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Dual-TaskComplexityAffectsGaitinPeopleWithMildCognitiveImpairment:TheInterplayBetweenGaitVariability,DualTasking,andRiskofFalls

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ORIGINAL ARTICLE

Dual-Task Complexity Affects Gait in People With MildCognitive Impairment: The Interplay Between GaitVariability, Dual Tasking, and Risk of FallsManuel Montero-Odasso, MD, PhD, Susan W. Muir, PhD, Mark Speechley, PhD

ABSTRACT. Montero-Odasso M, Muir SW, Speechley M.Dual-task complexity affects gait in people with mild cognitiveimpairment: the interplay between gait variability, dual tasking,and risk of falls. Arch Phys Med Rehabil 2012;93:293-9.

Objective: To determine the effect of 2 different dual tasks ongait variability in people with mild cognitive impairment(MCI) compared with control subjects.

Design: Cross-sectional study.Setting: Memory clinic at a university hospital.Participants: Older adults with MCI (n�43) and cognitively

normal control subjects (n�25) from the community. Gait wasassessed under single (usual walking) and dual tasking (naminganimals and subtracting serial 7s), using an electronic walkway.

Interventions: Not applicable.Main Outcome Measures: The dependent variable was the

coefficient of variation of gait variability, a marker of gaitstability and an established risk factor for falls. Two-wayrepeated-measures analysis of variance was used to examinemain effects (group, task) and their interaction.

Results: A significant difference was found within and be-tween groups (P�.016) of increasing gait variability as dual-task complexity increased. Gait velocity decreased within groupsas dual-task complexity increased. The magnitude of increasedgait variability across tasks was greater for the MCI group(2.68%– 9.84%) than for the control group (1.86%–3.74%), show-ing a significant between-group difference (P�.041).

Conclusions: Dual-task load significantly increased gait vari-ability in the MCI group compared with the control group, aneffect that was larger than the changes in gait velocity. Themagnitude of this impairment on gait stability was related tothe complexity of the dual task applied. Our findings help toexplain the high risk of falls recently described in older adultswith MCI, and may help in the identification of fall risk incognitively impaired persons.

Key Words: Gait; Rehabilitation; Cognition; Attention;Aged.

© 2012 by the American Congress of RehabilitationMedicine

FALL RISK IS DOUBLED among older adults with cog-nitive impairment, but the mechanisms of the increased fall

risk are not completely understood.1,2 Mild cognitive impair-ment (MCI) is considered a transitional phase between normalaging and dementia.3,4 People with MCI represent a highlyvulnerable population, as they face an elevated risk for con-version to dementia. Interestingly, it has been recently de-scribed that they are also at an increased risk for falls andmobility decline.5,6

Walking has long been considered primarily an automaticmotor task, but an emerging body of evidence suggests that thisview is simplistic, and by contrast, cognitive function plays akey role even in the regulation of routine walking.7-9 Theimportance of this cognitive control is most easily demon-strated in older people with memory problems and dementia.Since the seminal “stops walking while talking” study,10 whichdemonstrated that the inability to maintain a conversation whilewalking is a marker for future falls, observing people walkingwhile they perform a secondary task, the “dual-task paradigm,”has been used to assess the interaction between cognition, gait,and the risk of falling. During dual tasking, the subject per-forms an attention-demanding task while walking to assess forany modifications, compared with the reference task, on eitherthe cognitive or the walking subtasks.11 The underlying hy-pothesis is that 2 simultaneously performed tasks interfere andcompete for brain cortical resources.11,12-14 The change in anindividual’s gait performance from a single task to a dual taskis known as the “dual-task cost.” The magnitude of thesedual-task costs reveals the insufficiency of the cortical controlto regulate walking and has been associated with an increasedfall risk.15,16 Dual tasking is also clinically relevant becausemost activities of daily living involve the simultaneous perfor-mance of 2 or more cognitive and motor tasks, making itrepresentative of real-life situations where falls are likely tooccur.9

