Kaitlin B Casaletto1, Miguel Arce Rentería2, Judy Pa3, Sarah E Tom4, Amal Harrati5, Nicole M Armstrong6, K Bharat Rajan7, Dan Mungas7, Samantha Walters1, Joel Kramer1, Laura B Zahodne8. 1. Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA. 2. Department of Neurology, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA. 3. Department of Neurology, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA. 4. Department of Neurology, Vagelos College of Physicians and Surgeons and Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA. 5. Department of Primary Care and Population Health, Center for Population Health Sciences, Stanford University, Stanford, CA, USA. 6. Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA. 7. University of California, Davis, Davis, CA, USA. 8. Department of Psychology, University of Michigan, Ann Arbor, MI, USA.
Abstract
BACKGROUND: Active lifestyles are related to better cognitive aging outcomes, yet the unique role of different types of activity are unknown. OBJECTIVE: To examine the independent contributions of physical (PA) versus cognitive (CA) leisure activities to brain and cognitive aging. METHODS: Independent samples of non-demented older adults from University of California, San Francisco Hillblom Aging Network (UCSF; n = 344 typically aging) and University of California, Davis Diversity cohort (UCD; n = 485 normal to MCI) completed: 1) self-reported engagement in current PA and CA (UCSF: Physical Activity Scale for the Elderly and Cognitive Activity Scale; UCD: Life Experiences Assessment Form); 2) neuropsychological batteries; and 3) neuroimaging total gray matter volume, white matter hyperintensities, and/or global fractional anisotropy. PA and CA were simultaneously entered into multivariable linear regression models, adjusting for demographic characteristics and functional impairment severity. RESULTS: Brain outcomes: In UCSF, only PA was positively associated with gray matter volume and attenuated the relationship between age and fractional anisotropy. In UCD, only CA was associated with less white matter hyperintensities and attenuated the relationship between age and gray matter volume. Cognitive outcomes: In both cohorts, greater CA, but not PA, related to better cognition, independent of age and brain structure. In UCSF, CA attenuated the relationship between fractional anisotropy and cognition. In UCD, PA attenuated the association between white matter hyperintensities and cognition. CONCLUSIONS: Although their specificity was not easily teased apart, both PA and CA are clearly related to better brain and cognitive resilience markers across cohorts with differing educational, racial, and disease statuses. PA and CA may independently contribute to converging neuroprotective pathways for brain and cognitive aging.
BACKGROUND: Active lifestyles are related to better cognitive aging outcomes, yet the unique role of different types of activity are unknown. OBJECTIVE: To examine the independent contributions of physical (PA) versus cognitive (CA) leisure activities to brain and cognitive aging. METHODS: Independent samples of non-demented older adults from University of California, San Francisco Hillblom Aging Network (UCSF; n = 344 typically aging) and University of California, Davis Diversity cohort (UCD; n = 485 normal to MCI) completed: 1) self-reported engagement in current PA and CA (UCSF: Physical Activity Scale for the Elderly and Cognitive Activity Scale; UCD: Life Experiences Assessment Form); 2) neuropsychological batteries; and 3) neuroimaging total gray matter volume, white matter hyperintensities, and/or global fractional anisotropy. PA and CA were simultaneously entered into multivariable linear regression models, adjusting for demographic characteristics and functional impairment severity. RESULTS: Brain outcomes: In UCSF, only PA was positively associated with gray matter volume and attenuated the relationship between age and fractional anisotropy. In UCD, only CA was associated with less white matter hyperintensities and attenuated the relationship between age and gray matter volume. Cognitive outcomes: In both cohorts, greater CA, but not PA, related to better cognition, independent of age and brain structure. In UCSF, CA attenuated the relationship between fractional anisotropy and cognition. In UCD, PA attenuated the association between white matter hyperintensities and cognition. CONCLUSIONS: Although their specificity was not easily teased apart, both PA and CA are clearly related to better brain and cognitive resilience markers across cohorts with differing educational, racial, and disease statuses. PA and CA may independently contribute to converging neuroprotective pathways for brain and cognitive aging.
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