Christiana M T VAN Loo1, Anthony D Okely, Marijka J Batterham, Trina Hinkley, Ulf Ekelund, Søren Brage, John J Reilly, Stewart G Trost, Rachel A Jones, Xanne Janssen, Dylan P Cliff. 1. 1Early Start Research Institute and Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, AUSTRALIA; 2School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, AUSTRALIA; 3School of Exercise and Nutrition Sciences, Institute for Physical Activity and Nutrition (IPAN), Deakin University, Geelong, AUSTRALIA; 4Norwegian School of Sports Sciences, Oslo, NORWAY; 5MRC Epidemiology Unit, University of Cambridge, Cambridge, UNITED KINGDOM; 6School of Psychological Sciences and Health, University of Strathclyde, Glasgow, Scotland, UNITED KINGDOM; and 7Institute of Health and Biomedical Innovation at Queensland Centre for Children's Health Research, School of Exercise and Nutrition Science, Queensland University of Technology, Brisbane, AUSTRALIA.
Abstract
INTRODUCTION: This study aimed to examine the validity and accuracy of wrist accelerometers for classifying sedentary behavior (SB) in children. METHODS: Fifty-seven children (5-8 and 9-12 yr) completed an ~170-min protocol, including 15 semistructured activities and transitions. Nine ActiGraph (GT3X+) and two GENEActiv wrist cut points were evaluated. Direct observation was the criterion measure. The accuracy of wrist cut points was compared with that achieved by the ActiGraph hip cut point (≤25 counts per 15 s) and the thigh-mounted activPAL3. Analyses included equivalence testing, Bland-Altman procedures, and area under the receiver operating curve (ROC-AUC). RESULTS: The most accurate ActiGraph wrist cut points (Kim; vector magnitude, ≤3958 counts per 60 s; vertical axis, ≤1756 counts per 60 s) demonstrated good classification accuracy (ROC-AUC = 0.85-0.86) and accurately estimated SB time in 5-8 yr (equivalence P = 0.02; mean bias = 4.1%, limits of agreement = -20.1% to 28.4%) and 9-12 yr (equivalence P < 0.01; -2.5%, -27.9% to 22.9%). The mean bias of SB time estimates from Kim were smaller than ActiGraph hip (5-8 yr: 15.8%, -5.7% to 37.2%; 9-12 yr: 17.8%, -3.9% to 39.5%) and similar to or smaller than activPAL3 (5-8 yr: 12.6%, -39.8% to 14.7%; 9-12 yr: -1.4%, -13.9% to 11.0%), although classification accuracy was similar to ActiGraph hip (ROC-AUC = 0.85) but lower than activPAL3 (ROC-AUC = 0.92-0.97). Mean bias (5-8 yr: 6.5%, -16.1% to 29.1%; 9-12 yr: 10.5%, -13.6% to 34.6%) for the most accurate GENEActiv wrist cut point (Schaefer: ≤0.19 g) was smaller than ActiGraph hip, and activPAL3 in 5-8 yr, but larger than activPAL3 in 9-12 yr. However, SB time estimates from Schaefer were not equivalent to direct observation (equivalence P > 0.05) and classification accuracy (ROC-AUC = 0.79-0.80) was lower than for ActiGraph hip and activPAL3. CONCLUSION: The most accurate SB ActiGraph (Kim) and GENEActiv (Schaefer) wrist cut points can be applied in children with similar confidence as the ActiGraph hip cut point (≤25 counts per 15 s), although activPAL3 was generally more accurate.
