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Are Cognitive Subtypes Associated with Dual-Task Gait Performance in a Clinical Setting?

Abstract

Background:

Poor dual-task gait (walking while performing a cognitively demanding task) has been linked to progression to dementia in older adults with mild cognitive impairment (MCI). However, many of these findings come from research environments; gait performance across the cognitive spectrum has not previously been studied in a clinical setting.

Objective:

To examine whether patients from a memory clinic show differences in usual and dual-task gait speed and dual-task cost (DTC) based on cognitive diagnosis.

Methods:

Patients in the Aging Brain and Memory Clinic (London, ON) performed a usual gait walk and three dual-task gait walks: counting backwards by ones, naming animals, and counting backwards by seven (serial sevens) out loud. Patients were timed with a stopwatch over a six-meter path marked on the floor. One-way ANOVA was performed to evaluate associations between gait speed and DTC (%) across groups.

Results:

One hundred ninety-four patients with subjective cognitive impairment (SCI; n = 46), MCI (n = 77), or dementia (n = 71) were assessed. Performance in usual (p < 0.001) and dual-task gait speed (counting gait p < 0.001; naming animals p < 0.001; serial sevens p = 0.004) decreased across the spectrum of cognitive impairment. Patients with dementia had significantly higher DTC in both counting gait (p = 0.02) and naming animals (p = 0.04) conditions compared with patients with SCI and MCI, who had statistically similar DTC in all conditions.

Conclusion:

Dual-task gait performance significantly declines across the cognitive spectrum in a clinical setting. Dual-task gait testing may be used in conjunction with traditional assessments for diagnosing cognitive impairments.

INTRODUCTION

Dementia is one of the most devastating conditions faced by older adults, as it often causes loss of independence in daily activities [1]. There are currently over 46 million people living with dementia worldwide, and this number is expected to almost triple by 2050 [2]. Unfortunately, current drug treatments have not been effective in halting decline. The discovery of low-cost, feasible and effective methods for earlier detection and monitoring of disease symptoms is needed for successes of both pharmaceutical and non-pharmaceutical interventions [3].

Recently, studies have found that changes in mobility and gait in older adults may manifest even before cognitive symptoms of dementia are evident. Decrease in gait speed below what is expected for an individual’s age is one of the earliest physical symptoms of Alzheimer’s disease and can be indicative of later impairments [4]. For example, decreased lower limb function is associated with progression to dementia, and slow gait speed specifically increases short term risk of dementia by 94% [5]. Poor gait performance often co-exists with impairments in working memory and executive function in pre-dementia states such as mild cognitive impairment (MCI) [6]. This growing body of evidence suggests that changes in gait performance have clinical significance to determine the onset of cognitive impairments before they can be detected by cognitive tests.

Dual-task gait testing (walking and simultaneously performing a cognitively demanding task) has been recently investigated as a measure of cognitive load in older adults with and without cognitive impairments. The first investigation of this type showed that the inability to hold a conversation while walking was associated with future risk of falls [7]. The rationality behind this phenomenon is that the two tasks share brain networks and compete for a limited amount of brain resources [8]. Thus, the magnitude of changes in gait performance while dual-tasking could be used as an estimate of an individual’s cognitive capacity. Different types of cognitive tasks have been shown to rely on different memory domains; for example, category fluency tasks rely on semantic memory [9], while arithmetic tasks rely more on working memory and executive functions [10]. Many gait variables can be collected from this type of testing, of which gait speed is the most common and easiest to collect. Using a participant’s usual or preferred gait speed and their dual-task speed, we can calculate dual-task gait cost (DTC). DTC is the magnitude of gait slowing due to complexity of the added cognitive task, expressed as a percent of usual gait speed. Notably, DTC was found to predict incident dementia within a 6-year follow up in patients with MCI [11]. The decline in dual-task gait performance was shown to have a higher attributable risk of conversion from MCI to dementia, particularly Alzheimer’s disease, than the decline on traditional cognitive assessments [12].

