title: Quality control methods in accelerometer data processing: defining minimum wear time.
abstract: BACKGROUND
  When using accelerometers to measure physical activity, researchers need to determine whether subjects have worn their device for a sufficient period to be included in analyses. We propose a minimum wear criterion using population-based accelerometer data, and explore the influence of gender and the purposeful inclusion of children with weekend data on reliability.
  
  
  METHODS
  Accelerometer data obtained during the age seven sweep of the UK Millennium Cohort Study were analysed. Children were asked to wear an ActiGraph GT1M accelerometer for seven days. Reliability coefficients(r) of mean daily counts/minute were calculated using the Spearman-Brown formula based on the intraclass correlation coefficient. An r of 1.0 indicates that all the variation is between- rather than within-children and that measurement is 100% reliable. An r of 0.8 is often regarded as acceptable reliability. Analyses were repeated on data from children who met different minimum daily wear times (one to 10 hours) and wear days (one to seven days). Analyses were conducted for all children, separately for boys and girls, and separately for children with and without weekend data.
  
  
  RESULTS
  At least one hour of wear time data was obtained from 7,704 singletons. Reliability increased as the minimum number of days and the daily wear time increased. A high reliability (r = 0.86) and sample size (n = 6,528) was achieved when children with ≥ two days lasting ≥10 hours/day were included in analyses. Reliability coefficients were similar for both genders. Purposeful sampling of children with weekend data resulted in comparable reliabilities to those calculated independent of weekend wear.
  
  
  CONCLUSIONS
  Quality control procedures should be undertaken before analysing accelerometer data in large-scale studies. Using data from children with ≥ two days lasting ≥10 hours/day should provide reliable estimates of physical activity. It's unnecessary to include only children with accelerometer data collected during weekends in analyses.
authors.affiliation: Medical Research Centre of Epidemiology for Child Health, University College London, London, United Kingdom. c.rich@ucl.ac.uk
authors.forename: Carly
authors.initials: C
authors.lastname: Rich
authors.forename: Marco
authors.initials: M
authors.lastname: Geraci
authors.forename: Lucy
authors.initials: L
authors.lastname: Griffiths
authors.forename: Francesco
authors.initials: F
authors.lastname: Sera
authors.forename: Carol
authors.initials: C
authors.lastname: Dezateux
authors.forename: Mario
authors.initials: M
authors.lastname: Cortina-Borja
mesh_terms: D061725:Accelerometry / Q000379:methods* / Q000592:standards*; D002648:Child; D015331:Cohort Studies; D001330:Electronic Data Processing / Q000379:methods* / Q000592:standards*; D005260:Female; D006801:Humans; D008297:Male; D011786:Quality Control; D015203:Reproducibility of Results; D013997:Time Factors; D006113:United Kingdom