title: Impact of accelerometer data processing decisions on the sample size, wear time and physical activity level of a large cohort study.
abstract: BACKGROUND
  Accelerometers objectively assess physical activity (PA) and are currently used in several large-scale epidemiological studies, but there is no consensus for processing the data. This study compared the impact of wear-time assessment methods and using either vertical (V)-axis or vector magnitude (VM) cut-points on accelerometer output.
  
  
  METHODS
  Participants (7,650 women, mean age 71.4 y) were mailed an accelerometer (ActiGraph GT3X+), instructed to wear it for 7 days, record dates and times the monitor was worn on a log, and return the monitor and log via mail. Data were processed using three wear-time methods (logs, Troiano or Choi algorithms) and V-axis or VM cut-points.
  
  
  RESULTS
  Using algorithms alone resulted in "mail-days" incorrectly identified as "wear-days" (27-79% of subjects had >7-days of valid data). Using only dates from the log and the Choi algorithm yielded: 1) larger samples with valid data than using log dates and times, 2) similar wear-times as using log dates and times, 3) more wear-time (V, 48.1 min more; VM, 29.5 min more) than only log dates and Troiano algorithm. Wear-time algorithm impacted sedentary time (~30-60 min lower for Troiano vs. Choi) but not moderate-to-vigorous (MV) PA time. Using V-axis cut-points yielded ~60 min more sedentary time and ~10 min less MVPA time than using VM cut-points.
  
  
  CONCLUSIONS
  Combining log-dates and the Choi algorithm was optimal, minimizing missing data and researcher burden. Estimates of time in physical activity and sedentary behavior are not directly comparable between V-axis and VM cut-points. These findings will inform consensus development for accelerometer data processing in ongoing epidemiologic studies.
authors.affiliation: Nutritional Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA. sarah.keadle@nih.gov.
authors.forename: Sarah Kozey
authors.initials: SK
authors.lastname: Keadle
authors.forename: Eric J
authors.initials: EJ
authors.lastname: Shiroma
authors.forename: Patty S
authors.initials: PS
authors.lastname: Freedson
authors.forename: I-Min
authors.initials: IM
authors.lastname: Lee
mesh_terms: D061725:Accelerometry / Q000295:instrumentation* / Q000379:methods*; D000328:Adult; D000368:Aged; D000465:Algorithms; D015992:Body Mass Index; D015331:Cohort Studies; D001330:Electronic Data Processing / Q000295:instrumentation* / Q000379:methods*; D015991:Epidemiologic Measurements; D015444:Exercise / Q000502:physiology*; D005260:Female; D006801:Humans; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000295:instrumentation; D010808:Physical Examination; D018401:Sample Size; D013997:Time Factors