Evidence map›Paper›PMID 34806474›Full record

SynthesisSports health

Effectiveness of Exercise Training on Male Factor Infertility: A Systematic Review and Network Meta-analysis.

Behzad Hajizadeh Maleki, Bakhtyar Tartibian, Mohammad Chehrazi

Registry-linked trialOpen access · greenAbstract readSystematic ReviewNetwork Meta-Analysis
In one paragraph

Synthesis in Sports health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06867627 (Effect of Moderate-intensity Combined Aerobic and Resistance Exercise on Semen Quality in Chinese College Students), which is not on this map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
3.3field-weighted citation impact, top 8% of its field
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.

NCT06867627 nacompletednot on this map

Effect of Moderate-intensity Combined Aerobic and Resistance Exercise on Semen Quality in Chinese College Students

TypeinterventionalSponsorAnhui Medical UniversityRan2025 to 2025Enrolled60ConditionsSemen QualityArmsModerate-intensity combined aerobic and resistance exercise training
3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 22 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Review
  6. Review
  7. Review
  8. Review
  9. The influence of lifestyle and biological factors on semen variability.Journal of assisted reproduction and genetics · 2024
    Article
  10. Review
  11. Article
  12. Male Fertility and Physical Exercise.The world journal of men's health · 2023
    Review
  13. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 2 countries.

Behzad Hajizadeh MalekiDepartment of Exercise Physiology and Sports Therapy, Justus Liebig University, Giessen, Germany.
Bakhtyar TartibianDepartment of Exercise Physiology, Faculty of Physical Education and Sport Sciences, Allameh Tabataba'i University, Tehran, Iran.
Mohammad ChehraziDepartment of Biostatistics and Epidemiology School of Public Health, Babol University of Medical Sciences, Babol, Iran.
Allameh Tabataba'i University · IRBabol University of Medical Sciences · IRUniversity of Giessen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextMounting evidence from the literature suggests that different types of training interventions can be successful at improving several aspects of male reproductive function in both fertile and infertile populations.

objectiveThe aim of this study was to evaluate the effectiveness of exercise training on male factor infertility and seminal markers of inflammation. DATA SOURCES: We searched PubMed, CISCOM, Springer, Elsevier Science, Cochrane Central Register of Controlled Trials, Scopus, PEDro, Ovid (Medline, EMBASE, PsycINFO), Sport Discus, Orbis, CINAHL, Web of Science, ProQuest, and the ClinicalTrials.gov registry for randomized controlled trials (RCTs) that analyzed the impacts of selected types of exercise interventions on markers of male reproductive function and reproductive performance. STUDY SELECTION: A total of 336 records were identified, of which we included 7 trials reporting on 2641 fertile and infertile men in the systematic review and network meta-analysis. LEVEL OF EVIDENCE: Level 1 (because this is a systematic review of RCTs). DATA EXTRACTION: The data included the study design, participant characteristics, inclusion and exclusion, intervention characteristics, outcome measures, and the main results of the study.

resultsThe results of network meta-analysis showed that, compared with a nonintervention control group, the top-ranking interventions for pregnancy rate were for combined aerobic and resistance training (CET) (relative risk [RR] = 27.81), moderate-intensity continuous training (MICT) (RR = 26.67), resistance training (RT) (RR = 12.54), high-intensity continuous training (HICT) (RR = 5.55), and high-intensity interval training (HIIT) (RR = 4.63). While the top-ranking interventions for live birth rate were for MICT (RR = 10.05), RT (RR = 4.92), HIIT (RR = 4.38), CET (RR = 2.20), and HICT (RR = 1.55). Also, with the following order of effectiveness, 5 training strategies were significantly better at improving semen quality parameters (CET > MICT > HICT > RT > HIIT), seminal markers of oxidative stress (CET > MICT > HIIT > HICT > RT), seminal markers of inflammation (CET > MICT > HIIT > RT > HICT), as well as measures of body composition and VO

conclusionThe review recommends that the intervention with the highest probability of being the best approach out of all available options for improving the male factor infertility was for CET.

Indexed as

High-Intensity Interval TrainingInfertilityBiomarkersExerciseHumansInflammationMaleBiomarkersDNA fragmentationexercise trainingmale factor infertilitynetwork meta-analysisspermatogenesis

Identifiers

PMID34806474
PMCPMC9214906
OpenAlexW3216196861

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.