Michael A Rosenblat1,2, Edward Lin3,4, Bruno R da Costa5,6,7, Scott G Thomas3. 1. Department of Exercise Science, Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, ON, Canada. michael@evidencebasedcoaching.ca. 2. Department of Biomedical Physiology and Kinesiology, Faculty of Science, Simon Fraser University, Burnaby, BC, Canada. michael@evidencebasedcoaching.ca. 3. Department of Exercise Science, Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, ON, Canada. 4. Schulich School of Medicine and Dentistry, Western University, London, ON, Canada. 5. Institute of Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada. 6. Applied Health Research Center (AHRC), Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, ON, Canada. 7. Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland.
Abstract
BACKGROUND: Interval training has become an essential component of endurance training programs because it can facilitate a substantial improvement in endurance sport performance. Two forms of interval training that are commonly used to improve endurance sport performance are high-intensity interval training (HIIT) and sprint interval training (SIT). Despite extensive research, there is no consensus concerning the optimal method to manipulate the interval training programming variables to maximize endurance performance for differing individuals. OBJECTIVE: The objective of this manuscript was to perform a systematic review and meta-analysis of interval training studies to determine the influence that individual characteristics and training variables have on time-trial (TT) performance. DATA SOURCES: SPORTDiscus and Medline with Full Text were explored to conduct a systematic literature search. STUDY SELECTION: The following criteria were used to select studies appropriate for the review: 1. the studies were prospective in nature; 2. included individuals between the ages of 18 and 65 years; 3. included an interval training (HIIT or SIT) program at least 2 weeks in duration; 4. included a TT test that required participants to complete a set distance; 5. and programmed HIIT by power or velocity. RESULTS: Twenty-nine studies met the inclusion criteria for the quantitative analysis with a total of 67 separate groups. The participants included males (n = 400) and females (n = 91) with a mean group age of 25 (range 19-45) years and mean [Formula: see text] of 52 (range 32-70) mL·kg-1·min-1. The training status of the participants comprised of inactive (n = 75), active (n = 146) and trained (n = 258) individuals. Training status played a significant role in improvements in TT performance with trained individuals only seeing improvements of approximately 2% whereas individuals of lower training status demonstrated improvements as high as 6%. The change in TT performance with HIIT depended on the duration but not the intensity of the interval work-bout. There was a dose-response relationship with the number of HIIT sessions, training weeks and total work with changes in TT performance. However, the dose-response was not present with SIT. CONCLUSION: Optimization of interval training programs to produce TT performance improvements should be done according to training status. Our analysis suggests that increasing interval training dose beyond minimal requirements may not augment the training response. In addition, optimal dosing differs between high intensity and sprint interval programs.
BACKGROUND: Interval training has become an essential component of endurance training programs because it can facilitate a substantial improvement in endurance sport performance. Two forms of interval training that are commonly used to improve endurance sport performance are high-intensity interval training (HIIT) and sprint interval training (SIT). Despite extensive research, there is no consensus concerning the optimal method to manipulate the interval training programming variables to maximize endurance performance for differing individuals. OBJECTIVE: The objective of this manuscript was to perform a systematic review and meta-analysis of interval training studies to determine the influence that individual characteristics and training variables have on time-trial (TT) performance. DATA SOURCES: SPORTDiscus and Medline with Full Text were explored to conduct a systematic literature search. STUDY SELECTION: The following criteria were used to select studies appropriate for the review: 1. the studies were prospective in nature; 2. included individuals between the ages of 18 and 65 years; 3. included an interval training (HIIT or SIT) program at least 2 weeks in duration; 4. included a TT test that required participants to complete a set distance; 5. and programmed HIIT by power or velocity. RESULTS: Twenty-nine studies met the inclusion criteria for the quantitative analysis with a total of 67 separate groups. The participants included males (n = 400) and females (n = 91) with a mean group age of 25 (range 19-45) years and mean [Formula: see text] of 52 (range 32-70) mL·kg-1·min-1. The training status of the participants comprised of inactive (n = 75), active (n = 146) and trained (n = 258) individuals. Training status played a significant role in improvements in TT performance with trained individuals only seeing improvements of approximately 2% whereas individuals of lower training status demonstrated improvements as high as 6%. The change in TT performance with HIIT depended on the duration but not the intensity of the interval work-bout. There was a dose-response relationship with the number of HIIT sessions, training weeks and total work with changes in TT performance. However, the dose-response was not present with SIT. CONCLUSION: Optimization of interval training programs to produce TT performance improvements should be done according to training status. Our analysis suggests that increasing interval training dose beyond minimal requirements may not augment the training response. In addition, optimal dosing differs between high intensity and sprint interval programs.
Authors: Daniel A Keir; Federico Y Fontana; Taylor C Robertson; Juan M Murias; Donald H Paterson; John M Kowalchuk; Silvia Pogliaghi Journal: Med Sci Sports Exerc Date: 2015-09 Impact factor: 5.411