Dose‐response effects of exercise on bone mineral density and content in post‐menopausal women
Bibliographic record
Abstract
Exercise is one of the most widely used non‐pharmacological strategies to prevent bone resorption during menopause. Given the detrimental consequences of bone demineralization, the purpose of this study was to examine the effects of prescribing different exercise volumes on bone mineral density and content in previously inactive, post‐menopausal women during a 12‐month intervention and 1 year after intervention completion. Four hundred post‐menopausal women were randomized to either 150 min/wk (MODERATE dose group) or 300 min/wk (HIGH dose group) of aerobic exercise. Total bone mineral density (g/cm2) and bone mineral content (g) were assessed at baseline, 12 months (end of the intervention) and 24 months (follow‐up) using whole body dual‐energy X‐ray absorptiometry. At 12 months, mean bone mineral density among women in the HIGH dose group was estimated to be 0.006 g/cm2 (95% CI: 0.001‐0.010; P = 0.02) higher than that of women randomized to the MODERATE dose group. At 24 months, the mean difference between groups remained statistically significant, indicating higher mean bone mineral density among women in the HIGH dose group (0.007 g/cm2; 0.001‐0.001; P = 0.04). No significant differences between groups were found at any time point for bone mineral content. In an exploratory analysis, women who completed more min/wk of impact exercises had significantly higher mean levels of bone mineral density at 12 months compared to baseline (0.006 g/cm2, 95% CI: 0.006‐0.012; P = 0.03). These findings suggest that higher volumes of exercise, especially impact exercise, lead to a smaller decline in total bone mineral density, which may remain following intervention completion.
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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 | 0.001 | 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 | 0.001 | 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".