Effect of Exercise on Bone Mineral Density and Lean Mass in Postmenopausal Women
Bibliographic record
Abstract
PURPOSE: To evaluate the effects of physical activity on bone mineral density, bone mineral content, and lean mass in postmenopausal, overweight/obese women. METHODS: We conducted a 12-month randomized controlled aerobic exercise intervention versus control in 173 sedentary, overweight/obese, postmenopausal women, aged 50-75 yr. The exercise prescription consisted of >or=45 min of moderate-intensity aerobic exercise (60-75% of maximal heart rate), 5 d.wk for 12 months. Control participants attended 45-min stretching sessions once a week. Ninety-eight percent (N=170) completed the trial. Exercisers averaged 172 min.wk (SD=89) of exercise and expended 3828 kJ.wk (SD=2053). We assessed body fat, total lean mass, and total body bone mineral density and content using dual-energy x-ray absortiometry (DXA). We compared baseline with 12-month changes in exercisers versus controls. RESULTS: Exercisers lost significantly more weight than stretchers (1.3-kg loss vs 0.1-kg gain, P=0.01). However, no differences between exercisers and controls in the change from baseline to 12 months were detected: exercisers' average bone mineral density increased by 0.005 g.cm and controls' by 0.003 g.cm (P=0.61). Similarly, no significant differences were detected for bone mineral content. Lean mass increased by 0.2 kg in both groups (P=0.84). CONCLUSION: Overall, the results from this randomized controlled study suggest that a yearlong moderate-intensity aerobic exercise intervention does not affect total body bone mineral density, bone mineral content, or lean mass in overweight/obese postmenopausal women.
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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) | 0.001 | 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".