Assessment of Leisure Time Physical Activity and Brain Health in a Multiethnic Cohort of Older Adults | Dementia and Cognitive Impairment | JAMA Network Open | JAMA Network

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          Figure. ?Brain Measures by Leisure Time Physical Activity Levels
          Brain Measures by Leisure Time Physical Activity Levels

          Brain measures are standardized (by z scores) for convenient comparisons across different brain measures. Solid lines represent significant associations between leisure time physical activity (LTPA) and brain measures (see trend test in Table 2), while dotted and dashed lines indicate nonsignificant associations. TBV indicates total brain volume; TGMV, total gray matter volume; TWMV, total white matter volume; WMH, white matter hypersensitivity.

          Table 1. ?Characteristics of Study Participants According to the Total Physical Activity Amount
          Characteristics of Study Participants According to the Total Physical Activity Amount
          Table 2. ?Association Between Leisure Time Physical Activity (LTPA) Levels and Brain Magnetic Resonance Imaging (MRI) Measures
          Association Between Leisure Time Physical Activity (LTPA) Levels and Brain Magnetic Resonance Imaging (MRI) Measures
          Table 3. ?Association Between Leisure Time Physical Activity Levels According to Physical Activity Guidelines for Americans (PAGA) and Brain Magnetic Resonance Imaging Measures
          Association Between Leisure Time Physical Activity Levels According to Physical Activity Guidelines for Americans (PAGA) and Brain Magnetic Resonance Imaging Measures
          Table 4. ?Association of Leisure Time Physical Activity and Total Brain Volume, by Race/Ethnicity, Sex, and Apolipoprotein E ?4a
          Association of Leisure Time Physical Activity and Total Brain Volume, by Race/Ethnicity, Sex, and Apolipoprotein E ?4a
          1.
          Scarmeas ?N?, Luchsinger ?JA?, Schupf ?N?, ?et al. ?Physical activity, diet, and risk of Alzheimer disease.?? ?JAMA. 2009;302(6):627-637. doi:10.1001/jama.2009.1144PubMedGoogle ScholarCrossref
          2.
          Ogino ?E?, Manly ?JJ?, Schupf ?N?, Mayeux ?R?, Gu ?Y?. ?Current and past leisure time physical activity in relation to risk of Alzheimer’s disease in older adults.?? ?Alzheimers Dement. 2019;15(12):1603-1611. doi:10.1016/j.jalz.2019.07.013PubMedGoogle ScholarCrossref
          3.
          de Bruijn ?RF?, Schrijvers ?EM?, de Groot ?KA?, ?et al. ?The association between physical activity and dementia in an elderly population: the Rotterdam Study.?? ?Eur J Epidemiol. 2013;28(3):277-283. doi:10.1007/s10654-013-9773-3PubMedGoogle ScholarCrossref
          4.
          Podewils ?LJ?, Guallar ?E?, Kuller ?LH?, ?et al. ?Physical activity, APOE genotype, and dementia risk: findings from the Cardiovascular Health Cognition Study.?? ?Am J Epidemiol. 2005;161(7):639-651. doi:10.1093/aje/kwi092PubMedGoogle ScholarCrossref
          5.
          Piercy ?KL?, Troiano ?RP?, Ballard ?RM?, ?et al. ?The physical activity guidelines for Americans.?? ?JAMA. 2018;320(19):2020-2028. doi:10.1001/jama.2018.14854PubMedGoogle ScholarCrossref
          6.
          Physical Activity Guidelines Advisory Committee.? 2018 Physical Activity Guidelines Advisory Committee Scientific Report. US Department of Health and Human Services; 2018.
          7.
          Brickman ?AM?, Tosto ?G?, Gutierrez ?J?, ?et al. ?An MRI measure of degenerative and cerebrovascular pathology in Alzheimer disease.?? ?Neurology. 2018;91(15):e1402-e1412. doi:10.1212/WNL.0000000000006310PubMedGoogle ScholarCrossref
          8.
          Fl?el ?A?, Ruscheweyh ?R?, Krüger ?K?, ?et al. ?Physical activity and memory functions: are neurotrophins and cerebral gray matter volume the missing link??? ?Neuroimage. 2010;49(3):2756-2763. doi:10.1016/j.neuroimage.2009.10.043PubMedGoogle ScholarCrossref
          9.
          Erickson ?KI?, Raji ?CA?, Lopez ?OL?, ?et al. ?Physical activity predicts gray matter volume in late adulthood: the Cardiovascular Health Study.?? ?Neurology. 2010;75(16):1415-1422. doi:10.1212/WNL.0b013e3181f88359PubMedGoogle ScholarCrossref
          10.
          Rovio ?S?, Spulber ?G?, Nieminen ?LJ?, ?et al. ?The effect of midlife physical activity on structural brain changes in the elderly.?? ?Neurobiol Aging. 2010;31(11):1927-1936. doi:10.1016/j.neurobiolaging.2008.10.007PubMedGoogle ScholarCrossref
          11.
          Benedict ?C?, Brooks ?SJ?, Kullberg ?J?, ?et al. ?Association between physical activity and brain health in older adults.?? ?Neurobiol Aging. 2013;34(1):83-90. doi:10.1016/j.neurobiolaging.2012.04.013PubMedGoogle ScholarCrossref
          12.
          Gow ?AJ?, Bastin ?ME?, Mu?oz Maniega ?S?, ?et al. ?Neuroprotective lifestyles and the aging brain: activity, atrophy, and white matter integrity.?? ?Neurology. 2012;79(17):1802-1808. doi:10.1212/WNL.0b013e3182703fd2PubMedGoogle ScholarCrossref
          13.
          Doi ?T?, Makizako ?H?, Shimada ?H?, ?et al. ?Objectively measured physical activity, brain atrophy, and white matter lesions in older adults with mild cognitive impairment.?? ?Exp Gerontol. 2015;62:1-6. doi:10.1016/j.exger.2014.12.011PubMedGoogle ScholarCrossref
          14.
          Colcombe ?SJ?, Erickson ?KI?, Raz ?N?, ?et al. ?Aerobic fitness reduces brain tissue loss in aging humans.?? ?J Gerontol A Biol Sci Med Sci. 2003;58(2):176-180. doi:10.1093/gerona/58.2.M176PubMedGoogle ScholarCrossref
          15.
          Sexton ?CE?, Betts ?JF?, Demnitz ?N?, Dawes ?H?, Ebmeier ?KP?, Johansen-Berg ?H?. ?A systematic review of MRI studies examining the relationship between physical fitness and activity and the white matter of the ageing brain.?? ?Neuroimage. 2016;131:81-90. doi:10.1016/j.neuroimage.2015.09.071PubMedGoogle ScholarCrossref
          16.
          Jochem ?C?, Baumeister ?SE?, Wittfeld ?K?, ?et al. ?Domains of physical activity and brain volumes: a population-based study.?? ?Neuroimage. 2017;156:101-108. doi:10.1016/j.neuroimage.2017.05.020PubMedGoogle ScholarCrossref
          17.
          Stephen ?R?, Liu ?Y?, Ngandu ?T?, ?et al; FINGER study group. ?Brain volumes and cortical thickness on MRI in the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER).?? ?Alzheimers Res Ther. 2019;11(1):53. doi:10.1186/s13195-019-0506-zPubMedGoogle ScholarCrossref
          18.
          Tang ?MX?, Cross ?P?, Andrews ?H?, ?et al. ?Incidence of AD in African Americans, Caribbean Hispanics, and Caucasians in northern Manhattan.?? ?Neurology. 2001;56(1):49-56. doi:10.1212/WNL.56.1.49PubMedGoogle ScholarCrossref
          19.
          American Psychiatric Association. ?Diagnostic and Statistical Manual of Mental Disorders. 3rd ed.? American Psychiatric Press; 1987.
          20.
          McKhann ?G?, Drachman ?D?, Folstein ?M?, Katzman ?R?, Price ?D?, Stadlan ?EM?. ?Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease.?? ?Neurology. 1984;34(7):939-944. doi:10.1212/WNL.34.7.939PubMedGoogle ScholarCrossref
          21.
          Petersen ?RC?. ?Mild cognitive impairment as a diagnostic entity.?? ?J Intern Med. 2004;256(3):183-194. doi:10.1111/j.1365-2796.2004.01388.xPubMedGoogle ScholarCrossref
          22.
          Manly ?JJ?, Bell-McGinty ?S?, Tang ?MX?, Schupf ?N?, Stern ?Y?, Mayeux ?R?. ?Implementing diagnostic criteria and estimating frequency of mild cognitive impairment in an urban community.?? ?Arch Neurol. 2005;62(11):1739-1746. doi:10.1001/archneur.62.11.1739PubMedGoogle ScholarCrossref
          23.
          Brickman ?AM?, Schupf ?N?, Manly ?JJ?, ?et al. ?Brain morphology in older African Americans, Caribbean Hispanics, and whites from northern Manhattan.?? ?Arch Neurol. 2008;65(8):1053-1061. doi:10.1001/archneur.65.8.1053PubMedGoogle ScholarCrossref
