Skip to main content

Advertisement

SpringerLink
Log in

The relationship between gait variability and cognitive functions differs between fallers and non-fallers in MS

  • Neurology and Preclinical Neurological Studies - Original Article
  • Published:
Journal of Neural Transmission Aims and scope Submit manuscript

Abstract

The objective of the study was to determine if cognitive function is associated with step time variability in people with multiple sclerosis (PwMS). The study included 355 PwMS (218 women), average age 41.1 (SD = 13.5), disease duration 5.9 (SD = 7.3) years, and a median expanded disability status scale score of 2.5. We separately analyzed the sample group of fallers and non-fallers based on their fall history. Gait variability was measured by an electronic walkway and all participants completed a computerized cognitive test battery designed to evaluate multiple cognitive domains. Fallers (43.7%) demonstrated elevated step time variability (%CV), 5.0 (SD = 3.4) vs. 3.5 (SD = 1.6), P < 0.001 compared to the non-faller subjects. According to the regression analysis in the non-fallers’ group, step time variability was found significantly associated with the global cognitive score (P = 0.001), executive function subcategory (P = 0.038), and motor skills subcategory (P < 0.001). No relationship between step time variability and any cognitive domain was demonstrated in the faller group. This study illustrated that the association between gait variability and cognition occurs only in PwMS without a fall history. From a clinical standpoint, these findings might help medical professionals to create improved assessment tests and rehabilitation strategies in the MS population.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Achiron A, Doniger GM, Harel Y, Appleboim-Gavish N, Lavie M, Simon ES (2007) Prolonged response times characterize cognitive performance in multiple sclerosis. Eur J Neurol 14:1102–1108

    Article  PubMed  CAS  Google Scholar 

  • Allali G, Laidet M, Herrmann FR, Armand S, Elsworth-Edelsten C, Assal F, Lalive PH (2016) Gait variability in multiple sclerosis: a better falls predictor than EDSS in patients with low disability. J Neural Transm (Vienna) 123:447–450

    Article  Google Scholar 

  • Beauchet O, Annweiler C, Celle S, Bartha R, Barthelemy JC, Roche F (2014a) Higher gait variability is associated with decreased parietal gray matter volume among healthy older adults. Brain Topogr 27(2):293–295

    Article  PubMed  Google Scholar 

  • Beauchet O, Lauay CP, Allali G, Hermann FR, Annweiller C (2014b) Gait changes with anti-dementia drugs: a prospective, open-label study combining single and dual task assessments in patients with Alzheimer’s disease. Drugs Aging 31(5):363–372

    Article  PubMed  CAS  Google Scholar 

  • Beauchet O, Launay CP, Barden J et al (2017) Association between falls and brain subvolumes: results from a cross-sectional analysis in healthy older adults. Brain Topogr 30:272–280

    Article  PubMed  Google Scholar 

  • Boisgontier MP, Cheval B, Chalavi S et al (2017) Individual differences in brainstem and basal ganglia structure predict postural control and balance loss in young and older adults. Neurobiol Aging 50:47–59

    Article  PubMed  Google Scholar 

  • Crenshaw SJ, Royer TD, Richards JG, Hudson DJ (2006) Gait variability in people with multiple sclerosis. Mult Scler 12(5):613–619

    Article  PubMed  CAS  Google Scholar 

  • De Cock AM, Fransen E, Perkisas S, Verhoeven V, Beauchet O, Remmen R, Vandewoude M (2017) Gait characteristics under different walking conditions: association with the presence of cognitive impairment in community-dwelling older people. PLoS One 12(6):e0178566

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • D’Orio VL, Foley FW, Armentano F, Picone MA, Kim S, Holtzer R (2012) Cognitive and motor functioning in patients with multiple sclerosis: neuropsychological predictors of walking speed and falls. J Neurol Sci 316(1–2):42–46

    Article  PubMed  Google Scholar 

  • Finlayson ML, Peterson EW, Cho CC (2006) Risk factors for falling among people aged 45 to 90 years with multiple sclerosis. Arch Phys Med Rehabil 87:1274–1279

    Article  PubMed  Google Scholar 

  • Hausdorff JM (2005) Gait variability: methods, modeling and meaning. J Neuroeng Rehabil 2:19