While dual-task gait testing has been shown to correlate well with cognitive decline, there is limited evidence on its use, feasibility, and effectiveness in a clinical setting. Few studies have been published on dual-task gait testing using patients who were seeking treatment in a memory clinic, and in general, included small sample sizes [13, 14]. While these studies showed that dual-task testing may be sensitive to clinical diagnoses, there are still many gaps that need to be addressed, such as assessment of patients with subjective cognitive impairment (SCI), and the consideration of DTC.

The purpose of our study was to determine whether dual-task gait testing and the magnitude of DTC changes for gait speed, are associated with cognitive impairment diagnoses in a clinical setting using a handheld stopwatch [15]. We hypothesized that gait speed particularly during dual-task conditions will be different across the cognitive spectrum (SCI, MCI, and dementia). We also hypothesized that DTC would be higher across the spectrum of cognitive impairment.

METHODS

Study design and participants

Clinic-based cross-sectional study that included all consecutive older adults who were assessed for memory complaints at the Aging Brain and Memory Clinic at Parkwood Institute in London, Ontario, Canada between July 2015 and November 2017. In order to be included in the current study, participants had to 1) be over 50 years of age, 2) be able to safely ambulate six meters without an assistive device, and 3) be fluent in English and able to understand test instructions. To maximize inclusion and to ensure an accurate representation of the population seen in our clinics, no additional exclusion criteria were used. Participants were grouped into three categories based on final diagnosis: SCI, MCI, and dementia. Diagnosis was achieved using a consensus conference and established criteria (Petersen criteria for MCI [16] and the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition revised (DSM IV-TR) criteria for dementia [17]) after assessment performed by a geriatrician specialized in cognitive aging and dementia. Petersen criteria for MCI was ascertained by satisfying the following four criteria: 1) subjective cognitive complaints; 2) objective cognitive impairment in at least one of the following cognitive domains: memory, executive function, attention, and language; 3) preserved activities of daily living; confirmed by a geriatrician specialized in cognitive aging and dementia; and 4) absence of dementia using criteria from the DSM IV-TR. This study was approved by the Health Science Research Ethics Board at Western University and the Clinical Research Impact Committee at Lawson Health Research Institute, both in London, Ontario, Canada.

Demographic and clinical variables

All participant information and gait testing results were collected from patient charts. Demographic and clinical information collected included age, sex, falls history, years of education, medications, and comorbidities. Comorbidities were measured as total number of “yes” responses on a clinical comorbidities checklist. Cognitive variables include Mini-Mental State Examination (MMSE) score and the Montreal Cognitive Assessment (MoCA) score.

Gait testing procedure

All gait assessments were performed at the start of the clinical visit in a hallway outside the clinic room using a six-meter path. Six meters was chosen as it has been shown to be an appropriate length to be used for older adults without mobility impairments to ensure steady state walking is achieved [18]. Lines were marked on the floor to determine the stop and start points. One meter was added to each end of the pathway (as shown in Fig. 1) to ensure acceleration and deceleration phases were not recorded. Walking trials were timed using a handheld stopwatch and recorded to two decimal places. Speed was calculated by dividing the known distance by the time spent walking from start to end points marked on the floor, in each trial, for each participant, and then converted to cm/s. The assessment takes on average 5–8 minutes per patient and requires only one administrator.

Fig.1

Bird’s eye view of the gait testing path.

Bird’s eye view of the gait testing path.

