Role of gait speed and grip strength in predicting 10-year cognitive decline among community-dwelling older people

Ming-Yueh Chou, Yukiko Nishita, Takeshi Nakagawa, Chikako Tange, Makiko Tomida, Hiroshi Shimokata, Rei Otsuka, Liang-Kung Chen, Hidenori Arai, Ming-Yueh Chou, Yukiko Nishita, Takeshi Nakagawa, Chikako Tange, Makiko Tomida, Hiroshi Shimokata, Rei Otsuka, Liang-Kung Chen, Hidenori Arai

Abstract

Background: The gait speed and handgrip strength represented the core determinants of physical frailty and sarcopenia, which were reported to be associated with cognitive impairment and decline. Different physical measures might differentially affect cognitive changes, such as higher-level cognitive change and global cognitive decline. This study examined the differential associations of gait speed and handgrip strength with 10-year cognitive changes among community-dwelling older people.

Methods: Participants aged 60 years and over living in the community were invited for study. Gait speed and handgrip strength were classified into 5 groups based on quintiles at baseline. Cognitive functions were assessed using the Mini-Mental State Examination (MMSE) and Digit Symbol Substitution Test (DSST) every 2 years from baseline for a period of 10 years. Linear mixed effects models were used to determine the role of gait speed and handgrip strength in the prediction of 10-year cognitive changes by adjusting covariates, including age, gender, education, depressive symptoms, marital status, smoking status, instrumental activities of daily life (IADL), Charlson Comorbidity Index (CCI), and body mass index (BMI) at baseline.

Results: A total of 1096 participants were enrolled in the study. The mean age was 69.4 ± 5.8 years and 50.9% were male. The slowest gait speed group showed a significantly greater decline in the DSST scores over 10 years than the highest group (estimate = 0.28 and P = 0.003), but not in the MMSE scores (estimate = 0.05 and P = 0.078). The lowest handgrip strength group showed a significantly greater decline in the MMSE scores than the highest group (estimate = 0.06 and P = 0.039) and in the DSST scores than the highest two quintiles (estimate = 0.20 and P = 0.033 for the fourth quintile; estimate = 0.20 and P = 0.040 for the highest quintile) over 10-year follow-up.

Conclusions: A slow gait speed could predict 10-year cognitive decline using DSST, and a low handgrip strength could predict 10-year cognitive decline using MMSE in addition to DSST. Thus both physical measures are lined to cognitive decline but there may be different mechanisms between brain and physical functions.

Keywords: Cognition; DSST; Gait speed; Handgrip strength; MMSE.

Conflict of interest statement

The authors declare that Liang-Kung Chen is a member of the editorial board as Associated Editor of BMC Geriatrics.

Figures

Fig. 1
Fig. 1
Model-predicted 10-year cognitive decline using the MMSE and DSST in the different gait speed and lowest handgrip strength quintile groups. ns: no significant. *: P-value < 0.05

