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. Author manuscript; available in PMC: 2023 Jan 16.
Published in final edited form as: Int J Stroke. 2022 Sep 9;18(1):53–61. doi: 10.1177/17474930221114562

Gait in cerebral small vessel disease, pre-dementia, and dementia: A systematic review

Helena M Blumen 1,2, Oshadi Jayakody 1, Joe Verghese 1,2
PMCID: PMC9841467  NIHMSID: NIHMS1861277  PMID: 35797006

Abstract

Background:

The interrelationships between gait, cerebral small vessel disease (CSVD), and cognitive impairments in aging are not well-understood—despite their common co-occurrence.

Objective:

To systematically review studies of gait impairment in CSVD, pre-dementia, and dementia, and to identify key gaps for future research and novel pathways toward intervention.

Methods:

A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-guided search strategy was implemented in PubMed to identify relevant studies. Potential articles (n = 263) published prior to 1 December 2021 were screened by two reviewers. Studies with sample sizes >20 and including some adults over > 65 years (n = 202) were included.

Results:

The key findings were that (1) adverse gait and cognitive outcomes were associated with several (rather than select) CSVD pathologies distributed across the brain, and (2) poor gait and CSVD pathologies were more strongly associated with dementia with a vascular, rather than an Alzheimer’s disease-related, cause.

Discussion:

A better understanding of the interrelationships between gait performance in CSVD, pre-dementia, and dementia requires studies examining (1) comprehensive patterns in the clinical manifestations of CSVD, (2) racially/ethnically diverse samples, (3) samples followed for extended periods of time or across the adult life span, (4) non-traditional CSVD neuroimaging markers (e.g. resting-state functional magnetic resonance imaging (fMRI)), and (5) continuous (e.g. wearable sensors) and complex (e.g. dual-task) walking performance.

Keywords: Cerebral small vessel disease, gait, cognition, aging, cognitive impairment, dementia, gait abnormalities

Introduction

Poor gait performance is observed in older adults with cerebral small vessel disease (CSVD), pre-dementia, and dementia. Traditional neuroimaging markers of CSVD, such as subcortical infarcts, lacunes, and white matter hyperintensities (WMHs), for instance, are associated with gait impairments. These gait impairments are also associated with future onset of pre-dementias and dementias, including those that could be the downstream results of CSVD (e.g. vascular dementia). Note that pre-dementia syndromes, such as mild cognitive impairment (MCI), are marked by poor cognitive performance, but are not accompanied with the daily functional limitations observed in individuals with dementia. The objective of this systematic review was to generate a better understanding of the interrelationships between qualitative (e.g. apraxia) and quantitative (e.g. gait speed) gait performance in older adults with CSVD, pre-dementia, and dementia—and to identify important areas of research, and novel paths toward intervention. The focus and scope of this review is further illustrated in Figure 1.

Figure 1.

Figure 1.

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Gait outcomes and older adult populations examined in this review.

Methods

Search strategy and selection criteria

The search strategy was guided by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and is summarized in Figure 2(a).1 PubMed was systematically screened to identify studies of qualitative and quantitative gait in CSVD, pre-dementia, and dementia populations. The specific search terms are provided in Figure 2(b). The identified studies were first independently and then collaboratively screened by H.M.B and O.J to ensure they met inclusion/exclusion criteria. Key findings and demographic characteristics were then tabulated (Supplementary Tables 2–4) and categorized (Supplementary Figures 1–2). To reduce bias, both positive and negative findings were considered. Clinical gait abnormalities and quantitative gait outcomes in CSVD were reviewed in the “Clinical gait abnormalities and CSVD,” “Quantitative gait and CSVD,” “Gait decline and CSVD,” and “Gait and CSVD in pre-dementia and dementia” sections Clinical gait abnormalities and quantitative gait outcomes associated with cognitive decline, MCI, and dementia were reviewed in the “Clinical gait abnormalities in pre-dementia and dementia,” “Quantitative gait measures as markers for MCI and dementia,” and “Gait as a predictor of cognitive decline, MCI, and dementia” sections.

Figure 2.

Figure 2.

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(a) PRISMA flow diagram of study selection and (b) key words used in systematic PubMed search.

