Kids are not little adults: what MET threshold captures sedentary behavior in children?
OBJECTIVE
The study compares MET-defined cutpoints used to classify sedentary behaviors in children using a simulated free-living design.


METHODS
A sample of 102 children (54 boys and 48 girls; 7-13 years) completed a set of 12 activities (randomly selected from a pool of 24 activities) in a random order. Activities were predetermined and ranged from sedentary to vigorous intensities. Participant's energy expenditure was measured using a portable indirect calorimetry system, Oxycon mobile. Measured minute-by-minute VO2 values (i.e., ml/kg/min) were converted to an adult- or child-MET value using the standard 3.5 ml/kg/min or the estimated child resting metabolic rate, respectively. Classification agreement was examined for both the "standard" (1.5 adult-METs) and an "adjusted" (2.0 adult-METs) MET-derived threshold for classifying sedentary behavior. Alternatively, we also tested the classification accuracy of a 1.5 child-MET threshold. Classification accuracy of sedentary activities was evaluated relative to the predetermined intensity categorization using receiver operator characteristic curves.


RESULTS
There were clear improvements in the classification accuracy for sedentary activities when a threshold of 2.0 adult-METs was used instead of 1.5 METs (Se1.5 METs = 4.7%, Sp1.5 METs = 100.0%; Se2.0 METs = 36.9%, Sp2.0 METs = 100.0 %). The use of child-METs while maintaining the 1.5 threshold also resulted in improvements in classification (Se = 45.1%, Sp = 100.0%).


CONCLUSIONS
Adult-MET thresholds are not appropriate for children when classifying sedentary activities. Classification accuracy for identifying sedentary activities was improved when either an adult-MET of 2.0 or a child-MET of 1.5 was used.
Department of Kinesiology, Iowa State University, 235 Forker Building, Ames, IA, 50011, USA. pedrosm@iastate.edu.|School of Psychology: CIPsi, University of Minho, Braga, Portugal. pedrosm@iastate.edu.
Pedro F
PF
Saint-Maurice
Department of Kinesiology, Iowa State University, 235 Forker Building, Ames, IA, 50011, USA. youngwon.kim@mrc-epid.cam.ac.uk.|MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge, CB2 0QQ, UK. youngwon.kim@mrc-epid.cam.ac.uk.
Youngwon
Y
Kim
Department of Kinesiology, Iowa State University, 235 Forker Building, Ames, IA, 50011, USA. gwelk@iastate.edu.
Gregory J
GJ
Welk
School of Nutrition and Health Promotion, Arizona State University, 550 N Third St, Phoenix, AZ, 85004, USA. glenn.gaesser@asu.edu.
Glenn A
GA
Gaesser
D000293:Adolescent; D000294:Adolescent Behavior; D000328:Adult; D000367:Age Factors; D001481:Basal Metabolism / Q000502:physiology*; D002153:Calorimetry, Indirect / Q000523:psychology*; D002648:Child; D002652:Child Behavior; D004734:Energy Metabolism / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D009043:Motor Activity / Q000502:physiology*; D010101:Oxygen Consumption / Q000502:physiology; D057185:Sedentary Behavior
Measurement; Public health; Resting energy expenditure; Youth