INTRODUCTION: This study aimed to examine the validity and accuracy of wrist accelerometers for classifying sedentary behavior (SB) in children. METHODS: Fifty-seven children (5-8 and 9-12 yr) completed an ~170-min protocol, including 15 semistructured activities and transitions. Nine ActiGraph (GT3X+) and two GENEActiv wrist cut points were evaluated. Direct observation was the criterion measure. The accuracy of wrist cut points was compared with that achieved by the ActiGraph hip cut point (≤25 counts per 15 s) and the thigh-mounted activPAL3. Analyses included equivalence testing, Bland-Altman procedures, and area under the receiver operating curve (ROC-AUC). RESULTS: The most accurate ActiGraph wrist cut points (Kim; vector magnitude, ≤3958 counts per 60 s; vertical axis, ≤1756 counts per 60 s) demonstrated good classification accuracy (ROC-AUC = 0.85-0.86) and accurately estimated SB time in 5-8 yr (equivalence P = 0.02; mean bias = 4.1%, limits of agreement = -20.1% to 28.4%) and 9-12 yr (equivalence P < 0.01; -2.5%, -27.9% to 22.9%). The mean bias of SB time estimates from Kim were smaller than ActiGraph hip (5-8 yr: 15.8%, -5.7% to 37.2%; 9-12 yr: 17.8%, -3.9% to 39.5%) and similar to or smaller than activPAL3 (5-8 yr: 12.6%, -39.8% to 14.7%; 9-12 yr: -1.4%, -13.9% to 11.0%), although classification accuracy was similar to ActiGraph hip (ROC-AUC = 0.85) but lower than activPAL3 (ROC-AUC = 0.92-0.97). Mean bias (5-8 yr: 6.5%, -16.1% to 29.1%; 9-12 yr: 10.5%, -13.6% to 34.6%) for the most accurate GENEActiv wrist cut point (Schaefer: ≤0.19 g) was smaller than ActiGraph hip, and activPAL3 in 5-8 yr, but larger than activPAL3 in 9-12 yr. However, SB time estimates from Schaefer were not equivalent to direct observation (equivalence P > 0.05) and classification accuracy (ROC-AUC = 0.79-0.80) was lower than for ActiGraph hip and activPAL3. CONCLUSION: The most accurate SB ActiGraph (Kim) and GENEActiv (Schaefer) wrist cut points can be applied in children with similar confidence as the ActiGraph hip cut point (≤25 counts per 15 s), although activPAL3 was generally more accurate.
Authors: Marijka J Batterham; Christel Van Loo; Karen E Charlton; Dylan P Cliff; Anthony D Okely Journal: Br J Nutr Date: 2016-02-16 Impact factor: 3.718
Authors: Charles E Matthews; Kong Y Chen; Patty S Freedson; Maciej S Buchowski; Bettina M Beech; Russell R Pate; Richard P Troiano Journal: Am J Epidemiol Date: 2008-02-25 Impact factor: 4.897
Authors: D P Cliff; K D Hesketh; S A Vella; T Hinkley; M D Tsiros; N D Ridgers; A Carver; J Veitch; A-M Parrish; L L Hardy; R C Plotnikoff; A D Okely; J Salmon; D R Lubans Journal: Obes Rev Date: 2016-02-24 Impact factor: 9.213
Authors: Dylan P Cliff; Rachel A Jones; Tracy L Burrows; Philip J Morgan; Clare E Collins; Louise A Baur; Anthony D Okely Journal: Obesity (Silver Spring) Date: 2014-05 Impact factor: 5.002
Authors: Robert J Kuczmarski; Cynthia L Ogden; Shumei S Guo; Laurence M Grummer-Strawn; Katherine M Flegal; Zuguo Mei; Rong Wei; Lester R Curtin; Alex F Roche; Clifford L Johnson Journal: Vital Health Stat 11 Date: 2002-05
Authors: Soyang Kwon; Patricia Zavos; Katherine Nickele; Albert Sugianto; Mark V Albert Journal: Int J Environ Res Public Health Date: 2019-07-21 Impact factor: 3.390
Authors: Christian L Roth; M Jennifer Abuzzahab; Ashley H Shoemaker; Heidi J Silver; Maciej Buchowski; James C Slaughter; Jack A Yanovski; Clinton Elfers Journal: Int J Obes (Lond) Date: 2022-01-03 Impact factor: 5.551
Authors: Christiana Maria Theodora VAN Loo; Anthony D Okely; Marijka J Batterham; Trina Hinkley; Ulf Ekelund; Søren Brage; John J Reilly; Stewart G Trost; Rachel A Jones; Xanne Janssen; Dylan P Cliff Journal: Med Sci Sports Exerc Date: 2018-03 Impact factor: 5.411
Authors: David Arteaga; Thomas Donnelly; Kimberly Crum; Larry Markham; Mary Killian; W Bryan Burnette; Jonathan Soslow; Maciej S Buchowski Journal: J Neuromuscul Dis Date: 2020
Authors: Kar Hau Chong; Anne-Maree Parrish; Dylan P Cliff; Dorothea Dumuid; Anthony D Okely Journal: Int J Environ Res Public Health Date: 2021-06-03 Impact factor: 3.390