Note: The key words for gait were sequentially paired with each CSVD, pre-dementia, and dementia keyword during PubMed search, using an AND statement.

1Bugalho P, Guimarães J. Gait disturbance in normal pressure hydrocephalus: a clinical study. Parkinsonism & related disorders. 2007 Oct 1;13(7):434–7.

2Rutherford BR, Choi J, Slifstein M, O’Boyle K. Abi-Dargham A, Brown PJ, Wall MW, Vanegas-Arroyave N, Sakhardande J, Stern Y, Roose SP. Neuroanatomical predictors of L-DOPA response in older adults with psychomotor slowing and depression: A pilot study. Journal of affective disorders. 2020 Mar 15;265:439–44.

3Wolfson L, Wei X, Hall CB, et al. Accrual of MRI white matter abnormalities in elderly with normal and impaired mobility. 2005; 232: 23–27.

4Abbott RD, White LR, Ross GW, et al. Walking and dementia in physically capable elderly men. Jama 2004; 292: 1447–1453.

5Aggarwal NT, Wilson RS, Beck TL, Bienias JL, Bennett DA. Motor dysfunction in mild cognitive impairment and the risk of incident Alzheimer disease. Archives of Neurology. 2006;63(12):1763–1769

6Waite L, Grayson D, Piguet O, Creasey H, Bennett H, Broe G. Gait slowing as a predictor of incident dementia: 6-year longitudinal data from the Sydney Older Persons Study. Journal of the neurological sciences. 2005;229:89–93

7Katsumata Y, Todoriki H, Yasura S, Dodge HH. Timed up and go test predicts cognitive decline in healthy adults aged 80 and older in Okinawa: Keys to Optimal Cognitive Aging (KOCOA) Project. Journal of the American Geriatrics Society. 2011;59(11):2188

8Alves G, Larsen JP, Emre M, Wentzel-Larsen T, Aarsland D. Changes in motor subtype and risk for incident dementia in Parkinson’s disease. Movement disorders: official journal of the Movement Disorder Society. 2006;21(8):1123–1130

9Senanarong V, Harnphadungkit K, Poungvarin N, Vannasaeng S, Chongwisal S, Chakorn T, Jamjumrus P, Raksthaput A, Chaichanettee S, Aoonkaew N, Udompunthurak S. The dementia and disability project in Thai elderly: rational, design, methodology and early results. BMC neurology. 2013 Dec; 13(1):1–1.

10Staekenborg SS, Van der Flier WM, Van Straaten EC, Lane R, Barkhof F, Scheltens P. Neurological signs in relation to type of cerebrovascular disease in vascular dementia. Stroke. 2008 Feb 1;39(2):317–22.

11Nadkarni NK, Perera S, Studenski SA, Rosano C, Aizenstein HJ, VanSwearingen JM. Callosal hyperintensities and gait speed gain from two types of mobility interventions in older adults. Archives of physical medicine and rehabilitation. 2015 Jun 1;96(6):1154–7.

12Voss MW, Heo S, Prakash RS, Erickson KI, Alves H, Chaddock L, Szabo AN, Mailey EL. Wo jcicki TR, White SM, Gothe N, McAuley E, Sutton BP, Kramer AF. 2013; The influence of aerobic fitness on cerebral white matter integrity and cognitive function in older adults: results of a one-year exercise intervention. Human Brain Mapping.;34:2972–85.

Results

A total of 263 studies were screened, 202 studies were reviewed (Supplementary Tables 1–5 and Supplementary Figures 1–2), and 72 of these studies were qualitatively interpreted below.

