Literature DB >> 23196761

Accuracy of accelerometer regression models in predicting energy expenditure and METs in children and youth.

Sofiya Alhassan1, Kate Lyden, Cheryl Howe, Sarah Kozey Keadle, Ogechi Nwaokelemeh, Patty S Freedson.   

Abstract

This study examined the validity of commonly used regression equations for the Actigraph and Actical accelerometers in predicting energy expenditure (EE) in children and adolescents. Sixty healthy (8-16 yrs) participants completed four treadmill (TM) and five self-paced activities of daily living (ADL). Four Actigraph (AG) and three Actical (AC) regression equations were used to estimate EE. Bias (± 95% CI) and root mean squared errors were used to assess the validity of the regression equations compared with indirect calorimetry. For children, the Freedson (AG) model accurately predicted EE for all activities combined and the Treuth (AG) model accurately predicted EE for TM activities. For adolescents, the Freedson model accurately predicted EE for TM activities and the Treuth model accurately predicted EE for all activities and for TM activities. No other equation accurately estimated EE. The percent agreement for the AG and AC equations were better for light and vigorous compared with moderate intensity activities. The Trost (AG) equation most accurately classified all activity intensity categories. Overall, equations yield inconsistent point estimates of EE.

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Year:  2012        PMID: 23196761      PMCID: PMC4005275          DOI: 10.1123/pes.24.4.519

Source DB:  PubMed          Journal:  Pediatr Exerc Sci        ISSN: 0899-8493            Impact factor:   2.333


  25 in total

1.  Validation and calibration of physical activity monitors in children.

Authors:  Maurice R Puyau; Anne L Adolph; Firoz A Vohra; Nancy F Butte
Journal:  Obes Res       Date:  2002-03

2.  Defining accelerometer thresholds for activity intensities in adolescent girls.

Authors:  Margarita S Treuth; Kathryn Schmitz; Diane J Catellier; Robert G McMurray; David M Murray; M Joao Almeida; Scott Going; James E Norman; Russell Pate
Journal:  Med Sci Sports Exerc       Date:  2004-07       Impact factor: 5.411

Review 3.  Calibration of accelerometer output for children.

Authors:  Patty Freedson; David Pober; Kathleen F Janz
Journal:  Med Sci Sports Exerc       Date:  2005-11       Impact factor: 5.411

4.  Moderate-to-vigorous physical activity among children: discrepancies in accelerometry-based cut-off points.

Authors:  Comlavi B Guinhouya; Hervé Hubert; Stéphane Soubrier; Christian Vilhelm; Mohamed Lemdani; Alain Durocher
Journal:  Obesity (Silver Spring)       Date:  2006-05       Impact factor: 5.002

5.  Validity of four motion sensors in measuring moderate intensity physical activity.

Authors:  D R Bassett; B E Ainsworth; A M Swartz; S J Strath; W L O'Brien; G A King
Journal:  Med Sci Sports Exerc       Date:  2000-09       Impact factor: 5.411

6.  Validity of the computer science and applications (CSA) activity monitor in children.

Authors:  S G Trost; D S Ward; S M Moorehead; P D Watson; W Riner; J R Burke
Journal:  Med Sci Sports Exerc       Date:  1998-04       Impact factor: 5.411

7.  Predicting activity energy expenditure using the Actical activity monitor.

Authors:  Daniel P Heil
Journal:  Res Q Exerc Sport       Date:  2006-03       Impact factor: 2.500

Review 8.  Physical activity assessment in children and adolescents.

Authors:  R R Pate
Journal:  Crit Rev Food Sci Nutr       Date:  1993       Impact factor: 11.176

9.  Relationships between accelerometer-assessed physical activity and health in children: impact of the activity-intensity classification method.

Authors:  Michelle R Stone; Ann V Rowlands; Roger G Eston
Journal:  J Sports Sci Med       Date:  2009-03-01       Impact factor: 2.988

10.  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

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  7 in total

1.  Variations of body composition, physical activity and caloric intake in schoolchildren during national holidays.

Authors:  Carlos Cristi-Montero; Cristian Munizaga; Constanza Tejos; Raquel Ayala; Raúl Henríquez; Patricio Solís-Urra; Fernando Rodríguez-Rodríguez
Journal:  Eat Weight Disord       Date:  2015-10-06       Impact factor: 4.652

2.  Rates of Obesity and Obesogenic Behaviors of Rural Appalachian Adolescents: How Do They Compare to Other Adolescents or Recommendations?

Authors:  Laureen H Smith; Devin Laurent; Erica Baumker; Rick L Petosa
Journal:  J Phys Act Health       Date:  2018-10-13

3.  Ankle Accelerometry for Assessing Physical Activity Among Adolescent Girls: Threshold Determination, Validity, Reliability, and Feasibility.

Authors:  Erin R Hager; Margarita S Treuth; Candice Gormely; LaShawna Epps; Soren Snitker; Maureen M Black
Journal:  Res Q Exerc Sport       Date:  2015-08-19       Impact factor: 2.500

4.  Prediction models discriminating between nonlocomotive and locomotive activities in children using a triaxial accelerometer with a gravity-removal physical activity classification algorithm.

Authors:  Yuki Hikihara; Chiaki Tanaka; Yoshitake Oshima; Kazunori Ohkawara; Kazuko Ishikawa-Takata; Shigeho Tanaka
Journal:  PLoS One       Date:  2014-04-22       Impact factor: 3.240

5.  Study protocol and rationale of the "Cogni-action project" a cross-sectional and randomized controlled trial about physical activity, brain health, cognition, and educational achievement in schoolchildren.

Authors:  Patricio Solis-Urra; Jorge Olivares-Arancibia; Ernesto Suarez-Cadenas; Javier Sanchez-Martinez; Fernando Rodríguez-Rodríguez; Francisco B Ortega; Irene Esteban-Cornejo; Cristina Cadenas-Sanchez; Jose Castro-Piñero; Alejandro Veloz; Steren Chabert; Kabir P Sadarangani; Juan Pablo Zavala-Crichton; Jairo H Migueles; Jose Mora-Gonzalez; Milton Quiroz-Escobar; Diego Almonte-Espinoza; Alfonso Urzúa; Constantino D Dragicevic; Aland Astudillo; Eduardo Méndez-Gassibe; Daniel Riquelme-Uribe; Marcela Jarpa Azagra; Carlos Cristi-Montero
Journal:  BMC Pediatr       Date:  2019-07-26       Impact factor: 2.125

6.  Comparison of Accelerometer-Based Cut-Points for Children's Physical Activity: Counts vs. Steps.

Authors:  Cheryl A Howe; Kimberly A Clevenger; Ryann E Leslie; Moira A Ragan
Journal:  Children (Basel)       Date:  2018-08-03

7.  Simple Prediction of Metabolic Equivalents of Daily Activities Using Heart Rate Monitor without Calibration of Individuals.

Authors:  Yuko Caballero; Takafumi J Ando; Satoshi Nakae; Chiyoko Usui; Tomoko Aoyama; Motofumi Nakanishi; Sho Nagayoshi; Yoko Fujiwara; Shigeho Tanaka
Journal:  Int J Environ Res Public Health       Date:  2019-12-27       Impact factor: 3.390

  7 in total

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