BACKGROUND: Emerging interest in the health impacts of sedentary behaviors has driven the exploration of objective instrumentation capable of capturing these behaviors. The purpose was to compare (under laboratory conditions) outputs from ActiGraph (AG), Intelligent Device for Energy Expenditure and Physical Activity (IDEEA), and activPAL Professional (AP) against direct observation (DO) in sedentary, standing, and active behaviors; and assess convergent validity of instrument outputs under free-living conditions. METHODS: Participants (13 males/16 females; 28.9 ± 6.2 years) wore instruments concurrently during laboratory and free-living studies. AG cutpoints of ≤50, <100, and ≤259 counts/minute were used to determine time in sedentary behaviors. Laboratory data were evaluated using mean percent error. Free-living data were analyzed using dependent t tests and RM ANOVA. RESULTS: AP precisely measured all identified DO behaviors under laboratory conditions; IDEEA precisely identified sitting and standing. For the free-living study, there was no difference in sedentary time detected by AP and IDEEA but a significant difference was observed in standing time. No difference was apparent between AP and AG259 in sit/lie/stand or ambulatory activity time. CONCLUSIONS: In a laboratory setting, the utility of all instruments to classify activities into behavioral categories was confirmed. This may enhance research on sedentary behaviors and health-related outcomes.
BACKGROUND: Emerging interest in the health impacts of sedentary behaviors has driven the exploration of objective instrumentation capable of capturing these behaviors. The purpose was to compare (under laboratory conditions) outputs from ActiGraph (AG), Intelligent Device for Energy Expenditure and Physical Activity (IDEEA), and activPAL Professional (AP) against direct observation (DO) in sedentary, standing, and active behaviors; and assess convergent validity of instrument outputs under free-living conditions. METHODS:Participants (13 males/16 females; 28.9 ± 6.2 years) wore instruments concurrently during laboratory and free-living studies. AG cutpoints of ≤50, <100, and ≤259 counts/minute were used to determine time in sedentary behaviors. Laboratory data were evaluated using mean percent error. Free-living data were analyzed using dependent t tests and RM ANOVA. RESULTS: AP precisely measured all identified DO behaviors under laboratory conditions; IDEEA precisely identified sitting and standing. For the free-living study, there was no difference in sedentary time detected by AP and IDEEA but a significant difference was observed in standing time. No difference was apparent between AP and AG259 in sit/lie/stand or ambulatory activity time. CONCLUSIONS: In a laboratory setting, the utility of all instruments to classify activities into behavioral categories was confirmed. This may enhance research on sedentary behaviors and health-related outcomes.
Authors: Michelle W Voss; Timothy B Weng; Agnieszka Z Burzynska; Chelsea N Wong; Gillian E Cooke; Rachel Clark; Jason Fanning; Elizabeth Awick; Neha P Gothe; Erin A Olson; Edward McAuley; Arthur F Kramer Journal: Neuroimage Date: 2015-10-19 Impact factor: 6.556
Authors: Mette Korshøj; Peter Krustrup; Marie Birk Jørgensen; Eva Prescott; Åse Marie Hansen; Jesper Kristiansen; Jørgen Henrik Skotte; Ole Steen Mortensen; Karen Søgaard; Andreas Holtermann Journal: BMC Public Health Date: 2012-08-13 Impact factor: 3.295
Authors: Agnieszka Z Burzynska; Chelsea N Wong; Michelle W Voss; Gillian E Cooke; Neha P Gothe; Jason Fanning; Edward McAuley; Arthur F Kramer Journal: PLoS One Date: 2015-08-05 Impact factor: 3.240
Authors: Agnieszka Zofia Burzynska; Laura Chaddock-Heyman; Michelle W Voss; Chelsea N Wong; Neha P Gothe; Erin A Olson; Anya Knecht; Andrew Lewis; Jim M Monti; Gillian E Cooke; Thomas R Wojcicki; Jason Fanning; Hyondo David Chung; Elisabeth Awick; Edward McAuley; Arthur F Kramer Journal: PLoS One Date: 2014-09-17 Impact factor: 3.240