Gait is a complex motor behavior with many measurablefacets beside gait velocity,17 and with the advent of equipmentto precisely measure several quantitative aspects of walking,the variability of the stride time is a growing research field thatprovides an interesting window for the study of the cognitivecontrol of gait and risk of falls.18 For instance, low stride-to-stride variability reflects automatic processes that require min-

From the Department of Medicine, Division of Geriatric Medicine, ParkwoodHospital, University of Western Ontario, London (Montero-Odasso, Muir); Gait andBrain Lab, Lawson Health Research Institute, London (Montero-Odasso); and De-partment of Epidemiology & Biostatistics, University of Western Ontario, London(Speechley), ON, Canada.

Supported by operating grants from the Drummond Foundation, Montréal, thePhysician Services Incorporated Foundation, Toronto and the Canadian Institutes ofHealth Research.

No commercial party having a direct financial interest in the results of the researchsupporting this article has or will confer a benefit on the authors or on any organi-zation with which the authors are associated.

Reprint requests to Manuel Montero-Odasso, MD, PhD, Parkwood Hospital, Di-vision of Geriatrics, 801 Commissioners Rd E, Room 280, London, Ontario, CanadaN6A 5A5, e-mail: mmontero@uwo.ca.

0003-9993/12/9302-00564$36.00/0doi:10.1016/j.apmr.2011.08.026

List of Abbreviations

a-MCI amnestic mild cognitive impairmentANOVA analysis of varianceCDR Clinical Dementia Rating ScaleCoV coefficient of variationMCI mild cognitive impairmentna-MCI nonamnestic mild cognitive impairmentMMSE Mini-Mental State ExaminationMoCA Montreal Cognitive Assessment

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imal attention and is associated with efficient gait control andgait safety.19 By contrast, high stride time variability has beenassociated with executive and attentional deficits, Parkinson’sdisease, and Alzheimer’s disease.20-23 Additionally, high stridetime variability has been shown to predict future falls in com-munity-dwelling older persons even when gait velocity failedto distinguish between those who fell and those who had not.24

Gait variability characteristics and how these are affected bydual-task challenges have not been evaluated in older adultswith MCI. Therefore, the aim of this study was to characterizethe effect of 2 different dual-task challenges on gait variabilityand to determine whether an increase in the secondary taskcomplexity would yield a predictable cost in gait performancein people with MCI. We tested the following hypotheses: (1)gait performance is affected more by dual-task challenges inpeople with MCI than in cognitively normal control subjects;(2) a worsening gait performance in people with MCI (ie,decreased gait velocity and increased gait variability) will begreater while doing more complex mental task such as sub-tracting serials 7s, than when simply naming words; and (3) theincrease in gait variability is greater than the reduction in gaitvelocity.

METHODS

Study ParticipantsA convenience sample of participants with MCI and cogni-

tively normal control subjects were recruited. Participants withnewly diagnosed MCI were recruited from the “Aging Brainand Memory Clinic” at Parkwood Hospital. The identificationof MCI was based on the most recent consensus criteria4 thatincluded the presence of subjective memory complaints fromthe patient and family, objective memory impairment (assessedusing the Mini-Mental State Examination [MMSE] and Mon-treal Cognitive Assessment [MoCA]), preserved general intel-lectual function (assessed clinically), absence of significantfunctional impairment, and absence of clinical dementia.4 Ad-ditionally, participants needed to score 0.5 on the ClinicalDementia Rating Scale (CDR). Controls were recruited bynewspaper advertisement and from a community-based fitnessprogram for older adults.

