PUYAU, M. R., A. L. ADOLPH, F. A. VOHRA, I. ZAKERI, and N. F. BUTTE. Prediction of Activity Energy Expenditure Using Accelerometers in Children. Med. Sci. Sports Exerc., Vol. 36, No. 9, pp. 1625–1631, 2004.
Purpose: To validate two accelerometer-based activity monitors as measures of children’s physical activity using energy expenditure as the criterion measure.
Methods: Actiwatch (AW) and Actical (AC) activity monitors were validated against continuous 4-h measurements of energy expenditure (EE) in a respiratory room calorimeter and 1-h measurements in an exercise laboratory using a portable calorimeter and treadmill in 32 children, ages 7–18 yr. The children performed structured activities including basal metabolic rate (BMR), playing Nintendo, using a computer, cleaning, aerobic exercise, ball toss, treadmill walking, and running. Equations were developed to predict activity energy expenditure (AEE = EE − BMR), and physical activity ratio (PAR = EE/BMR) from a power function of AW or AC, and age, sex, weight, and height. Thresholds were determined to categorize sedentary, light, moderate, and vigorous levels of physical activity.
Results: Activity counts accounted for the majority of the variability in AEE and PAR, with small contributions of age, sex, weight, and height. Overall, AW equations accounted for 76–79% and AC equations accounted for 81% of the variability in AEE and PAR. Relatively wide 95% prediction intervals suggest the accelerometers are best applied to groups rather than individuals. Sensitivities were higher for the vigorous threshold (97%) than the other thresholds (86–92%). Specificities were on the order of 66–73%. The positive predictive values for sedentary, light, moderate, and vigorous categories were 80, 66, 69, and 74% for AW, respectively, and 81, 68, 72, 74% for AC, respectively.
Conclusion: Both accelerometer-based activity monitors provided valid measures of children’s AEE and PAR, and can be used to discriminate sedentary, light, moderate, and vigorous levels of physical activity but require further development to accurately predict AEE and PAR of individuals.