          24.
          Brickman ?AM?, Zahodne ?LB?, Guzman ?VA?, ?et al. ?Reconsidering harbingers of dementia: progression of parietal lobe white matter hyperintensities predicts Alzheimer’s disease incidence.?? ?Neurobiol Aging. 2015;36(1):27-32. doi:10.1016/j.neurobiolaging.2014.07.019PubMedGoogle ScholarCrossref
          25.
          Sanfilipo ?MP?, Benedict ?RH?, Zivadinov ?R?, Bakshi ?R?. ?Correction for intracranial volume in analysis of whole brain atrophy in multiple sclerosis: the proportion vs residual method.?? ?Neuroimage. 2004;22(4):1732-1743. doi:10.1016/j.neuroimage.2004.03.037PubMedGoogle ScholarCrossref
          26.
          Gu ?Y?, Brickman ?AM?, Stern ?Y?, ?et al. ?Mediterranean diet and brain structure in a multiethnic elderly cohort.?? ?Neurology. 2015;85(20):1744-1751. doi:10.1212/WNL.0000000000002121PubMedGoogle ScholarCrossref
          27.
          Godin ?G?, Shephard ?RJ?. ?A simple method to assess exercise behavior in the community.?? ?Can J Appl Sport Sci. 1985;10(3):141-146.PubMedGoogle Scholar
          28.
          Jacobs ?DR ?Jr?, Ainsworth ?BE?, Hartman ?TJ?, Leon ?AS?. ?A simultaneous evaluation of 10 commonly used physical activity questionnaires.?? ?Med Sci Sports Exerc. 1993;25(1):81-91. doi:10.1249/00005768-199301000-00012PubMedGoogle ScholarCrossref
          29.
          Halloway ?S?, Arfanakis ?K?, Wilbur ?J?, Schoeny ?ME?, Pressler ?SJ?. ?Accelerometer physical activity is associated with greater gray matter volumes in older adults without dementia or mild cognitive impairment.?? ?J Gerontol B Psychol Sci Soc Sci. 2019;74(7):1142-1151. doi:10.1093/geronb/gby010PubMedGoogle ScholarCrossref
          30.
          Hamer ?M?, Sharma ?N?, Batty ?GD?. ?Association of objectively measured physical activity with brain structure: UK Biobank study.?? ?J Intern Med. 2018;284(4):439-443. doi:10.1111/joim.12772PubMedGoogle ScholarCrossref
          31.
          Spartano ?NL?, Davis-Plourde ?KL?, Himali ?JJ?, ?et al. ?Association of accelerometer-measured light-intensity physical activity with brain volume: the Framingham Heart Study.?? ?JAMA Netw Open. 2019;2(4):e192745. doi:10.1001/jamanetworkopen.2019.2745PubMedGoogle Scholar
          32.
          Kim ?RE?, Yun ?CH?, Thomas ?RJ?, ?et al. ?Lifestyle-dependent brain change: a longitudinal cohort MRI study.?? ?Neurobiol Aging. 2018;69:48-57. doi:10.1016/j.neurobiolaging.2018.04.017PubMedGoogle ScholarCrossref
          33.
          Ludyga ?S?, Gerber ?M?, Pühse ?U?, Looser ?VN?, Kamijo ?K?. ?Systematic review and meta-analysis investigating moderators of long-term effects of exercise on cognition in healthy individuals.?? ?Nat Hum Behav. 2020;4(6):603-612. doi:10.1038/s41562-020-0851-8PubMedGoogle ScholarCrossref
          34.
          Stern ?Y?, Lee ?S?, Predovan ?D?, P Sloan ?R?. ?Sex moderates the effect of aerobic exercise on some aspects of cognition in cognitively intact younger and middle-age adults.?? ?J Clin Med. 2019;8(6):E886. doi:10.3390/jcm8060886PubMedGoogle Scholar
          35.
          Dougherty ?RJ?, Schultz ?SA?, Boots ?EA?, ?et al. ?Relationships between cardiorespiratory fitness, hippocampal volume, and episodic memory in a population at risk for Alzheimer’s disease.?? ?Brain Behav. 2017;7(3):e00625. doi:10.1002/brb3.625PubMedGoogle Scholar
          36.
          Varma ?VR?, Chuang ?YF?, Harris ?GC?, Tan ?EJ?, Carlson ?MC?. ?Low-intensity daily walking activity is associated with hippocampal volume in older adults.?? ?Hippocampus. 2015;25(5):605-615. doi:10.1002/hipo.22397PubMedGoogle ScholarCrossref
          37.
          Barha ?CK?, Best ?JR?, Rosano ?C?, Yaffe ?K?, Catov ?JM?, Liu-Ambrose ?T?. ?Sex-specific relationship between long-term maintenance of physical activity and cognition in the Health ABC Study: potential role of hippocampal and dorsolateral prefrontal cortex volume.?? ?J Gerontol A Biol Sci Med Sci. 2020;75(4):764-770.PubMedGoogle Scholar
          38.
          Folley ?S?, Zhou ?A?, Llewellyn ?DJ?, Hypp?nen ?E?. ?Physical activity, APOE genotype, and cognitive decline: exploring gene-environment interactions in the UK Biobank.?? ?J Alzheimers Dis. 2019;71(3):741-750. doi:10.3233/JAD-181132PubMedGoogle ScholarCrossref
          39.
          Jensen ?CS?, Simonsen ?AH?, Siersma ?V?, ?et al. ?Patients with Alzheimer’s disease who carry the APOE ε4 allele benefit more from physical exercise.?? ?Alzheimers Dement (N Y). 2019;5:99-106. doi:10.1016/j.trci.2019.02.007PubMedGoogle ScholarCrossref
          40.
          Tan ?ZS?, Spartano ?NL?, Beiser ?AS?, ?et al. ?Physical activity, brain volume, and dementia risk: the Framingham Study.?? ?J Gerontol A Biol Sci Med Sci. 2017;72(6):789-795.PubMedGoogle Scholar
          41.
          Firth ?J?, Stubbs ?B?, Vancampfort ?D?, ?et al. ?Effect of aerobic exercise on hippocampal volume in humans: a systematic review and meta-analysis.?? ?Neuroimage. 2018;166:230-238. doi:10.1016/j.neuroimage.2017.11.007PubMedGoogle ScholarCrossref
          42.
          Jack ?CR ?Jr?, Knopman ?DS?, Jagust ?WJ?, ?et al. ?Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade.?? ?Lancet Neurol. 2010;9(1):119-128. doi:10.1016/S1474-4422(09)70299-6PubMedGoogle ScholarCrossref
          43.
          Farmer ?J?, Zhao ?X?, van Praag ?H?, Wodtke ?K?, Gage ?FH?, Christie ?BR?. ?Effects of voluntary exercise on synaptic plasticity and gene expression in the dentate gyrus of adult male Sprague-Dawley rats in vivo.?? ?Neuroscience. 2004;124(1):71-79. doi:10.1016/j.neuroscience.2003.09.029PubMedGoogle ScholarCrossref
          44.
          Joris ?PJ?, Mensink ?RP?, Adam ?TC?, Liu ?TT?. ?Cerebral blood flow measurements in adults: a review on the effects of dietary factors and exercise.?? ?Nutrients. 2018;10(5):E530. doi:10.3390/nu10050530PubMedGoogle Scholar
          45.
          Baker ?LD?, Frank ?LL?, Foster-Schubert ?K?, ?et al. ?Effects of aerobic exercise on mild cognitive impairment: a controlled trial.?? ?Arch Neurol. 2010;67(1):71-79. doi:10.1001/archneurol.2009.307PubMedGoogle ScholarCrossref
          46.
          Okonkwo ?OC?, Schultz ?SA?, Oh ?JM?, ?et al. ?Physical activity attenuates age-related biomarker alterations in preclinical AD.?? ?Neurology. 2014;83(19):1753-1760. doi:10.1212/WNL.0000000000000964PubMedGoogle ScholarCrossref
          47.
          Rabin ?JS?, Klein ?H?, Kirn ?DR?, ?et al. ?Associations of physical activity and β-amyloid with longitudinal cognition and neurodegeneration in clinically normal older adults.?? ?JAMA Neurol. 2019;76(10):1203-1210. doi:10.1001/jamaneurol.2019.1879PubMedGoogle ScholarCrossref
          48.
          Rostanski ?SK?, Zimmerman ?ME?, Schupf ?N?, ?et al. ?Sleep disordered breathing and white matter hyperintensities in community-dwelling elders.?? ?Sleep. 2016;39(4):785-791. doi:10.5665/sleep.5628PubMedGoogle ScholarCrossref
          49.
          Thompson ?PD?, Buchner ?D?, Pina ?IL?, ?et al; American Heart Association Council on Clinical Cardiology Subcommittee on Exercise, Rehabilitation, and Prevention; American Heart Association Council on Nutrition, Physical Activity, and Metabolism Subcommittee on Physical Activity. ?Exercise and physical activity in the prevention and treatment of atherosclerotic cardiovascular disease: a statement from the Council on Clinical Cardiology (Subcommittee on Exercise, Rehabilitation, and Prevention) and the Council on Nutrition, Physical Activity, and Metabolism (Subcommittee on Physical Activity).?? ?Circulation. 2003;107(24):3109-3116. doi:10.1161/01.CIR.0000075572.40158.77PubMedGoogle ScholarCrossref
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            Original Investigation
            Geriatrics
            November?19, 2020