Inclusion criteria for the MCI group were a recent diagnosisof MCI, aged 65 years and older, and able to walk indepen-dently without a gait aid (eg, cane or walker). In the controlgroup, inclusion criteria were aged 65 years and older, anabsence of subjective cognitive complaints, normal objectivecognitive testing, absence of functional impairment, and able towalk independently without a gait aid. Exclusion criteria forboth groups included the inability to understand English, par-kinsonism or any neurologic disorder with residual motor def-icits (eg, stroke, epilepsy), musculoskeletal disorders or a his-tory of knee or hip replacement surgery that affected gaitperformance, use of psychotropic medications that affectedmotor performance (eg, neuroleptics, benzodiazepines), or ac-tive major depression. During assessment, a formal clinicalexamination was done to evaluate the effect of diseases andcomorbidities that might affect gait performance. The projectwas approved by the University of Western Ontario HealthSciences Research Ethics Board, and all participants providedinformed consent.

Medical and Cognitive AssessmentsSociodemographic characteristics, comorbidities, a history

of falls in the past 6 months, fear of falling, self-reportedphysical activity level, functionality on activities of daily liv-

ing, and medications were recorded. Basic and instrumentalactivities of daily living were evaluated using the Lawton-Brody25 scale, to ensure absence of functional impairment.Objective cognitive status of all participants was assessed usingthe MMSE (score, 0–30)26 and the MoCA (score, 0–30; higherscore indicating better performance).27,28 A CDR was per-formed in all participants with MCI. Objective cognitive im-pairment in our MCI participants was operationalized as anormal MMSE score (�26) combined with a low MoCA score(�26); this pattern has been previously validated for MCIidentification.27,29 Finally, we subcategorized our participantswith MCI as amnestic MCI (a-MCI) and nonamnestic MCI(na-MCI) by using a simple and valid approach29 for descrip-tive purposes only.

Quantitative Gait AssessmentGait performance under single- and dual-task challenges was

assessed using an electronic walkway system (GAITRite Sys-tema) that is 600cm in length and 64cm in width. As partici-pants walk along the mat, imbedded sensors are activated bythe pressure of their feet and deactivated when the pressure isreleased. A computer processed the footsteps, providing datafor both spatial and temporal parameters. Start and end pointswere marked on the floor with tape 1m from either end of themat to avoid the recording of acceleration and decelerationphases. Participants performed 1 practice trial walking on themat to familiarize themselves with the protocol. Gait velocity(cm/s), stride time (ms), and stride time variability (percentageof coefficient of variation [%CoV]), the principal gait measuresof interest, were measured during the single-task and dual-tasktrials. The single-task trial consisted of walking the length ofthe mat at a self-selected usual pace. For the dual-task trials,participants walked the length of the mat while subtractingserial 7s from 100 aloud or while naming animals aloud. These2 different dual-task conditions were selected based on previ-ous research which demonstrated that subtractions dependmore on working memory and attention, while naming animalsout loud is more related to verbal fluency, which relies onsemantic memory.30,31

To balance and minimize the effects of learning and fatigue,the order of the single and dual tasks was randomized. Whileperforming the dual-task trials, there was no instruction toprioritize the gait or cognitive task. Allowing both gait andcognitive tasks to vary has previously been shown to provide amore natural representation of daily living activities of olderindividuals.8,32 Reliability has been previously established byour group for the use of this gait assessment protocol in peoplewith MCI.33

Data AnalysisDemographic and medical characteristics were summarized

using either means and SDs, or frequencies and percentages, asappropriate. Comparisons between groups were made usingunpaired t tests or Mann-Whitney tests as deemed appropriate,with adjustment made for multiple comparisons using the Bon-ferroni correction. The CoV for stride time was used to quan-tify gait variability under each testing condition. The CoV wascalculated as follows:

COVst ��� SDst

meanst�� 100

where CoVst is the CoV of stride time, SDst is the SD of stridetime, and meanst is the mean stride time.

