title: Identifying walking trips from GPS and accelerometer data in adolescent females.
abstract: BACKGROUND
  Studies that have combined accelerometers and global positioning systems (GPS) to identify walking have done so in carefully controlled conditions. This study tested algorithms for identifying walking trips from accelerometer and GPS data in free-living conditions. The study also assessed the accuracy of the locations where walking occurred compared with what participants reported in a diary.
  
  
  METHODS
  A convenience sample of high school females was recruited (N = 42) in 2007. Participants wore a GPS unit and an accelerometer, and recorded their out-of-school travel for 6 days. Split-sample validation was used to examine agreement in the daily and total number of walking trips with Kappa statistics and count regression models, while agreement in locations visited by walking was examined with geographic information systems.
  
  
  RESULTS
  Agreement varied based on the parameters of the algorithm, with algorithms exhibiting moderate to substantial agreement with self-reported daily (Kappa = 0.33-0.48) and weekly (Kappa = 0.41-0.64) walking trips. Comparison of reported locations reached by walking and GPS data suggest that reported locations are accurate.
  
  
  CONCLUSIONS
  The use of GPS and accelerometers is promising for assessing the number of walking trips and the walking locations of adolescent females.
authors.affiliation: Dept of City and Regional Planning, University of North Carolina, Chapel Hill, USA.
authors.forename: Daniel A
authors.initials: DA
authors.lastname: Rodriguez
authors.forename: Gi-Hyoug
authors.initials: GH
authors.lastname: Cho
authors.forename: John P
authors.initials: JP
authors.lastname: Elder
authors.forename: Terry L
authors.initials: TL
authors.lastname: Conway
authors.forename: Kelly R
authors.initials: KR
authors.lastname: Evenson
authors.forename: Bonnie
authors.initials: B
authors.lastname: Ghosh-Dastidar
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Shay
authors.forename: Deborah
authors.initials: D
authors.lastname: Cohen
authors.forename: Sara
authors.initials: S
authors.lastname: Veblen-Mortenson
authors.forename: Julie
authors.initials: J
authors.lastname: Pickrell
authors.forename: Leslie
authors.initials: L
authors.lastname: Lytle
mesh_terms: D000054:Acceleration; D000293:Adolescent; D000294:Adolescent Behavior / Q000502:physiology*; D000465:Algorithms; D016001:Confidence Intervals; D005260:Female; D040362:Geographic Information Systems / Q000295:instrumentation*; D015438:Health Behavior; D006801:Humans; D008499:Medical Records; D009043:Motor Activity / Q000502:physiology*; D012044:Regression Analysis; D057566:Self Report; D013223:Statistics as Topic; D016138:Walking / Q000502:physiology*; D016387:Women's Health