Cortical Function, Postural Control, and Gait
Executive Functions Are Associated With Gait and
Balance in Community-Living Elderly People
Marianne B. van Iersel,1Roy P. C. Kessels,1,2,5Bastiaan R. Bloem,3
Andre ´ L. M. Verbeek,4and Marcel G. M. Olde Rikkert1
Departments of1Geriatrics,2Medical Psychology,3Neurology, and4Epidemiology and
Biostatistics, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands.
5Nijmegen Institute for Cognition and Information, Radboud University
Nijmegen, the Netherlands.
Background. Cognition influences gait and balance in elderly people. Executive functions seem to play a key role in
this mechanism. Previous studies used only a single test to probe executive functions, and outcome measures were
restricted to gait variables. We extend this prior work by examining the association between two different executive
functions and measures of both gait and balance, with and without two different cognitive dual tasks.
Methods. This is a cross-sectional study with randomly selected community-living elderly people. Executive functions
were tested with the Trail Making Test Parts A and B and the Stroop Color Word Test; memory with Cambridge
Neuropsychological Test Automated Battery (CANTAB) subtests. Patients walked without and with two dual tasks
(subtracting serial sevens and animal naming). Main outcomes focused on gait (velocity, stride length, and stride time
variability), measured on an electronic walkway, and balance, measured as trunk movements during walking. Associations
were assessed with multiple regression models.
Results. One hundred elderly people, with a mean age 80.6 years (range 75–93 years) participated. Both dual tasks
decreased gait velocity and increased variability and trunk sway. Executive functions were associated with only stride
length variability and mediolateral trunk sway during performance of animal naming as the dual task. Memory was not
associated with the gait and balance variables.
Conclusions. In community-living elderly people, executive functions are associated with gait and balance impairment
during a challenging dual-task condition that also depends on executive integrity. Next steps will be to explore the value of
executive functions in defining fall-risk profiles and in fall-prevention interventions for frail patients.
Key Words: Gait—Balance—Executive functions—Memory—Elderly people.
functions. However, it is becoming increasingly clear that
walking is in fact tightly linked to cognitive functioning,
and this interplay takes place at several levels (1). First, both
gait impairment and cognitive problems are common with
aging, and they frequently coincide in elderly people.
Second, gait and cognitive problems both have a great
impact on quality of life and everyday functioning of older
people and their caregivers. In the last decade, evidence has
also emerged for an actual pathophysiological interaction
between gait and cognition. Having a gait disorder increases
the chances of developing non-Alzheimer dementia by
threefold (2). Conversely, people with dementia more often
have gait disorders and also sustain an increased risk of
falling (3,4). This interdependence between cognition with
gait and balance can also be found in healthy older people
(5). Dual tasks are one method of investigating the effect
of cognition on gait and balance control (5). Dual tasks
may result in a suboptimal performance in gait, cognition, or
both, because attention has to be divided or because of
ALKING is traditionally seen as an automatic motor
task that requires little, if any, higher mental
structural inference in neural networks of the frontal and
motor cortex (5,6). Another explanation is that the demands
of cognition and gait go beyond the limited central
A key cognitive factor in gait and balance control seems to
be executive functioning. Executive functions are defined as
a set of cognitive skills that are necessary to plan, monitor,
and execute a sequence of goal-directed complex actions (7).
Older people with poor executive functioning walk slower,
have increased stride variability, fall more often, and have
poorer performance on complex mobility tasks (8,9). These
previous studies clearly show that executive functions play
an important role in gait control. In the present study, we
aimed to extend this prior work in three ways. First, previous
studies probed executive functions with only a single test. In
contrast, we aimed to use a more extensive cognitive test
battery, including two different executive functioning tests
and two memory tests. These memory tests were included
because memory decline in old age is highly prevalent, and
there has been little study of the effects of memory
impairment on gait (8–12). We also included two different
Journal of Gerontology: MEDICAL SCIENCES
2008, Vol. 63A, No. 12, 1344–1349
Copyright 2008 by The Gerontological Society of America
cognitive dual tasks, because execution of a secondary task
during walking (talking, route planning) partially depends on
executive functions such as concept shifting and mental
flexibility (5,6). Second, previous studies concentrated on
a selected population of elderly people without dementia
or other neurological disorders. Here, we included an
unselected population of elderly persons living in the
community. Finally, because executive functions have thus
far only been linked with gait variables, the present study
quantitatively studies both gait and balance.