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A 2-way repeated-measures analysis of variance (ANOVA)was performed to evaluate the effect of cognitive status (group)across the increasing complexity of gait tasks (condition) andtheir interaction (group � condition). If the overall F test wassignificant, post hoc testing was performed (Tukey procedure)to identify which pair-wise comparisons between and withingroups were significantly different from one another. A sensi-tivity analysis of the ANOVA analysis adjusted for age andhistory of falls was performed. The level of statistical signifi-cance was set at P�.05 (2-sided), and the statistical analyseswere conducted using SAS software version 8.2.b

RESULTSForty-eight people with a diagnosis of MCI were eligible for

this study, and 43 met the study inclusion criteria. Five peoplewith an MCI diagnosis were excluded for the following rea-sons: MoCA greater than 26 (n�3), MMSE less than 26 (n�1),and English language difficulties (n�1). Twenty-nine peoplewere assessed for the cognitively normal group, and 25 peoplemet the study inclusion criteria, with 4 people excluded for ageless than 65 years (n�1), MMSE less than 26 (n�1), andMoCA less than 26 (n�2). All participants were fully func-tional in their basic and instrumental activities of daily living.Demographic and clinical characteristics are presented in table1. As expected, the MCI group differed from the control groupon cognitive status. The MCI group was also older, more oftenhad a positive fall history, and was more likely to be sedentary.The level of physical activity and age was highly correlated.Among the MCI group, 31 (72%) met the criteria for a-MCI, 11(26%) for na-MCI, and 1 participant did not have data availableto allow group assignment.

Results from the repeated-measures ANOVA are presentedin table 2. Statistically significant differences in the meanvalues were found within each cognitive group across thedifferent walking test conditions for gait velocity (P�.0001),stride time (P�.0008), and gait variability (P�.0013). Differ-

ences in the mean values between groups on each walking testcondition were also found for gait velocity (P�.0001), stridetime (P�.0001), and gait variability (P�.0001). The magni-tude of increased gait variability across tasks was greater forthe MCI (2.68%–9.84%) than the control group (1.86%–3.74%), showing a between-group significant difference(P�.041). The test for interaction between cognitive status andthe walking test condition for gait velocity was not statisticallysignificant (P�.23) (fig 1). A statistically significant interactioneffect was found, though, between cognitive status and walkingtest condition in favor of the MCI group for gait variability,demonstrating that gait variability increased as complexity ofthe gait task increased (fig 2). A sensitivity analysis to evaluatethe robustness of the main analyses was performed, adjustingfor age and history of falls; the directions and magnitude ofassociations (a difference �10%) of the results were main-tained. Figure 3A demonstrates the nonsignificant interactioneffect of dual tasking on gait velocity; in contrast, this effectwas evident and significant on gait variability (fig 3B). Finally,the effect of a complex dual-task challenge (serial 7s subtrac-tion) on gait variability can be seen in figure 4 when comparingvariability in stride time between a control participant and aparticipant with MCI.

DISCUSSIONThis study has demonstrated that gait performance differs

between people with MCI and people with normal cognition,particularly under dual tasking. Both groups showed a decreasein gait velocity and an increase in gait variability with thedifferent dual-task challenges. However, the effect of the dual-task load on the regulation of stride-to-stride time, assessed asgait variability, was significantly greater in those with MCI.This effect on gait variability was much larger than the effectseen on gait velocity.

The dual-task cost for gait velocity found in our study isconsistent with previous research among patient populations

Table 1: Demographic and Clinical Characteristics of Study Participants Stratified by Cognitive Status Group

Variable Controls (n�25) MCI (n�43) P

Age (y) 71.5�4.1 75.1�6.3 .013*MMSE 29.5�0.6 27.8�1.6 �.0001*MoCA 28.2�1.5 23.0�2.3 �.0001*Sex (female) 22 (88) 23 (54) .012*Body mass index (kg/m2) 26.8�4.1 25.8�3.8 .31Had fall in past 6 months 5 (20) 23 (54) .01*Fear of falling 5 (20) 11 (26) .77Years of education 13.0�3.2 12.7�3.3 .72No. of current medications† 4.1�3.4 5.8�3.6 .24Comorbidities