References

    1. Prince M, Wimo A, Guerchet M, Ali G, Wu Y, Prina M. World Alzheimer Report 2015. In: The global impact of dementia. Alzheimer’s disease international. London: Alzheimer’s Disease International (ADI). p. 2015.
    1. Prince M, Bryce R, Albanese E, Wimo A, Ribeiro W, Ferri CP. The global prevalence of dementia: a systematic review and metaanalysis. Alzheimers Dement. 2013;9(1):63–75 e62.
    1. Li C, Dowling NM, Chappell R. Quantile regression with a change-point model for longitudinal data: an application to the study of cognitive changes in preclinical alzheimer's disease. Biometrics. 2015;71(3):625–635.
    1. Howieson DB. Cognitive decline in Presymptomatic Alzheimer disease. JAMA Neurol. 2016;73(4):384–385.
    1. Brasure M, Desai P, Davila H, Nelson VA, Calvert C, Jutkowitz E, Butler M, Fink HA, Ratner E, Hemmy LS, et al. Physical activity interventions in preventing cognitive decline and Alzheimer-type dementia: a systematic review. Ann Intern Med. 2018;168(1):30–38.
    1. de la Torre JC. Alzheimer's disease is incurable but preventable. J Alzheimers Dis. 2010;20(3):861–870.
    1. Livingston G, Sommerlad A, Orgeta V, Costafreda SG, Huntley J, Ames D, Ballard C, Banerjee S, Burns A, Cohen-Mansfield J, et al. Dementia prevention, intervention, and care. Lancet. 2017;390(10113):2673–2734.
    1. Wolinsky FD, Bentler SE, Hockenberry J, Jones MP, Weigel PA, Kaskie B, Wallace RB. A prospective cohort study of long-term cognitive changes in older Medicare beneficiaries. BMC Public Health. 2011;11(1):710.
    1. Martin KL, Blizzard L, Wood AG, Srikanth V, Thomson R, Sanders LM, Callisaya ML. Cognitive function, gait, and gait variability in older people: a population-based study. J Gerontol A Biol Sci Med Sci. 2013;68(6):726–732.
    1. Verghese J, Wang C, Lipton RB, Holtzer R, Xue X. Quantitative gait dysfunction and risk of cognitive decline and dementia. J Neurol Neurosurg Psychiatry. 2007;78(9):929–935.
    1. Inzitari M, Newman AB, Yaffe K, Boudreau R, de Rekeneire N, Shorr R, Harris TB, Rosano C. Gait speed predicts decline in attention and psychomotor speed in older adults: the health aging and body composition study. Neuroepidemiology. 2007;29(3–4):156–162.
    1. Hsu CL, Liang CK, Liao MC, Chou MY, Lin YT. Slow gait speed as a predictor of 1-year cognitive decline in a veterans' retirement community in southern Taiwan. Geriatr Gerontol Int. 2017;17:14–19.
    1. Sternäng O, Reynolds CA, Finkel D, Ernsth-Bravell M, Pedersen NL, Dahl Aslan AK. Grip strength and cognitive abilities: associations in old age. J Gerontol B Psychol Sci Soc Sci. 2015;71(5):841–848.
    1. Chang K-V, Hsu T-H, Wu W-T, Huang K-C, Han D-S. Association between sarcopenia and cognitive impairment: a systematic review and meta-analysis. J Am Med Dir Assoc. 2016;17(12):1164 e1167–1164 e1115.
    1. Buracchio T, Dodge HH, Howieson D, Wasserman D, Kaye J. The trajectory of gait speed preceding mild cognitive impairment. Arch Neurol. 2010;67(8):980–986.
    1. Demnitz N, Esser P, Dawes H, Valkanova V, Johansen-Berg H, Ebmeier KP, Sexton C. A systematic review and meta-analysis of cross-sectional studies examining the relationship between mobility and cognition in healthy older adults. Gait Posture. 2016;50:164–174.
    1. Kobayashi-Cuya Kimi Estela, Sakurai Ryota, Suzuki Hiroyuki, Ogawa Susumu, Takebayashi Toru, Fujiwara Yoshinori. Observational Evidence of the Association Between Handgrip Strength, Hand Dexterity, and Cognitive Performance in Community-Dwelling Older Adults: A Systematic Review. Journal of Epidemiology. 2018;28(9):373–381.
    1. Proust-Lima C, Amieva H, Dartigues J-F, Jacqmin-Gadda H. Sensitivity of four psychometric tests to measure cognitive changes in brain aging-population–based studies. Am J Epidemiol. 2006;165(3):344–350.
    1. Iwasa H, Kai I, Yoshida Y, Suzuki T, Kim H, Yoshida H. Information processing speed and 8-year mortality among community-dwelling elderly Japanese. J Epidemiol. 2014;24(1):52–59.
