Cognitive Domain Associations with Balance Performance in Community-Dwelling Older People with Cognitive Impairment

Abstract

Background:

In older people with cognitive impairment (CI), executive function (EF) has been associated with motor performance including balance and gait. The literature examining and supporting a relationship between balance performance and other cognitive domains is limited.

Objective:

To investigate the relationship between global cognition and cognitive domain function and balance performance in older people with CI.

Methods:

The iFOCIS randomized controlled trial recruited 309 community-dwelling older people with CI. Baseline assessments completed before randomization were used for analyses including the Addenbrooke’s Cognitive Examination-III (ACE-III; global cognition) and its individual cognitive domains (attention; memory; verbal fluency; language; visuospatial ability) and the Frontal Assessment Battery (FAB), a measure of EF. A composite balance score was derived from postural sway and leaning balance tests.

Results:

In linear regression analyses adjusted for covariates, global cognition and each cognitive domain were significantly associated with balance performance. EF (verbal fluency; β= –0.254, p < 0.001, adjusted R² = 0.387) and visuospatial ability (β= –0.258, p < 0.001, adjusted R² = 0.391) had the strongest associations with balance performance. In a comprehensively adjusted multivariable model including all of the ACE-III cognitive domains, visuospatial ability and EF (verbal fluency) were independently and significantly associated with balance performance.

Conclusion:

Poorer global cognition and cognitive domain function were associated with poorer balance performance in this sample of people with CI. Visuospatial ability and EF were independently associated with balance, highlighting potential shared neural networks and the role higher-level cognitive processes and spatial perception/processing play in postural control.

Keywords

Aged cognition dementia executive function postural control visuospatial

INTRODUCTION

The number of people living with dementia is growing exponentially as the worldwide population ages and is expected to reach 152 million by 2050. Dementia is associated with considerable disability and, in Australia, is the leading cause of disability in older people and the third leading cause of disability burden overall [1]. Community-dwelling older people with dementia decline more rapidly in physical function when compared to people with mild cognitive impairment and cognitively healthy older people [2]. These declines contribute to the high prevalence of falls in this group, with more than 60%falling annually [3]. Falls often have serious consequences in this population, e.g., morbidity, mortality, and placement in residential care, resulting in significant costs to the health care system and society [4].

More specifically, older people with dementia have poorer balance than their cognitively healthy peers and balance impairments are independent predictors of falls in this group [3 , 5–8]. Previously we have demonstrated that individuals with dementia and poorer executive function have significantly poorer balance than those with dementia and better executive function, and that balance and reaction time attenuate the relationship between executive function and falls [9]. This relationship between executive function and balance has also been reported in previous studies [7 , 11]. However, the evidence to support relationships between balance and global cognition and other cognitive domains is limited [7 , 10–12]. These inconsistent findings are potentially due to the different approaches to analyses (e.g., adjusted versus unadjusted) and sample factors (e.g., relatively small sample sizes, level of cognitive impairment, dementia type [Alzheimer’s disease (AD) versus all cause]).

Whereas the relationship between gait, particularly gait speed, and cognition has been well studied [13, 14], the relationship between balance performance and cognition in older people has had less research focus [14]. Both balance and gait require effective central processing, and both are affected by attention-demanding secondary tasks, highlighting the influence of cognitive reserve [15, 16]. Further, both gait and balance impairments have been associated with negative health outcomes, e.g., falls, incident dementia and mortality [16 –18]. Therefore, a better understanding of the cognitive domain associations with balance and gait performance may assist in determining individuals at risk of impairment in either domain, as well as possible avenues for targeted interventions.

We investigated the relationship between global cognition and cognitive domain function and balance performance in community-dwelling older people with cognitive impairment. We hypothesized that executive function would have the strongest association with balance performance.

METHODS

Study design

This cross-sectional study examined baseline data of 309 community-dwelling participants with cognitive impairment from the Intervention–Falls in Older Cognitively Impaired Subjects (iFOCIS) study [19, 20]. The iFOCIS study is a fall prevention randomized controlled trial comprising home-based tailored exercise and home hazard reduction programs.

