title: Accelerometer adherence and performance in a cohort study of US Hispanic adults.
abstract: OBJECTIVE
  This study described participant adherence to wearing the accelerometer and accelerometer performance in a cohort study of adults.
  
  
  METHODS
  From 2008 to 2011, 16,415 US Hispanic/Latino adults age 18-74 yr enrolled in the Hispanic Community Health Study/Study of Latinos. Immediately after the baseline visit, participants wore an Actical accelerometer for 1 wk. This study explored correlates of accelerometer participation and adherence, defined as wearing it for at least three of a possible six days for ≥10 h·d. Accelerometer performance was assessed by exploring the number of different values of accelerometer counts per minute for each participant.
  
  
  RESULTS
  Overall, 92.3% (n = 15,153) had at least 1 d with accelerometer data and 77.7% (n = 12,750) were adherent. Both accelerometer participation and adherence were higher among participants who were married or partnered, reported a higher household income, were first-generation immigrants, or reported lower sitting time. Participation was also higher among those with no stair limitations. Adherence was higher among participants who were male, older, employed or retired, not US born, preferred Spanish over English, reported higher work activity or lower recreational activity, and with a lower body mass index. Among the sample that met the adherence definition, the maximum recorded count per minute was 12,000, and there were a total of 5846 different counts per minute. On average, participants had 112.5 different counts per minute over 6 d (median, 106; interquartile range, 91-122). The number of different counts per minute was higher among men, younger ages, normal weight, and those with higher accelerometer-assessed physical activity.
  
  
  CONCLUSIONS
  Several correlates differed between accelerometer participation and adherence. These characteristics could be targeted in future studies to improve accelerometer wear. The performance of the accelerometer provided insight into creating a more accurate nonwear algorithm.
authors.affiliation: 1Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina-Chapel Hill, Chapel Hill, NC; 2Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina-Chapel Hill, Chapel Hill, NC; 3Department of Family and Preventive Medicine, University of California, San Diego, La Jolla, CA; 4Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY; 5School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, England, UNITED KINGDOM.
authors.forename: Kelly R
authors.initials: KR
authors.lastname: Evenson
authors.forename: Daniela
authors.initials: D
authors.lastname: Sotres-Alvarez
authors.forename: Y U
authors.initials: YU
authors.lastname: Deng
authors.forename: Simon J
authors.initials: SJ
authors.lastname: Marshall
authors.forename: Carmen R
authors.initials: CR
authors.lastname: Isasi
authors.forename: Dale W
authors.initials: DW
authors.lastname: Esliger
authors.forename: Sonia
authors.initials: S
authors.lastname: Davis
mesh_terms: D061725:Accelerometry / Q000295:instrumentation; D000293:Adolescent; D000328:Adult; D000368:Aged; D005260:Female; D006630:Hispanic or Latino; D006801:Humans; D008297:Male; D008875:Middle Aged; D009043:Motor Activity / Q000502:physiology*; D010349:Patient Compliance; D014481:United States; D055815:Young Adult