            Assessment of Leisure Time Physical Activity and Brain Health in a Multiethnic Cohort of Older Adults

            Author Affiliations
            • 1Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Columbia University, New York, New York
            • 2Department of Neurology, Columbia University, New York, New York
            • 3Gertrude H. Sergievsky Center, Columbia University, New York, New York
            • 4Joseph P. Mailman School of Public Health, Department of Epidemiology, Columbia University, New York, New York
            JAMA Netw Open. 2020;3(11):e2026506. doi:10.1001/jamanetworkopen.2020.26506
            Key Points

            Question? Is physical activity associated with brain volume and white matter hyperintensity burden?

            Findings? In this cross-sectional study of 1443 older (≥65 years) individuals without dementia, more physical activity was associated with larger brain volumes.

            Meaning? The findings of this study suggest that there may be a potential beneficial role of physical activity on brain health.

            Abstract

            Importance? Results from longitudinal studies suggest that regular leisure time physical activity (LTPA) is associated with reduced risk of dementia or Alzheimer disease. Data on the association between LTPA and brain magnetic resonance imaging (MRI) measures remain scarce and inconsistent.

            Objective? To examine the association of LTPA and MRI-assessed brain aging measures in a multiethnic elderly population.

            Design, Setting, and Participants? This cross-sectional study included 1443 older (≥65 years) adults without dementia who were participants of the Washington/Hamilton Heights-Inwood Columbia Aging Project study. LTPA, from self-reported questionnaire, was calculated as metabolic equivalent of energy expenditure. Both moderate to vigorous LTPA, assessed as meeting Physical Activity Guidelines for Americans (≥150 minutes/week) or not, and light-intensity LTPA were also examined.

            Exposures? LTPA.

            Main Outcomes and Measures? Primary outcomes included total brain volume (TBV), cortical thickness, and white matter hyperintensity volume, all derived from MRI scans with established methods and adjusted for intracranial volume when necessary. We examined the association of LTPA with these imaging markers using regression models adjusted for demographic, clinical, and vascular risk factors.

            Results? The 1443 participants of the study had a mean (SD) age of 77.2 (6.4) years; 921 (63.8%) were women; 27.0%, 34.4%, and 36.3% were non-Hispanic White, non-Hispanic African American, and Hispanic individuals, respectively; and 27.3% carried the apolipoprotein E (APOE) ?4 allele. Compared with the LTPA of nonactive older adults, those with the most LTPA had larger (in cm3) TBV (β [SE], 13.17 [4.42] cm3; P?=?.003; P for trend?=?.006) and greater cortical thickness (β [SE], 0.016 [0.008] mm; P?=?.05; P for trend?=?.03). The effect size comparing the highest LTPA level with the nonactive group was equivalent to approximately 3 to 4 years of aging (β for 1 year older, ?3.06 and ?0.005 for TBV and cortical thickness, respectively). A dose-response association was found and even the lowest LTPA level had benefits (eg, TBV: β [SE], 9.03 [4.26] cm3; P?=?.03) compared with the nonactive group. Meeting Physical Activity Guidelines for Americans (TBV: β [SE], 18.82 [5.14] cm3; P?<?.001) and light-intensity LTPA (TBV: β [SE], 9.26 [4.29] cm3; P?=?.03) were also associated with larger brain measures. The association between LTPA and TBV was moderated by race/ethnicity, sex, and APOE status, but generally existed in all subgroups. The results remained similar after excluding participants with mild cognitive impairment.

            Conclusions and Relevance? In this study, more physical activity was associated with larger brain volume in older adults. Longitudinal studies are warranted to explore the potential role of physical activity in brain health among older individuals.

            Introduction

            A large body of evidence from longitudinal studies1-4 has found that regular leisure time physical activity (LTPA) is associated with reduced risk of dementia or Alzheimer disease (AD). Accordingly, the recently released second edition of Physical Activity Guidelines for Americans (PAGA)5,6 added cognitive health and reduced dementia risk to the growing list of LTPA benefits.

