Estimating physical activity in youth using a wrist accelerometer.

PURPOSE The purpose of this study was to develop and validate methods for analyzing wrist accelerometer data in youth. METHODS A total of 181 youth (mean ± SD; age, 12.0 ± 1.5 yr) completed 30 min of supine rest and 8 min each of 2 to 7 structured activities, selected from a list of 25. Receiver operating characteristic (ROC) curves and regression analyses were used to develop prediction equations for energy expenditure (child-METs; measured activity V˙O2 divided by measured resting V˙O2) and cut points for computing time spent in sedentary behaviors (SB), light (LPA), moderate (MPA), and vigorous (VPA) physical activity. Both vertical axis (VA) and vector magnitude (VM) counts per 5 s were used for this purpose. The validation study included 42 youth (age, 12.6 ± 0.8 yr) who completed approximately 2 h of unstructured PA. During all measurements, activity data were collected using an ActiGraph GT3X or GT3X+, positioned on the dominant wrist. Oxygen consumption was measured using a Cosmed K4b. Repeated-measures ANOVA were used to compare measured versus predicted child-METs (regression only) and time spent in SB, LPA, MPA, and VPA. RESULTS All ROC cut points were similar for area under the curve (≥0.825), sensitivity (≥0.756), and specificity (≥0.634), and they significantly underestimated LPA and overestimated VPA (P < 0.05). The VA and VM regression models were within ±0.21 child-METs of mean measured child-METs and ±2.5 min of measured time spent in SB, LPA, MPA, and VPA, respectively (P > 0.05). CONCLUSIONS Compared to measured values, the VA and VM regression models developed on wrist accelerometer data had insignificant mean bias for child-METs and time spent in SB, LPA, MPA, and VPA; however, they had large individual errors.