Energy Expenditure Equation Choice: Effects on Cycling Efficiency and its Reliability

in International Journal of Sports Physiology and Performance
Restricted access

Purchase article

USD $24.95

Student 1 year subscription

USD $107.00

1 year subscription

USD $142.00

Student 2 year subscription

USD $203.00

2 year subscription

USD $265.00

Purpose: There are several published equations to calculate energy expenditure (EE) from gas exchanges. The authors assessed whether using different EE equations would affect gross efficiency (GE) estimates and their reliability. Methods: Eleven male and 3 female cyclists (age 33 [10] y; height: 178 [11] cm; body mass: 76.0 [15.1] kg; maximal oxygen uptake: 51.4 [5.1] mL·kg−1·min−1; peak power output: 4.69 [0.45] W·kg−1) completed 5 visits to the laboratory on separate occasions. In the first visit, participants completed a maximal ramp test to characterize their physiological profile. In visits 2 to 5, participants performed 4 identical submaximal exercise trials to assess GE and its reliability. Each trial included three 7-minute bouts at 60%, 70%, and 80% of the gas exchange threshold. EE was calculated with 4 equations by Péronnet and Massicotte, Lusk, Brouwer, and Garby and Astrup. Results: All 4 EE equations produced GE estimates that differed from each other (all P < .001). Reliability parameters were only affected when the typical error was expressed in absolute GE units, suggesting a negligible effect—related to the magnitude of GE produced by each EE equation. The mean coefficient of variation for GE across different exercise intensities and calculation methods was 4.2%. Conclusions: Although changing the EE equation does not affect GE reliability, exercise scientists and coaches should be aware that different EE equations produce different GE estimates. Researchers are advised to share their raw data to allow for GE recalculation, enabling comparison between previous and future studies.

The authors are with the School of Sport and Exercise Sciences, University of Kent, Chatham, Kent, United Kingdom.

Bossi (asnb3@kent.ac.uk) is corresponding author.
International Journal of Sports Physiology and Performance
Article Sections
References
  • 1.

    Hopker JPassfield LColeman DJobson SEdwards LCarter H. The effects of training on gross efficiency in cycling: a review. Int J Sports Med. 2009;30(12):845850. PubMed ID: 19941249 doi:

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

    Hopker JGJobson SAGregson HCColeman DPassfield L. Reliability of cycling gross efficiency using the Douglas bag method. Med Sci Sports Exerc. 2012;44(2):290296. PubMed ID: 21796054 doi:

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

    Bell PGFurber MJvan Someren KAAnton-Solanas ASwart J. The physiological profile of a multiple Tour de France winning cyclist. Med Sci Sports Exerc. 2017;49(1):115123. PubMed ID: 27508883 doi:

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

    Mogensen MBagger MPedersen PKFernstrom MSahlin K. Cycling efficiency in humans is related to low UCP3 content and to type I fibres but not to mitochondrial efficiency. J Physiol. 2006;571(Pt 3):669681. PubMed ID: 16423857 doi:

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

    Noordhof DAde Koning JJvan Erp Tet al. The between and within day variation in gross efficiency. Eur J Appl Physiol. 2010;109(6):12091218. PubMed ID: 20464413 doi:

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

    Kipp SByrnes WCKram R. Calculating metabolic energy expenditure across a wide range of exercise intensities: the equation matters. Appl Physiol Nutr Metab. 2018;43(6):639642. PubMed ID: 29401411 doi:

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

    Péronnet FMassicotte D. Table of nonprotein respiratory quotient: an update. Can J Sport Sci. 1991;16(1):2329. PubMed ID: 1645211

  • 8.

    Lansley KEDimenna FJBailey SJJones AM. A ‘new’ method to normalise exercise intensity. Int J Sports Med. 2011;32(7):535541. PubMed ID: 21563028 doi:

  • 9.

    Lusk G. Animal calorimetry: twenty-fourth paper. Analysis of the oxidation of mixtures of carbohydrate and fat. J Biol Chem. 1924;59(1):4142.

    • Search Google Scholar
    • Export Citation
  • 10.

    Brouwer E. On simple formulae for calculating the heat expenditure and the quantities of carbohydrate and fat oxidized in metabolism of men and animals, from gaseous exchange (oxygen intake and carbonic acid output) and urine-N. Acta Physiol Pharmacol Neerl. 1957;6:795802. PubMed ID: 13487422

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Garby LAstrup A. The relationship between the respiratory quotient and the energy equivalent of oxygen during simultaneous glucose and lipid oxidation and lipogenesis. Acta Physiol Scand. 1987;129(3):443444. PubMed ID: 3577829 doi:

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

    Hopkins WG. Spreadsheets for analysis of validity and reliability. Sportscience. 2015;19:3642.

  • 13.

    Moseley LJeukendrup AE. The reliability of cycling efficiency. Med Sci Sports Exerc. 2001;33(4):621627. PubMed ID: 11283439 doi:

Article Metrics
All Time Past Year Past 30 Days
Abstract Views 191 191 91
Full Text Views 10 10 5
PDF Downloads 10 10 4
Altmetric Badge
PubMed
Google Scholar