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This study examined the classification accuracy of the activPAL, including total time spent sedentary and total number of breaks in sedentary behavior (SB) in 4- to 6-year-old children. Forty children aged 4–6 years (5.3 ± 1.0 years) completed a ~150-min laboratory protocol involving sedentary, light, and moderate- to vigorous-intensity activities. Posture was coded as sit/lie, stand, walk, or other using direct observation. Posture was classified using the activPAL software. Classification accuracy was evaluated using sensitivity, specificity and area under the receiver operating characteristic curve (ROC-AUC). Time spent in each posture and total number of breaks in SB were compared using paired sample t-tests. The activPAL showed good classification accuracy for sitting (ROC-AUC = 0.84) and fair classification accuracy for standing and walking (0.76 and 0.73, respectively). Time spent in sit/lie and stand was overestimated by 5.9% (95% CI = 0.6−11.1%) and 14.8% (11.6−17.9%), respectively; walking was underestimated by 10.0% (−12.9−7.0%). Total number of breaks in SB were significantly overestimated (55 ± 27 over the course of the protocol; p < .01). The activPAL performed well when classifying postures in young children. However, the activPAL has difficulty classifying other postures, such as kneeling. In addition, when predicting time spent in different postures and total number of breaks in SB the activPAL appeared not to be accurate.
Janssen, Cliff, Jones, and Okley are with the Interdisciplinary Educational Research Institute, University of Wollongong, Wollongong, Australia. Reilly is with the Physical Activity for Health Group, University of Strathclyde, Glasgow, UK. Hinkley is with the Centre for Physical Activity and Nutrition Research, Deakin University, Burwood, Australia. Batterham is with the School of Psychological Sciences and Health, University of Wollongong, Wollongong, Australia. Ekelund is with the Dept. of Sport Medicine, Norwegian School of Sport Sciences, Oslo, Norway. Brage is with the MRC Epidemiology Unit, Institute of Metabolic Science, Cambridge, UK.