We hypothesize that, in unselected community-living
elderly people, executive functions would have a stronger
relationship with gait and balance than would memory itself,
and that this association would be particularly evident
during walking under dual-task conditions.
We performed a cross-sectional study in community-
living elderly people. We recruited our participants from the
Nijmegen Biomedical Study (NBS), a population-based
survey conducted by the Department of Epidemiology and
Biostatistics of the Radboud University Nijmegen Medical
Centre, which started in 2002–2003. A group of 22,500 age-
and gender-stratified, randomly selected adult inhabitants
of the municipality of Nijmegen received an invitation to
complete a postal questionnaire on lifestyle and medical
history. From the second survey in 2005–2006, we ran-
domly invited a subset of 300 elderly people to participate in
additional measurements. Participants were eligible if they
were 75 years old or older, could walk short distances,
understood simple tasks, and were willing to give written
informed consent. Exclusion criteria were visual impair-
ments that prevented the participant from reading a newspa-
per, even with correction or glasses. Baseline characteristics
are displayed in Table 1. The institutional review board of
the Radboud University Nijmegen Medical Centre approved
We used the Mini-Mental State Examination (MMSE)
score (range 0–30; a score ,24 indicates clear cognitive
impairment) to characterize the participants and assess
global cognitive status (13). We assessed executive
functions with the Trail Making Test (TMT), a well-
established psychomotor test that is used clinically to assess
deficits in psychomotor speed (Part A) and mental flexibility
(Part B) (7). In this study, we used a ratio score, calculated
as (TMT B – TMT A)/TMT A that controls for the effect of
motor speed. Furthermore, the Stroop Color Word Test was
used as test of response inhibition (7). It measures the ability
to suppress an over-learned response (i.e., automatic reading
of a word while the incongruent color of the ink has to be
named) and consists of three parts: I: reading of color words,
II: naming of colors, and III: naming of the color of
incongruent color words. In the analysis, we used a ratio
score fStroop III – (I þ II)g/fI þ IIg to control for motor
speed and reading ability. For memory tests, we used
subtests of the Cambridge Neuropsychological Test Auto-
mated Battery (CANTAB), which includes the Paired
Associates Learning (PAL) to assess learning and episodic
memory, and Pattern Recognition Memory (PRM) to assess
visual recognition memory (14).