All participants were asked to complete a total of four walk trials. The first trial was always the preferred or usual gait speed trial. For this trial, the participants were asked to walk at their normal, every-day walking speed. The next three trials were the dual-task walking trials, which comprised walking at usual speed while preforming an added cognitively demanding task. The order of dual-task trials was fully randomized. The three tasks used for this study were counting backwards by 1 s from 100 out loud, naming animals out loud, and counting backwards by 7 s from 100 out loud, which have been previously validated and are listed here in order of increasing cognitive demand [19–22]. Participants were instructed to equally prioritize both walking and the cognitive task to accurately replicate normal daily activities [8, 23]. Number of enumerations and errors per each dual-task trial was also recorded in the patient’s chart along with the speed for each trial. Participants were included in the analysis as long as they completed the usual gait speed trial and at least one of the dual-task trials. This gait protocol followed the Canadian guidelines for gait assessment published elsewhere [24].

Calculation of dual-task gait cost (DTC)

DTC was calculated for each dual-task trial using the appropriate velocities. DTC was calculated in Microsoft Excel 2010 using the following formula: DTC = [(usual gait speed – dual-task gait speed)/usual gait speed]×100. DTC is expressed as a percentage of slowing from the usual gait speed as a result of the added cognitive task.

Statistical analyses

Means and standard deviations or frequencies and percentages were used to describe clinical and demographic characteristics of the three groups (SCI, MCI, and dementia), as appropriate. Differences between groups were examined using one-way ANOVA for means and chi-square tests for frequencies. All data was checked for normal distribution using the Kolmogorov-Smirnov test and homogeneity of variance for ANOVAs using Levene’s test. Statistical power for gait speed comparisons among all three groups in our study was above 80%. One-way ANOVA was used to compare gait velocities and DTC among groups. Both unadjusted and adjusted models were created using the following covariates: age, sex, years of education, total number of medications, total number of comorbidities, and number of errors made in the cognitive dual-task. Post-hoc testing of gait velocities and DTC was done for both models using the Bonferroni correction to adjust for multiple comparisons. Effect size was calculated as η2 (Eta squared) from the one-way ANOVA. Statistical significance was set at p < 0.05. Statistical analyses were conducted using SPSS, version 23 (IBM Corporation).

RESULTS

Participant characteristics

One hundred ninety-four patients (72±10.8 years; 52% women) met inclusion criteria. Characteristics of the study sample stratified by cognitive diagnosis are presented in Table 1. The groups increased significantly in age across the spectrum of cognitive impairment. As expected, MMSE and MoCA scores dropped significantly along with cognitive impairment classifications. Participants with dementia were significantly older, had fewer years of education and had more falls in the previous 12 months than participants in both the SCI and MCI groups. Participants with MCI were significantly older than participants with SCI, but they had similar years of education and 12-month fall histories.

Table 1

Demographic and clinical characteristics of study participants stratified by cognitive diagnosis

VariableTotal Cohort (n = 194)SCI (n = 46)MCI (n = 77)Dementia (n = 71)p
Age (mean, SD)72.1 (10.8)65.2 (11.0)71.2 (10.4)77.6 (8.0)<0.001
Female (n, %)101 (52%)27 (59%)39 (51%)35 (49%)0.58
No. of comorbidities (mean, SD)6.4 (3.6)6.1 (3.8)7.0 (3.4)6.0 (3.6)0.16
No. of medications (mean, SD)8.2 (4.4)7.3 (4.9)8.2 (4.0)8.7 (4.4)0.28
MMSE score (mean, SD)25.7 (4.3)29.0 (1.4)26.8 (2.7)22.5 (4.9)<0.001
MoCA score (mean, SD)21.4 (5.2)27.0 (2.2)21.3 (3.8)17.2 (4.4)<0.001
Years of education (mean, SD)12.8 (3.7)14.0 (3.4)12.6 (3.7)12.2 (3.7)0.04
Falls in 3 categories (n, %)0.04
  No falls145 (75%)37 (80%)62 (81%)46 (65%)
  1 fall29 (15%)8 (17%)6 (8%)15 (21%)
  2+ falls20 (10%)1 (2%)9 (12%)10 (14%)

Bolded values are significant at p < 0.05. Falls history as reported in the last 12 months. SCI, subjective cognitive impairment; MCI, mild cognitive impairment; MMSE, Mini-Mental State Examination; MoCA, Montreal Cognitive Assessment.

