Research Study Abstract

Association between brain volumes and patterns of physical activity in community-dwelling older adults

  • Published on November 24, 2020

Background: Larger brain volumes are often associated with more free-living physical activity (PA) in cognitively normal older adults. Yet, whether greater brain volumes are associated with more favorable (less fragmented) PA patterns, and whether this association is stronger than with total PA, remains unknown.

Methods: Brain magnetic resonance imaging and wrist-worn accelerometer data were collected in 301 participants (mean age=77[SD=7] years, 59% women) enrolled in the Baltimore Longitudinal Study of Aging. Linear regression models were fit to examine whether brain volumes (cc) were cross-sectionally associated with: 1) total daily PA minutes; and 2) activity fragmentation (mean number of PA bouts / total PA minutes x 100). Sensitivity analyses were conducted by adjusting for counterpart PA variables (e.g., fragmentation covariate included in the PA minutes model).

Results: Greater white matter volumes in the parietal and temporal lobes were associated with higher daily PA minutes (2.6(SE=1.0) and 3.8(0.9)min/day, respectively; p<0.009 for both) after adjusting for demographics, behavioral factors, medical conditions, gait speed, apolipoprotein E e4 status, and intracranial volume. Greater temporal white matter volume was associated with lower fragmentation (-0.16(0.05)%, p=0.003). In sensitivity analyses, observed associations between brain volumes and daily PA minutes remained significant while associations with fragmentation no longer remained significant.

Conclusions: Our results suggest white matter brain structure in cognitively normal older adults is associated with the total amount of PA and, to a lesser extent, the PA accumulation patterns. More work is needed to elucidate the longitudinal relationship between brain structure and function and PA patterns with aging.

Read more


  • Amal A Wanigatunga 1,2
  • Hang Wang 2
  • Yang An 3
  • Eleanor M Simonsick 3
  • Qu Tian 3
  • Christos Davatzikos 4
  • Jacek K Urbanek 5
  • Vadim Zipunnikov 6
  • Adam P Spira 2,7,8
  • Luigi Ferrucci 3
  • Susan M Resnick 3
  • Jennifer A Schrack 1,2,3


  • 1

    Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

  • 2

    Center on Aging and Health, Johns Hopkins University, Baltimore, Maryland, USA

  • 3

    Intramural Research Program, National Institute on Aging, Baltimore, Maryland USA

  • 4

    Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA

  • 5

    Division of Geriatric Medicine, Johns Hopkins University and Medical Institutions, Baltimore, Maryland, USA

  • 6

    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

  • 7

    Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

  • 8

    Department of Psychiatry and Behavioral Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA


Journals of Gerontology: Medical Sciences

Download Abstract



, , ,