Gait and Balance Measures
Quantitative gait analysis was performed with a 5.6-meter-
long, 0.89-meter-wide electronic walkway (GAITRite; CIR
Systems Inc, Havertown, PA) with sensor pads (12.7 mm
Table 1. Characteristics of Participants
Mean 6 SD
Voorrips sport (27)
Number of drugs
Participants fallen in
previous year, N (%)
Number of falls per person
80.6 6 4.0 (range 75–93)
1.72 6 0.09
75.7 6 10.9
48.7 6 16.9 (range 16–80)
25.7 6 8.4
7.4 6 5.1
7.1 6 3.5
3.5 6 2.7
0.6 6 1.5
(N ¼ 26 1 fall; N ¼ 6 ?2 falls)
74.9 6 17.7
28.4 6 1.5
1.6 6 0.8
54.0 6 16.8
139.7 6 54.9
1.1 6 0.5
54.3 6 9.2
69.7 6 14.5
131.1 6 41.4
Fear of falling (yes/no), N (%)
ABC score (20)
TMT ratio (7)
Stroop interference ratio (7)
Stroop part I, s
Stroop part II, s
Stroop part III, s
PAL (total number of
PRM (% correct answers) (14)
Walking aid during
measurement, N (%)
UPDRS-motor part (28)
TUG, s (29)
Handgrip strength, kg (23)
11.3 6 9.1
79.9 6 12.0
2.1 6 4.2 (median 1.0)
3.2 6 3.8
10.4 6 4.1
32.5 6 8.7
Note: SD ¼ standard deviation; ISEI-92 ¼ International Socio-Economic
Index of occupational status 1992, range 16–87 (higher score indicates higher
status); Voorrips sport ¼ sport participation subscale Voorrips, range 0–18
(higher score means more participation); CIRS-G ¼ Cumulative Illness Rating
Scale-Geriatrics, a comorbidity index (a score of ?6 indicates frailty); GARS¼
Groningen Activity Restriction Scale, range 18–76 (higher score indicates higher
dependency); MMSE ¼ Mini-Mental State Examination, range 0–30 (a score
of ,24 indicates cognitive impairment); ABC score ¼ Activity Balance
Confidence, range 0–100% (a score of ,67% indicates fear of falling); TMT ¼
Trail Making Test ratio (TMT part B – part A)/TMT part A; Stroop ¼ Stroop
Color Word Test ratio (fStroop III – (IþII)g/fIþIIg); PAL¼Paired Associated
Learning test (short version, range 0–72 errors); PRM ¼ Paired Recognition
Memory, range 0–100% (a higher score means better memory); MADRS ¼
Montgomery Asberg Depression Rating Scale, range 0–60 (a score of .18
indicates depression); UPDRS-motor part¼Unified Parkinson’s Disease Rating
Scale-motor part (a higher score indicates more parkinsonism); TUG ¼ Timed
Up and Go test (time .13.5 s indicates an increased risk of falling).
EXECUTIVE FUNCTION, GAIT, AND BALANCE
apart from each other) connected to a computer. The
electronic walkway has good concurrent validity and test–
retest reliability (15). Balance was measured with two
angular velocity transducers (Sway Star; Balance Interna-
tional Innovations GmbH, Iseltwlad, Switzerland) that
recorded mediolateral and anteroposterior angular velocities
at 100 Hz. The device was attached as a small box with a belt
to the lower back of the participants and was connected to the
computer with a long wire. The software calculated 90%
ranges of angular velocities and angles in mediolateral and
anteroposterior direction. Primary outcomes of our study
were stride variability (stride length and stride time) and
mediolateral body sway, all associated with an increased risk
of falling (16,17).
During the measurements, participants walked over
the walkway on low-heeled shoes. To measure steady-state
walking, they started 2 meters before the walkway
and walked toward a chair positioned 2 meters behind the
walkway. First, the participants were instructed to walk at
their preferred, slow, fast, and very fast speed over the
walkway without a dual task. Subsequently, they walked at
their preferred speed while performing two different dual
tasks in a fixed order: subtracting serial sevens from 100,
and then naming as many animals as possible during
walking over the walkway (verbal fluency task). Participants
had to verbalize their answers, permitting us to score
secondary task performance. The participants started
simultaneously with walking and the cognitive task. We
did not prioritize the tasks in the instructions for the
participants (18). Single task performance on the cognitive
tasks was tested an hour after completion of the walking
tests. We had chosen these two cognitive tasks because
performance of the serial sevens during walking primarily
requires division of attention, and animal naming requires
more abstract thinking and word generation [and probably
tests more aspects of executive functioning (19)]. We did
not use a physical secondary task such as carrying a tray,
because such a task would also require more motor
coordination and would diminish rescue reflexes by the
arms, aspects in which we were not interested.