Participants

Three hundred and nine participants were recruited from health-related services including geriatric medi-cine, memory and cognitive disorders clinics, and dementia specific day centers from two sites in Syd-ney (Prince of Wales Hospital and Hornsby Ku-ring-gai Hospital), Australia. To be eligible for study participation, participants were aged 65 years or older, community-dwelling and cognitively impaired (defined as a Mini-Mental State Examination [MMSE] score or Mini-Addenbrooke’s Cognitive Examination Australian Version [m-ACE] < 24, an Adden-brooke’s Cognitive Examination –III, Australian Version [ACE-III] < 83 or a specialist clinician diagnosis of cognitive impairment). The ACE-III and m-ACE have excellent to good sensitivity (93%and 73%, respectively) and excellent specificity (100%and 97%, respectively) for dementia using cut-points of 82/83 and 23/24 respectively [21, 22]. Participants also needed to have a “person responsible/caregiver” who had at least 3.5 h of face-to-face contact with the participant each week and was willing to assist with reporting falls and supervising the exercise intervention. Exclusion criteria included residing in a residential aged care facility (RACF), severe cognitive impairment (i.e., a MMSE or Mini-ACE score < 12/30), insufficient English to understand the assessment and intervention procedures, inability to walk more than 1 meter with the use of a walking aid and/or another person (if required), blindness, severe psychiatric condition, a progressive neurological disease other than dementia (e.g., Parkinson’s disease even if accompanied by dementia), and/or any medical condition precluding exercise (e.g., unstable cardiac disease). Nine-hundred and ninety-nine people were assessed for eligibility, 152 did not meet the inclusion criteria, in 517 cases the participant or caregiver declined to participate and 21 could not participate due to other reasons, e.g., newly started dementia drug, out of area, and palliative.

Written informed consent was obtained from either the participant or person responsible depending on a capacity assessment performed at the time of consent [19]. Ethical approval was obtained from the South Eastern Sydney Local Health District Human Research Ethics Committee (HREC 14/046) and the study was conducted in accordance with the National Statement on Ethical Conduct in Human Research (2007).

Assessments

All assessments took place in participants’ homes by trained assessors. Demographic data, including past medical history and medication use, were self-reported with the assistance of the person responsible/caregiver. Physical activity was assessed using the Incidental and Planned Exercise Questionnaire (IPEQ) and expressed as hours of activity per week [23].

Cognitive and psychological

Global cognition was assessed using the ACE-III (/100; higher scores indicate better performance) [21]. The ACE-III assesses five cognitive domains: attention (/18), memory (/26), verbal fluency (/14), language (/26), and visuospatial ability (/16). Verbal fluency (words/min) involves enumerating as many words as possible in 60 s and includes phonemic/letter and semantic/category fluency, which test executive function. The Frontal Assessment Battery (FAB) was also completed to further assess executive function [24]. The FAB (/18; higher scores indicate better performance) comprises six subtests that explore cognitive control processes responsible for appropriate goal-directed behavior and response to challenging situations. Depressive symptoms were measured using the 15-item Geriatric Depression Scale (/15; higher scores indicate greater symptomatology) [25].

Balance

Balance was assessed by measuring postural sway on floor and foam and the coordinated stability and maximal balance range tests. Postural sway, a measure of static balance, was assessed using a simple swaymeter [26, 27]. The swaymeter consists of a 40 cm rod attached to the participant at waist level by a firm belt. Testing was performed on a firm surface and on a medium density foam rubber mat (70 cm×62 cm×15 cm thick) with the participant standing in the center with feet shoulder width apart and eyes open for 30 s. Sway path was recorded in millimeters (mm). The coordinated stability test assesses controlled leaning balance and measures the ability to adjust body position in a steady and coordinated way while navigating a pen on the end of a swaymeter (secured to the participant’s waist and extending anteriorly) around a convoluted track placing the participant at or near the limits of their stability [28]. The number of times the participant leaves the track (1 point) or fails to round a corner (5 points) is recorded and added to give the final error score. Two trials were completed, with the best score used for analyses. The maximal balance range test involves participants leaning forward and backward from the ankles as far as possible without moving their feet. With a swaymeter extending anteriorly from the participants waist, maximal anterio-posterior movement is recorded. A composite balance score was derived by averaging the z-scores from the whole population for the two postural sway, maximal balance range and coordinated stability tests [the z-score for the maximal balance range test was reversed so high scores in each test indicated worse performance].

