A Comparison of Heart Rate Training Load and Perceptual Effort Between Masters and Young Cyclists

in International Journal of Sports Physiology and Performance
Restricted access

Purchase article

USD  $24.95

Student 1 year online subscription

USD  $112.00

1 year online subscription

USD  $149.00

Student 2 year online subscription

USD  $213.00

2 year online subscription

USD  $284.00

Purpose: Due to age-related changes in the psychobiological state of masters athletes, this brief report aimed to compare training load responses using heart rate (HR) and ratings of perceived exertion (RPE) during standardized training sessions between masters and young cyclists. Methods: Masters (n = 10; 55.6 [5.0] y) and young (n = 8; 25.9 [3.0] y) cyclists performed separate endurance and high-intensity interval training sessions. Endurance intensity was set at 95% of ventilatory threshold 2 for 1 hour. High-intensity interval training consisted of 6 × 30-second intervals at 175% peak power output with 4.5-minute rest between intervals. HR was monitored continuously and RPE collected at standardized time periods during each session. Banister training impulse and summated-HR-zones training loads were also calculated. Results: Despite a significantly lower mean HR in masters cyclists during endurance (P = .04; d = 1.06 [±0.8], moderate) and high-intensity interval training (P = .01; d = 1.34 [±0.8], large), no significant differences were noted (P > .05) when responses were determined relative to maximum HR or converted to training impulse and summated-HR-zone loads. Furthermore, no interaction or between-group differences were evident for RPE across either session (P > .05). Conclusions: HR and RPE values were comparable between masters and young cyclists when relative HR responses and HR training load models are used. This finding suggests HR and RPE methods used to monitor or prescribe training load can be used interchangeably between masters and young athletes irrespective of chronological age.

Borges is with the School of Environmental and Life Sciences, The University of Newcastle, Ourimbah, NSW, Australia. Scanlan is with Human Exercise and Training Laboratory, Central Queensland University, Rockhampton, QLD, Australia; and the School of Medical and Applied Sciences, Central Queensland University, Rockhampton, QLD, Australia. Reaburn is with the Bond Inst of Health & Sport, Bond University, Gold Coast, QLD, Australia. Doering is with the School of Allied Health Sciences, Griffith University, Nathan, QLD, Australia.

Borges (Nattai.Borges@newcastle.edu.au) is corresponding author.
  • 1.

    Borges N, Reaburn P, Driller M, Argus C. Age-related changes in performance and recovery kinetics in masters athletes: a narrative review. J Aging Phys Act. 2016;24(1):149157. PubMed ID: 25880787 doi:10.1123/japa.2015-0021

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Sanders D, Abt G, Hesselink MK, Myers T, Akubat I. Methods of monitoring training load and their relationships to changes in fitness and performance in competitive road cyclists. Int J Sports Physiol Perform. 2017;12(5):668675. PubMed ID: 28095061 doi:10.1123/ijspp.2016-0454

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Bourdon PC, Cardinale M, Murray A, et al. Monitoring athlete training loads: consensus statement. Int J Sports Physiol Perform. 2017;12(suppl 2):S2161S2170. doi:10.1123/IJSPP.2017-0208

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Ferrari AU, Radaelli A, Centola M. Invited review: aging and the cardiovascular system. J Appl Physiol. 2003;95(6):25912597. PubMed ID: 14600164 doi:10.1152/japplphysiol.00601.2003

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Fell J, Reaburn P, Harrison G. Altered perception and report of fatigue and recovery in veteran athletes. J Sports Med Phys Fitness. 2008;48(2):272. PubMed ID: 18427425

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Borges NR, Reaburn PR, Doering TM, Argus CK, Driller MW. Age-related changes in physical and perceptual markers of recovery following high-intensity interval cycle exercise. Exp Aging Res. 2018;44(4):338349. PubMed ID: 29843564 doi:10.1080/0361073X.2018.1477361

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7.

    Lucía A, Hoyos J, Pérez M, Chicharro JL. Heart rate and performance parameters in elite cyclists: a longitudinal study. Med Sci Sports Exerc. 2000;32(10):17771782. doi:10.1097/00005768-200010000-00018

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Wasserman K, Whipp BJ, Koyl S, Beaver W. Anaerobic threshold and respiratory gas exchange during exercise. J Appl Physiol. 1973;35(2):236243. PubMed ID: 4723033 doi:10.1152/jappl.1973.35.2.236

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Banister E. Modeling elite athletic performance. In: Green H, McDougal J, Wegner H, eds. Physiological Testing of the High-Performance Athlete. Champaign, IL: Human Kinetics; 1991:403424.

    • Search Google Scholar
    • Export Citation
  • 10.

    Edwards S. The Heart Rate Monitor Book. Sacramento, CA: Fleet Feet Press; 1993.

  • 11.

    Hopkins W, Marshall S, Batterham A, Hanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc. 2009;41(1):313. PubMed ID: 19092709 doi:10.1249/MSS.0b013e31818cb278

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Borges NR, Reaburn PR, Doering TM, Argus CK, Driller MW. Autonomic cardiovascular modulation in masters and young cyclists following high-intensity interval training. Clin Auton Res. 2017;27(2):8390. PubMed ID: 28154947 doi:10.1007/s10286-017-0398-6

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 458 458 40
Full Text Views 18 18 0
PDF Downloads 15 15 0