The baseline gait characteristics of patients were
summarized as mean 6 standard deviation (SD). We used
the coefficient of variation (CV): SD/mean 3 100% as
a measure of variability for stride time, stride length, and
stride width. We used analyses of covariance (ANCOVA) to
compare the outcomes for each primary variable of the three
different walks of each participant, and used paired Student
t tests in a secondary analysis to compare the results of the
dual-task condition with the reference condition (walking
without a dual task). The effect of the addition of a dual task
on the gait and balance variables was expressed in effect
sizes with Cohen’s d, of which 0.5 has to be interpreted as
a moderate and 0.8 as a large change.
We used multiple linear regression models to investigate
the relationship between cognition (as measured by TMT
ratio, Stroop ratio, PAL, and PRM), gait (gait velocity,
stride length, and time variability), and balance during
walking (mediolateral displacement and velocity) with and
without a dual task. We ensured that the requirements for
linear regression models were fulfilled. We used log trans-
formation in skewed distributions. Potential confounders
tested for inclusion in the regression models were use of a
walking aid; fear of falling, with Activities-specific Balance
Confidence (ABC) score (20); history of falls in the year
before measurements; number of medications; age; score on
a comorbidity index (Cumulative Illness Rating Scale-
Geriatrics; CIRS-G) (21); depressive symptoms (Montgomery-
A˚sberg Depression Rating Scale [MADRS]) (22), and
handgrip strength (23).
A decrease in gait velocity is often used as strategy to
maintain balance in more difficult circumstances. Because
gait velocity has a strong influence on other gait and balance
variables, we investigated the associations of executive
function and memory with the primary gait and balance
outcomes standardized for gait velocity (24).
All data were analyzed using SPSS statistical software,
version 12.0 (SPSS, Chicago, IL). Because of the multiple
comparisons, statistical significance for all regression mod-
els was accepted at p , .01.
Of the 300 people who received an invitation to
participate, 118 agreed to be approached. Seven eligible
people declined participation because they perceived the
burden of the measurements as too high, and 11 people
could not participate because of an acute illness (themselves
or that of their partner). The final sample consisted of 100
persons (36 women) with a mean age of 80.6 years (SD 4.0).
The values in Table 1 show that most participants had
several health problems, needed some assistance in activities
of daily living, and came from all social backgrounds. The
participants had a mean gait velocity of 0.96 m/s 6 0.23,
with a stride length of 115 cm 6 20 and cadence of 99
steps/min 6 14.
Table 2 displays the primary gait and balance variables
during the different dual-task conditions. Of the balance
variables, mediolateral trunk displacement increased signif-
icantly after the addition of the dual tasks, but mediolateral
angular velocity remained unchanged under all conditions.
Gait velocity was reduced during dual-task performance. Of
the gait variables, variability in stride length and stride time
increased after addition of the dual tasks (p , .001). The
effect sizes varied from 0.37 to 0.75. Standardization for gait
velocity showed that both dual tasks significantly increased
stride length variability, stride time variability, and medio-
lateral displacement by 30%–40% (p , .01). The mean
number of responses on the serial sevens was 3.1 (SD 1.8)
and for the animal naming condition 6.5 (SD 1.7). The
percentage of correct answers decreased from 90 during the
single task to 77 during the dual-task condition for the serial
sevens, and from 100 to 97 for the animal naming test
(changes not statistically significant).
After addition of the dual task (animal naming) in the
multiple regression analysis, the TMT ratio became
significantly associated with stride length variability and
mediolateral angular velocity (Table 3). Neither of the two
memory tests was independently associated with gait or
VAN IERSEL ET AL.
balance variables (data not shown). CIRS-G, MADRS,
ABC, and handgrip strength results were confounders in
the multiple regression analyses. During the single task
condition, none of the tests for executive function or
memory was independently associated with gait and
balance variables. Stride width variability remained constant
under all conditions.