    Article  PubMed  PubMed Central  Google Scholar 

  • Gianni C, Prosperini L, Jonsdottir J, Catteneo D (2014) A systematic review of factors associated with accidental falls in people with multiple sclerosis: a meta-analytic approach. Clin Rehabil 28(7):704–716

    Article  PubMed  Google Scholar 

  • Gunn HJ, Newell P, Haas B, Marsden JF, Freeman JA (2013) Identification of risk factors for falls in multiple sclerosis: a systematic review and meta-analysis. Phys Ther 93:504–513

    Article  PubMed  Google Scholar 

  • Hausdorff JM, Balash J, Giladi N (2003) Effects of cognitive challenge on gait variability in patients with Parkinson’s disease. J Geriatr Psychiatry Neurol 16(1):53–58

    Article  PubMed  Google Scholar 

  • Herman T, Mirelman A, Giladi N, Schweiger A, Hausdorff J (2010) Executive control deficits as a prodrome to falls in healthy older adults: a prospective study linking thinking, walking, and falling. J Gerontol A Biol Med Sci 65(10):1086–1092

    Article  Google Scholar 

  • Hsieh KL, Sun R, Sosnoff JJ (2017) Cognition is associated with gait variability in individuals with multiple sclerosis. J Neurol Transm 124(12):1503–1508

    Article  Google Scholar 

  • Huisinga JM, Schmid KK, Filipi ML, Stergiou N (2013) Gait mechanics are different between healthy controls and patients with multiple sclerosis. J Appl Biomech 29:303–311

    Article  PubMed  Google Scholar 

  • Ijmker T, Lamoth CJ (2012) Gait and cognition: the relationship between gait stability and variability with executive function in persons with and without dementia. Gait Posture 35(1):126–130

    Article  PubMed  Google Scholar 

  • Kaipust JP, Huisinga JM, Fillipi M, Stergiou N (2012) Gait variability measures reveal differences between multiple sclerosis patients and healthy controls. Mot Control 16(2):229–244

    Article  Google Scholar 

  • Kalron A (2014) The relationship between specific cognitive domains, fear of falling, and falls in people with multiple sclerosis. Biomed Res Int 2014:281760

    Article  PubMed  PubMed Central  Google Scholar 

  • Kalron A (2016a) Gait variability across the disability spectrum in people with multiple sclerosis. J Neurol Sci 361:1–6

    Article  PubMed  Google Scholar 

  • Kalron A (2016b) The relationship between static posturography measures and specific cognitive domains in individuals with multiple sclerosis. Int J Rehabil Res 39(3):249–254

    Article  PubMed  Google Scholar 

  • Kalron A (2017) Association between gait variability, falls and mobility in people with multiple sclerosis: a specific observation on the EDSS 4.0–4.5 level. NeuroRehabilitation 40(4):579–585

    Article  PubMed  Google Scholar 

  • Kalron A, Frid L (2015) The “butterfly diagram”: a gait marker for neurological and cerebellar impairment in people with multiple sclerosis. J Neurol Sci 358(1–2):92–100

    Article  PubMed  Google Scholar 

  • Krieger SC, Cook K, De Nino S, Fletcher M (2016) The topographical model of multiple sclerosis: a dynamic visualization of disease course. Neurol Neuroimmunol Neuroinflamm 3(5):e279

    Article  PubMed  PubMed Central  Google Scholar 

  • Kurtzke JF (1983) Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 33:1444–1452

    Article  PubMed  CAS  Google Scholar 

  • Laidet M, Hermann FR, Armand S, Assai F, Lalive PH, Allali G (2017) Does fear of falling predict gait variability in multiple sclerosis? J Neurol Sci 380:212–214

    Article  PubMed  Google Scholar 

  • Lallart E, Jouvent R, Hermann FR, Perez-Diaz F, Lallart X, Beauchet O, Allali G (2014) Gait control and executive dysfunction in early schizophrenia. J Neurol Transm 121(4):443–450

    Article  CAS  Google Scholar 

  • Langdon DW (2011) Cognition in multiple sclerosis. Curr Opin Neurol 24:244–249

    Article  PubMed  Google Scholar 

  • Manor B, Newton E, Abduljalil A, Novak V (2012) The relationship between brain volume and walking outcomes in older adults with and without diabetic peripheral neuropathy. Diabetes Care 35(9):1907–1912