            Multiple brain structural changes, including both neurodegeneration such as volume loss and cerebrovascular lesions such as white matter hyperintensities (WMH), are powerful predictors for subsequent AD development.7 It would therefore be interesting to examine whether LTPA is associated with these brain measures. Several observational and interventional studies have found that greater activities are associated with larger brain volume8-14 and/or less WMH,15 but inconsistent results also have been reported.15-17 Few studies have taken into consideration different activity intensity levels. While PAGA and many previous studies focused on moderate to vigorous LTPA, it is important to evaluate whether light-intensity LTPA can help slow the brain morphological changes among older adults who may have limited-moderate to vigorous LTPA. Similarly, it would be of practical interest to evaluate what would be a threshold level for older adults to gain brain health benefits. In addition, with LTPA as a promising precision prevention target, it is important to evaluate the role of LTPA in brain health among certain subgroup populations, especially those at higher risk of developing AD such as racial/ethnic minority groups, women, and genetic risk factor carriers.

            Previous research in the Washington/Hamilton Heights-Inwood Columbia Aging Project (WHICAP)1,2 showed that participating more in LTPA was associated with lower AD risk. The aim of this study was to examine whether higher LTPA is associated with larger brain volume, cortical thickness, and less WMH as measured by magnetic resonance imaging (MRI) in this multiethnic elderly cohort.

            Methods
            Participants and Setting

            WHICAP is a community-based, longitudinal study on aging and dementia in a multiethnic sample of older (aged ≥65 years) residents of uptown Manhattan.18 There were 3 recruitment waves in 1992, 1999, and 2009, all using similar sampling, assessments, and study procedures.2,18 Participants repeated the baseline examinations every 18 to 24 months in follow-up appointments. The diagnosis of dementia and the type of dementia were based on standard research criteria.19,20 The diagnosis of mild cognitive impairment (MCI) used Petersen21 criteria as described elsewhere.22

            A total of 1584 participants in the WHICAP study received MRI assessment. The detailed information regarding the enrollment into the neuroimaging substudy has been described previously.7,23,24 We excluded 63 participants who were diagnosed with dementia around the time of the scan. Among the remaining 1521 participants, LTPA was not available for 78. Compared with the 78 participants with incomplete data, the 1443 participants included in the current study were older (mean [SD], 77.2 [6.4] vs 73.9 [7.2]) but otherwise similar.

            Ethical approval was obtained from the institutional review boards of Columbia University. All participants provided written informed consent.

            MRI Protocol
            Image Acquisition

            Scans were acquired on a 1.5T Intera scanner (Philips Healthcare) for the 1999 wave and a 3T Achieva scanner (Philips Healthcare) for the 2009 wave at Columbia University.7 For the 1999 wave, T1-weighted (repetition time [RT]?=?20 ms, echo time [ET]?=?2.1 ms, field of view [FOV]?=?240 cm, 256?×?160 matrix, 1.3 mm slice thickness) and T2-weighted fluid-attenuated inversion recovery (FLAIR) (RT?=?11?000 ms, ET?=?144.0 ms, inversion time?=?2800 ms, FOV?=?25 cm, 2 excitations, 256?×?192 matrix with 3 mm slice thickness) images were acquired in the axial orientation. For the 2009 wave, T1-weighted (RT?=?6.6 ms, ET?=?3.0 ms, FOV?=?256?×?256?×?165, 1.0 mm slice thickness) and T2-weighted FLAIR (RT?=?8000 ms, ET?=?332 ms, FOV?=?240?×?240?×?180, 0.43 mm slice thickness) images were acquired axially.

            Volume and Cortical Thickness Measures

            All T1 images were analyzed using Freesurfer (versions 5.1 and 6.0 for 1999 and 2009 waves, respectively; Laboratory for Computational Neuroimaging at the Athinoula A. Martinos Center for Biomedical Imaging).7 Freesurfer output underwent visual quality control and manual correction whenever necessary.23 We examined brain volumetric measures (cm3) including total brain volume (TBV), total gray matter volume (TGMV), total white matter volume (TWMV), and hippocampal volume. To adjust for differences in head size across participants, regression models were run with intracranial volume (ICV) as the independent variable and brain volume as the outcome variable, and the regression residuals were then used in the analyses.25 We calculated mean cortical thickness (mm)26 across all regions of interest within each participant.

            WMH Quantification

            The quantification of global and regional WMH volumes has been previously described.7,24 First, each participant’s T2-weighted FLAIR image was skull stripped, and a single gaussian curve was fit to voxel intensity values in the resultant image. An intensity threshold of 1.8 and 2.1 SD above the mean intensity value for 1999 and 2009 waves, respectively, were set to define the lower boundary of hyperintense voxels, and voxels above that threshold were labeled. The resulting map was further visually inspected and corrected for false-positive and false-negative errors for each participant. Total WMH volume in cubic centimeters was defined as the number of labeled voxels multiplied by voxel dimensions. Log-transformed total WMH volume was used in the analysis.

            Leisure Time Physical Activity

            Information about current LTPA was collected using the Godin leisure time exercise questionnaire.27 Past studies have shown that reports of LTPA using the Godin questionnaire are reliable27,28 and valid.1 At baseline, participants were queried about the frequency of LTPA during the most recent 2 weeks and duration (measured in metabolic-equivalent minutes [MET-minutes]) per session for 3 different intensity categories of LTPAs: vigorous, moderate, and light.2 Total MET-minutes in 2 weeks for each intensity category was calculated,2,27 and summed across the 3 categories to obtain each individual’s total LTPA amount (MET-minutes per 2 wk). The LTPA was further categorized into no LTPA and tertiles of nonzero values (low, middle, or high LTPA).

            We also determined whether an individual did or did not meet the current PAGA guidelines, ie, averaging 150 minutes/week or more of moderate and/or vigorous LTPA. In addition, an individual was considered as meeting the guidelines if their light-intensity LTPA was above 250 minutes/week (light PAGA), which had an equivalent total LTPA amount as the PAGA (ie, 750 METs-minutes/week). The light LTPA was categorized into no, lower-middle, higher-middle, or meeting light PAGA, with the middle 2 groups based on median split (120 minutes/week).

            Covariates

            Information about age, sex, education, ethnicity, body mass index (BMI, calculated as weight in kilograms divided by height in meters squared), smoking status, and alcohol use was obtained from baseline interviews. Race and ethnicity were self-reported using the format of the 2000 US Census. Participants were then assigned to 1 of 3 groups: African American (non-Hispanic), Hispanic, White (non-Hispanic), or other. Years of education was self-reported and used as a continuous variable. Caloric intake was calculated from the baseline food-frequency questionnaire. Apolipoprotein E (APOE) genotype was categorized as ε4 carriers (either 1 or 2 ε4) or noncarriers. Presence or absence of heart disease, diabetes, hypertension, head injury, and depression were based on self-reported information as well as the use of medication for any conditions, and stroke was determined by self-report, neurologic examination, or a review of medical records. Alcohol use and smoking history was self-reported by standard questionnaires.26 Self-reported occupation was used as a categorical variable (ie, manager or professional vs others).

