = 0.003), which was also the only variable inserted into the FC prediction equation derived from the stepwise regression model (r = 0.19, F = 9.582, P = 0.003). CONCLUSIONS: Our results demonstrate an association between abdominal obesity and FC in active postmenopausal women and that the strongest association and the best predictor of FC was lower limb muscle strength. Thus, active postmenopausal women with abdominal obesity may not necessarily have a reduced FC if lower limb muscle strength is preserved.
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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) | 0.002 | 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".