Statistical analysis

Data were analyzed using IBM SPSS 25.0 and descriptive data presented are n (%) or mean±standard deviation (SD). All statistical tests were two tailed and p < 0.05 was considered statistically significant. Individuals who were unable to complete the balance assessments due to physical impairments, were given a value of the baseline mean±3SD from the scores of participants who could complete the test. 3SDs were added or subtracted depending on whether higher or lower scores indicated better performance, and if subtracting 3SD from the mean resulted in a negative value, a score of 0.1 was allocated (sway on floor: n = 10; sway on foam: n = 91; coordinated stability n = 51; maximal balance range: n = 27). The associations between balance (dependent variable) and the ACE-III, the FAB, and each ACE-III domain were analyzed separately using linear regression. Initially, each variable was examined in unadjusted linear regression. Then minimally adjusted multivariable linear regression was undertaken including established confounders for cognitive function (age, sex, and education) in each model. Given the multiple contributors to balance disorders and co-existent morbidity in this population, we subsequently performed comprehensively adjusted analyses by including baseline variables that demonstrated a significant association with balance performance in simple linear regression analyses (p < 0.05) as covariates. A comprehensively adjusted multivariable linear regression was then undertaken, balance performance was the dependent variable and the ACE-III domains (attention, memory, verbal fluency, language, and visuospatial ability) and covariates were entered as predictor variables. Assumptions of collinearity, normality, linearity, and homoscedasticity were met. The aforementioned linear regression analyses were conducted on the whole sample, then the minimally and comprehensively adjusted models were repeated using the same approach on subgroups with AD and other dementia types (vascular, mixed, frontotemporal and unspecified dementia, and dementia with Lewy bodies). Between subgroup differences were examined with independent samples t-tests and χ² for continuous and categorical variables, respectively.

RESULTS

Participants had a mean age of 82±6 years and 151 (49%) were female (Table 1). Participant characteristics including demographic characteristics, self-reported medical history and medication use, physical activity levels and neuropsychological and balance performance are reported in Table 1. Two-hundred and twenty-five (74%) participants reported a diagnosis of dementia. Ninety-six (31%) reported Alzheimer’s disease, 31 (10%) vascular dementia, 24 (8%) mixed dementia, 3 (1%) frontotemporal dementia, 1 (0.3%) dementia with Lewy bodies, and 70 (23%) unspecified dementia. Eighty-one (26%) did not report a diagnosis of dementia.

Table 1

Baseline descriptive characteristics

Characteristic, n (%) or mean±SD	n = 309
Demographics
Age, y	82±6
Female	151 (49)
Education, y	12±4
Lives alone	60 (19)
Indoor walking aid use	73 (24)
Fall past year	163 (53)
Medical conditions and medication use
Stroke	38 (12)
Heart disease	100 (32)
Hypertension	150 (49)
Diabetes	50 (16)
Arthritis	172 (56)
Depression	79 (26)
Dementia	225 (74)
Number of medications	6±3
Neuropsychological performance
Addenbrooke’s Cognitive Examination-III	63±19
Attention	12.9±4.3
Memory	12.4±6.0
Verbal fluency	5.4±3.3
Phonemic, n correct	7.9±5.0
Animals, n correct	7.8±4.5
Language	20.3±5.7
Visuospatial ability	11.7±3.4
Mini-Addenbrooke’s Cognitive Examination	14.4±7.0
Frontal Assessment Battery	11.5±4.5
Geriatric Depression Scale (15-item)	2.9±2.7
Physical Activity
Physical Activity (IPEQ), h/week	17.6±13.7
Balance Performance
Sway on floor, eyes open, mm	147±92
Sway on foam, eyes open, mm	396±220
Maximal balance range, mm	141±58
Coordinated stability, errors	31±22

SD, standard deviation; IPEQ, Incidental and Planned Exercise Questionnaire. Higher scores indicate better performance for Addenbrooke’s Cognitive Examination-III (ACE-III; /100); ACE-III domains: Attention (/18), memory (/26), verbal fluency (/14), language (/26), visuospatial ability (/16); Mini-Addenbrooke’s Cognitive Examination (/30); Frontal Assessment Battery (/18) and Maximal balance range. Higher scores indicate more depressive symptoms assessed using the Geriatric Depression Scale (/15) and poorer performance for sway on floor and foam and coordinated stability.