    1. Rapp MA, Reischies FM. Attention and executive control predict Alzheimer disease in late life: results from the Berlin aging study (BASE) Am J Geriatr Psychiatry. 2005;13(2):134–141.
    1. Iwasa H, Gondo Y, Yoshida Y, Kwon J, Inagaki H, Kawaai C, Masui Y, Kim H, Yoshida H, Suzuki T. Cognitive performance as a predictor of functional decline among the non-disabled elderly dwelling in a Japanese community: a 4-year population-based prospective cohort study. Arch Gerontol Geriatr. 2008;47(1):139–149.
    1. Edwards JD, Wadley VG, Vance DE, Wood K, Roenker DL, Ball KK. The impact of speed of processing training on cognitive and everyday performance. Aging Ment Health. 2005;9(3):262–271.
    1. Clouston SA, Brewster P, Kuh D, Richards M, Cooper R, Hardy R, Rubin MS, Hofer SM. The dynamic relationship between physical function and cognition in longitudinal aging cohorts. Epidemiol Rev. 2013;35:33–50.
    1. Shimokata H, Ando F, Niino N. A new comprehensive study on aging--the National Institute for longevity sciences, longitudinal study of aging (NILS-LSA) J Epidemiol. 2000;10(1 Suppl):S1–S9.
    1. Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, Martin FC, Michel J-P, Rolland Y, Schneider SM, Cruz-Gentoft AJ, et al. Sarcopenia: European consensus on definition and diagnosis Report of the European working group on sarcopenia in older People. Age Ageing. 2010;39(4):412–423.
    1. Chen LK, Liu LK, Woo J, Assantachai P, Auyeung TW, Bahyah KS, Chou MY, Chen LY, Hsu PS, Krairit O, et al. Sarcopenia in Asia: consensus report of the Asian working Group for Sarcopenia. J Am Med Dir Assoc. 2014;15(2):95–101.
    1. Nakamoto M, Otsuka R, Yuki A, Nishita Y, Tange C, Tomida M, Kato Y, Ando F, Shimokata H, Suzuki T. Higher gait speed and smaller sway area decrease the risk for decline in higher-level functional capacity among middle-aged and elderly women. Arch Gerontol Geriatr. 2015;61(3):429–436.
    1. Kozakai R, Ando F, Kim HY, Yuki A, Otsuka R, Shimokata H. Sex-differences in age-related grip strength decline: a 10-year longitudinal study of community-living middle-aged and older Japanese. Jpn J Phys Fitness Sports Med. 2016;5(1):87–94.
    1. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–198.
    1. Mori E. Usefulness of a Japanese version of the mini-mental state test in neurological patients. Jpn J Neuropsychol. 1985;1:82–90.
    1. Misawa G, Kobayashi S, Fujita K, Maekawa H, Dairoku H. Japanese wechsler adult intelligence scale-revised short forms. Tokyo: Nihon Bunka Kagakusha; 1993.
    1. Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1(3):385–401.
    1. Koyano W, Shibata H, Nakazato K, Haga H, Suyama Y. Measurement of competence: reliability and validity of the TMIG index of competence. Arch Gerontol Geriatr. 1991;13(2):103–116.
    1. Chaudhry Saima, Jin Lei, Meltzer David. Use of a Self-Report-Generated Charlson Comorbidity Index for Predicting Mortality. Medical Care. 2005;43(6):607–615.
    1. Laird NM, Ware JH. Random-effects models for longitudinal data. Biometrics. 1982;38(4):963–974.
    1. Morrell CH, Brant LJ, Ferrucci L. Model choice can obscure results in longitudinal studies. J Gerontol A Biol Sci Med Sci. 2009;64(2):215–222.
    1. Piercy KL, Troiano RP, Ballard RM, Carlson SA, Fulton JE, Galuska DA, George SM, Olson RD. The physical activity guidelines for Americans. Jama. 2018;320(19):2020–2028.
    1. Singh-Manoux A, Richards M, Marmot M. Leisure activities and cognitive function in middle age: evidence from the Whitehall II study. J Epidemiol Community Health. 2003;57(11):907–913.
    1. McDermott LM, Ebmeier KP. A meta-analysis of depression severity and cognitive function. J Affect Disord. 2009;119(1–3):1–8.
    1. Hsu YH, Liang CK, Chou MY, Liao MC, Lin YT, Chen LK, Lo YK. Association of cognitive impairment, depressive symptoms and sarcopenia among healthy older men in the veterans retirement community in southern T aiwan: a cross-sectional study. Geriatr Gerontol Int. 2014;14:102–108.
