Literature DB >> 22975460

Validity of ActiGraph 2-regression model, Matthews cut-points, and NHANES cut-points for assessing free-living physical activity.

Scott E Crouter1, Diane M DellaValle, Jere D Haas, Edward A Frongillo, David R Bassett.   

Abstract

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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Mesh:

Year:  2012        PMID: 22975460      PMCID: PMC4199088          DOI: 10.1123/jpah.10.4.504

Source DB:  PubMed          Journal:  J Phys Act Health        ISSN: 1543-3080


  27 in total

1.  Validation of the COSMED K4 b2 portable metabolic system.

Authors:  J E McLaughlin; G A King; E T Howley; D R Bassett; B E Ainsworth
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Review 2.  Calibration of accelerometer output for adults.

Authors:  Charles E Matthew
Journal:  Med Sci Sports Exerc       Date:  2005-11       Impact factor: 5.411

3.  A novel method for using accelerometer data to predict energy expenditure.

Authors:  Scott E Crouter; Kurt G Clowers; David R Bassett
Journal:  J Appl Physiol (1985)       Date:  2005-12-01

4.  Amount of time spent in sedentary behaviors in the United States, 2003-2004.

Authors:  Charles E Matthews; Kong Y Chen; Patty S Freedson; Maciej S Buchowski; Bettina M Beech; Russell R Pate; Richard P Troiano
Journal:  Am J Epidemiol       Date:  2008-02-25       Impact factor: 4.897

5.  Comparing the performance of three generations of ActiGraph accelerometers.

Authors:  Megan P Rothney; Gregory A Apker; Yanna Song; Kong Y Chen
Journal:  J Appl Physiol (1985)       Date:  2008-07-17

6.  Statistical methods for assessing agreement between two methods of clinical measurement.

Authors:  J M Bland; D G Altman
Journal:  Lancet       Date:  1986-02-08       Impact factor: 79.321

7.  Validation of the ActiGraph two-regression model for predicting energy expenditure.

Authors:  Megan P Rothney; Robert J Brychta; Natalie N Meade; Kong Y Chen; Maciej S Buchowski
Journal:  Med Sci Sports Exerc       Date:  2010-09       Impact factor: 5.411

8.  Comparison of four ActiGraph accelerometers during walking and running.

Authors:  Dinesh John; Brian Tyo; David R Bassett
Journal:  Med Sci Sports Exerc       Date:  2010-02       Impact factor: 5.411

9.  Physical activity in the United States measured by accelerometer.

Authors:  Richard P Troiano; David Berrigan; Kevin W Dodd; Louise C Mâsse; Timothy Tilert; Margaret McDowell
Journal:  Med Sci Sports Exerc       Date:  2008-01       Impact factor: 5.411

10.  Television time and continuous metabolic risk in physically active adults.

Authors:  Genevieve N Healy; David W Dunstan; Jo Salmon; Jonathan E Shaw; Paul Z Zimmet; Neville Owen
Journal:  Med Sci Sports Exerc       Date:  2008-04       Impact factor: 5.411

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  40 in total

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Authors:  Shao-Hsien Liu; Charles B Eaton; Jeffrey B Driban; Timothy E McAlindon; Kate L Lapane
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2.  Accelerometer measured sedentary behavior and physical activity in white and black adults: The REGARDS study.

Authors:  Steven P Hooker; Brent Hutto; Wenfei Zhu; Steven N Blair; Natalie Colabianchi; John E Vena; David Rhodes; Virginia J Howard
Journal:  J Sci Med Sport       Date:  2015-04-17       Impact factor: 4.319

3.  Validity of ActiGraph child-specific equations during various physical activities.

Authors:  Scott E Crouter; Magdalene Horton; David R Bassett
Journal:  Med Sci Sports Exerc       Date:  2013-07       Impact factor: 5.411

4.  Accelerometer-measured dose-response for physical activity, sedentary time, and mortality in US adults.

Authors:  Charles E Matthews; Sarah Kozey Keadle; Richard P Troiano; Lisa Kahle; Annemarie Koster; Robert Brychta; Dane Van Domelen; Paolo Caserotti; Kong Y Chen; Tamara B Harris; David Berrigan
Journal:  Am J Clin Nutr       Date:  2016-10-05       Impact factor: 7.045

5.  Modifying Accelerometer Cut-Points Affects Criterion Validity in Simulated Free-Living for Adolescents and Adults.

Authors:  Paul R Hibbing; David R Bassett; Scott E Crouter
Journal:  Res Q Exerc Sport       Date:  2020-02-05       Impact factor: 2.500

6.  Deriving a GPS Monitoring Time Recommendation for Physical Activity Studies of Adults.

Authors:  Katelyn M Holliday; Annie Green Howard; Michael Emch; Daniel A Rodríguez; Wayne D Rosamond; Kelly R Evenson
Journal:  Med Sci Sports Exerc       Date:  2017-05       Impact factor: 5.411

7.  Accelerometry: Improving Objective Assessments of Therapeutic Impact in Pediatric Pulmonary Arterial Hypertension.

Authors:  Eric D Austin; Jeffrey A Feinstein
Journal:  Am J Respir Crit Care Med       Date:  2017-07-15       Impact factor: 21.405

8.  Validation of a method for estimating energy expenditure during walking in middle-aged adults.

Authors:  Nathan Caron; Teddy Caderby; Nicolas Peyrot; Chantal Verkindt; Georges Dalleau
Journal:  Eur J Appl Physiol       Date:  2017-12-09       Impact factor: 3.078

9.  Accelerometer and GPS Data to Analyze Built Environments and Physical Activity.

Authors:  Kosuke Tamura; Jeffrey S Wilson; Keith Goldfeld; Robin C Puett; David B Klenosky; William A Harper; Philip J Troped
Journal:  Res Q Exerc Sport       Date:  2019-06-14       Impact factor: 2.500

10.  Predictors of discordance in self-report versus device-measured physical activity measurement.

Authors:  Jessica Gorzelitz; Paul E Peppard; Kristen Malecki; Keith Gennuso; F Javier Nieto; Lisa Cadmus-Bertram
Journal:  Ann Epidemiol       Date:  2018-03-30       Impact factor: 3.797

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