            Statistical Analysis

            Brain measures, LTPA levels, and other characteristics of participants were compared across the levels of LTPAs using ANOVA for continuous variables and χ2 test for categorical variables. We used multivariable linear regression models to estimate the association between LTPA and imaging markers (ie, TBV, cortical thickness, WMH volume). The analyses were performed in a series of models, with Model 1 adjusted for age, enrollment wave, and ICV (except for cortical thickness); Model 2 additionally adjusted for demographic and socioeconomic variables including sex, race/ethnicity, education, occupation, and MCI status at scan visit; and Model 3 further adjusted for vascular and other comorbidities including comorbidity score and BMI. We also examined whether meeting the PAGA guideline and light LTPA were associated with brain measures by including them simultaneously in the models, adjusted for the same variables as above.

            Effect modifications by sex, race/ethnicity, and APOE were tested by including an interaction term (ie, ordinal LTPA x effect modifier; P for interaction) into the regression models with TBV as the outcome variable, then adjusting for Model 2 covariates, followed by stratified analyses by significant effect modifiers. To reduce the possibility of potential reverse causality and recall bias, we excluded participants with MCI. Post-hoc analyses were performed, globally and separately for left and right hemispheres, for regional volumes: TGMV, TWMV, and hippocampal volume.

            All analyses were performed using SPSS Statistics 25.0 (IBM). The level of statistical significance was set at P?<?.05.

            Results
            Characteristics of the Study Participants

            The MRI scans were assessed a mean (SD) 2.69 (2.17) years after the LTPA assessment in the 1443 participants included in the study. Approximately two-thirds of these participants were women (921 [63.8%]), and the mean (SD) age was 77.2 (6.4) years; 390 (27.0%) of participants were non-Hispanic White, 497 (34.4%) were African American, 524 (36.3%) Hispanic, and 32 (2.2%) were of other race/ethnicity; 27.3% carried the apolipoprotein E (APOE) ?4 allele. (Table 1).

            Those who had more LTPA were younger (eg, mean [SD] age: low LTPA, 78.4 [6.2] years vs high LTPA, 75.1 [5.7] years; P?<?.001), more likely to be men, more likely to be White and less likely to be Hispanic, less likely to have MCI, and had more years of education, lower BMI, fewer comorbidities, and larger brain volumes (Table 1). There was no difference across LTPA levels in APOE ε4 allele status or WMH volume (Table 1).

            In this study population of older adults, most participants performed some amount of light LTPA, but only 16.7% performed moderate and 10.3% performed vigorous LTPA. Overall, 136 (9.4%) of the participants met the PAGA.

            Association Between LTPA and Brain Measures

            More LTPA was associated with larger TBV and more cortical thickness, both with a dose-response association (Model 2: TBV, P for trend?=?.006; cortical thickness, P for trend?=?.03; Table 2; Figure). Compared with no LTPA in Model 2, the highest level of LTPA had a β (SE) of 13.17 (4.42) cm3 larger size in TBV (P?=?.003; P for trend?=?.006) and a 0.016 (0.008) mm (P?=?.053; P for trend?=?.03) larger size in cortical thickness, respectively (Table 2), which is the equivalent to approximately 3 to 4 years of aging (β?=??3.06 cm3 on TBV and ?0.005 mm on cortical thickness for 1-year increase in age). When additionally adjusted for BMI and comorbidities in Model 3, the associations were attenuated generally but remained significant for TBV (β [SE], 9.47 [4.51] cm3) (Table 2). Meeting PAGA was associated with larger TBV (β [SE], 18.82 [5.14]) and more cortical thickness (β [SE], 0.02 [0.01]) (Table 3). Meeting light PAGA was also associated with larger TBV (β [SE], 9.26 [4.29]) (Model 2 in Table 3) independent of moderate or vigorous LTPA, although the magnitude of association was about half of the size of meeting PAGA through moderate to vigorous LTPA

            In general, there was no association between LTPA and WMH. After adjusting for BMI and comorbidities, low levels of LTPA were associated with larger WMH volume (eg, β [SE], 0.10 [0.05]; see Model 3 in Tables 2 and 3).

            Supplementary Analyses

            The association between LTPA with TBV was modified by race/ethnicity such that it was stronger for non-Hispanic White individuals than for Hispanic individuals (P for interaction?=?.05); the difference from non-Hispanic African American individuals was not significant (P for interaction?=?.07) (Table 4). However, benefits of LTPA were seen in all racial/ethnic groups, depending on amount and intensity-type of LTPA (Table 4).

            Sex (P for interaction?=?.05) and APOE genotype (P for interaction?=?.09) also modified the interaction between LTPA and TBV, although the difference was not significant. Meeting PAGA was associated with TBV in both men and women (Table 4). In APOE ε4 noncarriers, the results were similar to the main analyses, while in APOE ε4 carriers, only low LTPA or meeting PAGA were associated with larger TBV (Table 4).

            In 1172 participants who did not have MCI, LTPA remained to be associated with all brain volumes and cortical thickness, but not with WMH. Meeting PAGA also remained to be significantly associated with TBV (data not shown).

            Higher LTPA (Table 2) and meeting PAGA and performing light LTPA were associated with larger TGMV, TWMV and hippocampal volume (Table 3). Physical activity was positively associated with both left and right hemisphere cortical gray matter, cortical white matter, and hippocampal volumes (eTable in the Supplement). Middle LTPA (β [SE], 0.246 [0.086]; P?=?.004) and higher-middle light LTPA (β [SE], 0.223 [0.091]; P?=?.01) were associated with hippocampal volume in Hispanic individuals but not in non-Hispanic White or African American individuals; similar results for low LTPA were not significant (β [SE], 0.166 [0.085]; P?=?.05). Both LTPA (comparing high vs non: β [SE], 0.210 [0.109]; P for trend?=?.03) and light-intensity LTPA (light PAGA vs no light PAGA: β [SE], 0.203 [0.104]; P for trend?=?.03) were associated with hippocampal volume in men, but total LTPA was not significantly associated with hippocampal volume in women. In APOE ?4 noncarriers, the results were similar to the main analyses (data not shown), while in APOE ?4 carriers, performing low (β [SE], 0.281 [0.113]; P?=?.01) or middle (β [SE], 0.264 [0.112]; P?=?.02) LTPA was associated with larger hippocampal volume.

            Discussion

            In the present study of older adults, we found individuals who reported more LTPA had larger brain volume and cortical thickness than those who reported less LTPA. Our findings are in line with previous reports that show positive associations between LTPA and brain volume among older adults.8-12,29-31 Only 2 previous studies9,31 examined different LTPA amount levels in relation to brain volume, but no dose-response relationship was established. We found a dose-response association between total LTPA and brain volume or cortical thickness, with benefit gain starting from even low amounts of LTPA. The Framingham study31 found light-intensity PA, but not meeting PAGA from moderate or vigorous activities, was associated with higher TBV. In contrast, in a study of 323 older participants with MCI,13 moderate and vigorous, but not light-intensity, LTPA was associated with less brain atrophy. We found both light and moderate or vigorous intensity activities were independently associated with larger brain volumes, albeit with different effect sizes. Considering the much larger prevalence of light activities in the older adult population than moderate or vigorous activities, future health education needs to take into consideration both the effect size and practical feasibility for a better physical activity promotion in elderly populations.