    1. Gao Y, Huang C, Zhao K, Ma L, Qiu X, Zhang L, Xiu Y, Chen L, Lu W, Huang C. Retracted: depression as a risk factor for dementia and mild cognitive impairment: a meta-analysis of longitudinal studies. Int J Geriatr Psychiatry. 2013;28(5):441–449.
    1. Weaver JD, Huang MH, Albert M, Harris T, Rowe JW, Seeman TE. Interleukin-6 and risk of cognitive decline: MacArthur studies of successful aging. Neurology. 2002;59(3):371–378.
    1. Cesari M, Penninx BW, Pahor M, Lauretani F, Corsi AM, Rhys Williams G, Guralnik JM, Ferrucci L. Inflammatory markers and physical performance in older persons: the InCHIANTI study. J Gerontol A Biol Sci Med Sci. 2004;59(3):242–248.
    1. Hogervorst E, Bandelow S, Combrinck M, Smith A. Low free testosterone is an independent risk factor for Alzheimer's disease. Exp Gerontol. 2004;39(11–12):1633–1639.
    1. Best JR, Liu-Ambrose T, Boudreau RM, Ayonayon HN, Satterfield S, Simonsick EM, Studenski S, Yaffe K, Newman AB, Rosano C. An evaluation of the longitudinal, bidirectional associations between gait speed and cognition in older women and men. J Gerontol A Biol Sci Med Sci. 2016;71(12):1616–1623.
    1. Gale CR, Allerhand M, Sayer AA, Cooper C, Deary IJ. The dynamic relationship between cognitive function and walking speed: the English longitudinal study of ageing. Age. 2014;36(4):9682.
    1. Smith EE, O’Donnell M, Dagenais G, Lear SA, Wielgosz A, Sharma M, Poirier P, Stotts G, Black SE, Strother S, et al. Early cerebral small vessel disease and brain volume, cognition, and gait. Ann Neurol. 2015;77(2):251–261.
    1. Holtzer R, Epstein N, Mahoney JR, Izzetoglu M, Blumen HM. Neuroimaging of mobility in aging: a targeted review. J Gerontol A Biol Sci Med Sci. 2014;69(11):1375–1388.
    1. Baillieux H, De Smet HJ, Paquier PF, De Deyn PP, Mariën P. Cerebellar neurocognition: insights into the bottom of the brain. Clin Neurol Neurosurg. 2008;110(8):763–773.
    1. Belghali M, Chastan N, Cignetti F, Davenne D, Decker LM. Loss of gait control assessed by cognitive-motor dual-tasks: pros and cons in detecting people at risk of developing Alzheimer’s and Parkinson’s diseases. GeroScience. 2017;39(3):305–329.
    1. Alfaro-Acha A, Al Snih S, Raji MA, Kuo YF, Markides KS, Ottenbacher KJ. Handgrip strength and cognitive decline in older Mexican Americans. J Gerontol A Biol Sci Med Sci. 2006;61(8):859–865.
    1. Auyeung TW, Lee J, Kwok T, Woo J. Physical frailty predicts future cognitive decline—a four-year prospective study in 2737 cognitively normal older adults. J Nutr Health Aging. 2011;15(8):690–694.
    1. Taekema DG, Gussekloo J, Maier AB, Westendorp RG, de Craen AJ. Handgrip strength as a predictor of functional, psychological and social health. A prospective population-based study among the oldest old. Age Ageing. 2010;39(3):331–337.
    1. Ward NS, Newton JM, Swayne OB, Lee L, Frackowiak RS, Thompson AJ, Greenwood RJ, Rothwell JC. The relationship between brain activity and peak grip force is modulated by corticospinal system integrity after subcortical stroke. Eur J Neurosci. 2007;25(6):1865–1873.
    1. Ismail S, Mohamad M, Syazarina S, Nafisah W. Journal of Physics: Conference Series. 2014. Hand grips strength effect on motor function in human brain using fMRI: a pilot study; p. 012005.
    1. Olivier E, Davare M, Andres M, Fadiga L. Precision grasping in humans: from motor control to cognition. Curr Opin Neurobiol. 2007;17(6):644–648.
    1. Callisaya ML, Beare R, Phan TG, Blizzard L, Thrift AG, Chen J, Srikanth VK. Brain structural change and gait decline: a longitudinal population-based study. J Am Geriatr Soc. 2013;61(7):1074–1079.
    1. Heuninckx S, Wenderoth N, Debaere F, Peeters R, Swinnen SP. Neural basis of aging: the penetration of cognition into action control. J Neurosci. 2005;25(29):6787–6796.

Source: PubMed

스폰서 및 공동 작업자

건강 상태

약물 개입

3
구독하다