Literature DB >> 24807838

High responders and low responders: factors associated with individual variation in response to standardized training.

Theresa N Mann1, Robert P Lamberts, Michael I Lambert.   

Abstract

The response to an exercise intervention is often described in general terms, with the assumption that the group average represents a typical response for most individuals. In reality, however, it is more common for individuals to show a wide range of responses to an intervention rather than a similar response. This phenomenon of 'high responders' and 'low responders' following a standardized training intervention may provide helpful insights into mechanisms of training adaptation and methods of training prescription. Therefore, the aim of this review was to discuss factors associated with inter-individual variation in response to standardized, endurance-type training. It is well-known that genetic influences make an important contribution to individual variation in certain training responses. The association between genotype and training response has often been supported using heritability estimates; however, recent studies have been able to link variation in some training responses to specific single nucleotide polymorphisms. It would appear that hereditary influences are often expressed through hereditary influences on the pre-training phenotype, with some parameters showing a hereditary influence in the pre-training phenotype but not in the subsequent training response. In most cases, the pre-training phenotype appears to predict only a small amount of variation in the subsequent training response of that phenotype. However, the relationship between pre-training autonomic activity and subsequent maximal oxygen uptake response appears to show relatively stronger predictive potential. Individual variation in response to standardized training that cannot be explained by genetic influences may be related to the characteristics of the training program or lifestyle factors. Although standardized programs usually involve training prescribed by relative intensity and duration, some methods of relative exercise intensity prescription may be more successful in creating an equivalent homeostatic stress between individuals than other methods. Individual variation in the homeostatic stress associated with each training session would result in individuals experiencing a different exercise 'stimulus' and contribute to individual variation in the adaptive responses incurred over the course of the training program. Furthermore, recovery between the sessions of a standardized training program may vary amongst individuals due to factors such as training status, sleep, psychological stress, and habitual physical activity. If there is an imbalance between overall stress and recovery, some individuals may develop fatigue and even maladaptation, contributing to variation in pre-post training responses. There is some evidence that training response can be modulated by the timing and composition of dietary intake, and hence nutritional factors could also potentially contribute to individual variation in training responses. Finally, a certain amount of individual variation in responses may also be attributed to measurement error, a factor that should be accounted for wherever possible in future studies. In conclusion, there are several factors that could contribute to individual variation in response to standardized training. However, more studies are required to help clarify and quantify the role of these factors. Future studies addressing such topics may aid in the early prediction of high or low training responses and provide further insight into the mechanisms of training adaptation.

Entities:  

Mesh:

Year:  2014        PMID: 24807838     DOI: 10.1007/s40279-014-0197-3

Source DB:  PubMed          Journal:  Sports Med        ISSN: 0112-1642            Impact factor:   11.136


  103 in total

Review 1.  Sleep deprivation as a neurobiologic and physiologic stressor: Allostasis and allostatic load.

Authors:  Bruce S McEwen
Journal:  Metabolism       Date:  2006-10       Impact factor: 8.694

2.  Exercise at given percentages of VO2max: heterogeneous metabolic responses between individuals.

Authors:  Friederike Scharhag-Rosenberger; Tim Meyer; Nina Gässler; Oliver Faude; Wilfried Kindermann
Journal:  J Sci Med Sport       Date:  2009-02-20       Impact factor: 4.319

3.  Monitoring endurance running performance using cardiac parasympathetic function.

Authors:  Martin Buchheit; A Chivot; J Parouty; D Mercier; H Al Haddad; P B Laursen; S Ahmaidi
Journal:  Eur J Appl Physiol       Date:  2009-12-22       Impact factor: 3.078

4.  Commentary on viewpoint: Perspective on the future use of genomics in exercise prescription.

Authors:  John A Hawley
Journal:  J Appl Physiol (1985)       Date:  2008-04

5.  Last word on viewpoint: Perspective on the future use of genomics in exercise prescription.

Authors:  Stephen M Roth
Journal:  J Appl Physiol (1985)       Date:  2008-04

6.  Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans.

Authors:  James A Timmons; Steen Knudsen; Tuomo Rankinen; Lauren G Koch; Mark Sarzynski; Thomas Jensen; Pernille Keller; Camilla Scheele; Niels B J Vollaard; Søren Nielsen; Thorbjörn Akerström; Ormond A MacDougald; Eva Jansson; Paul L Greenhaff; Mark A Tarnopolsky; Luc J C van Loon; Bente K Pedersen; Carl Johan Sundberg; Claes Wahlestedt; Steven L Britton; Claude Bouchard
Journal:  J Appl Physiol (1985)       Date:  2010-02-04

7.  Influence of cold water face immersion on post-exercise parasympathetic reactivation.

Authors:  Hani Al Haddad; Paul B Laursen; Said Ahmaidi; Martin Buchheit
Journal:  Eur J Appl Physiol       Date:  2009-10-31       Impact factor: 3.078

Review 8.  Genetic influences in sport and physical performance.

