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

in Journal of Physical Activity and Health
Restricted access

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.

Crouter is with the Dept of Exercise and Health Sciences, University of Massachusetts–Boston. DellaValle and Haas are with the Division of Nutritional Sciences, Cornell University, Ithaca, NY. Frongillo is with the Dept of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, SC. Bassett is with the Dept of Exercise, Sport, and Leisure Studies, University of Tennessee, Knoxville, TN.