Clinical gait abnormalities and CSVD

Studies of clinical gait abnormalities and CSVD pathologies were primarily cross-sectional. Gait abnormalities or gait disturbance severity were associated with several CSVD pathologies and brain regions—including subcortical infarcts, overall, subcortical, periventricular, and frontal WMH, white matter integrity in frontal, parietal, and corpus callosum regions, and thickness of the corpus callosum.2–6 Apraxia (frontal gait) was associated with WMH in frontal and basal ganglia regions, white matter integrity in the genu of corpus callosum, and subcortical and lacunar strokes.4,7,8

The distributed CSVD pathologies associated with clinical gait abnormalities suggest that examining patterns in the pathological and clinical manifestations of CSVD could improve our understanding of gait abnormalities and CSVD. A recent example of this approach employed cluster analyses to identify different neuroimaging profiles in individuals with severe CSVD.9 One cluster displayed widespread periventricular WMH, multiple lacunes and microbleeds, atrophy, severe cognitive and gait abnormalities, and down-regulation of vascular endothelial growth factor-A (indicative of widespread vascular wall damage). The other cluster displayed deep WMH, white matter lacunes, and enlarged perivascular spaces, but relatively less microbleeds and atrophy, less severe cognitive and gait abnormalities, and upregulation of tumor necrosis factor alpha (indicative of systemic inflammation). This study underscored the heterogeneity of the neuroimaging and clinical manifestations of severe CSVD and identified two distinct pathways that could guide future intervention design.

Quantitative gait and CSVD

Cross-sectional studies of quantitative gait and CSVD in aging can be categorized into (1) those contrasting CSVD in mobility-impaired versus mobility-intact individuals—determined by gait speed cuts (using a stopwatch), clinical evaluation, and/or semi-quantitative gait measures (e.g. Timed Up and Go (TUG) test);10 (2) those examining associations between CSVD and quantitative gait with instrumented walkways.

Mobility impairment and CSVD.

Mobility impairments were associated with CSVD pathologies in distributed brain regions, evident as greater overall WMH burden, more periventricular and deep WMH, more WMH in posterior, occipito-parietal, frontal and corpus callosum regions, worse white matter integrity in the thalamic radiation and corpus callosum, and a smaller caudate nucleus.11–17 Non-traditional CSVD neuroimaging markers shed light onto how the brain adapted to (or compensated for) CSVD. One study of cerebral perfusion revealed that mobility-impaired (compared to mobility-intact) individuals with CSVD showed relative under-activation of supplementary motor, thalamus, and basal ganglia regions and over-activation of premotor regions.18 Another study of resting-state functional magnetic resonance imaging (fMRI) revealed that mobility-impaired (compared to mobility-intact) individuals displayed reduced functional connectivity in the supplementary motor and superior parietal components of sensorimotor and fronto-parietal resting-state networks—and between supplementary motor and temporal lobe regions.19

Gait speed and CSVD.

Slow gait speed during usual pace (single-task) walking was associated with widepread-WMH,20–27 frontal and thalamic lacunes, microbleeds, widespread cortical and hippocampal atrophy, and reduced white matter integrity in specific tracts.21,23,24,28–32 A better understanding of the temporal interrelationship between adverse gait outcomes and CSVD requires studying these associations across the adult life span.

Dual-task walking and CSVD.

Associations between dual-task walking (DTW; walking while reciting alternate letters of the alphabet) and CSVD were inconsistent.33 One study suggested that DTW speed was not associated with WMH, whereas in another study increased dual-task costs (the percent difference between single-task and DTW-speed) was associated with less gray matter in medial prefrontal, cingulate, and thalamic regions.17,32 Furthermore, functional connectivity in sensorimotor, visual, vestibular, and left frontal-parietal resting-state networks were associated with both single-task and DTW-speeds—yet the supplementary and prefrontal components of sensorimotor and fronto-parietal networks were more strongly associated with DTW than single-task walking.34 Thus, current evidence suggests that DTW is associated with some but not all CSVD pathologies.

Additional gait measures and CSVD.

Absolute measures and step-to-step variability in stride length (distance between initial contacts of the same foot) and double support time (time when both feet are on the ground) were associated with different CSVD pathologies and brain regions. Shorter stride/step length was associated with overall, periventricular, and frontal WMH,21,24 a composite measure of CSVD (lacunes, WMH, microbleeds, and periventricular space),35 and lower overall, sensorimotor, and fronto-parietal volumes.36,37 Greater step length variability was associated with WMH and basal ganglia infarcts,38 and a widespread gray matter pattern that included frontal, temporal, insular, occipital, and cerebellar regions.39 Longer double support time was associated with WMH and less volume in sensorimotor and fronto-parietal regions.21,37 Finally, greater double support time variability was associated with gray matter volume in frontal, medial, temporal, anterior cingulate, insular, cerebellar and striatal regions, and cortical thickness in frontal and temporal regions.39,40 These studies suggest that distributed CSVD pathologies are associated with additional gait measures.

