The Relations Between Physical Activity Level, Executive Function, and White Matter Microstructure in Older Adults

in Journal of Physical Activity and Health
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The population of older adults is increasing, indicating a need to examine factors that may prevent or mitigate age-related cognitive decline. The current study examined whether microstructural white matter characteristics mediated the relation between physical activity and executive function in older adults without any self-reported psychiatric and neurological disorders or cognitive impairment (N = 43, mean age = 73 y). Physical activity was measured by average intensity and number of steps via accelerometry. Diffusion tensor imaging was used to examine microstructural white matter characteristics, and neuropsychological testing was used to examine executive functioning. Parallel mediation models were analyzed using microstructural white matter regions of interest as mediators of the association between physical activity and executive function. Results indicated that average steps was significantly related to executive function (β = 0.0003, t = 2.829, P = .007), while moderate to vigorous physical activity was not (β = 0.0007, t = 1.772, P = .08). White matter metrics did not mediate any associations. This suggests that microstructural white matter characteristics alone may not be the mechanism by which physical activity impacts executive function in aging.

At the time of this study, the authors were with the Department of Psychology, University of Georgia, Athens, GA, USA.

Gogniat (mag53440@uga.edu) is corresponding author.
  • 1.

    Ortman JM, Velkoff VA, Hogan H. An Aging Nation: The older Population in the United States, Current Population Reports, P25-1140. Washington, DC: U.S. Census Bureau; 2014.

    • Search Google Scholar
    • Export Citation
  • 2.

    Good CD, Johnsrude IS, Ashburner J, Hensona RNA, Friston KJ, Frackowiak RSJ. A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage. 2001;14:2136. doi:10.1006/nimg.2001.0786

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Molloy CJ, Nugent S, Bokde AL. Alterations in diffusion measures of white matter integrity associated with healthy aging. J Gerontol A Biol Sci Med Sci. 2021;76(6):945954. doi:10.1093/gerona/glz289

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Salthouse TA. Memory aging from 18 to 80. Alzheimer Dis Assoc Disord. 2003;17:162167.

  • 5.

    Harada CN, Natelson Love MC, Triebel K. Normal Cognitive Aging. Clin Geriatr Med. 2013;29:737752. doi:10.1016/j.cger.2013.07.002

  • 6.

    Salthouse TA. Selective review of cognitive aging. J Int Neuropsychol Soc. 2010;16:754760. doi:10.1017/S1355617710000706

  • 7.

    Brickman AM, Meier IB, Korgaonkar MS, et al. Testing the white matter retrogenesis hypothesis of cognitive aging. Neurobiol Aging. 2012;33:16991715. doi:10.1016/j.neurobiolaging.2011.06.001

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Stricker NH, Schweinsburg BC, Delano-Wood L, et al. Decreased white matter integrity in late-myelinating fiber pathways in Alzheimer’s disease supports retrogenesis. NeuroImage. 2009;45(1):1016. doi:10.1016/j.neuroimage.2008.11.027

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Arain M, Haque M, Johal L, et al. Maturation of the adolescent brain. Neuropsychiatr Dis Treat. 2013;9:449461. doi:10.2147/NDT.S39776

  • 10.

    Otero TM, Barker LA. The frontal lobes and executive functioning. In: Goldstein S, Naglieri J, eds., Handbook of Executive Functioning. New York, NY: Springer; 2014:2944.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 11.

    Razani J, Casas R, Wong JT, et al. The relationship between executive functioning and activities of daily living in patients with relatively mild dementia. Appl Neuropsychol. 2007;14:208214. doi:10.1080/09084280701509125

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Brickman AM, Zimmerman ME, Paul RH, et al. Regional white matter and neuropsychological functioning across the adult lifespan. Biol Psychiatry. 2006;60:444453. doi:10.1016/j.biopsych.2006.01.011

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13.

    Canu E, McLaren DG, Fitzgerald ME, et al. Microstructural diffusion changes are independent of macrostructural volume loss in moderate to severe Alzheimer’s disease. J Alzheimers Dis. 2010;19:963976. doi:10.3233/JAD-2010-1295

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Hugenschmidt CE, Peiffer AM, Kraft RA, et al. Relating imaging indices of white matter integrity and volume in healthy older adults. Cereb Cortex. 2008;18:433442. doi:10.1093/cercor/bhm080

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15.

    Bosch B, Arenaza-Urquijo EM, Rami L, et al. Multiple DTI index analysis in normal aging, amnestic MCI and AD. Relationship with neuropsychological performance. Neurobiol Aging. 2010;33:6174. doi:10.1016/j.neurobiolaging.2010.02.004

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 16.

