Save the Date!
ActiGraph Digital Data Summit 2021November 4 - 5 | Register for Event Updates Now
Predicting Chinese children and youth's energy expenditure using ActiGraph accelerometers: a calibration and cross-validation study.
- Published on December 2013
Purpose The purpose of this study was to develop and cross-validate an equation based on ActiGraph accelerometer GT3X output to predict children and youth’s energy expenditure (EE) of physical activity (PA).
Method Participants were 367 Chinese children and youth (179 boys and 188 girls, aged 9 to 17 years old) who wore 1 ActiGraph GT3X accelerometer on their right hip during the following tests/activities: resting metabolic rate (RMR), six 5-min treadmill walk/runs (tested at different speeds: 3 km x h(-1), 4 km x h(-1), 5 km x h(-1), 6 km x h(-1), 7 km x h(-1), and 8 km x h(-1)), 1 broadcast gymnastics, and 2 table-tennis exercises. Participants’ oxygen consumption was measured using Cosmed K4b(2). The participants were randomly divided into a calibration group (n = 331, 90%) and a cross-validation group (n = 36, 10%). The calibration group’s data were used to determine the relationship between EE and triaxial vector magnitude counts (VM) using the Pearson correlation and to derive the equation using a stepwise multiple regression. In the cross-validation group, differences between measured and predicted EE were evaluated using pairwise t tests.
Results VM activity counts had a moderately high correlation with EE (r = .758, p < .01). An EE prediction equation was developed: EE (kcal x min(-1)) = 0.00083 x VM + 0.073 x weight-2.01 (R2 = .72, SEE = 1.45 kcal x min(-1)). According to the cross-validation study results, this equation could predict the EE within the range of known accuracy (i.e., about 20% error).
Conclusions An equation based on ActiGraph accelerometer VM activity counts was derived to predict EE of PA in Chinese children and youth within the range of known accuracy.