Is functional capacity related to the daily amount of steps in postmenopausal women?
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to investigate the relationship between functional capacity, muscle function, and daily step count in postmenopausal women. METHODS: Fifty-seven postmenopausal women aged 50 to 70 years were recruited. Body composition (body weight, body mass index, fat mass, and skeletal muscle mass), energetic metabolism (maximal oxygen consumption, total energy expenditure, daily step count), and functional capacity (muscle strength, muscle quality, chair stand, balance and alternate step tests) were measured. Women were divided into three groups (sedentary [n = 19], <7,500 steps; moderately active [n = 20], 7,500-10,000 steps; active [n = 18], >10,000 steps). RESULTS: A higher number of steps per day was associated with higher maximal oxygen consumption (mL/min per kg; P = 0.001) and total energy expenditure (P = 0.004) as well as lower body weight (P = 0.035) and fat mass (P = 0.048). Surprisingly, no differences for skeletal muscle mass, muscle strength, muscle quality, and functional capacity were observed between the groups, although this could have been because of the small sample size. CONCLUSIONS: A daily amount of 10,000 steps seems to be associated with better body composition and higher cardiovascular functions. However, neither functional capacity nor muscle functions seem to be related to the daily amount of steps in postmenopausal women. Further prospective studies are needed to confirm our preliminary results because cross-sectional study designs do not permit the understanding of temporal relations.
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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 | 0.002 |
| 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 | 0.001 | 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".