Gait decline and CSVD

The current literature on gait decline and CSVD is limited and mixed. Some studies of older adults without dementia suggested that baseline and the progression of overall and periventricular WMH, hippocampal atrophy, and the integrity of the corona radiata were associated with gait speed and step length decline.41–45

In contrast, in relatively young older adults (50–85 years) baseline lacunes, microbleeds, white matter integrity, and brain volume were not associated with gait speed decline after 5 years.46

Gait and CSVD in pre-dementia and dementia

In individuals with MCI, more subcortical WMH, less gray matter (in motor, frontal, middle temporal, cuneus, precuneus, and striatal regions) and greater lateral ventricular volume were associated with slower gait and greater stride time variability during single-task walking and DTW.47–49 The motoric cognitive risk syndrome (MCR syndrome; slow gait speed and subjective cognitive complaint) was associated with widespread cortical thinning and gray matter atrophy.50,51 In older Indian adults without dementia, cortical microbleeds were not associated with MCI or MCR, and frontal lacunes were associated only with MCR.52 In individuals with vascular dementia (VaD), WMH, cerebral infarcts, and thalamic lesions were associated with clinical gait abnormalities (hemiplegic or Parkinsonian gait).53 Interestingly, the relationship between dual-task gait and CSVD differed by MCI subtype.49,54 Less superior and middle frontal, temporal, striatal, and cerebellar volumes were associated with slower DTW-speed in non-amnestic MCI, while less occipital, parahippocampal, cuneus, and inferior frontal volumes were associated with DTW speed in amnestic MCI.49,54

Clinical gait abnormalities in pre-dementia and dementia

Neurological gait abnormalities (e.g. Parkinsonian gait) were more common in MCI than in cognitively healthy individuals,55 but results were inconclusive regarding whether they were different between amnestic and non-amnestic MCI.55,56 Individuals with MCR had a higher prevalence of non-neurological gait abnormalities (i.e. arthritis) than those without MCR.57 Neurological gait abnormalities were common in dementia than in cognitively healthy individuals—and in those with non-Alzheimer dementias (e.g. VaD or Lewy body dementia (LBD)) than those with AD.58

Quantitative gait measures as markers for MCI and dementia

Gait speed, usual pace walking and DTW.

Usual pace walking in individuals with dementia was slower than in MCI, and in those with MCI than cognitively healthy individuals.59 In subtypes, individuals with non-amnestic MCI had slower gait speed and faster gait speed decline than amnestic MCI.59,60 Interestingly, most studies found slower gait speed in those with non-AD dementia, including VaD and LBD, compared to those with AD.61,62 Finally, in individuals with MCI and dementia, DTW-speed was slower than usual pace gait speed, and compared to cognitively healthy individuals.63,64

Additional gait measures, MCI, and dementia.

Individuals with MCI had shorter stride length,65 smaller cadence,56,63 greater step, stance, and double support time during usual pace and DTW,66 compared to cognitively healthy individuals. Worse performance was observed among those with non-amnestic MCI than amnestic MCI.56,59 In one study, variability in stride length and stride width during usual pace walking were greater in non-amnestic MCI compared to amnestic MCI.59 In other studies, stride length variability and gait speed variability were greater in amnestic than non-amnestic MCI, and cognitively healthy older adults.56,67 Individuals with dementia showed poorer performance than MCI and cognitively healthy individuals on most gait measures59,68 and people with VaD had shorter stride length than those with AD.61

Gait as a predictor of cognitive decline, MCI, and dementia

Slow usual pace gait speed predicted decline in global cognition,69 memory,69–71 and non-memory related (executive function, visuospatial function, processing speed, and language) functions.69,70,72 Greater variability in space-related (i.e. stride length) and time-related (i.e. double support time, stance time) gait measures were also associated with decline in memory, executive function, and language.70,72 During DTW, slow speed and greater stride time variability were associated with decline in global cognition, but there was limited evidence on decline in specific cognitive functions.73,74 Additional studies showed that slow gait speed during usual and DTW conditions predicted cognitive impairment and MCI.73,75,76 Interestingly, those who converted to MCI had faster decline in usual pace gait speed than non-converters—which started to accelerate approximately 12 years before MCI diagnosis in men, and 6 years before MCI diagnosis in women.76

