The effects of vitamin D supplementation on muscle strength and mobility in postmenopausal women: a systematic review and meta‐analysis of randomised controlled trials
Bibliographic record
Abstract
Abstract Background The results obtained from previous trials regarding the effects of vitamin D supplementation on muscle strength and mobility in postmenopausal women have been inconsistent. This systematic review and meta‐analysis of randomised controlled trials (RCTs) aimed to investigate the effect of vitamin D supplementation on muscle strength and mobility in postmenopausal women. Methods A comprehensive search on EMBASE, PubMed, MEDLINE and SCOPUS was performed to identify relevant articles published up to 28 March 2019. RCTs published in English measuring the effect of all forms and doses of vitamin D supplementation with or without calcium on muscle strength and mobility outcomes in postmenopausal women were included. Results In total, 29 eligible studies were included in the systematic review. The pooled findings using a random effects model showed that vitamin D supplementation insignificantly increased hand grip strength (HGS) as the measurement of muscle strength (MD = 0.656; 95% confidence interval = −0.037 to 1.350, P = 0.06). However, it did not affect timed‐up‐and‐go (TUG) as the measurement of mobility (MD = 0.118; 95% confidence interval = −0.655 to 0.892, P = 0.76). The subgroup analyses showed that vitamin D supplementation improved HGS with respect to dosages >1000 IU day − 1 ( P = 0.016), a treatment duration of 3 months ( P ˂ 0.001) and subjects with baseline vitamin D <30 ng mL − 1 ( P = 0.033). Conclusions The present review demonstrates that vitamin D supplementation resulted in small but nonsignificant improvements in muscle strength compared to control in postmenopausal women. No significant effect was observed in mobility after vitamin D administration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.050 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.034 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".