Evidence map›Paper›PMID 41048273›Full record

SynthesisFrontiers in public health2025

Impact of physical exercise on health and social interaction in older adults: a meta-analysis.

Meng Tao, Shuang Li, Luyao Li, Yuanyuan Cao, Jie Zhuang

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Trial
  2. Article
  3. Impacts of Geri-FitHealthcare (Basel, Switzerland) · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Meng TaoSchool of Exercise and Health, Shanghai University of Sport, Shanghai, China.
Shuang LiTaizhou Vocational College of Science and Technology, Taizhou, China.
Luyao LiSchool of Exercise and Health, Shanghai University of Sport, Shanghai, China.
Yuanyuan CaoSchool of Exercise and Health, Shanghai University of Sport, Shanghai, China.
Jie ZhuangSchool of Exercise and Health, Shanghai University of Sport, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study aimed to evaluate the effect of physical exercise on the physical and mental health of older adults using meta-analysis and to analyze the moderating variables influencing this relationship. The goal was to provide a scientific basis for identifying effective exercise methods to enhance the physical and mental health of the older adults. Methods: A literature search was conducted in databases such as PubMed, Web of Science, Cochrane Library, and Google Scholar. Data were processed using Review Manager 5.4 and Stata 18.0 statistical software. Meta-analysis was performed using the random effects model, and relevant moderating variables were tested. Results: The study findings indicated that physical activity significantly improves the physical and mental health of older adults across various dimensions. Specifically, it showed a large effect size for enhancing social interactions (standardized mean difference (SMD) = 0.78, 95% confidence interval (CI) [0.14, 0.69], Conclusion: Physical exercise has a positive impact on improving the physical and mental health of older adults, particularly in enhancing physical health, psychological well-being, and social interactions.

Indexed as

ExerciseHealth StatusMental HealthSocial InteractionAgedFemaleHumansMalemental healthmeta-analysisolder adultsphysical exercisephysical healthsocial interaction

Identifiers

PMID41048273
PMCPMC12488397

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.