Step Length, But Not Stepping Cadence, Strongly Predicts Physical Activity Intensity During Jogging and Running.
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, c...
| Publicado en: | Measurement in Physical Education & Exercise Science Vol. 27; no. 4; pp. 352 - 362 |
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| Autores principales: | , , , , , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Oct-Dec2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=172758332&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 172758332 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1091367X 7MM jtl: Measurement in Physical Education & Exercise Science issn: 1091367X maglogo: N pubinfo: dt: Oct-Dec2023 vid: 27 iid: 4 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 172758332 162293818 172758332 172758332 10.1080/1091367X.2023.2188118 172758332 ppf: 352 ppct: 10 formats: tig: atl: Step Length, But Not Stepping Cadence, Strongly Predicts Physical Activity Intensity During Jogging and Running. aug: au: Pellerine, Liam P. Petterson, Jennifer L. Shivgulam, Madeline E. Johansson, Peter J. Hettiarachchi, Pasan Kimmerly, Derek S. Frayne, Ryan J. O'Brien, Myles W. affil: Division of Kinesiology, School of Health and Human Performance, Faculty of Health, Dalhousie University, Halifax, Canada sug: subj: Step Walking Speed Physical Activity Evaluation Exercise Intensity Evaluation Jogging Oxygen Consumption Task Performance and Analysis Human Correlational Studies Treadmills Exercise Equipment and Supplies Male Female Adolescence Adult Prediction Models Activities of Daily Living Descriptive Statistics Wearable Sensors Adolescent: 13-18 years Adult: 19-44 years Male Female ab: 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. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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