This study shows that, in community-living elderly
people, mental flexibility, an important aspect of executive
function, is independently associated with both an important
gait variable (stride length variability) and a measure of
balance instability (mediolateral trunk sway), while walking
under dual-task circumstances. Both dual tasks influenced
gait and balance, but in the multiple regression analysis this
effect was seen with only the verbal fluency (animal
naming) dual task but not during a mental arithmetic dual
task (subtracting serial sevens). Although it can be argued
that both dual tasks rely on executive functioning, animal
naming probably will apply more cognitive resources than
will serial subtraction (7). The larger effect of the verbal
fluency dual task on gait and balance may thus be the result
of a higher cognitive load; it interferes with frontal neural
pathways to a greater extent. Memory tasks were not related
to any of the gait or balance measures.
Our results fit in with the results of the group of
Alexander and colleagues (30) and Persad and colleagues
(31) but are partially in contrast to the results reported by the
groups of Hausdorff and colleagues (33) and Holtzer and
colleagues (32). They found that even normal walking
(without secondary tasks) was related to executive func-
tions, suggesting that simple undisturbed gait is already
a complex process that requires input from executive
functions (8,32). Corresponding with our results, both
groups also found that the associations with executive
functions increased further during dual-tasks conditions.
Hausdorff and colleagues (8,32) reported that memory was
not independently associated with gait performance. There
are three possible explanations for the discrepancy. First, we
used a ratio score for the TMT and Stroop tests, whereas
Table 2. Gait and Balance Variables With and Without Dual Tasking (Reference Condition);
Measured Values and Values Standardized for Gait Velocity in Percentages
Walking at Preferred Gait Velocity
Cognitive Dual Tasks
No Dual Task
Serial SevensAnimal Naming
Outcome Variables Mean 6 SD
Standard (%)Mean 6 SD
Standardized Mean 6 SD (%)Mean 6 SD
Standardized Mean 6 SD (%)
Displacement M-L, degrees
Angular velocity M-L, degrees/s
3.6 6 1.6
27.6 6 1.6
4.5 6 1.6*
28.8 6 1.4
135 6 96y
107 6 32
4.4 6 1.5*
28.8 6 1.5
128 6 69y
107 6 33
Gait velocity, m/s
Stride length variability, %CV
Stride time variability, %CV
0.96 6 0.23
2.3 6 1.9
1.4 6 2.7
0.91 6 0.28y
3.0 6 2.0*
2.6 6 1.9*
NA0.92 6 0.28
2.8 6 1.9y
2.4 6 2.0
145 6 82y
140 6 76y
136 6 76y
131 6 83y
Notes: Mean 6 SD (standard deviation) refers to measured values. All means are back-transformed from the log-transformed values, except gait velocity.
Standardized mean 6 SD (%) refers to percent change in the variable relative to the reference condition (walking without a dual task; set at 100%) after standardization
for gait velocity. Data were tested for difference versus reference condition (walking without a dual task) with analyses of covariance.
*p , .001;yp , .01 (paired t tests, relative to the reference condition).
M-L ¼ body sway in mediolateral direction; NA ¼ not applicable; CV ¼ coefficient of variation.
Table 3. Multiple Linear Regression Analysis of the Association of Executive Function With Gait and Balance Variables in
Community-Living Elderly People During Walking Without Dual Task and Under a Dual-Task Condition (Animal Naming)
TMT Ratio Stroop Ratio
No Dual Task Animal NamingNo Dual Task Animal Naming
ML displacement, degrees
ML angular velocity, degrees/s
Gait velocity, m/s
Stride length variability, %CV
Stride time variability, %CV
Notes: Independent variables: cognitive measures. Dependent variables: gait and balance variables.
TMT ratio ¼ Trail Making Test (TMT part B – part A)/TMT part A; Stroop ratio ¼ Stroop Color Word Test ratio (fStroop III – (I þ II)g/fI þ IIg); ML ¼
mediolateral trunk sway; %CV ¼ coefficient of variation; R2¼ percentage of explained variation in the outcome variable by the regression model in %.
EXECUTIVE FUNCTION, GAIT, AND BALANCE
others used absolute differences in test scores (10,11). The
use of absolute differences, however, may have increased
the contrast between the extremes in test scores and have
made a spurious finding of an association more likely.