Authors:  Zudin Puthucheary; James R A Skipworth; Jai Rawal; Mike Loosemore; Ken Van Someren; Hugh E Montgomery
Journal:  Sports Med       Date:  2011-10-01       Impact factor: 11.136

Review 9.  Training adaptation and heart rate variability in elite endurance athletes: opening the door to effective monitoring.

Authors:  Daniel J Plews; Paul B Laursen; Jamie Stanley; Andrew E Kilding; Martin Buchheit
Journal:  Sports Med       Date:  2013-09       Impact factor: 11.136

10.  Glucose ingestion during exercise blunts exercise-induced gene expression of skeletal muscle fat oxidative genes.

Authors:  Anthony E Civitarese; Matthijs K C Hesselink; Aaron P Russell; Eric Ravussin; Patrick Schrauwen
Journal:  Am J Physiol Endocrinol Metab       Date:  2005-07-19       Impact factor: 4.310

View more
  84 in total

1.  Refuting the myth of non-response to exercise training: 'non-responders' do respond to higher dose of training.

Authors:  David Montero; Carsten Lundby
Journal:  J Physiol       Date:  2017-05-14       Impact factor: 5.182

2.  Maximum Strength Development and Volume-Load during Concurrent High Intensity Intermittent Training Plus Strength or Strength-Only Training.

Authors:  Valéria L G Panissa; David H Fukuda; Flaviane P de Oliveira; Sergio S Parmezzani; Eduardo Z Campos; Fabrício E Rossi; Emerson Franchini; Fabio S Lira
Journal:  J Sports Sci Med       Date:  2018-11-20       Impact factor: 2.988

3.  Understanding the individual responsiveness to resistance training periodization.

Authors:  Jonato Prestes; Dahan da Cunha Nascimento; Ramires Alsamir Tibana; Tatiane Gomes Teixeira; Denis Cesar Leite Vieira; Vitor Tajra; Darlan Lopes de Farias; Alessandro Oliveira Silva; Silvana Schwerz Funghetto; Vinicius Carolino de Souza; James Wilfred Navalta
Journal:  Age (Dordr)       Date:  2015-05-14

Review 4.  Response Heterogeneity With Exercise Training and Physical Activity Interventions Among Persons With Multiple Sclerosis.

Authors:  Jessica F Baird; Robert W Motl
Journal:  Neurorehabil Neural Repair       Date:  2018-12-26       Impact factor: 3.919

Review 5.  Implications of Impaired Endurance Performance following Single Bouts of Resistance Training: An Alternate Concurrent Training Perspective.

Authors:  Kenji Doma; Glen B Deakin; David J Bentley
Journal:  Sports Med       Date:  2017-11       Impact factor: 11.136

6.  Influence of Baseline Physical Activity Level on Exercise Training Response and Clinical Outcomes in Heart Failure: The HF-ACTION Trial.

Authors:  Mauro F F Mediano; Eric S Leifer; Lawton S Cooper; Steven J Keteyian; William E Kraus; Robert J Mentz; Jerome L Fleg
Journal:  JACC Heart Fail       Date:  2018-12       Impact factor: 12.035

7.  Change in VO2max and time trial performance in response to high-intensity interval training prescribed using ventilatory threshold.

Authors:  Todd A Astorino; Jamie deRevere; Theodore Anderson; Erin Kellogg; Patrick Holstrom; Sebastian Ring; Nicholas Ghaseb
Journal:  Eur J Appl Physiol       Date:  2018-06-19       Impact factor: 3.078

8.  Skeletal Muscle PGC1α -1 Nucleosome Position and -260 nt DNA Methylation Determine Exercise Response and Prevent Ectopic Lipid Accumulation in Men.

Authors:  Sudip Bajpeyi; Jeffrey D Covington; Erin M Taylor; Laura K Stewart; Jose E Galgani; Tara M Henagan
Journal:  Endocrinology       Date:  2017-07-01       Impact factor: 4.736

9.  Inter-Individual Responses of Maximal Oxygen Uptake to Exercise Training: A Critical Review.

Authors:  Philip J Williamson; Greg Atkinson; Alan M Batterham
Journal:  Sports Med       Date:  2017-08       Impact factor: 11.136

10.  Intelligent Personalized Exercise Prescription Based on an eHealth Promotion System to Improve Health Outcomes of Middle-Aged and Older Adult Community Dwellers: Pretest-Posttest Study.

Authors:  Ting Sun; Yang Xu; Hui Xie; Zuchang Ma; Yu Wang
Journal:  J Med Internet Res       Date:  2021-05-24       Impact factor: 7.076

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.