title: Assessing the "physical cliff": detailed quantification of age-related differences in daily patterns of physical activity.
abstract: BACKGROUND
  In spite of evidence that physical activity has beneficial effects on health and age-related functional decline, there is a scarcity of detailed and accurate information on objectively measured daily activity and patterns of such activity in older adults.
  
  
  METHODS
  Participants in the Baltimore Longitudinal Study of Aging (n = 611, 50% male, mean age 67, range 32-93) wore the Actiheart portable activity monitor for 7 days in the free-living environment. The association between activity and age was modeled using a continuous log-linear regression of activity counts on age with sex, body mass index, employment status, functional performance, and comorbid conditions as covariates.
  
  
  RESULTS
  In the fully adjusted model, continuous analyses demonstrated that overall physical activity counts were 1.3% lower for each year increase in age. Although there were no differences among morning levels of activity, there was significantly lower afternoon and evening activity in older individuals (p < .01). After adjusting for age, poor functional performance, nonworking status, and higher body mass index were independently associated with less physical activity (p < .001).
  
  
  CONCLUSIONS
  The use of accelerometers to characterize minute-by-minute intensity, cumulative physical activity counts, and daily activity patterns provides detailed data not gathered by traditional subjective methods, particularly at low levels of activity. The findings of a 1.3% decrease per year in activity from mid-to-late life, and the corresponding drop in afternoon and evening activity, provide new information that may be useful when targeting future interventions. Further, this methodology addresses essential gaps in understanding activity patterns and trends in more sedentary sectors of the population.
authors: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland. Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, Maryland. jschrack@jhsph.edu.
authors: Jennifer A
authors: JA
authors: Schrack
authors: Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
authors: Vadim
authors: V
authors: Zipunnikov
authors: Department of Biostatistics, Columbia University Mailman School of Public Health, New York.
authors: Jeff
authors: J
authors: Goldsmith
authors: Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
authors: Jiawei
authors: J
authors: Bai
authors: Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, Maryland.
authors: Eleanor M
authors: EM
authors: Simonsick
authors: Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
authors: Ciprian
authors: C
authors: Crainiceanu
authors: Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, Maryland.
authors: Luigi
authors: L
authors: Ferrucci
mesh_terms: D061725:Accelerometry; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D004651:Employment; D005260:Female; D015438:Health Behavior; D006801:Humans; D016014:Linear Models; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D009043:Motor Activity; D010809:Physical Fitness / Q000502:physiology; D057185:Sedentary Behavior
keywords: Epidemiology; Functional performance; Physical activity; Public health.