Development of a Cadence-based Metabolic Equation for Walking

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(-1), increasing by 0.22 m.s(-1) 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(-1)) and all (0.22-2.24 m.s(-1)) walking speeds through k-fold cross-validation and converted to METs (1 MET = 3.5 mL.kg(-1).min(-1)). Results:On average, the simple CME predicted intensity within similar to 1.8 mL.kg(-1).min(-1) (similar to 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(-1).min(-1) [<= 0.1 METs]), but may account for larger (up to 2.5 mL.kg(-1).min(-1) [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(-1).min(-1) (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.

Automated summary

The study aimed to compare cadence-based metabolic equations (CME) with the ACSM Metabolic Equation for predicting walking intensity. It was found that the CME demonstrated higher accuracy and lower bias compared to the ACSM equation, with the inclusion of factors like age, leg length, and BMI improving predictive accuracy to a marginal extent. The CME developed in this study allows for accurate quantification of walking intensity in overground walking scenarios, providing a more accessible metric for real-world applications.