Predicting Chinese children and youth's energy expenditure using ActiGraph accelerometers: a calibration and cross-validation study

Res Q Exerc Sport. 2013 Dec:84 Suppl 2:S56-63. doi: 10.1080/02701367.2013.850989.

Abstract

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.

Publication types

  • Validation Study

MeSH terms

  • Accelerometry / instrumentation*
  • Adolescent
  • Calibration
  • Calorimetry, Indirect
  • Child
  • China
  • Energy Metabolism*
  • Female
  • Health Behavior
  • Health Surveys
  • Humans
  • Male
  • Motor Activity*
  • Random Allocation
  • Regression Analysis