Second, in contrast to previous studies, we have applied
a correction for multiple comparisons, which obviously has
restricted the number of independent associations, but
results in statistically more robust findings. Third, our
population of community-living elderly people is different
than the idiopathic fallers or healthy older adults in the
studies of Hausdorff and colleagues (8,12) and the younger
and quicker (mean gait velocity 1.20 m/s) participants in the
InChianti study (10,11). However, the participants in the
Einstein aging study (32) were comparable in gait velocity
and TMT performance; therefore, population differences do
not seem to be the main explanation.
A major strength of our study is that we examined both
gait and balance variables during walking. Our results
showed that frontal executive functioning was related not
only to stride length variability [an important gait variable
that is related to falls by elderly persons and patients with
neurological diseases (33)], but also to balance instability
during walking (as reflected by an increased mediolateral
trunk sway related to lateral falls and hip fractures). Another
strength is that we have used several cognitive tests and two
different cognitive dual tasks. Executive function consists of
various, complex cognitive processes that differ in nature
and, consequently, cannot be assessed using one single test.
We have selected the TMT and the Stroop test because they
represent executive abilities that are probably most im-
portant to everyday walking: mental flexibility and response
inhibition. An explanation for the difference in results
between the TMT and Stroop test could be that the ability to
adapt to changing circumstances during walking requires
more mental flexibility, tested with the TMT, than response
inhibition, measured by the Stroop test. We refrained from
including additional executive function tests because the
limited attention span of our elderly participants could have
influenced their performance negatively by fatigue and
decreased motivation. Another concern would be the
increased risk of finding a chance association when the
number of variables increases. Such risks were already
considered for the present experimental design, which was
essentially an explorative study with many possible
comparisons. To accommodate this, we selected the most
important outcome variables before the start of the study,
and set the a level at 0.01.
We should note one additional drawback, related to the
use of the relatively short (5.6 m) electronic walkway, which
limited the number of steps available (on average 5.6 steps,
SD 1.4) for analysis in each walk. This may have reduced
the precision of our measurements compared to approaches
in which participants wear pressure-sensitive insoles during
prolonged walking episodes (9). However, Holzer and
colleagues and Coppin and colleagues measured gait
velocity over an equally short distance. Furthermore, even
our short walkway was sensitive enough to detect effects of
dual tasking on gait variability. Furthermore, previous stud-
ies have shown that changes in trunk sway under dual-task
circumstances can be detected during a comparably short
walking trajectory (34). Changes in stride length variability,
stride time variability, or trunk sway cannot be used on their
own to indicate the risk of falling in individual patients, and
have to be combined with all other clinical findings. Future
studies should explore the underlying pathophysiological
mechanisms behind the associations of executive functions
with gait and balance, as well as their ability to predict the
development of gait disorders and risk of falling.
This study provides additional insight in the interaction of
executive functions and memory with gait and balance
control during walking in community-living elderly people:
Executive functions are associated with gait and balance,
but only in a dual-task condition. In future research, the
pathophysiology and further clinical implications should be
We thank Brad McFadyen for his critical review of the data and Miriam
Reelick for her assistance with the measurements.
All authors had access to all data, made a substantial contribution to this
manuscript, and approved the final version.
Contributors: Marianne van Iersel, Roy Kessels, and Marcel Olde
Rikkert contributed to study design, conduct, analysis and writing of the
manuscript. Bas Bloem and Andre ´ Verbeek contributed to data analysis and
writing of the manuscript.
Address correspondence to Marianne van Iersel, MD, PhD, Radboud
University Nijmegen Medical Centre, Department of Geriatrics, internal
code 925, PO Box 9101, 6500 HB Nijmegen, the Netherlands. E-mail:
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Received February 3, 2007
Accepted September 24, 2007
Decision Editor: Luigi Ferrucci, MD, PhD
EXECUTIVE FUNCTION, GAIT, AND BALANCE