            For individuals who are at higher risk of developing AD, it is particularly important to identify potential protective factors that can slow down the trajectory into the clinical stage of the disease. To our knowledge, this is the first study to show the association between LTPA and brain volume among African American and Hispanic individuals who had a higher risk of AD than White individuals.18 We also found a significant association between LTPA and brain volume in both women and men, although to a lesser extent for women than for men. Our findings are in accordance with a 2018 longitudinal study32 that found a significant association of LTPA with brain atrophy in men but not in women, and may help explain why older women have cognitive benefits from exercise to a lesser extent than older men.33,34 However, other studies found association between LTPA and hippocampal volumes among older women but not older men.35-37 The discrepancy might be due to the difference in LTPA level definition and brain regions examined.37 While the association of LTPA with TBV among APOE ?4 carriers was not as strong as among noncarriers, a low to middle level of LTPA was significantly associated with larger hippocampal volume in carriers. Previous studies have found either no interaction38 between LTPA and APOE status on cognition or that APOE ε4 carriers benefitted more from the exercise intervention than APOE ε4 noncarriers.39 Thus, the current study adds to the literature suggesting that LTPA might be an important intervention target for brain health and dementia prevention among APOE ε4 carriers. Among specific brain regions, hippocampal volume seems to be the key region responsive to LTPA,9,30,37,40,41 probably due to its plasticity and susceptibility to age-related atrophy.42 Thus, among at-risk individuals carrying the APOE ?4 allele, the association between LTPA and hippocampal volume may indeed reflect the results of this susceptible brain region being compensated by LTPA.

            We found LTPA in general was not associated with WMH. According to a 2016 review,15 most studies did not find a negative association between LTPA and WMH. We found that compared with no activity, low LTPA, particularly of light intensity, was associated with larger WMH volumes, echoing the findings of the Framingham Heart Study.31 The reason for this seemingly counterintuitive finding is unclear. With no clear dose-response association and with little evidence, cautions are needed to interpret the results. Nevertheless, future studies could elucidate the potential association between LTPA and WMH, especially with consideration of cognitive-stimulating leisure activities, light-intensity LTPA, and vascular comorbidities.

            The exact mechanisms for the positive association between LTPA and brain volume remains to be clarified but likely involves multiple biological mechanisms. Higher levels of physical activity are associated with higher levels of the neurotrophins such as brain-derived neurotrophic factor,8 synaptic plasticity,43 increased cerebral blood flow,44 and decreased β-amyloid 1-42 in cerebrospinal fluid.45 In addition to direct effects, physical activity may also contribute to brain maintenance, such as reducing the aging effect on amyloid deposition or glucose metabolism,46 and brain resilience, such as reducing the effect of amyloid on TBV.47

            Limitations and Strengths

            There are a few limitations in our study. This is a cross-sectional study, so we could not rule out the reverse causality. Self-reported activities may have certain misclassification errors which might have biased our results toward null. However, the design of the questionnaire allows analysis of LTPA intensity levels and reflects long-term habitual physical activity. While we adjusted for many potential confounders, residual confounding from other factors, such as diet26 and sleep,48 might remain. The subgroup analyses were limited by small sample size and might have been underpowered. We did not examine particular types of LTPA, but it might be less important than amount of activities.49

            There are many strengths of this study. Our study is among the largest ones that have examined LTPA and brain measures in community-based populations. The study controlled for many potential confounders including demographics, occupation, and comorbidities. We examined both the total amount/volume and intensity of LTPA and found even low-dose and low-intensity activities might have benefits for brain health. We found certain effect modifications by race/ethnicity, sex, and APOE ?4 status, supporting future investigation among at risk subpopulations. We found significant associations between LTPA and brain volume in 3 racial/ethnic groups, thus increasing the generalizability to the increasingly diverse US population.

            Conclusions

            Habitual LTPA is associated with larger brain volumes in older adults. Future longitudinal studies are warranted to confirm whether LTPA can prevent brain atrophy in older individuals.

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            Article Information

            Accepted for Publication: September 22, 2020.

            Published: November 19, 2020. doi:10.1001/jamanetworkopen.2020.26506

            Open Access: This is an open access article distributed under the terms of the CC-BY License. ? 2020 Gu Y et al. JAMA Network Open.

            Corresponding Author: Yian Gu, PhD, Columbia University, 630 W 168th St, Box 16, New York, NY 10032 (yg2121@cumc.columbia.edu).

            Author Contributions: Dr Gu had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

            Concept and design: Gu, Brickman.

            Acquisition, analysis, or interpretation of data: All authors.

            Drafting of the manuscript: Gu, Beato.

            Critical revision of the manuscript for important intellectual content: Amarante, Chesebro, Manly, Schupf, Mayeux, Brickman.

            Statistical analysis: Gu, Schupf.

            Obtained funding: Gu, Manly, Schupf, Mayeux.

            Administrative, technical, or material support: Beato, Amarante, Chesebro, Manly, Mayeux, Brickman.

            Conflict of Interest Disclosures: Dr Brickman reported receiving personal fees from Cognition Therapeutics, Inc, personal fees from Regeneron Pharmaceuticals, and shares from Mars Holding Ltd and Venus Medtech outside the submitted work; in addition, Dr Brickman had US patent No. 9867566 issued related to technologies for white matter hyperintensity quantification and a patent pending for methods and systems for evaluating age-related memory loss. No other disclosures were reported.

            Funding/Support: Data collection and sharing for this project was supported by the Washington Heights-Inwood Columbia Aging Project (WHICAP) grants PO1AG007232, R01AG037212, RF1AG054023, AG054520, AG061008, R01AG059013, and R56AG060156, funded by the National Institute on Aging, and by the National Center for Advancing Translational Sciences, National Institutes of Health, through grant No. UL1TR001873.

            Role of the Funder/Sponsor: The funders had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

            Additional Contributions: This manuscript has been reviewed by WHICAP investigators for scientific content and consistency of data interpretation with previous WHICAP study publications. We acknowledge the WHICAP study participants and the WHICAP research and support staff for their contributions to this study.