Cognitive associations with balance for the whole sample (n = 309)

Results from separate linear regression analyses of associations between global and individual domains of cognitive function and balance performance (z-score) are presented in Table 2. In unadjusted linear regression, global cognition (ACE-III) and each cognitive domain were significantly associated with balance performance (Table 2). Visuospatial ability, verbal fluency, global cognitive function (ACE-III) and the FAB explained the greatest variance in balance performance (adjusted R² = 0.108, 0.092, 0.075, and 0.074, respectively; Table 2). In minimally adjusted models (adjusted for age, sex, and education), global cognitive function (ACE-III), attention, verbal fluency, language, visuospatial ability, and the FAB were each associated with balance performance (Table 2). Executive function, assessed by verbal fluency, and visuospatial ability, had the strongest association and explained the greatest variance in balance performance (adjusted R² = 0.183 and 0.186, respectively; Table 2). When the analyses were comprehensively adjusted (additionally adjusted for fall in the previous year, walking aid use, heart disease, hypertension, arthritis, depression, number of medications, and the Incidental and Planned Exercise Questionnaire), global cognitive function and each cognitive domain were significantly associated with balance performance (Table 2). Verbal fluency and the FAB, measures of executive function, and visuospatial ability demonstrated the strongest association and explained the greatest variance in balance performance (adjusted R² = 0.387, 0.383, and 0.391, respectively). In unadjusted and, minimally and comprehensively adjusted analyses, memory had the weakest and visuospatial ability the strongest association with balance performance (Table 2).

Table 2

Cognitive domain contributions to balance: multivariable linear regression with the balance domain z-score as the dependent variable and cognitive domain (with covariates for minimally and comprehensively adjusted models) as the predictor variable

	Unadjusted models^a				Minimally adjusted models^a,b				Comprehensively adjusted models^a,c
	B (95%CI)	β	p	Adjusted R²	B (95%CI)	β	p	Adjusted R²	B (95%CI)	β	p	Adjusted R²
ACE-III	–0.011 (–0.015, –0.007)	–0.279	< 0.001	0.075	–0.009 (–0.013, –0.005)	–0.231	< 0.001	0.151	–0.009 (–0.013, –0.006)	–0.235	< 0.001	0.378
Attention	–0.045 (–0.065, –0.025)	–0.251	< 0.001	0.060	–0.039 (–0.058, –0.020)	–0.217	< 0.001	0.151	–0.041 (–0.057, –0.024)	–0.227	< 0.001	0.376
Memory	–0.019 (–0.033, –0.005)	–0.151	0.009	0.019	–0.011 (–0.025, 0.003)	–0.084	0.135	0.107	–0.015 (–0.028, –0.003)	–0.121	0.015	0.341
Verbal fluency	–0.071 (–0.095, –0.046)	–0.309	< 0.001	0.092	–0.066 (–0.091, –0.042)	–0.290	< 0.001	0.183	–0.058 (–0.080, –0.037)	–0.254	< 0.001	0.387
Language	–0.030 (–0.045, –0.015)	–0.224	< 0.001	0.047	–0.023 (–0.038, –0.009)	–0.176	0.002	0.133	–0.024 (–0.037, –0.012)	–0.182	< 0.001	0.357
Visuospatial	–0.075 (–0.099, –0.051)	–0.334	< 0.001	0.108	–0.066 (–0.090, –0.043)	–0.296	< 0.001	0.186	–0.058 (–0.078, –0.037)	–0.258	< 0.001	0.391
FAB	–0.047 (–0.065, –0.028)	–0.277	< 0.001	0.074	–0.045 (–0.063, –0.026)	–0.264	< 0.001	0.170	–0.038 (–0.054, –0.022)	–0.225	< 0.001	0.383

Results from the comprehensively adjusted multivariable linear regression including all five ACE-III cognitive domains and covariates are presented in Table 3. Verbal fluency and visuospatial ability were independently and significantly associated with balance performance when adjusted for attention, memory, language, covariates and each other (Table 3). In contrast, none of the other ACE-III cognitive domains (attention, memory, language) withstood adjustment (Table 3).

