Nancy F Butte1, William W Wong, Jong Soo Lee, Anne L Adolph, Maurice R Puyau, Issa F Zakeri. 1. 1USDA/ARS Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX; 2Department of Applied Economics and Statistics, University of Delaware, Newark, DE; and 3Department of Epidemiology and Biostatistics, Drexel University, Philadelphia, PA.
Abstract
PURPOSE: Accurate, nonintrusive, and feasible methods are needed to predict energy expenditure (EE) and physical activity (PA) levels in preschoolers. Herein, we validated cross-sectional time series (CSTS) and multivariate adaptive regression splines (MARS) models based on accelerometry and heart rate (HR) for the prediction of EE using room calorimetry and doubly labeled water (DLW) and established accelerometry cut points for PA levels. METHODS: Fifty preschoolers, mean ± SD age of 4.5 ± 0.8 yr, participated in room calorimetry for minute-by-minute measurements of EE, accelerometer counts (AC) (Actiheart and ActiGraph GT3X+), and HR (Actiheart). Free-living 105 children, ages 4.6 ± 0.9 yr, completed the 7-d DLW procedure while wearing the devices. AC cut points for PA levels were established using smoothing splines and receiver operating characteristic curves. RESULTS: On the basis of calorimetry, mean percent errors for EE were -2.9% ± 10.8% and -1.1% ± 7.4% for CSTS models and -1.9% ± 9.6% and 1.3% ± 8.1% for MARS models using the Actiheart and ActiGraph+HR devices, respectively. On the basis of DLW, mean percent errors were -0.5% ± 9.7% and 4.1% ± 8.5% for CSTS models and 3.2% ± 10.1% and 7.5% ± 10.0% for MARS models using the Actiheart and ActiGraph+HR devices, respectively. Applying activity EE thresholds, final accelerometer cut points were determined: 41, 449, and 1297 cpm for Actiheart x-axis; 820, 3908, and 6112 cpm for ActiGraph vector magnitude; and 240, 2120, and 4450 cpm for ActiGraph x-axis for sedentary/light, light/moderate, and moderate/vigorous PA (MVPA), respectively. On the basis of confusion matrices, correctly classified rates were 81%-83% for sedentary PA, 58%-64% for light PA, and 62%-73% for MVPA. CONCLUSIONS: The lack of bias and acceptable limits of agreement affirms the validity of the CSTS and MARS models for the prediction of EE in preschool-aged children. Accelerometer cut points are satisfactory for the classification of sedentary, light, and moderate/vigorous levels of PA in preschoolers.
PURPOSE: Accurate, nonintrusive, and feasible methods are needed to predict energy expenditure (EE) and physical activity (PA) levels in preschoolers. Herein, we validated cross-sectional time series (CSTS) and multivariate adaptive regression splines (MARS) models based on accelerometry and heart rate (HR) for the prediction of EE using room calorimetry and doubly labeled water (DLW) and established accelerometry cut points for PA levels. METHODS: Fifty preschoolers, mean ± SD age of 4.5 ± 0.8 yr, participated in room calorimetry for minute-by-minute measurements of EE, accelerometer counts (AC) (Actiheart and ActiGraph GT3X+), and HR (Actiheart). Free-living 105 children, ages 4.6 ± 0.9 yr, completed the 7-d DLW procedure while wearing the devices. AC cut points for PA levels were established using smoothing splines and receiver operating characteristic curves. RESULTS: On the basis of calorimetry, mean percent errors for EE were -2.9% ± 10.8% and -1.1% ± 7.4% for CSTS models and -1.9% ± 9.6% and 1.3% ± 8.1% for MARS models using the Actiheart and ActiGraph+HR devices, respectively. On the basis of DLW, mean percent errors were -0.5% ± 9.7% and 4.1% ± 8.5% for CSTS models and 3.2% ± 10.1% and 7.5% ± 10.0% for MARS models using the Actiheart and ActiGraph+HR devices, respectively. Applying activity EE thresholds, final accelerometer cut points were determined: 41, 449, and 1297 cpm for Actiheart x-axis; 820, 3908, and 6112 cpm for ActiGraph vector magnitude; and 240, 2120, and 4450 cpm for ActiGraph x-axis for sedentary/light, light/moderate, and moderate/vigorous PA (MVPA), respectively. On the basis of confusion matrices, correctly classified rates were 81%-83% for sedentary PA, 58%-64% for light PA, and 62%-73% for MVPA. CONCLUSIONS: The lack of bias and acceptable limits of agreement affirms the validity of the CSTS and MARS models for the prediction of EE in preschool-aged children. Accelerometer cut points are satisfactory for the classification of sedentary, light, and moderate/vigorous levels of PA in preschoolers.
Authors: Karin A Pfeiffer; Kerry L McIver; Marsha Dowda; Maria J C A Almeida; Russell R Pate Journal: Med Sci Sports Exerc Date: 2006-01 Impact factor: 5.411
Authors: R H DuRant; T Baranowski; J Puhl; T Rhodes; H Davis; K A Greaves; W O Thompson Journal: Med Sci Sports Exerc Date: 1993-12 Impact factor: 5.411
Authors: Alissa D Smethers; Liane S Roe; Christine E Sanchez; Faris M Zuraikat; Kathleen L Keller; Barbara J Rolls Journal: Physiol Behav Date: 2019-03-01
Authors: Nancy F Butte; William W Wong; Theresa A Wilson; Anne L Adolph; Maurice R Puyau; Issa F Zakeri Journal: Am J Clin Nutr Date: 2014-05-07 Impact factor: 7.045
Authors: Alissa D Smethers; Liane S Roe; Christine E Sanchez; Faris M Zuraikat; Kathleen L Keller; Samantha M R Kling; Barbara J Rolls Journal: Am J Clin Nutr Date: 2019-05-01 Impact factor: 7.045
Authors: Rebecca E Lee; Elizabeth Lorenzo; Jacob Szeszulski; Anel Arriola; Meg Bruening; Paul A Estabrooks; Jennie Hill; Flavio F Marsiglia; Teresia O'Connor; Kim Sellers Pollins; Gabriel Q Shaibi; Erica Soltero; Michael Todd Journal: Contemp Clin Trials Date: 2018-12-12 Impact factor: 2.226
Authors: Nancy F Butte; Maurice R Puyau; Theresa A Wilson; Yan Liu; William W Wong; Anne L Adolph; Issa F Zakeri Journal: Obesity (Silver Spring) Date: 2016-04-18 Impact factor: 5.002
Authors: C Delisle Nyström; J Pomeroy; P Henriksson; E Forsum; F B Ortega; R Maddison; J H Migueles; M Löf Journal: Eur J Clin Nutr Date: 2017-07-26 Impact factor: 4.016
Authors: Shari L Barkin; William J Heerman; Evan C Sommer; Nina C Martin; Maciej S Buchowski; David Schlundt; Eli K Po'e; Laura E Burgess; Juan Escarfuller; Charlotte Pratt; Kimberly P Truesdale; June Stevens Journal: JAMA Date: 2018-08-07 Impact factor: 56.272
Authors: Jairo H Migueles; Cristina Cadenas-Sanchez; Ulf Ekelund; Christine Delisle Nyström; Jose Mora-Gonzalez; Marie Löf; Idoia Labayen; Jonatan R Ruiz; Francisco B Ortega Journal: Sports Med Date: 2017-09 Impact factor: 11.136