            References
            1.
            Scarmeas ?N?, Luchsinger ?JA?, Schupf ?N?, ?et al. ?Physical activity, diet, and risk of Alzheimer disease.?? ?JAMA. 2009;302(6):627-637. doi:10.1001/jama.2009.1144PubMedGoogle ScholarCrossref
            2.
            Ogino ?E?, Manly ?JJ?, Schupf ?N?, Mayeux ?R?, Gu ?Y?. ?Current and past leisure time physical activity in relation to risk of Alzheimer’s disease in older adults.?? ?Alzheimers Dement. 2019;15(12):1603-1611. doi:10.1016/j.jalz.2019.07.013PubMedGoogle ScholarCrossref
            3.
            de Bruijn ?RF?, Schrijvers ?EM?, de Groot ?KA?, ?et al. ?The association between physical activity and dementia in an elderly population: the Rotterdam Study.?? ?Eur J Epidemiol. 2013;28(3):277-283. doi:10.1007/s10654-013-9773-3PubMedGoogle ScholarCrossref
            4.
            Podewils ?LJ?, Guallar ?E?, Kuller ?LH?, ?et al. ?Physical activity, APOE genotype, and dementia risk: findings from the Cardiovascular Health Cognition Study.?? ?Am J Epidemiol. 2005;161(7):639-651. doi:10.1093/aje/kwi092PubMedGoogle ScholarCrossref
            5.
            Piercy ?KL?, Troiano ?RP?, Ballard ?RM?, ?et al. ?The physical activity guidelines for Americans.?? ?JAMA. 2018;320(19):2020-2028. doi:10.1001/jama.2018.14854PubMedGoogle ScholarCrossref
            6.
            Physical Activity Guidelines Advisory Committee.? 2018 Physical Activity Guidelines Advisory Committee Scientific Report. US Department of Health and Human Services; 2018.
            7.
            Brickman ?AM?, Tosto ?G?, Gutierrez ?J?, ?et al. ?An MRI measure of degenerative and cerebrovascular pathology in Alzheimer disease.?? ?Neurology. 2018;91(15):e1402-e1412. doi:10.1212/WNL.0000000000006310PubMedGoogle ScholarCrossref
            8.
            Fl?el ?A?, Ruscheweyh ?R?, Krüger ?K?, ?et al. ?Physical activity and memory functions: are neurotrophins and cerebral gray matter volume the missing link??? ?Neuroimage. 2010;49(3):2756-2763. doi:10.1016/j.neuroimage.2009.10.043PubMedGoogle ScholarCrossref
            9.
            Erickson ?KI?, Raji ?CA?, Lopez ?OL?, ?et al. ?Physical activity predicts gray matter volume in late adulthood: the Cardiovascular Health Study.?? ?Neurology. 2010;75(16):1415-1422. doi:10.1212/WNL.0b013e3181f88359PubMedGoogle ScholarCrossref
            10.
            Rovio ?S?, Spulber ?G?, Nieminen ?LJ?, ?et al. ?The effect of midlife physical activity on structural brain changes in the elderly.?? ?Neurobiol Aging. 2010;31(11):1927-1936. doi:10.1016/j.neurobiolaging.2008.10.007PubMedGoogle ScholarCrossref
            11.
            Benedict ?C?, Brooks ?SJ?, Kullberg ?J?, ?et al. ?Association between physical activity and brain health in older adults.?? ?Neurobiol Aging. 2013;34(1):83-90. doi:10.1016/j.neurobiolaging.2012.04.013PubMedGoogle ScholarCrossref
            12.
            Gow ?AJ?, Bastin ?ME?, Mu?oz Maniega ?S?, ?et al. ?Neuroprotective lifestyles and the aging brain: activity, atrophy, and white matter integrity.?? ?Neurology. 2012;79(17):1802-1808. doi:10.1212/WNL.0b013e3182703fd2PubMedGoogle ScholarCrossref
            13.
            Doi ?T?, Makizako ?H?, Shimada ?H?, ?et al. ?Objectively measured physical activity, brain atrophy, and white matter lesions in older adults with mild cognitive impairment.?? ?Exp Gerontol. 2015;62:1-6. doi:10.1016/j.exger.2014.12.011PubMedGoogle ScholarCrossref
            14.
            Colcombe ?SJ?, Erickson ?KI?, Raz ?N?, ?et al. ?Aerobic fitness reduces brain tissue loss in aging humans.?? ?J Gerontol A Biol Sci Med Sci. 2003;58(2):176-180. doi:10.1093/gerona/58.2.M176PubMedGoogle ScholarCrossref
            15.
            Sexton ?CE?, Betts ?JF?, Demnitz ?N?, Dawes ?H?, Ebmeier ?KP?, Johansen-Berg ?H?. ?A systematic review of MRI studies examining the relationship between physical fitness and activity and the white matter of the ageing brain.?? ?Neuroimage. 2016;131:81-90. doi:10.1016/j.neuroimage.2015.09.071PubMedGoogle ScholarCrossref
            16.
            Jochem ?C?, Baumeister ?SE?, Wittfeld ?K?, ?et al. ?Domains of physical activity and brain volumes: a population-based study.?? ?Neuroimage. 2017;156:101-108. doi:10.1016/j.neuroimage.2017.05.020PubMedGoogle ScholarCrossref
            17.
            Stephen ?R?, Liu ?Y?, Ngandu ?T?, ?et al; FINGER study group. ?Brain volumes and cortical thickness on MRI in the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER).?? ?Alzheimers Res Ther. 2019;11(1):53. doi:10.1186/s13195-019-0506-zPubMedGoogle ScholarCrossref
            18.
            Tang ?MX?, Cross ?P?, Andrews ?H?, ?et al. ?Incidence of AD in African Americans, Caribbean Hispanics, and Caucasians in northern Manhattan.?? ?Neurology. 2001;56(1):49-56. doi:10.1212/WNL.56.1.49PubMedGoogle ScholarCrossref
            19.
            American Psychiatric Association. ?Diagnostic and Statistical Manual of Mental Disorders. 3rd ed.? American Psychiatric Press; 1987.
            20.
            McKhann ?G?, Drachman ?D?, Folstein ?M?, Katzman ?R?, Price ?D?, Stadlan ?EM?. ?Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease.?? ?Neurology. 1984;34(7):939-944. doi:10.1212/WNL.34.7.939PubMedGoogle ScholarCrossref
            21.
            Petersen ?RC?. ?Mild cognitive impairment as a diagnostic entity.?? ?J Intern Med. 2004;256(3):183-194. doi:10.1111/j.1365-2796.2004.01388.xPubMedGoogle ScholarCrossref
            22.
            Manly ?JJ?, Bell-McGinty ?S?, Tang ?MX?, Schupf ?N?, Stern ?Y?, Mayeux ?R?. ?Implementing diagnostic criteria and estimating frequency of mild cognitive impairment in an urban community.?? ?Arch Neurol. 2005;62(11):1739-1746. doi:10.1001/archneur.62.11.1739PubMedGoogle ScholarCrossref
            23.
            Brickman ?AM?, Schupf ?N?, Manly ?JJ?, ?et al. ?Brain morphology in older African Americans, Caribbean Hispanics, and whites from northern Manhattan.?? ?Arch Neurol. 2008;65(8):1053-1061. doi:10.1001/archneur.65.8.1053PubMedGoogle ScholarCrossref
            24.
            Brickman ?AM?, Zahodne ?LB?, Guzman ?VA?, ?et al. ?Reconsidering harbingers of dementia: progression of parietal lobe white matter hyperintensities predicts Alzheimer’s disease incidence.?? ?Neurobiol Aging. 2015;36(1):27-32. doi:10.1016/j.neurobiolaging.2014.07.019PubMedGoogle ScholarCrossref
            25.
            Sanfilipo ?MP?, Benedict ?RH?, Zivadinov ?R?, Bakshi ?R?. ?Correction for intracranial volume in analysis of whole brain atrophy in multiple sclerosis: the proportion vs residual method.?? ?Neuroimage. 2004;22(4):1732-1743. doi:10.1016/j.neuroimage.2004.03.037PubMedGoogle ScholarCrossref
            26.
            Gu ?Y?, Brickman ?AM?, Stern ?Y?, ?et al. ?Mediterranean diet and brain structure in a multiethnic elderly cohort.?? ?Neurology. 2015;85(20):1744-1751. doi:10.1212/WNL.0000000000002121PubMedGoogle ScholarCrossref