Neurological gait patterns (e.g. apraxia) were associated with increased risk of dementia and VaD.77 Slow gait speed and accelerated gait speed decline predicted risk of incident dementia and AD in cognitively healthy older adults, and in those with subjective cognitive impairment or MCI.78 Although there were some inconsistencies regarding whether gait is a stronger predictor of AD,79,80 than non-AD dementias a large-scale study (n = 3663; follow-up: 9 years) found that slow gait was associated with a two-fold increased risk for AD, and a 12-fold increased risk for VaD.78 DTW was a stronger predictor of dementia than usual pace gait speed in cognitively intact and MCI individuals.81,82 Finally, slower DTW speed, greater dual-task cost and greater swing time variability were associated with increased risk of dementia and VaD.73,82

Discussion

Most clinical and quantitative gait measures in aging are associated with several CSVD pathologies (see Figure 3)—and these pathologies were widely distributed across the brain. A better understanding of the interrelationship and shared pathophysiology of CSVD and adverse gait outcomes in aging will come from (1) examining comprehensive patterns in gait and neuroimaging manifestations of CSVD, (2) identifying the earliest signs of gait decline and CSVD from studies across the adult life span and longitudinal studies with extensive follow-up, and (3) using non-traditional CSVD markers (e.g. resting-state functional connectivity). Gait impairments in pre-dementia and dementia also differed as a function of whether they have a vascular- or AD-related cause. Yet, more longitudinal studies, and direct comparisons of gait, CSVD, and different forms of dementia are needed to speak the temporal interrelationships between them, and to guide future disease monitoring and development of interventions.

Figure 3.

Figure 3.

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The interrelationship between gait outcomes and cerebral small vessels disease, pre-dementia, and dementia discussed in this review. A connecting line between gait outcomes and cerebral small vessel disease and pre-dementia and dementia indicates that at least one article discussed observed a significant association.

Strong evidence also suggest that poor qualitative and quantitative gait performance are important markers for distinguishing between individuals with and without cognitive impairment, and for early identification of those at increased risk for cognitive decline, MCI, and dementia. Yet, additional studies need to determine the potential of gait in predicting different subtypes of MCI, and to validate gait measures for differential diagnosis (e.g. compared to neuroimaging and other biomarkers). Additional studies also need to determine if more regular monitoring of gait (e.g. wearable or in-home sensors versus clinical gait assessments) or more complex gait performance (e.g. DTW) can assist in identifying the earliest signs of gait, cognitive, and CSVD changes in aging. Taken together, this systematic review strongly confirms that gait impairment, CSVD, pre-dementia, and dementia often co-occur in aging—and recommends early, simultaneous, regular and longitudinal tracking of gait, CSVD and cognitive measures to support the development of novel, and potentially more successful pathways toward intervention.

It is important to recognize that this review (like other reviews) was subject to different biases with unknown effects, including publication biases. Most of the studies reviewed herein sampled (primarily white) Western older adults, and evidence suggests that the relationship between CSVD and cognitive impairment may be different in Eastern populations.52 The anatomical distribution of CSVD, for example, has been shown to be different in Eastern and Western populations—indicating pathophysiological differences with potential implications for the diagnosis and treatment of CSVD.83 Thus, future studies are needed to examine the interrelationship between gait, CSVD, pre-dementia and dementia in different racial/ethnic groups.

Supplementary Material

SupplementaryMaterial1
SupplementaryMateril2
SupplementaryMaterial3
SupplementaryMaterial4

Acknowledgements

The authors thank Daniel Schlehofer, Dachel Sanchez-Castellanos, and Bennett Kautz for their assistance in identifying articles.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: National Institute on Aging Grants (1R01AG062659-01A1; R01AG057548-01A1) played no role in data collection or interpretation.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Supplemental material

Supplemental material for this article is available online.

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