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New Generalized Equation for Predicting Maximal Oxygen Uptake (from the Fitness Registry and the Importance of Exercise National Database)

  • Peter Kokkinos
    Correspondence
    Corresponding author: Tel: (202) 745-8430; fax: (202) 745-2261.
    Affiliations
    Department of Cardiology, Veterans Affairs Medical Center, Washington, DC

    Department of Clinical Research and Leadership, George Washington University School of Medicine and Health Sciences, Washington, DC

    Department of Cardiology, Georgetown University School of Medicine, Washington, DC

    Department of Exercise Science, University of South Carolina, Arnold School of Public Health, Columbia, South Carolina
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  • Leonard A. Kaminsky
    Affiliations
    Fisher Institute of Health and Well-Being and Clinical Exercise Physiology, Ball State University, Muncie, Indiana
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  • Ross Arena
    Affiliations
    Department of Physical Therapy and Integrative Physiology Laboratory, College of Applied Health Sciences, University of Illinois at Chicago, Chicago, Illinois
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  • Jiajia Zhang
    Affiliations
    Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, South Carolina
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  • Jonathan Myers
    Affiliations
    Department of Cardiology, Veterans Affairs Palo Alto Health Care System, Palo Alto, California

    Department of Cardiology, Stanford University, Stanford, California
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      Impaired cardiorespiratory fitness (CRF) is closely linked to chronic illness and associated with adverse events. The American College of Sports Medicine (ACSM) regression equations (ACSM equations) developed to estimate oxygen uptake have known limitations leading to well-documented overestimation of CRF, especially at higher work rates. Thus, there is a need to explore alternative equations to more accurately predict CRF. We assessed maximal oxygen uptake (VO2 max) obtained directly by open-circuit spirometry in 7,983 apparently healthy subjects who participated in the Fitness Registry and the Importance of Exercise National Database (FRIEND). We randomly sampled 70% of the participants from each of the following age categories: <40, 40 to 50, 50 to 70, and ≥70 and used the remaining 30% for validation. Multivariable linear regression analysis was applied to identify the most relevant variables and construct the best prediction model for VO2 max. Treadmill speed and treadmill speed × grade were considered in the final model as predictors of measured VO2 max and the following equation was generated: VO2 max in ml O2/kg/min = speed (m/min) × (0.17 + fractional grade × 0.79) + 3.5. The FRIEND equation predicted VO2 max with an overall error >4 times lower than the error associated with the traditional ACSM equations (5.1 ± 18.3% vs 21.4 ± 24.9%, respectively). Overestimation associated with the ACSM equation was accentuated when different protocols were considered separately. In conclusion, The FRIEND equation predicts VO2 max more precisely than the traditional ACSM equations with an overall error >4 times lower than that associated with the ACSM equations.
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