Group differences in gait speed

Results of the adjusted and unadjusted models comparing gait velocities between cognitive diagnoses are shown in Table 2. Within each diagnosis group, gait speed decreased from usual gait to dual-tasking, showing that an added cognitive task does cause participants in all groups to slow down. Gait speed also decreased in each group as dual-task difficulty increased. For each walking condition, gait speed was significantly different between groups, decreasing with increasing cognitive impairment (usual gait p < 0.001; counting gait p < 0.001; naming animals p < 0.001; serial sevens p = 0.004). All associations remained significant, except for the serial sevens condition, after adjusting for age, sex, years of education, number of medications, and number of comorbidities (usual gait p = 0.040; counting gait p < 0.001; naming animals p = 0.001; serial sevens p = 0.227). The counting and naming animals gait conditions also maintained significance after adjusting for age, sex, and number of errors made in the cognitive dual-task (counting gait p < 0.001; naming animals p < 0.001). The serial sevens gait condition was again not significant after this adjustment.

Table 2

Association between cognitive diagnosis and gait speed for each walking test condition

Gait Speed (cm/s)SCI (n = 46)MCI (n = 77)Dementia (n = 71)p Model 1 (Unadjusted)p Model 2 (Adjusted)p Model 3 (Adjusted)
Usual gait (mean, SD)115.31 (25.6)104.24 (27.1)90.25 (23.0)<0.0010.040n/a
Counting gait (mean, SD)93.71 (25.6)86.96 (27.4)67.33 (22.4)<0.001<0.001<0.001
Naming animals (mean, SD)86.41 (21.9)77.54 (24.6)61.64 (21.4)<0.0010.001<0.001
Serial sevens (mean, SD)66.24 (21.0)64.59 (20.8)53.38 (18.0)0.0040.2270.107

Bolded values are significant at p < 0.05. Model 1: unadjusted. Model 2: adjusted for age, sex, years of education, number of medications, and number of comorbidities. Model 3: adjusted for age, sex, and number of errors made in the cognitive dual-task. SCI, subjective cognitive impairment; MCI, mild cognitive impairment.

Results of the post-hoc testing are shown in Fig. 2. In all four walking conditions, patients with dementia had significantly slower gait speed than those with SCI and MCI, but SCI and MCI groups were not significantly different. These associations also maintained significance after adjustments for demographic covariates (age, sex, years of education, number of medications, and number of comorbidities).

Fig.2

Results of post-hoc analysis of mean gait speed for each walking test condition. Significant differences (p < 0.05) are marked with an asterisk.

Results of post-hoc analysis of mean gait speed for each walking test condition. Significant differences (p < 0.05) are marked with an asterisk.

Group differences in DTC

Table 3 reports the results of the adjusted and unadjusted models comparing DTC between cognitive diagnoses. DTC showed an ordered pattern of increase as cognitive impairment increased for both counting gait (p = 0.023) and naming animals (p = 0.037) conditions. However, DTC for serial sevens condition was comparable among groups (p = 0.912). These associations also maintained significance after adjustments for age, sex, years of education, number of medications, and number of comorbidities (counting gait p = 0.001; naming animals p = 0.015). The counting and naming animals gait conditions also maintained significance after adjusting for age, sex, and number of errors made in the cognitive dual-task (counting gait p = 0.015; naming animals p = 0.005).

