SwePub - sökning: WFRF:(O’Brien Myles W.)

Numrering	Referens	Omslagsbild	Hitta
1.	Pellerine, Liam P., et al. (författare) Step Length, But Not Stepping Cadence, Strongly Predicts Physical Activity Intensity During Jogging and Running 2023 Ingår i: Measurement in Physical Education and Exercise Science. - : Taylor & Francis. - 1091-367X .- 1532-7841. ; 27:4, s. 352-361 Tidskriftsartikel (refereegranskat)abstract Device-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.

Pellerine, Liam P., et al. (författare)
Step Length, But Not Stepping Cadence, Strongly Predicts Physical Activity Intensity During Jogging and Running
2023
Ingår i: Measurement in Physical Education and Exercise Science. - : Taylor & Francis. - 1091-367X .- 1532-7841. ; 27:4, s. 352-361
Tidskriftsartikel (refereegranskat)abstract
- Device-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.

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