Evidence map›Paper›PMID 30377780›Full record

ReviewEuropean journal of applied physiology2019

The interactions of physical activity, exercise and genetics and their associations with bone mineral density: implications for injury risk in elite athletes.

Adam J Herbert, Alun G Williams, Philip J Hennis, Robert M Erskine, Craig Sale, Stephen H Day, Georgina K Stebbings

Abstract readReview
In one paragraph

Review in European journal of applied physiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

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

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Sport Activity Load and Skeletomuscular Robustness in Elite Youth Athletes.International journal of environmental research and public health · 2022
    Article
  12. Article
  13. Article
  14. Article
  15. Molecular Portrait of an Athlete.Diagnostics (Basel, Switzerland) · 2021
    Review
  16. Article
  17. Article
  18. Bone Mineral Reference Values for Athletes 11 to 20 Years of Age.International journal of environmental research and public health · 2020
    Article
  19. Article
  20. 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

7 authors.

Adam J HerbertDepartment of Sport and Exercise, School of Health Sciences, Faculty of Health, Education and Life Sciences, Birmingham City University, Birmingham, UK. adam.herbert@bcu.ac.uk.ORCID http://orcid.org/0000-0001-8964-0087
Alun G WilliamsSports Genomics Laboratory, Manchester Metropolitan University, Cheshire Campus, Crewe Green Road, Crewe, CW1 5DU, UK.
Philip J HennisMusculoskeletal Physiology Research Group, Sport, Health and Performance Enhancement Research Centre, Nottingham Trent University, Clifton Lane, Clifton, Nottingham, NG11 8NS, UK.
Robert M ErskineResearch Institute for Sport and Exercise Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK.
Craig SaleMusculoskeletal Physiology Research Group, Sport, Health and Performance Enhancement Research Centre, Nottingham Trent University, Clifton Lane, Clifton, Nottingham, NG11 8NS, UK.
Stephen H DayDepartment of Biomedical Science & Physiology, School of Sciences, Faculty of Science and Engineering, University of Wolverhampton, Wolverhampton, UK.
Georgina K StebbingsSports Genomics Laboratory, Manchester Metropolitan University, Cheshire Campus, Crewe Green Road, Crewe, CW1 5DU, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Low bone mineral density (BMD) is established as a primary predictor of osteoporotic risk and can also have substantial implications for athlete health and injury risk in the elite sporting environment. BMD is a highly multi-factorial phenotype influenced by diet, hormonal characteristics and physical activity. The interrelationships between such factors, and a strong genetic component, suggested to be around 50-85% at various anatomical sites, determine skeletal health throughout life. Genome-wide association studies and case-control designs have revealed many loci associated with variation in BMD. However, a number of the candidate genes identified at these loci have no known associated biological function or have yet to be replicated in subsequent investigations. Furthermore, few investigations have considered gene-environment interactions-in particular, whether specific genes may be sensitive to mechanical loading from physical activity and the outcome of such an interaction for BMD and potential injury risk. Therefore, this review considers the importance of physical activity on BMD, genetic associations with BMD and how subsequent investigation requires consideration of the interaction between these determinants. Future research using well-defined independent cohorts such as elite athletes, who experience much greater mechanical stress than most, to study such phenotypes, can provide a greater understanding of these factors as well as the biological underpinnings of such a physiologically "extreme" population. Subsequently, modification of training, exercise or rehabilitation programmes based on genetic characteristics could have substantial implications in both the sporting and public health domains once the fundamental research has been conducted successfully.

Indexed as

Bone DensityExerciseGenetic Predisposition to DiseaseAthletesAthletic InjuriesHumansBoneExerciseFractureGeneticsPolymorphismRunning

Identifiers

PMID30377780
PMCPMC6342881

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.