Hypertension 9 (36) 24 (56) .14Diabetes 2 (8) 4 (9) 1.00Stroke or transient ischemic attack 0 (0) 4 (9) .29Parkinson’s disease 0 (0) 1 (2) 1.00Lung disease 1 (4) 4 (9) .64Myocardial infarction 0 (0) 6 (15) .08Congestive heart failure 0 (0) 2 (5) .52

Level of physical activityVigorous 17 (68) 15 (35) .0046*Moderate 8 (32) 17 (40)Sedentary 0 (0) 10 (23)

NOTE. Values are mean � SD, n (%), or as otherwise indicated.*Testing between groups was conducted using the Bonferroni correction for multiple comparisons to maintain statistically significantdifference at P�.05.†Only data from 42 MCI subjects were available to calculate current number of prescription medications.

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with MCI and Alzheimer’s disease2,34,35; however, this is 1 ofthe first studies to assess and compare the effect of 2 differenttypes of dual tasks and to assess their effect on gait variabilityin people with MCI.

Previously, it has been demonstrated that motor dysfunctionis present in older adults who will eventually develop cognitivedecline and dementia.36-38 This motor dysfunction, evaluatedas gait velocity, may have its onset up to 12 years before MCIconversion.36 Therefore, the presence of a slower gait in ourMCI group is consistent with these findings. Interestingly, bothgroups in our study had a normal gait velocity (�1m/s) underthe single-task test condition. However, and in line with ourfirst hypothesis, the type of dual task applied showed a differ-ential effect on the gait performance, principally in the MCIgroup. A more complex cognitive task with a profound corticaldemand, such as subtracting serial 7s from 100, produced agreater dual-task detrimental effect on gait performance whencompared with a less demanding task such as naming animals,as shown in figure 3. The significant and graded decline on gaitvelocity while engaging in a more demanding dual-task chal-

lenge in our study is in agreement with a previous study39,40 ofphysically frail older adults. In the same vein, the presentfindings are consistent with a recent study41 evaluating theeffect of different types of dual-task challenges in healthy olderadults. In that study, 2 different types of dual tasks, phonememonitoring and serial subtractions, had different effects on gaitperformance. The authors postulated that these 2 types of dualtasks might tax distinct cognitive resources since the nature ofthe dual task also differs: attentional demands of phonememonitoring are essentially uniform over time, when comparedwith the increased attention needed while doing serial subtrac-tions.

In the present study, gait variability was differentiallyaffected by the type of dual task performed, more signifi-cantly in people with MCI (see fig 3), demonstrating thatthis gait-derived parameter is a very sensitive quantitativemeasure of the concurrent task. These results underscore theobservation that the effects on gait are related to the nature

Table 2: Results of 2-Way ANOVA on Gait Parameters by Cognitive Status Group and Walking Test Condition

Walking Test Condition

Gait Variable Group Usual Gait Naming Animals Serial 7sRepeated-Measures 2-Way

ANOVA* (P)

Gait Velocity (cm/s) Control (n�25) 134.00�21.70 115.88�29.26 106.25�28.43 Group �.0001MCI (n�43) 110.98�20.67 89.26�25.25 74.79�24.40 Condition �.0001

Interaction .23

Stride time (ms) Control (n�25) 1035.74�66.54 1153.42�144.77 1219.04�230.54 Group .0008MCI (n�43) 1120.88�94.72 1390.11�361.56 1649.70�658.40 Condition �.0001

Interaction .0165

Gait variability (% CoV) Control (n�24) 1.86�0.66 3.59�2.95 3.74�3.31 Group .0013MCI (n�43) 2.68�1.31 7.16�7.76 9.84�10.13 Condition �.0001

Interaction .0419

NOTE. Values are mean � SD or as otherwise indicated.Abbreviation: % CoV, percent coefficient of variation in stride time.*P value reported for Main Effect of Group, Condition, and the interaction of Group x Condition with statistical significance set at P�.05.

Fig 1. Mean gait velocity, with SDs, in participants with MCI (n�43)and normal cognition (n�25) while performing a usual walking taskand 2 dual-task walking conditions.