Table 3

Multivariable comprehensively adjusted linear regression: balance domain z-score as the dependent variable and ACE-III cognitive domains and covariates as predictor variables

Variables	B (95%CI)	β	p
ACE-III cognitive domains
Attention	–0.019 (–0.045, 0.007)	–0.105	0.161
Memory	0.015 (–0.002, 0.032)	0.119	0.084
Verbal fluency	–0.041 (–0.071, –0.010)	–0.178	0.009
Language	0.007 (–0.012, 0.026)	0.050	0.491
Visuospatial	–0.041 (–0.070, –0.011)	–0.181	0.008
Covariates
Age, y	0.018 (0.005, 0.030)	0.139	0.005
Female	0.190 (0.044, 0.336)	0.124	0.011
Education, y	0.021 (0.000, 0.042)	0.095	0.055
Indoor walking aid use	0.626 (0.444, 0.809)	0.346	< 0.001
Fall past year	0.189 (0.048, 0.331)	0.124	0.009
Heart disease	0.133 (–0.023, 0.288)	0.082	0.094
Diabetes	0.124 (–0.077, 0.326)	0.059	0.226
Arthritis	0.070 (–0.076, 0.216)	0.046	0.346
Number of medications	0.016 (–0.011, 0.044)	0.062	0.240
Physical activity (IPEQ), h/week	–0.006 (–0.011, 0.000)	–0.101	0.037

Bold type denotes significant (p < 0.05) findings. ACE-III, Addenbrooke’s Cognitive Examination-III; B, unstandardized coefficients; β, standardized coefficients; IPEQ, Incidental and Planned Exercise Questionnaire. Multivariable model R² = 0.407.

Dementia (self-reported) sub-groups

The AD group (n = 96; mean age 81 years±6) were significantly younger and had significantly better balance (z-score mean –0.09±0.66) when compared to the other dementia type group (vascular, mixed, frontotemporal and unspecified dementia, and dementia with Lewy bodies [n = 128]; age: mean 83 years±6; t(222) = –2.7, p = 0.007; balance z-score mean 0.16±0.84, t(222) = –2.6, p = 0.011), but did not significantly differ in education (AD: mean 12 years±4; other dementia types: mean 12 years±3; t(222) = 0.9, p = 0.362), ACE-III (AD: mean 59±19; other dementia types: mean 59±18; t(222) = –0.1, p = 0.896) or sex (Female: AD: n = 54 [56%]; other dementia types: n = 58 [45%]; χ(1) = 2.6, p = 0.105).

Cognitive associations with balance in Alzheimer’s disease

Results from separate multiple linear regression analyses of associations between global and individual domains of cognitive function and balance performance (z-score) for participants reporting AD are presented in Table 4. In this group, global cognitive function (ACE-III), verbal fluency and visuospatial ability were each associated with balance performance in minimally adjusted models (adjusted for age, sex, and education; Table 4). In minimally adjusted models, verbal fluency (executive function) and visuospatial ability had the strongest association and explained the greatest variance in balance performance in participants with AD (adjusted R² = 0.193 and 0.144 respectively; Table 4). When the analyses were comprehensively adjusted (additionally adjusted for fall past year, indoor walking aid use, and the Incidental and Planned Exercise Questionnaire), global cognitive function, attention, verbal fluency, language and visuospatial ability were significantly associated with balance performance (Table 4). Executive function (verbal fluency and the FAB) and visuospatial ability demonstrated the strongest association with balance performance explaining approximately 34%of the variance. Overall, memory had the weakest and verbal fluency (executive function) the strongest association with balance performance in participants with AD in both minimally and comprehensively adjusted analyses.

Table 4

Cognitive domain contributions to balance: multivariable minimally and comprehensively adjusted linear regression with the balance domain z-score as the dependent variable and cognitive domain (with covariates) as the predictor variable by dementia type (Alzheimer’s disease [n = 96] and Other dementia types [vascular dementia, mixed, frontotemporal dementia, dementia with Lewy bodies and unspecified; n = 128])

