title: Identifying sedentary time using automated estimates of accelerometer wear time.
abstract: OBJECTIVE
  The authors evaluated the accuracy of three automated accelerometer wear-time estimation algorithms against self-report. Direct effects on sedentary time (<100 cpm) and indirect effects on moderate-to-vigorous physical activity (MVPA, ≥1952 cpm) time were examined.
  
  
  METHODS
  A subsample from the 2004/2005 Australian Diabetes, Obesity and Lifestyle Study (n=148) completed activity logs and wore accelerometers for a total of 987 days. A published algorithm that allows movement within non-wear periods (Algorithm 1) was compared with one that allows less movement (Algorithm 2) or no movement (Algorithm 3). Implications for population estimates were examined using 2003/2004 US National Health and Nutrition Examination Survey data.
  
  
  RESULTS
  Mean difference per day between the criterion and estimated wear time was negligible for all three algorithms (≤11 min), but 95% limits of agreement (LOA) were wide (±≥2 h). Respectively, the algorithms (1, 2 and 3) misclassified sedentary time as non-wear on 31.9%, 19.4% and 18% of days and misclassified non-wear time as sedentary on 42.8%, 43.7% and 51.3% of days. Use of Algorithm 2 (compared with Algorithm 1) affected population estimates of sedentary time (higher by 20 min/day) but not MVPA time. Agreement between Algorithms 1 and 2 was good for MVPA time (mean difference -0.08, LOA: -2.08, 1.91 min), but not for wear time or sedentary time.
  
  
  CONCLUSIONS
  Accelerometer wear time can be estimated accurately on average; however, misclassification can be substantial for individuals. Algorithm choice affects estimates of sedentary time. Allowing very limited movement within non-wear periods can improve accuracy.
authors.affiliation: School of Population Health,The University of Queensland, Brisbane, Australia. e.winkler@uq.edu.au
authors.forename: Elisabeth A H
authors.initials: EA
authors.lastname: Winkler
authors.forename: Paul A
authors.initials: PA
authors.lastname: Gardiner
authors.forename: Bronwyn K
authors.initials: BK
authors.lastname: Clark
authors.forename: Charles E
authors.initials: CE
authors.lastname: Matthews
authors.forename: Neville
authors.initials: N
authors.lastname: Owen
authors.forename: Genevieve N
authors.initials: GN
authors.lastname: Healy
mesh_terms: D000054:Acceleration; D000328:Adult; D000368:Aged; D000465:Algorithms; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000295:instrumentation*; D057185:Sedentary Behavior; D019876:Sports Equipment; D013997:Time Factors; D055815:Young Adult