Table 3

Association between cognitive diagnosis and dual-task cost (DTC) for each walking test condition

DTC (%)SCI (n = 46)MCI (n = 77)Dementia (n = 71)p Model 1 (Unadjusted)p Model 2 (Adjusted)p Model 3 (Adjusted)
Counting gait (mean, SD)17.99 (16.6)17.34 (18.0)25.32 (18.3)0.02<0.0010.015
Naming animals (mean, SD)23.98 (15.0)25.89 (17.4)31.74 (16.9)0.040.0150.005
Serial sevens (mean, SD)41.97 (17.6)40.85 (16.8)40.48 (15.7)0.920.920.848

Bolded values are significant at p < 0.05. Model 1: unadjusted. Model 2: adjusted for age, sex, years of education, number of medications, and number of comorbidities. Model 3: adjusted for age, sex, and number of errors made in the cognitive dual-task. SCI, subjective cognitive impairment; MCI, mild cognitive impairment.

Post-hoc testing revealed that in the counting gait condition, DTC was significantly higher in patients with dementia than in patients with MCI (p = 0.020). SCI and MCI groups were not significantly different in the counting gait condition. In the naming animals condition, patients with dementia had a significantly higher DTC than patients with SCI (p = 0.044), but not compared to those with MCI. Again, SCI and MCI groups had statistically comparable DTCs. These associations were all unchanged after adjustments for age, sex, years of education, number of medications, and number of comorbidities.

Effect size

Overall, all gait velocity conditions showed at least medium effect size. Usual gait velocity (η2 = 0.129) and serial sevens velocity (η2 = 0.073) showed medium effect size, while counting gait velocity (η2 = 0.157) and naming animals velocity (η2 = 0.157) showed large effect size. However, dual-task cost had small effect size for all three conditions (counting gait, η2 = 0.0415; naming animals, η2 = 0.0364; serial sevens, η2 = 0.0013).

DISCUSSION

Our results show that gait performance declined across the cognitive spectrum in patients from a memory clinic, confirming in a clinical setting the strong relationship between cognition and gait performance previously described in research samples [25]. Specifically, a clinical meaningful slowing of gait speed and increase in dual-task cost was found in a direct relationship with the increase of cognitive impairment ranging from normal cognition to pre-dementia and dementia states.

All groups had a mean usual gait speed above the slow gait cut-off of 80 cm/s [26], indicating our sample was comprised of mostly older adults with moderate to high level of physical function [18, 27]. Nevertheless, gait speed decreased across the cognitive spectrum from 115 cm/s in SCI, to 104 cm/s in MCI, to 90 cm/s in those with dementia, a between groups change that is over the 10 cm/s difference considered clinically meaningful [28]. To note, using just a single cut off of 80 cm/s would have been insufficient in detecting differences across groups.

Dual-task cost, an accepted marker of cognitive-motor interface [29], was worst in patients with dementia when compared with MCI and SCI, but interestingly, the SCI group had DTCs that were as high as the MCI groups. In other words, the SCI group scored within normal range [30, 31] on cognitive screening tools, but they had a statistically similar DTC to the MCI group. A possible explanation of this finding is that DTC is capturing subtleties in the cognitive motor-interface that global cognitive testing, such as the MoCA, is not able to differentiate between SCI and MCI. This finding is also aligned with the fact that patients with both SCI and MCI are at higher risk of further cognitive decline [32, 33] and that DTC can help to identify patients at risk to progress to dementia [11]. These results together show that dual-task gait testing, in conjunction with cognitive testing, may be useful to appraise the spectrum of cognitive impairments. Indeed, the effect sizes seen for dual-task gait velocity were in the medium-large range supporting their potential use to discriminate cognitive conditions in the clinical encounter.

While the neural mechanisms underlying dual-task gait performance are not yet fully understood, new evidence supports that both cognitive processes and regulation of walking rely on similar brain networks which are involved in executive function and working memory control [34, 35]. This concept is further supported by studies that show damage and/or atrophy in prefrontal and hippocampal regions leads to impairments in both cognitive tests and gait performance [36–39]. Imaging studies have shown higher functional MRI activation in prefrontal regions when imagining “walking and talking” versus “walking” alone [40]. Our results are aligned with this theory, as those with further cognitive impairment, and presumably further neurodegeneration or brain vascular changes, had poorer performance on the dual-task tests. Future research with advanced neuroimaging techniques would be needed to confirm this hypothesis.

