Christopher C Moore1, Elroy J Aguiar2, Scott W Ducharme3, Catrine Tudor-Locke4. 1. Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC. 2. Department of Kinesiology, The University of Alabama, Tuscaloosa, AL. 3. Department of Kinesiology, California State University Long Beach, Long Beach, CA. 4. College of Health and Human Services, University of North Carolina at Charlotte, Charlotte, NC.
Abstract
PURPOSE: This study aimed to develop cadence-based metabolic equations (CME) for predicting the intensity of level walking and evaluate these CME against the widely adopted American College of Sports Medicine (ACSM) Metabolic Equation, which predicts walking intensity from speed and grade. METHODS: Two hundred and thirty-five adults (21-84 yr of age) completed 5-min level treadmill walking bouts between 0.22 and 2.24 m·s, increasing by 0.22 m·s for each bout. Cadence (in steps per minute) was derived by dividing directly observed steps by bout duration. Intensity (oxygen uptake; in milliliters per kilogram per minute) was measured using indirect calorimetry. A simple CME was developed by fitting a least-squares regression to the cadence-intensity relationship, and a full CME was developed through best subsets regression with candidate predictors of age, sex, height, leg length, body mass, body mass index (BMI), and percent body fat. Predictive accuracy of each CME and the ACSM metabolic equation was evaluated at normal (0.89-1.56 m·s) and all (0.22-2.24 m·s) walking speeds through k-fold cross-validation and converted to METs (1 MET = 3.5 mL·kg·min). RESULTS: On average, the simple CME predicted intensity within ~1.8 mL·kg·min (~0.5 METs) at normal walking speeds and with negligible (<0.01 METs) bias. Including age, leg length, and BMI in the full CME marginally improved predictive accuracy (≤0.36 mL·kg·min [≤0.1 METs]), but may account for larger (up to 2.5 mL·kg·min [0.72 MET]) deviations in the cadence-intensity relationships of outliers in age, stature, and/or BMI. Both CME demonstrated 23%-35% greater accuracy and 2.2-2.8 mL·kg·min (0.6-0.8 METs) lower bias than the ACSM metabolic equation's speed-based predictions. CONCLUSIONS: Although the ACSM metabolic equation incorporates a grade component and is convenient for treadmill-based applications, the CME developed herein enables accurate quantification of walking intensity using a metric that is accessible during overground walking, as is common in free-living contexts.
PURPOSE: This study aimed to develop cadence-based metabolic equations (CME) for predicting the intensity of level walking and evaluate these CME against the widely adopted American College of Sports Medicine (ACSM) Metabolic Equation, which predicts walking intensity from speed and grade. METHODS: Two hundred and thirty-five adults (21-84 yr of age) completed 5-min level treadmill walking bouts between 0.22 and 2.24 m·s, increasing by 0.22 m·s for each bout. Cadence (in steps per minute) was derived by dividing directly observed steps by bout duration. Intensity (oxygen uptake; in milliliters per kilogram per minute) was measured using indirect calorimetry. A simple CME was developed by fitting a least-squares regression to the cadence-intensity relationship, and a full CME was developed through best subsets regression with candidate predictors of age, sex, height, leg length, body mass, body mass index (BMI), and percent body fat. Predictive accuracy of each CME and the ACSM metabolic equation was evaluated at normal (0.89-1.56 m·s) and all (0.22-2.24 m·s) walking speeds through k-fold cross-validation and converted to METs (1 MET = 3.5 mL·kg·min). RESULTS: On average, the simple CME predicted intensity within ~1.8 mL·kg·min (~0.5 METs) at normal walking speeds and with negligible (<0.01 METs) bias. Including age, leg length, and BMI in the full CME marginally improved predictive accuracy (≤0.36 mL·kg·min [≤0.1 METs]), but may account for larger (up to 2.5 mL·kg·min [0.72 MET]) deviations in the cadence-intensity relationships of outliers in age, stature, and/or BMI. Both CME demonstrated 23%-35% greater accuracy and 2.2-2.8 mL·kg·min (0.6-0.8 METs) lower bias than the ACSM metabolic equation's speed-based predictions. CONCLUSIONS: Although the ACSM metabolic equation incorporates a grade component and is convenient for treadmill-based applications, the CME developed herein enables accurate quantification of walking intensity using a metric that is accessible during overground walking, as is common in free-living contexts.
Authors: Catrine Tudor-Locke; Jose Mora-Gonzalez; Scott W Ducharme; Elroy J Aguiar; John M Schuna; Tiago V Barreira; Christopher C Moore; Colleen J Chase; Zachary R Gould; Marcos A Amalbert-Birriel; Stuart R Chipkin; John Staudenmayer Journal: Int J Behav Nutr Phys Act Date: 2021-09-23 Impact factor: 8.915