4.3 Article

Validity of ActiGraph 2-Regression Model, Matthews Cut-Points, and NHANES Cut-Points for Assessing Free-Living Physical Activity

期刊

JOURNAL OF PHYSICAL ACTIVITY & HEALTH
卷 10, 期 4, 页码 504-514

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HUMAN KINETICS PUBL INC
DOI: 10.1123/jpah.10.4.504

关键词

motion sensor; accelerometry; oxygen consumption; activity counts variability; objective monitors

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Background: The purpose of this study was to compare the 2006 and 2010 Crouter algorithms for the ActiGraph accelerometer and the NHANES and Matthews cut-points, to indirect calorimetry during a 6-hr free-living measurement period. Methods: Twenty-nine participants (mean +/- SD; age, 38 11.7 yrs; BMI, 25.0 +/- 4.6 kg.m(-2)) were monitored for 6 hours while at work or during their leisure time. Physical activity (PA) data were collected using an ActiGraph GT1M and energy expenditure (METs) was measured using a Cosmed K4b2. ActiGraph prediction equations were compared with the Cosmed for METs and time spent in sedentary behaviors, light PA (LPA), moderate PA (MPA), and vigorous PA (VPA). Results: The 2010 Crouter algorithm overestimated time spent in LPA, MPA, and VPA by 9.0%-44.5% and underestimated sedentary time by 20.8%. The NHANES cut-points overestimated sedentary time and LPA by 8.3%-9.9% and underestimated MPA and VPA by 50.4%-56.7%. The Matthews cut-points overestimated sedentary time (9.9%) and MPA (33.4%) and underestimated LPA (25.7%) and VPA (50.1%). The 2006 Crouter algorithm was within 1.8% of measured sedentary time; however, mean errors ranged from 34.4%-163.1% for LPA, MPA, and VPA. Conclusion: Of the ActiGraph prediction methods examined, none of them was clearly superior for estimating free-living PA compared with indirect calorimetry.

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