Korean J Community Nutr.  2017 Oct;22(5):413-425. 10.5720/kjcn.2017.22.5.413.

Accuracy of Accelerometer for the Prediction of Energy Expenditure and Activity Intensity in Athletic Elementary School Children During Selected Activities

• Choi SJ
• An HS
• Lee MR
• Lee JS
• Kim EK

• KMID: 2395248
• DOI: http://doi.org/10.5720/kjcn.2017.22.5.413

Abstract

OBJECTIVES
Accurate assessment of energy expenditure is important for estimation of energy requirements in athletic children. The objective of this study was to evaluate the accuracy of accelerometer for prediction of selected activities' energy expenditure and intensity in athletic elementary school children.
METHODS
The present study involved 31 soccer players (16 males and 15 females) from an elementary school (9-12 years). During the measurements, children performed eight selected activities while simultaneously wearing the accelerometer and carrying the portable indirect calorimeter. Five equations (Freedson/Trost, Treuth, Pate, Puyau, Mattocks) were assessed for the prediction of energy expenditure from accelerometer counts, while Evenson equation was added for prediction of activity intensity, making msix equations in total. The accuracy of accelerometer for energy prediction was assessed by comparing measured and predicted values, using the paired t-test. The intensity classification accuracy was evaluated with kappa statistics and ROC-Curve.
RESULTS
For activities of lying down, television viewing and reading, Freedson/Trost, Treuth were accurate in predicting energy expenditure. Regarding Pate, it was accurate for vacuuming and slow treadmill walking energy prediction. Mattocks was accurate in treadmill running activities. Concerning activity intensity classification accuracy, Pate (kappa=0.72) had the best performance across the four intensities (sedentary, light, moderate, vigorous). In case of the sedentary activities, all equations had a good prediction accuracy, while with light activities and Vigorous activities, Pate had an excellent accuracy (ROC-AUC=0.91, 0.94). For Moderate activities, all equations showed a poor performance.
CONCLUSIONS
In conclusion, none of the assessed equations was accurate in predicting energy expenditure across all assessed activities in athletic children. For activity intensity classification, Pate had the best prediction accuracy.

Keyword

energy expenditure; accelerometer; children; athlete

MeSH Terms

Athletes
Child*
Classification
Deception
Energy Metabolism*
Humans
Male
Running
Soccer
Sports*
Television
Vacuum
Walking

Figure

• 

  Fig. 1 Comparison of predicted energy expenditure by ActiGraph with measured energy expenditure by K4b2. * Statistically significant (p<0.001). (LD: Lying down, TV: Television viewing, RE: Reading, VA: Vacuuming, SW: Slow walking(2.5mph), BW: Brisk walking (3.5mph), SC: Stair climbing, RU: Running (5mph)).

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