title: Measuring Physical Activity with Hip Accelerometry among U.S. Older Adults: How Many Days Are Enough?
abstract: BACKGROUND
  Accelerometers are increasingly used in research. Four to 7 days of monitoring is preferred to estimate average activity but may be burdensome for older adults. We aimed to investigate: 1) 7-day accelerometry protocol adherence, 2) demographic predictors of adherence, 3) day of the week effect, and 4) average activity calculated from 7 versus fewer days among older adults.
  
  
  METHODS
  We used the 2003-2006 older adult hip accelerometry data from the National Health and Nutrition Examination Survey (NHANES) sample. We determined proportions with 1-7 valid (10-20 hours) wear days and identified wear day correlates using ordinal logistic regression. We determined the day of week effect on 5 accelerometry measures (counts per minute, CPM; % sedentary behavior; % light-lifestyle activity; % moderate-vigorous activity, MVPA; total activity counts) using multivariate linear regression and compared averages estimated over 2 or 3 versus 7 days using correlations, linear regression, and Bland-Altman plots.
  
  
  RESULTS
  Among 2,208 participants aged 65+, 85% of participants had ≥2 and 44% had 7 valid wear days. Increasing age (p = 0.01) and non-white race (p < 0.001) were associated with fewer days. Daily CPM, % MVPA, and total daily activity counts were similar Monday through Saturday, but significantly lower on Sundays (p < 0.001). Daily % sedentary behavior and % light-lifestyle activity were significantly different on Saturdays (p = 0.04-0.045) and Sundays (p < 0.001) compared to weekdays. Among participants with 7 valid days, 2 or 3 day averages were highly correlated with 7 day averages for all 5 accelerometry measures (2 versus 7 days: r = 0.90-0.93, 3 versus 7 days: r = 0.94-0.96).
  
  
  CONCLUSIONS
  Protocols of 2-3 days, adjusting for Sundays (average CPM, % moderate-vigorous activity, and average total daily activity counts) or weekends (% sedentary behavior and % light-lifestyle activity), give reliable estimates of older adult activity.
authors.affiliation: University of Chicago Medicine, Department of Public Health Sciences, Chicago, IL, United States of America.
authors.forename: Masha
authors.initials: M
authors.lastname: Kocherginsky
authors.affiliation: University of Chicago Medicine, Section of Geriatrics and Palliative Medicine, Chicago, IL, United States of America.
authors.forename: Megan
authors.identifier: http://orcid.org/0000-0002-3997-5791
authors.initials: M
authors.lastname: Huisingh-Scheetz
authors.affiliation: University of Chicago Medicine, Section of Geriatrics and Palliative Medicine, Chicago, IL, United States of America.
authors.forename: William
authors.initials: W
authors.lastname: Dale
authors.affiliation: University of Chicago Medicine, Department of Public Health Sciences, Chicago, IL, United States of America.
authors.forename: Diane S
authors.initials: DS
authors.lastname: Lauderdale
authors.affiliation: University of Chicago Medicine, Department of Sociology, Chicago, IL, United States of America.
authors.forename: Linda
authors.initials: L
authors.lastname: Waite
mesh_terms: D061725:Accelerometry; D000368:Aged; D015444:Exercise / Q000502:physiology*; D005260:Female; D006615:Hip / Q000502:physiology*; D006801:Humans; D016014:Linear Models; D016015:Logistic Models; D008297:Male; D009749:Nutrition Surveys; D057185:Sedentary Behavior; D014481:United States