Evidence map›Paper›PMID 37720640›Full record

ReviewFrontiers in psychology2023

Long-term exercise training and inflammatory biomarkers in healthy subjects: a meta-analysis of randomized controlled trials.

Ya-Hai Wang, Jingwang Tan, Huan-Huan Zhou, Meng Cao, Yu Zou

Abstract readReview
In one paragraph

Review in Frontiers in psychology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 pooled it
–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

23 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
  18. Review
  19. Article
  20. Review
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.

Ya-Hai WangCollege of Arts and Physical Education, Nanchang Normal College of Applied Technology, Nanchang, China.
Jingwang TanDepartment of Sport and Exercise Science, College of Education, Zhejiang University, Hangzhou, China.
Huan-Huan ZhouDepartment of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Meng CaoDepartment of Physical Education, College of Sport, Shenzhen University, Shenzhen, China.
Yu ZouDepartment of Sport and Exercise Science, College of Education, Zhejiang University, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This meta-analysis investigated the effect of long-term exercise training (ET) including aerobic, resistance, and multicomponent ET on the levels of inflammatory biomarkers in randomized controlled trials (RCTs) involving healthy subjects. Methods: We searched seven databases for articles until May 1st, 2023. A random-effect meta-analysis, subgroup analysis, meta-regressions as well as trim and fill method were conducted using STATA 16.0. Result: Thirty-eight studies were included in the meta-analysis, involving 2,557 healthy subjects (mean age varies from 21 to 86 years). Long-term ET induced significantly decreased in the levels of interleukin-6 (IL-6) (SMD -0.16, 95% CI -0.30 to -0.03, Conclusion: Long-term ET induced significant anti-inflammatory effects in healthy subjects. Long-term ET-induced anti-inflammatory effects were associated with exercise of moderate intensity and training conducted for more than 12 weeks.

Indexed as

C-reactive proteininflammationinterleukin-6long-term exercise trainingmeta-analysistumor necrosis factor alpha

Identifiers

PMID37720640
PMCPMC10499556

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.