    Burzynska AZ, Preuschhof C, Backman L, et al. Age-related differences in white-matter microstructure: region-specific patterns of diffusivity. Neuroimage. 2010;9:21042112. doi:10.1016/j.neuroimage.2009.09.041

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 17.

    Canu E, McLaren D, Fitzgerald M, et al. Mapping the structural brain changes in Alzheimer’s disease: the independent contribution of two imaging modalities. J Alzheimers Dis. 2011;26:263274. doi:10.3233/JAD-2011-0040

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Gold BT, Powell DK, Andersen AH, Smith CD. Alterations in multiple measures of white matter integrity in normal women at high risk for Alzheimer’s disease. Neuroimage. 2010;52:14871494. doi:10.1016/j.neuroimage.2010.05.036

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19.

    Teipel SJ, Meindl T, Wagner M, et al. Longitudinal changes in fiber tract integrity in healthy aging and mild cognitive impairment: a DTI follow-up study. J Alzheimers Dis. 2010;22:507522. doi:10.3233/JAD-2010-100234

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Head D, Buckner RL, Shimony JS, et al. Differential vulnerability of anterior white matter in nondemented aging with minimal acceleration in dementia of the Alzheimer type: evidence from diffusion tensor imaging. Cereb Cortex. 2004;14:410423. doi:10.1093/cercor/bhh003

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21.

    Salat DH, Tuch DS, Greve DN, et al. Age-related alterations in white matter microstructure measured by diffusion tensor imaging. Neurobiol Aging. 2005;26:12151227. doi:10.1016/j.neurobiolaging.2004.09.017

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Yoon B, Shim YS, Lee KS, Shon YM, Yang DW. Region-specific changes of cerebral white matter during normal aging: a diffusion-tensor analysis. Arch Gerontol Geriatr. 2008;47:129138. doi:10.1016/j.archger.2007.07.004

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Davis SW, Dennis NA, Buchler NG, White LE, Madden DJ, Cabeza R. Assessing the effects of aging on long white matter tracts using diffusion tensor tractography. Neuroimage. 2009;46:530541. doi:10.1016/j.neuroimage.2009.01.068

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 24.

    Bennett IJ, Madden DJ, Vaidya CJ, Howard DV, Howard JH. Age-related differences in multiple measures of white matter integrity: a diffusion tensor imaging study of healthy aging. Hum Brain Mapp. 2010;31:378390. doi:10.1002/hbm.20872

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Bhagat YA, Beaulieu C. Diffusion anisotropy in subcortical white matter and cortical gray matter: changes with aging and the role of CSF-suppression. J Magn Reson Imaging. 2004;20:216227. doi:10.1002/jmri.20102

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Angevaren M, Aufdemkampe G, Verhaar HJJ, Aleman A, Vanhees L. Physical activity and enhanced fitness to improve cognitive function in older people without known cognitive impairment. Cochrane Database Syst Rev. 2008;3:CD005381. doi:10.1002/14651858.CD005381.pub3

    • Search Google Scholar
    • Export Citation
  • 27.

    Colcombe S, Kramer AF. Fitness effects on the cognitive function of older adults: a meta-analytic study. Psychol Sci. 2003;14:125130. doi:10.1111/1467-9280.t01-101430

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28.

    Sanders L, Hortobágyi T, la Bastide-van Gemert S, van der Zee EA, van Heuvelen M. Dose-response relationship between exercise and cognitive function in older adults with and without cognitive impairment: a systematic review and meta-analysis. PLoS One. 2019;14:e0210036. doi:10.1371/journal.pone.0210036

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29.

    Smith PJ, Blumenthal JA, Hoffman BM, et al. Aerobic exercise and neurocognitive performance: a meta-analytic review of randomized controlled trials. Psychosom Med. 2010;72:239252. doi:10.1097/PSY.0b013e3181d14633

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30.

    Baker LD, Frank LL, Foster-Schubert K, et al. Effects of aerobic exercise on mild cognitive impairment: a controlled trial. Arch Neurol. 2010;67:7179. doi:10.1001/archneurol.2009.307

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31.

    Lawla LL, Barnett F, Yau MK, Gray MA. Effects of functional tasks exercise on older adults with cognitive impairment at risk of Alzheimer’s disease: a randomised controlled trial. Age Ageing. 2014;43:813820. doi:10.1093/ageing/afu055

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 32.

    van Uffelen JG, Chin Paw AMJ, Hopman-Rock M, van Mechelen W. The effects of exercise on cognition in older adults with and without cognitive decline: a systematic review. Clin J Sport Med. 2008;18:486500. doi:10.1097/JSM.0b013e3181845f0b

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 33.