            27.
            Godin ?G?, Shephard ?RJ?. ?A simple method to assess exercise behavior in the community.?? ?Can J Appl Sport Sci. 1985;10(3):141-146.PubMedGoogle Scholar
            28.
            Jacobs ?DR ?Jr?, Ainsworth ?BE?, Hartman ?TJ?, Leon ?AS?. ?A simultaneous evaluation of 10 commonly used physical activity questionnaires.?? ?Med Sci Sports Exerc. 1993;25(1):81-91. doi:10.1249/00005768-199301000-00012PubMedGoogle ScholarCrossref
            29.
            Halloway ?S?, Arfanakis ?K?, Wilbur ?J?, Schoeny ?ME?, Pressler ?SJ?. ?Accelerometer physical activity is associated with greater gray matter volumes in older adults without dementia or mild cognitive impairment.?? ?J Gerontol B Psychol Sci Soc Sci. 2019;74(7):1142-1151. doi:10.1093/geronb/gby010PubMedGoogle ScholarCrossref
            30.
            Hamer ?M?, Sharma ?N?, Batty ?GD?. ?Association of objectively measured physical activity with brain structure: UK Biobank study.?? ?J Intern Med. 2018;284(4):439-443. doi:10.1111/joim.12772PubMedGoogle ScholarCrossref
            31.
            Spartano ?NL?, Davis-Plourde ?KL?, Himali ?JJ?, ?et al. ?Association of accelerometer-measured light-intensity physical activity with brain volume: the Framingham Heart Study.?? ?JAMA Netw Open. 2019;2(4):e192745. doi:10.1001/jamanetworkopen.2019.2745PubMedGoogle Scholar
            32.
            Kim ?RE?, Yun ?CH?, Thomas ?RJ?, ?et al. ?Lifestyle-dependent brain change: a longitudinal cohort MRI study.?? ?Neurobiol Aging. 2018;69:48-57. doi:10.1016/j.neurobiolaging.2018.04.017PubMedGoogle ScholarCrossref
            33.
            Ludyga ?S?, Gerber ?M?, Pühse ?U?, Looser ?VN?, Kamijo ?K?. ?Systematic review and meta-analysis investigating moderators of long-term effects of exercise on cognition in healthy individuals.?? ?Nat Hum Behav. 2020;4(6):603-612. doi:10.1038/s41562-020-0851-8PubMedGoogle ScholarCrossref
            34.
            Stern ?Y?, Lee ?S?, Predovan ?D?, P Sloan ?R?. ?Sex moderates the effect of aerobic exercise on some aspects of cognition in cognitively intact younger and middle-age adults.?? ?J Clin Med. 2019;8(6):E886. doi:10.3390/jcm8060886PubMedGoogle Scholar
            35.
            Dougherty ?RJ?, Schultz ?SA?, Boots ?EA?, ?et al. ?Relationships between cardiorespiratory fitness, hippocampal volume, and episodic memory in a population at risk for Alzheimer’s disease.?? ?Brain Behav. 2017;7(3):e00625. doi:10.1002/brb3.625PubMedGoogle Scholar
            36.
            Varma ?VR?, Chuang ?YF?, Harris ?GC?, Tan ?EJ?, Carlson ?MC?. ?Low-intensity daily walking activity is associated with hippocampal volume in older adults.?? ?Hippocampus. 2015;25(5):605-615. doi:10.1002/hipo.22397PubMedGoogle ScholarCrossref
            37.
            Barha ?CK?, Best ?JR?, Rosano ?C?, Yaffe ?K?, Catov ?JM?, Liu-Ambrose ?T?. ?Sex-specific relationship between long-term maintenance of physical activity and cognition in the Health ABC Study: potential role of hippocampal and dorsolateral prefrontal cortex volume.?? ?J Gerontol A Biol Sci Med Sci. 2020;75(4):764-770.PubMedGoogle Scholar
            38.
            Folley ?S?, Zhou ?A?, Llewellyn ?DJ?, Hypp?nen ?E?. ?Physical activity, APOE genotype, and cognitive decline: exploring gene-environment interactions in the UK Biobank.?? ?J Alzheimers Dis. 2019;71(3):741-750. doi:10.3233/JAD-181132PubMedGoogle ScholarCrossref
            39.
            Jensen ?CS?, Simonsen ?AH?, Siersma ?V?, ?et al. ?Patients with Alzheimer’s disease who carry the APOE ε4 allele benefit more from physical exercise.?? ?Alzheimers Dement (N Y). 2019;5:99-106. doi:10.1016/j.trci.2019.02.007PubMedGoogle ScholarCrossref
            40.
            Tan ?ZS?, Spartano ?NL?, Beiser ?AS?, ?et al. ?Physical activity, brain volume, and dementia risk: the Framingham Study.?? ?J Gerontol A Biol Sci Med Sci. 2017;72(6):789-795.PubMedGoogle Scholar
            41.
            Firth ?J?, Stubbs ?B?, Vancampfort ?D?, ?et al. ?Effect of aerobic exercise on hippocampal volume in humans: a systematic review and meta-analysis.?? ?Neuroimage. 2018;166:230-238. doi:10.1016/j.neuroimage.2017.11.007PubMedGoogle ScholarCrossref
            42.
            Jack ?CR ?Jr?, Knopman ?DS?, Jagust ?WJ?, ?et al. ?Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade.?? ?Lancet Neurol. 2010;9(1):119-128. doi:10.1016/S1474-4422(09)70299-6PubMedGoogle ScholarCrossref
            43.
            Farmer ?J?, Zhao ?X?, van Praag ?H?, Wodtke ?K?, Gage ?FH?, Christie ?BR?. ?Effects of voluntary exercise on synaptic plasticity and gene expression in the dentate gyrus of adult male Sprague-Dawley rats in vivo.?? ?Neuroscience. 2004;124(1):71-79. doi:10.1016/j.neuroscience.2003.09.029PubMedGoogle ScholarCrossref
            44.
            Joris ?PJ?, Mensink ?RP?, Adam ?TC?, Liu ?TT?. ?Cerebral blood flow measurements in adults: a review on the effects of dietary factors and exercise.?? ?Nutrients. 2018;10(5):E530. doi:10.3390/nu10050530PubMedGoogle Scholar
            45.
            Baker ?LD?, Frank ?LL?, Foster-Schubert ?K?, ?et al. ?Effects of aerobic exercise on mild cognitive impairment: a controlled trial.?? ?Arch Neurol. 2010;67(1):71-79. doi:10.1001/archneurol.2009.307PubMedGoogle ScholarCrossref
            46.
            Okonkwo ?OC?, Schultz ?SA?, Oh ?JM?, ?et al. ?Physical activity attenuates age-related biomarker alterations in preclinical AD.?? ?Neurology. 2014;83(19):1753-1760. doi:10.1212/WNL.0000000000000964PubMedGoogle ScholarCrossref
            47.
            Rabin ?JS?, Klein ?H?, Kirn ?DR?, ?et al. ?Associations of physical activity and β-amyloid with longitudinal cognition and neurodegeneration in clinically normal older adults.?? ?JAMA Neurol. 2019;76(10):1203-1210. doi:10.1001/jamaneurol.2019.1879PubMedGoogle ScholarCrossref
            48.
            Rostanski ?SK?, Zimmerman ?ME?, Schupf ?N?, ?et al. ?Sleep disordered breathing and white matter hyperintensities in community-dwelling elders.?? ?Sleep. 2016;39(4):785-791. doi:10.5665/sleep.5628PubMedGoogle ScholarCrossref
            49.
            Thompson ?PD?, Buchner ?D?, Pina ?IL?, ?et al; American Heart Association Council on Clinical Cardiology Subcommittee on Exercise, Rehabilitation, and Prevention; American Heart Association Council on Nutrition, Physical Activity, and Metabolism Subcommittee on Physical Activity. ?Exercise and physical activity in the prevention and treatment of atherosclerotic cardiovascular disease: a statement from the Council on Clinical Cardiology (Subcommittee on Exercise, Rehabilitation, and Prevention) and the Council on Nutrition, Physical Activity, and Metabolism (Subcommittee on Physical Activity).?? ?Circulation. 2003;107(24):3109-3116. doi:10.1161/01.CIR.0000075572.40158.77PubMedGoogle ScholarCrossref
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