Step Length, But Not Stepping Cadence, Strongly Predicts Physical Activity Intensity During Jogging and Running

ABSTRACTDevice-based measures often rely on the positive relationship between walking cadence and metabolic equivalents of task (METs) to estimate physical activity. It is unknown whether this relationship remains during jogging/running. The study purpose was to investigate the relationships between METs, cadence, and step length during walking and jogging/running. A treadmill protocol with 5 walking (3.2–6.4 km•hr−1) and 5 jogging/running stages (8.0–11.3 km•hr−1) was completed in 43 adults (23 ± 5 years, 19♀). Predictors of METs during walking and jogging/running were determined by generalized mixed modeling. The strongest prediction models for walking (R2 = 0.72, P < .001) and jogging/running (R2 = 0.75, P < .001) included cadence2, cadence, step length, age, and leg length (all, P < .001). Step length accounted for 49.1% and 78.3% of model variance during walking and jogging/running, respectively. METs are poorly estimated by cadence during jogging/running but step length reduces error. Strategies to measure step length in free-living settings could better predict physical activity intensity.KEYWORDS: treadmill exercisemetabolic equivalents of taskstepping activitydevice-based measures Disclosure statementNo potential conflict of interest was reported by the authors.Data AvailabilityThe data that support the findings of this study are available from the corresponding author (MWO) upon reasonable request.Additional informationFundingLPP and JLP were supported by a Fredrick Banting and Charles Best CIHR Master's Award. MES was supported by a Heart & Stroke BrightRed Scholarship. MWO was supported by a CIHR Post-Doctoral Fellowship Award (#181747) and a Dalhousie University Department of Medicine University Internal Medicine Research Foundation Research Fellowship Award. PJJ and PH were supported by the research program "Balanced and Sustainable Working Life of the Future – Models and Methods for Developing and Supporting Sustainable Health Throughout Life", FORTE Swedish Research Council for Health, Working Life and Welfare (2021-01561), and Prof. Magnus Svartngren, Uppsala University, Sweden.