    Brown BM, Peiffer JJ, Sohrabi HR, Mondal A, Gupta VB, Rainey-Smith SR. Intense physical activity is associated with cognitive performance in the elderly. Transl Psychiatry. 2012;2:e191. doi:10.1038/tp.2012.118

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34.

    Ingold M, Tulliani N, Chan CC, Liu KP. Cognitive function of older adults engaging in physical activity. BMC Geriatr. 2020;20(1):113. doi:/10.1186/s12877-020-01620-w

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 35.

    Barnes DE, Blackwell T, Stone KL, Goldman SE, Hillier T, Yaffe K. Cognition in older women: the importance of daytime movement. J Am Geriatr Soc. 2008;56:16581664. doi:10.1111/j.1532-5415.2008.01841.x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 36.

    Daly M, McMinn D, Allan JL. A bidirectional relationship between physical activity and executive function in older adults. Front Hum Neurosci. 2015;8:1044. doi:10.3389/fnhum.2014.01044

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 37.

    Kerr J, Marshall SJ, Patterson RE, et al. Objectively measured physical activity is related to cognitive function in older adults. J Am Geriatr Soc. 2013;61(11):19271931. doi:10.1111/jgs.12524

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 38.

    Spartano NL, Demissie S, Himali JJ, et al. Accelerometer-determined physical activity and cognitive function in middle-aged and older adults from two generations of the Framingham Heart Study. Alzheimers Dement. 2019;5:618626. doi:10.1016/j.trci.2019.08.007

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 39.

    Colcombe SJ, Erickson KI, Scalf PE, et al. Aerobic exercise training increases brain volume in aging humans. J Gerontol A Biol Sci Med Sci. 2006;61:11661170. doi:10.1093/gerona/61.11.1166

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 40.

    Erickson KI, Voss MW, Prakash RS, et al. Exercise training increases size of hippocampus and improves memory. Proc Natl Acad Sci U S A. 2011;108:30173022. doi:10.1073/pnas.1015950108

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 41.

    Oberlin LE, Verstynen TD, Burzynska AZ, et al. White matter microstructure mediates the relationship between cardiorespiratory fitness and spatial working memory in older adults. NeuroImage. 2016;131:91101. doi:10.1016/j.neuroimage.2015.09.053

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 42.

    Voss MW, Heo S, Prakash RS, et al. The influence of aerobic fitness on cerebral white matter integrity and cognitive function in older adults: results of a one-year exercise intervention. Hum Brain Mapp. 2013;34:29722985. doi:10.1002/hbm.22119

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 43.

    Burzynska AZ, Jiao Y, Knecht AM, et al. White matter integrity declined over 6-months, but dance intervention improved integrity of the fornix of older adults. Front Aging Neurosci. 2017;9:59. doi:10.3389/fnagi.2017.00059

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 44.

    Yue C, Zou L, Mei J, et al. Tai Chi training evokes significant changes in brain white matter network in older women. Healthcare. 2020;8(1):57. doi:10.3390/healthcare8010057

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 45.

    Burzynska AZ, Chaddock-Heyman L, Voss MW, et al. Physical activity and cardiorespiratory fitness are beneficial for white matter in low-fit older adults. PLoS One. 2014;9:e107413. doi:10.1371/journal.pone.0107413

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 46.

    Bennett IJ, Greenia DE, Maillard P, et al. Age-related white matter integrity differences in oldest-old without dementia. Neurobiol Aging. 2017;56:108114. doi:10.1016/j.neurobiolaging.2017.04.013

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 47.

    Cox SR, Ritchie SJ, Tucker-Drob EM, et al. Ageing and brain white matter structure in 3,513 UK Biobank participants. Nat Commun. 2016;7(1):113. doi:10.1038/ncomms13629

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 48.

    Chanraud S, Zahr N, Sullivan EV, Pfefferbaum A. MR diffusion tensor imaging: a window into white matter integrity of the working brain. Neuropsychol Rev. 2010;20:209225. doi:10.1007/s11065-010-9129-7

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 49.

    New Lifestyles. NL-1000 Activity Monitor: User’s Guide & Record Book. Lees Summit, MO: New-Lifestyles Inc; 2005.

  • 50.