	Minimally adjusted^a				Comprehensively adjusted^b,c
	B (95%CI)	β	p	Adjusted R²	B (95%CI)	β	p	Adjusted R²
Alzheimer’s disease
ACE-III	–0.008 (–0.014, –0.001)	–0.226	0.027	0.122	–0.007 (–0.013, –0.001)	–0.205	0.025	0.329
Attention	–0.028 (–0.057, 0.000)	–0.192	0.054	0.126	–0.026 (–0.052, 0.000)	–0.179	0.047	0.311
Memory	–0.012 (–0.036, 0.012)	–0.103	0.319	0.081	–0.011 (–0.033, 0.010)	–0.097	0.288	0.297
Verbal fluency	–0.063 (–0.100, –0.026)	–0.331	0.001	0.193	–0.051 (–0.085, –0.016)	–0.267	0.005	0.343
Language	–0.021 (–0.044, 0.002)	–0.182	0.074	0.121	–0.023 (–0.044, –0.002)	–0.196	0.034	0.315
Visuospatial	–0.050 (–0.089, –0.012)	–0.256	0.011	0.144	–0.041 (–0.075, –0.007)	–0.210	0.019	0.336
FAB	–0.024 (–0.052, 0.004)	–0.181	0.089	0.116	–0.019 (–0.044, 0.005)	–0.144	0.122	0.341
Other dementia types^d
ACE-III	–0.009 (–0.017, –0.002)	–0.212	0.018	0.123	–0.010 (–0.016, –0.004)	–0.229	0.001	0.478
Attention	–0.047 (–0.080, –0.013)	–0.235	0.007	0.136	–0.050 (–0.077, –0.024)	–0.253	< 0.001	0.490
Memory	–0.004 (–0.030, 0.022)	–0.028	0.756	0.082	–0.012 (–0.033, 0.008)	–0.086	0.234	0.436
Verbal fluency	–0.070 (–0.117, –0.023)	–0.254	0.004	0.143	–0.070 (–0.108, –0.032)	–0.254	< 0.001	0.486
Language	–0.020 (–0.044, 0.004)	–0.149	0.098	0.102	–0.023 (–0.042, –0.004)	–0.168	0.019	0.455
Visuospatial	–0.072 (–0.112, –0.031)	–0.296	0.001	0.167	–0.059 (–0.092, –0.027)	–0.246	< 0.001	0.488
FAB	–0.056 (–0.089, –0.023)	–0.294	0.001	0.162	–0.044 (–0.071, –0.016)	–0.229	0.002	0.469

Bold type denotes significant (p < 0.05) findings. ACE-III, Addenbrooke’s Cognitive Examination-III; FAB, Frontal Assessment Battery; B, unstandardized coefficients; β, standardized coefficients. ^aadjusted for age, sex, education; cognitive domains were examined in separate models. ^bFor AD, adjusted for age, sex, education, fall previous year, indoor walking aid use and the Incidental and Planned Exercise Questionnaire; cognitive domains were examined in separate models. ^cFor other dementia types, adjusted for age, sex, education, fall previous year, indoor walking aid use, heart disease and number of medications; cognitive domains were examined in separate models. ^dOther dementia types: vascular, mixed, frontotemporal and unspecified dementia, and dementia with Lewy bodies.

Cognitive associations with balance in other dementias

Results from separate multiple linear regression analyses of associations between global and individual domains of cognitive function and balance performance (z-score) for participants reporting other dementia types (vascular, mixed, frontotemporal and unspecified dementia, and dementia with Lewy bodies) are presented in Table 4. Global cognitive function (ACE-III), attention, verbal fluency, visuospatial ability, and the FAB were each associated with balance performance in minimally adjusted models for participants with other dementia types (adjusted for age, sex, and education; Table 4). In minimally adjusted models, visuospatial ability and the FAB had the strongest association and explained the greatest variance in balance performance in this group (adjusted R² = 0.167 and 0.162, respectively; Table 4). When the analyses were comprehensively adjusted (additionally adjusted for fall past year, indoor walking aid use, heart disease and number of medications), global cognitive function, attention, verbal fluency, language, visuospatial ability and the FAB were significantly associated with balance performance (Table 4). Attention, verbal fluency (executive function) and visuospatial ability demonstrated the strongest association with balance performance explaining 49%of the variance in the comprehensively adjusted models.

DISCUSSION

In this sample of 309 cognitively impaired older people, executive function and visuospatial ability explained the greatest variance in balance performance and memory the least. In comprehensively adjusted models, global cognition and each cognitive domain were significantly associated with balance performance. However, executive function (verbal fluency) and visuospatial ability were the only cognitive domains to demonstrate an independent association with balance performance in a comprehensively adjusted model, each withstanding adjustment for the other cognitive domains, covariates and each other.