Our study also shows the feasibility of performing dual-task gait testing into the clinical setting. A stopwatch and a hallway with at least 8 meters of free unobstructed length are the only instruments needed, which could be available even in smaller clinics. Our testing gait protocol [24, 35] of using a stopwatch and a measured path is much more affordable and data is much simpler to collect than when using an electronic walkway, which makes it more suitable for non-specialized clinics. This gait protocol can be used by clinicians to identify patients at risk of accelerated cognitive decline who may require further testing or more frequent follow-up visits. The use of these three dual-task cognitive tasks together has been previously recommended, as they are quick to administer even when done in sequence and together are better at assessing different memory and cognitive domains where impairments may be present [24, 35].

Our study is not free of limitations. The cross-sectional nature of our design, which included only one clinic visit, limits the investigation of long-term predictability of cognitive decline using gait testing. It was recently shown that one single visit was not enough to detect high-risk individuals using dual-task gait testing [12], so a follow-up study using multiple time points for comparison is warranted. We included all subtypes of MCI and dementia into each of the respective diagnosis groups, which introduces a level of heterogeneity to our results, as these various subtypes may present different cognitive symptoms. Our study also did not include a healthy control group, so we could not compare dual-task performance of those with subjective and/or objective impairments with performance seen as a result of healthy aging. Also, this study was performed at only one clinic site in London, Ontario, Canada, which may limit its generalizability to other clinics.

Strengths of our study include the demonstration of feasibility of dual-task gait testing in a busy clinical setting and the use of validated dual-tasks which are currently being used in other large cohort studies [41], which allows for future comparison of results across studies. While using limited exclusion criteria allowed us to collect data from a wide sample that best represented the clinical population, this also allows the potential for confounding effects on results. However, we performed the adjusted analysis to try to limit these possible effects, and our results remained mostly significant after these adjustments.

In conclusion, our study demonstrated that usual gait speed and dual-task gait speed are significantly different in individuals subjectively and objectively considered at pre-dementia stages from those already diagnosed with dementia, although individuals at pre-dementia stages had comparable gait performances. This shows that gait assessment can be a useful complementary test to detect risks of progressive cognitive impairment in older adults at pre-dementia stages in clinical settings [42]. Further research is needed to verify the underlying cause of this decrease in dual-task performance, particularly in those with subjective cognitive impairment, including neuroimaging studies that may determine which networks and brain regions are involved in regulation of these processes. Also, studies that consist of multiple follow-up visits could better describe the value of dual-task gait testing in predicting rapid cognitive decline.

ACKNOWLEDGMENTS

Our gratitude goes to Ana Bianca Popa, former undergraduate student and laboratory member, who worked in creating and completing the database in early stages of this project. Dr. Montero-Odasso’s program in “Gait and Brain Health” is supported by grants from the Canadian Institute of Health and Research (CIHR), the Ontario Ministry of Research and Innovation, The Ontario Neurodegenerative Diseases Research Initiative (ONDRI), the Canadian Consortium on Neurodegeneration in Aging (CCNA), and the Department of Medicine Program of Experimental Medicine (POEM) Research Award, University of Western Ontario. He is the first recipient of the Schulich Clinician-Scientist Award. Stephanie Cullen is a Master’s candidate in Kinesiology under Dr. Montero-Odasso’s supervision and funded by the Gait and Brain Lab, Parkwood Institute, University of Western Ontario and Lawson Health Research Institute through the Early Research Award of Ontario. She is the recipient of the 2018-2019 Master’s student scholarship funded by the Alzheimer’s Society of London and Middlesex.

Authors’ disclosures available online (https://www.j-alz.com/manuscript-disclosures/18-1196r2).

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