    Ayabe M, Katamoto S, Kumahara H, Naito H, Tanaka H, Brubaker PH. Validity and reliability of the simple assessment of the time spent in moderate to vigorous intensity physical activity under the controlled conditions. Med Sci Sports Exerc. 2006; 38:S555. doi:10.1249/00005768-200605001-02310

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 51.

    McClain J& Tudor-Locke C. Objective monitoring of physical activity in children: considerations for instrument selection. J Sci Med Sport. 2009;12:526533. doi:10.1016/j.jsams.2008.09.012

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 52.

    Delis DC, Kramer JH, Kaplan E, Holdnack J. Reliability and validity of the Delis-Kaplan Executive Function System: an update. J Int Neuropsychol Soc. 2004;10:301303. doi:10.1017/S1355617704102191

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 53.

    Delis DC, Kaplan E, Kramer JH. Delis-Kaplan Executive Function System (D-KEFS). San Antonio, TX: The Psychological Corporation; 2001.

  • 54.

    Bland J, Altman D. Statistics notes: Cronbach’s alpha. BMJ. 1997;314:572. doi:10.1136/bmj.314.7080.572

  • 55.

    Hinton PR, Brownlow C, McMurray I, Cozens B. SPSS Explained. East Sussex, UK: Routledge; 2004.

  • 56.

    Soares JM, Marques P, Alves V, Sousa N. A hitchhiker’s guide to diffusion tensor imaging. Front Neurosci. 2013;7:31. doi:10.3389/fnins.2013.00031

  • 57.

    Behrens TE, Woolrich MW, Jenkinson M, et al. Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magn Reson Med. 2003;50:10771088. doi:10.1002/mrm.10609

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 58.

    Smith SM. Fast robust automated brain extraction. Hum Brain Mapp. 2002;17:143155. doi:10.1002/hbm.10062

  • 59.

    Smith SM, Jenkinson M, Johansen-Berg H, et al. Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage. 2006;31:14871505. doi:10.1016/j.neuroimage.2006.02.024

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 60.

    Smith SM, Jenkinson M, Woolrich MW, et al. Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage. 2004;23(suppl 1):S208S219. doi:10.1016/j.neuroimage.2004.07.051

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 61.

    Andersson JLR, Jenkinson M, Smith S. Non-Linear Optimisation. FMRIB technical report TR07JA1. 2007. www.fmrib.ox.ac.uk/analysis/techrep. Accessed November 29, 2018.

    • Search Google Scholar
    • Export Citation
  • 62.

    Andersson JLR, Jenkinson M, Smith S. Non-Linear Registration, Aka Spatial Normalization. FMRIB technical report TR07JA2. 2007. www.fmrib.ox.ac.uk/analysis/techrep. Accessed November 29, 2018.

    • Search Google Scholar
    • Export Citation
  • 63.

    Hua X, Leow AD, Parikshak N, et al. Tensor-based morphometry as a neuroimaging biomarker for Alzheimer’s disease: an MRI study of 676 AD, MCI, and normal subjects. NeuroImage. 2008;43:458469. doi:10.1016/j.neuroimage.2008.07.013

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 64.

    Mori S, Oishi K, Jiang H, et al. Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template. NeuroImage. 2008;40:570582. doi:10.1016/j.neuroimage.2007.12.035

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 65.

    Tian Q, Erickson KI, Simonsick EM, et al. Physical activity predicts microstructural integrity in memory-related networks in very old adults. J Gerontol Ser A Biol Med Sci. 2014;69:12841290. doi:10.1093/gerona/glt287

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 66.

    Erdfelder E, Faul F, Buchner A. Gpower: A general power analysis program. Behav. Res. Methods. Instruments, & Computers. 2013;28:111. doi:10.3758/BF03203630

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 67.

    Hayes AF. PROCESS: a versatile computational tool for observed variable mediation, moderation, and conditional process modeling. 2012. http://www.afhayes.com/public/process2012.pdf. Accessed January 10, 2019.

    • Search Google Scholar
    • Export Citation
  • 68.

    Rucker DD, Preacher KJ, Tormala ZL, Petty RE. Mediation analysis in social psychology: current practices and new recommendations. Soc Personal Psychol Compass. 2011;5(6):359371. doi:10.1111/j.1751-9004.2011.00355.x

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 69.

    Preacher KJ, Hayes AF. SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behav Res Methods Instrum Comput. 2004;36:717731. doi:10.3758/BF03206553

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 70.

    Peters R. Ageing and the brain. Postgrad Med J. 2006;82:8488. doi:10.1136/pgmj.2005.036665

  • 71.

    Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE. Permutation inference for the general linear model. Neuroimage. 2014;92(100):381397. doi:10.1016/j.neuroimage.2014.01.060

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 72.

    Lett TA, Waller L, Tost H, et al. Cortical surface-based threshold-free cluster enhancement and cortexwise mediation. Hum Brain Mapp. 2017;38:27952807. doi:10.1002/hbm.23563

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 73.

    Bubb EJ, Metzler-Baddeley C, Aggleton JP. The cingulum bundle: anatomy, function, and dysfunction. Neurosci Biobehav Rev. 2018;92:104127. doi:10.1016/j.neubiorev.2018.05.008

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 74.

    Cahn-Weiner DA, Farias ST, Julian L, et al. Cognitive and neuroimaging predictors of instrumental activities of daily living. J Int Neuropsychol Soc. 2007;13(5):747757. doi:10.1017/S1355617707070853

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 75.

    Metzler-Baddeley C, Jones DK, Steventon J, Westacott L, Aggleton JP, O’Sullivan MJ. Cingulum microstructure predicts cognitive control in older age and mild cognitive impairment. J Neurosci. 2012;32:1761217619. doi:10.1523/JNEUROSCI.3299-12.2012

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 76.

    Wang Z, Dai Z, Shu H, et al. Cortical thickness and microstructural white matter changes detect amnestic mild cognitive impairment. J Alzheimers Dis. 2017;56:415428. doi:10.3233/JAD-160724

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 77.

    Bettcher BM, Mungas D, Patel N, et al. Neuroanatomical substrates of executive functions: beyond prefrontal structures. Neuropsychologia. 2016;85:100109. doi:10.1016/j.neuropsychologia.2016.03.001

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 78.

    de Groot M, Cremers LG, Ikram MA, et al. White matter degeneration with aging: longitudinal diffusion MR imaging analysis. Radiology. 2015;279:532541.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 79.

    Gothe NP. Examining the effects of light versus moderate to vigorous physical activity on cognitive function in African American adults. Aging Ment Health. 2020:17. doi:10.1080/13607863.2020.1768216

    • Search Google Scholar
    • Export Citation
  • 80.

    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 Network Open. 2019;2:e192745. doi:10.1001/jamanetworkopen.2019.2745

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 81.

    Coetsee C, Terblanche E. The effect of three different exercise training modalities on cognitive and physical function in a healthy older population. Eur Rev Aging Phys Act. 2017;14:13. doi:10.1186/s11556-017-0183-5

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 82.

    Tian Q, Glynn NW, Erickson KI, et al. Objective measures of physical activity, white matter integrity and cognitive status in adults over age 80. Behav Brain Res. 2015;284:5157. doi:10.1016/j.bbr.2015.01.045

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 83.

    Dustman RE, Emmerson R, Shearer D. Physical activity, age, and cognitive-neuropsychological function. J Aging Phys Act. 1994;2:143181. doi:10.1123/japa.2.2.143

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 84.

    Opel N, Martin S, Meinert S, et al. White matter microstructure mediates the association between physical fitness and cognition in healthy, young adults. Sci Rep. 2019;9(1):19. doi:10.1038/s41598-019-49301-y

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 85.

    World Health Organization. Physical activity and older adults. 2020. https://www.who.int/dietphysicalactivity/factsheet_olderadults/en/. Accessed December 15, 2020.

    • Search Google Scholar
    • Export Citation
  • 86.

    Cooper C, Gross A, Brinkman C, et al. The impact of wearable motion sensing technology on physical activity in older adults. Exp Gerontol. 2018;112:919. doi:10.1016/j.exger.2018.08.002

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 87.

    Prescott S, Traynor JP, Shilliday I, Zanotto T, Rush R, Mercer TH. Minimum accelerometer wear-time for reliable estimates of physical activity and sedentary behaviour of people receiving haemodialysis. BMC Nephrol. 2020;21:230. doi:10.1186/s12882-020-01877-8

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 88.

    Leritz EC, McGlinchey RE, Kellison I, Rudolph JL, Milberg WP. Cardiovascular Disease risk factors and cognition in the elderly. Curr Cardiovasc Risk Rep. 2011;5:407412. doi:10.1007/s12170-011-0189-x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 89.

    Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol. 2001;56:146156.

  • 90.

    Brigola AG, Rossetti ES, Dos Santos BR, et al. Relationship between cognition and frailty in elderly: a systematic review. Dement Neuropsychol. 2015;9:110119. doi:10.1590/1980-57642015DN92000005

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
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