    Article  PubMed  PubMed Central  Google Scholar 

  • Martin KL, Blizzard L, Wood AG, Srikanth V, Thompson R, Sanders LM, Callisaya ML (2013) Cognitive function, gait, and gait variability in older people: a population-based study. J Gerontol A Biol Sci Med Sci 68(6):726–732

    Article  PubMed  Google Scholar 

  • Moon Y, Wajda DA, Motl RW, Sosnoff JJ (2015) Stride-time variability and fall risk in persons with multiple sclerosis. Mult Scler Int 2015:964790

    PubMed  PubMed Central  Google Scholar 

  • Mormina E, Petracca M, Bommarito G, Piaggio N, Cocozza S, Inglese M (2017) Cerebellum and neurodegenerative diseases: beyond conventional magnetic resonance imaging. World J Radiol 9(10):371–388

    Article  PubMed  PubMed Central  Google Scholar 

  • Myhr KM, Riise T, Vedeler C (2001) Disability and prognosis in multiple sclerosis: demographic and clinical variables important for the ability to walk and awarding of disability pension. Mult Scler 7:59–65

    Article  PubMed  CAS  Google Scholar 

  • Paul F (2016) Pathology and MRI: exploring cognitive impairment in MS. Acta Neurol Scand 134(200):24–33

    Article  PubMed  Google Scholar 

  • Pilutti LA, Dlugonski D, Sandroff BM, Suh Y, Pula JH, Sosnoff JJ, Motl RW (2013) Gait and six-minute walk performance in persons with multiple sclerosis. J Neurol Sci 334:72–76

    Article  PubMed  Google Scholar 

  • Polman CH, Reingold SC, Banwell B et al (2011) Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol 69:292–302

    Article  PubMed  PubMed Central  Google Scholar 

  • Prosperini L, Kouleridou A, Petsas N, Leonardi L, Tona F, Pantano P, Pozzilli C (2011) The relationship between infratentorial lesions, balance deficit and accidental falls in multiple sclerosis. J Neurol Sci 304(1–2):55–60

    Article  PubMed  Google Scholar 

  • Savica R, Wennberg AM, Hagen C et al (2017) Comparison of gait parameters for predicting cognitive decline: the mayo clinic study of aging. J Alzheimers Dis 55(2):559–567

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Schweiger A, Doniger GM, Dwolatzky T, Jaffe D, Simon ES (2003) Reliability of a novel computerized neuropsychological battery for mild cognitive impairment. Acta Neuropsychol 1(4):407–413

    Article  Google Scholar 

  • Socie MJ, Sosnoff JJ (2013) Gait variability and multiple sclerosis. Mult Scler Int 2013:645197

    PubMed  PubMed Central  Google Scholar 

  • Socie MJ, Sandroff BM, Pula JH, Hsiao-Wecksler ET, Motl RW, Sosnoff JJ (2013) Footfall placement variability and falls in multiple sclerosis. Ann Biomed Eng 41(8):1740–1747

    Article  PubMed  Google Scholar 

  • Sosnoff JJ, Balantrapu S, Pilutti LA, Sandroff BM, Morrison S, Motl RW (2013) Cognitive processing speed is related to fall frequency in older adults with multiple sclerosis. Arch Phys Med Rehabil 94(8):1567–1572

    Article  PubMed  Google Scholar 

  • Wennberg AM, Savica R, Hagen CE, Roberts RO, Knopman DS, Hollman JH, Vemuri P, Jack CR Jr, Peterson RC, Mielke MM (2016) Cerebral amyloid deposition is associated with gait parameters in the mayo clinic study of aging. J Am Geriatr Soc 65(4):792–799

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Physical Therapy, School of Health Professions, Sackler Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel

    Alon Kalron

  2. Multiple Sclerosis Center, Sheba Medical Center, Tel Hashomer, Israel

    Roy Aloni, Mark Dolev, Lior Frid, Uri Givon & Shay Menascu

  3. Sackler Faculty of Medicine, Tel-Aviv University, Tel Aviv, Israel

    Uri Givon & Shay Menascu

Authors
  1. Alon Kalron
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Roy Aloni
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mark Dolev
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lior Frid
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Uri Givon
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Shay Menascu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alon Kalron.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kalron, A., Aloni, R., Dolev, M. et al. The relationship between gait variability and cognitive functions differs between fallers and non-fallers in MS. J Neural Transm 125, 945–952 (2018). https://doi.org/10.1007/s00702-018-1843-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00702-018-1843-y

Keywords

Search

Navigation