Conclusions : We conclude that there is large heterogeneity across studies in the explained variance of AEE when estimated based on accelerometry .
Background / Objectives : Activity-related energy expenditure ( AEE ) might be an important factor in the etiology of chronic diseases .
However , measurement of free-living AEE is usually not feasible in large-scale epidemiological studies but instead has traditionally been estimated based on self-reported physical activity .
Impact of accelerometer wear time on physical activity data: a NHANES semisimulation data approach
Background Current research practice employs wide-ranging accelerometer wear time criteria to identify a valid day of  physical activity ( PA ) measurement . Objective To evaluate the effects of varying amounts of daily accelerometer wear time on PA data . Methods A total of 1000 days of accelerometer data from 1000 participants ( age=38.7±14.3 years ; body mass index=28.2±6.7 kg/m2 ) were selected from the 2005–2006 National Health and Nutrition Examination Study data set . A reference data set was created using 200 r and om days with 14 h/day of wear time . Four additional sample s of 200 days were r and omly selected with a wear time of 10 , 11 , 12 and 13 h/day1 . These data sets were used in day-to-day comparison to create four semisimulation data sets ( 10 , 11 , 12 , 13 h/day ) from the reference data set . Differences in step count and time spent in inactivity ( < 100 cts/min ) , light ( 100–1951 cts/min ) , moderate ( 1952–5724 cts/min ) and vigorous ( ≥5725 cts/min ) intensity PA were assessed using repeated- measures analysis of variance and absolute percent error ( APE ) . Results There were significant differences for moderate intensity PA between the reference data set and semisimulation data sets of 10 and 11 h/day . Differences were observed in 10–13 h/day1 for inactivity and light intensity PA , and 10–12 h/day for steps ( all p values < 0.05 ) . APE increased with shorter wear time ( 13 h/day=3.9–14.1 % ; 12 h/day=9.9–15.2 % , 11 h/day=17.1–35.5 % ; 10 h/day=24.6–40.3 % ) . Discussion These data suggest that using accelerometer wear time criteria of 12 h/day or less may underestimate step count and time spent in various PA levels
Conclusions : We conclude that there is large heterogeneity across studies in the explained variance of AEE when estimated based on accelerometry .
Background / Objectives : Activity-related energy expenditure ( AEE ) might be an important factor in the etiology of chronic diseases .
However , measurement of free-living AEE is usually not feasible in large-scale epidemiological studies but instead has traditionally been estimated based on self-reported physical activity .