Effects of Physical Exercise on Telomere Length in Healthy Adults: Systematic Review, Meta-Analysis, and Meta-Regression
Bibliographic record
Abstract
BACKGROUND: Physical exercise is one of the main nonpharmacological treatments for most pathologies. In addition, physical exercise is beneficial in the prevention of various diseases. The impact of physical exercise has been widely studied; however, existing meta-analyses have included diverse and heterogeneous samples. Therefore, to our knowledge, this is the first meta-analysis to evaluate the impact of different physical exercise modalities on telomere length in healthy populations. OBJECTIVE: In this review, we aimed to determine the effect of physical exercise on telomere length in a healthy population through a meta-analysis of randomized controlled trials. METHODS: A systematic review with meta-analysis and meta-regression of the published literature on the impact of physical exercise on telomere length in a healthy population was performed. PubMed, Cochrane Library, SCOPUS, Web of Science, and Embase databases were searched for eligible studies. Methodological quality was evaluated using the Risk Of Bias In Nonrandomized Studies of Interventions and the risk-of-bias tool for randomized trials. Finally, the certainty of our findings (closeness of the estimated effect to the true effect) was evaluated using Grading of Recommendations, Assessment, Development, and Evaluations (GRADE). RESULTS: We included 9 trials that met the inclusion criteria with fair methodological quality. Random-effects model analysis was used to quantify the difference in telomere length between the exercise and sham groups. Meta-analysis showed that exercise did not significantly increase telomere length compared with the control intervention (mean difference=0.0058, 95% CI -0.05 to 0.06; P=.83). Subgroup analysis suggested that high-intensity interventional exercise significantly increased telomere length compared with the control intervention in healthy individuals (mean difference=0.15, 95% CI 0.03-0.26; P=.01). Furthermore, 56% of the studies had a high risk of bias. Certainty was graded from low to very low for most of the outcomes. CONCLUSIONS: The findings of this systematic review and meta-analysis suggest that high-intensity interval training seems to have a positive effect on telomere length compared with other types of exercise such as resistance training or aerobic exercise in a healthy population. TRIAL REGISTRATION: PROSPERO CRD42022364518; http://tinyurl.com/4fwb85ff.
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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 | 0.022 | 0.052 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.056 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".