Time Allocation to Physical Activity and Sedentary Behaviour and Its Impact on Sarcopenia Risk: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
AIM: To evaluate the relationship between time spent in sedentary behaviour and physical activity and sarcopenia in older adults, and to analyse the effect of reallocating time between different intensities of activities on sarcopenia. DESIGN: Systematic review and meta-analysis. METHODS: statistic. Study quality was evaluated using the Newcastle-Ottawa Scale by two independent reviewers. DATA SOURCES: A comprehensive search was conducted in PubMed, Web of Science, Embase, CINAHL and Cochrane databases for studies published up to November 5, 2024, with no language or date restrictions. Relevant reference lists were also manually screened. RESULTS: The present review included six studies involving 9914 older adults. Three studies suggested that older adults without sarcopenia spent more time performing light physical activities (SMD: 0.35; 95% CI: 0.24-0.45) and moderate to vigorous physical activity (SMD: 0.61; 95% CI: 0.49-0.74) and had less sedentary behaviour (SMD: -0.34; 95% CI: -0.51 to -0.16) than did older adults with sarcopenia. Replacing sedentary behaviour with an equivalent amount of moderate to vigorous physical activity (10, 30, or 60 min) each day can reduce the risk of sarcopenia, with 30 min showing the best preventive effect. However, research findings on the relationship between substituting sedentary behaviour time with light physical activities and sarcopenia are inconsistent. IMPLICATIONS FOR THE PROFESSION: Encouraging older adults to engage in moderate to vigorous physical activity, even in short bouts of 10 min, can significantly reduce the risk of sarcopenia. Healthcare professionals should tailor activity recommendations to individual preferences and physical conditions to promote overall health and reduce sedentary behaviour. PATIENT AND PUBLIC CONTRIBUTION: No Patient or Public Contribution. TRIAL REGISTRATION: CRD42023416166.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".