Skip to main content
ARS Home » Plains Area » Houston, Texas » Children's Nutrition Research Center » Research » Publications at this Location » Publication #307537
Title: Prediction of energy expenditure and physical activity in preschoolers

Author
item BUTTE, NANCY - Children'S Nutrition Research Center (CNRC)
item WONG, WILLIAM - Children'S Nutrition Research Center (CNRC)
item LEE, JONG SOO - University Of Delaware
item ADOLPH, ANNE - Children'S Nutrition Research Center (CNRC)
item PUYAU, MAURICE - Children'S Nutrition Research Center (CNRC)
item ZAKERI, ISSA - Drexel University

Submitted to: American College of Sports Medicine
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/1/2013
Publication Date: 12/1/2013
Citation: Butte, N.F., Wong, W.W., Lee, J., Adolph, A.L., Puyau, M.R., Zakeri, I.F. 2013. Prediction of energy expenditure and physical activity in preschoolers. American College of Sports Medicine. 46:1216-1226.

Interpretive Summary: Scientists need to be able to measure the energy expended and physical activity done by preschoolers using ways that are accurate, that don't interfere with daily life, and that are cost-effective. In this study, we checked to see how accurate activity monitors (accelerometers) and heart rate monitoring devices can be used to predict energy expenditure in preschoolers using two statistical models called cross-sectional time series (CSTS) and multivariate adaptive regression splines (MARS). We compared our models against "gold standard" methods – room calorimetry and doubly labeled water for the measurement of energy expenditure. Fifty preschool children each stayed in a room calorimeter where we measured the calories they spent minute by minute while wearing the activity and heart rate monitors. A group of 105 children completed the doubly labeled water test while wearing the devices for 7 days at home. We found that CSTS and MARS models predicted the energy expended by preschool-aged children without bias and with acceptable errors. We also established cut points for the activity monitors for classifying sedentary, light, and moderate/vigorous levels of physical activity in preschoolers. This is important as we validate other inexpensive methods for measuring this age group.

Technical Abstract: 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. 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. 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. 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.