Fig 2. Mean gait variability in older adults with MCI (n�43) andnormal cognition (n�25) while performing a usual walking task and2 dual-task walking conditions. Abbreviation: % CoV, percent coef-ficient of variation in stride time.

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of the dual task, the aspect of the gait under study, and thecognitive reserve of the subject.

Our findings have novel research and clinical implications.From a research perspective, we found that gait variability ismore sensitive to dual-tasking load than gait velocity, whichmay help to refine the measures used in future research studiesfor fall risk in cognitively impaired populations. Additionally,we showed that the type of dual tasking with different cognitive

loads might generate differential decrements in gait perfor-mance. This is particularly important for the comparison ofresults across studies, as different tasks have the potential toidentify different populations of at-risk individuals.

A potential clinical implication of our findings relates to theidentification of possible fall risk and mobility dysfunction inpeople with MCI. Gait variability is an established marker offall risk, and it has been prospectively proven to predict falls

Fig 3. Interaction between cognitive status and 3 different walking conditions for gait velocity (A) and gait variability (B). Abbreviation: %CoV, percent coefficient of variation in stride time.

Fig 4. Effect of complex dual-task load (serials subtractions by 7s) in stride time in a participant with normal cognition (A) compared witha participant with MCI (B).

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even when gait velocity failed to identify fallers in community-dwelling older adults. Additionally, the recent advent of por-table gait mats allows for easy quantification for gait variabilityin clinical settings, facilitating fall risk identification in olderpeople who have an otherwise unremarkable gait performance.Recent recommendations concerning fall prevention and inter-ventions to decrease falls among cognitively impaired olderadults advocate to screen/test people with MCI according to theevidence available for cognitively intact, community-dwellingolder adults.42 However, we have found that changes in gaitbehavior under dual tasking are a clear marker of fall risk inolder adults with MCI. This suggests that people with MCI,when they are exposed to a cognitive challenge while walking,have an increased risk of falls. Interestingly, gait velocity undersingle-task condition was within normal limits in both groups(�1m/s), and only dual-task testing revealed “abnormal slow-ing” (�1 m/s) and gait instability (high variability) in the MCIgroup. Therefore, dual-task assessment may be a more sensi-tive measure of gait impairment than single-task assessment,thereby providing a means to identify cognitively impairedpersons at risk of falls. A future prospective study is needed totest this hypothesis.

Study LimitationsSome limitations of this study should be noted. In the data

analysis, we were not able to adjust for all potential confound-ers that may affect gait and cognition; however, our findingswere maintained after controlling for age and a history of falls.The limited sample size precluded our ability to further exploreassociations between MCI subtypes or impairment in specificcognitive domains, such as executive and attentional function,with the use of the dual-task cost approach.43 These limitationsdo not detract or alter the importance of our findings, whichshowed a differential effect of dual-task challenges in gaitvariability in people with MCI when compared with cogni-tively normal older adults.

CONCLUSIONSDual-task load impairs and increases gait variability in peo-

ple with MCI, an effect that was larger than the effect seen ongait velocity. These findings also suggest that cognitive controlof gait is differentially challenged by the complexity of dual-task load. Older people with MCI had an impaired ability toregulate and minimize gait variability while performing dual-task challenges, and the magnitude of this impairment is relatedto the kind and complexity of the dual task performed. Ourfindings may explain the high risk of falls recently described inthis population, and suggest that their fall risk should not beassessed using methodology established among cognitivelynormal older adults.

Acknowledgments: We thank Maggie Hall for her help in theparticipants’ assessment and data gathering, and Kevin Hansen for hishelp in the manuscript preparation.

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Suppliersa. CIR Systems Inc, 69 Garlor Dr, Havertown, PA 19083.b. SAS Institute Inc, 100 SAS Campus Dr, Cary, NC 27513.

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Arch Phys Med Rehabil Vol 93, February 2012