These findings differ from some previous studies that have addressed this issue [10 –12]. For example, Tangen and colleagues reported an association between executive function and balance performance in a mixed cohort with subjective cognitive complaints, mild cognitive impairment, and AD, though 75%were diagnosed with mild to moderate (67%mild) AD [10]. In adjusted models, global cognition, memory, processing speed, visuoconstructive ability (clock drawing test), and verbal fluency were not significantly associated with balance performance. In contrast, balance assessed using the short physical performance battery was significantly correlated with global cognition, processing speed, category fluency and the clock drawing test in a smaller cohort of 50 older people with all-cause dementia, though these analyses were not adjusted for confounders [7]. These inconsistencies are potentially due to population characteristics and differing approaches to analyses. For example, the Norwegian sample was approximately 10 years younger than our sample and included a mixed cohort (subjective cognitive decline, MCI, mild–moderate AD) that presented with milder cognitive impairment [10]. Our results are more consistent with those previously reported in the smaller sample of participants with all-cause dementia who were approximately 8 years younger and presented with poorer cognition than the Norwegian sample, but superior to those in the current study [7]. The limitations of this previous study were that they did not comprehensively adjust for confounders, likely secondary to the small sample size, and did not assess the domains of attention, visuospatial ability or language [7]. As highlighted by our study, these domains are also important contributors to balance performance, particularly visuospatial ability.

Interestingly, when AD and other dementia types were investigated separately, in minimally adjusted models for both groups, executive function and visuospatial ability continued to explain the greatest variance in balance performance and memory the least. However, in comprehensively adjusted models, attention explained the greatest amount of variance in balance performance for participants with other dementia types including vascular, mixed, frontotemporal and unspecified dementia, and dementia with Lewy bodies. This suggests that the cognitive contributors to balance performance may differ by pathological process. Future research could examine sub-groups in more detail with larger sample sizes.

Recently, we reported impaired attention, memory, verbal fluency, language, visuospatial ability, executive function, and global cognition were all associated with reduced gait performance, with executive function explaining the greatest variance in gait speed [29]. While the findings are similar, suggesting potential shared neural networks, there are some subtle differences in the findings. When examining both gait speed and balance, executive function and visuospatial ability explained the greatest variance in performance and memory the least. In the current study of balance, visuospatial ability explained the greatest variance in balance performance. In contrast, when considering the relationship between cognitive performance and gait speed, the FAB explained the greatest variance. These findings highlight the importance of visuospatial ability in balance control in older people with cognitive impairment. These results may help explain the relationship we have previously demonstrated between poorer visuospatial ability and increased falls risk [3].

The strengths of this study are the relatively large sample size, the broad assessment of cognitive and balance performance and the robust, comprehensively adjusted analyses. However, this study also has some limitations. Firstly, causality cannot be determined secondary to the cross-sectional design. Secondly, 517 (52%) of 999 potential participants or their caregivers invited to participate declined, which may influence the generalizability of these findings. Thirdly, although collinearity assumptions were met, cognitive domains, while unique, often overlap as cognitive assessments frequently require overlapping processes. For example, verbal fluency, a measure of executive function, also requires language skills and processing speed. Similarly, visuospatial assessment included constructional praxis (i.e., clock drawing) which has also been described as a measure of executive function. Finally, dementia sub-groups relied on self-report, nearly one quarter reported ‘unspecified dementia’ and few participants reported dementia with Lewy bodies and frontotemporal dementia. This and the respective sample sizes of the sub-groups limited our ability to examine dementia types separately and affect the generalizability of our conclusions to these underrepresented dementia types. Future research could recruit larger samples and conduct longitudinal follow-up. This would assist in establishing causality and help investigate whether sub-groups by dementia pathology reveal different patterns of associations.

In conclusion, in this study of community-dwelling older people with cognitive impairment, global cognition and each cognitive domain were associated with balance performance. Executive function and visuospatial ability explained the greatest variance in balance performance and each withstood adjustment for other cognitive domains and each other in a comprehensively adjusted multivariable model. When AD and other dementia types were examined separately, the cognitive contributors to balance performance differed in comprehensively adjusted models. This suggests that neuropathological changes may differentially affect cognitive domains relationship with balance performance. This work adds to the growing body of literature demonstrating an association between executive and physical function in older people with cognitive impairment and has highlighted the added contribution of visuospatial ability in balance control. Future research could look at the temporal relationships between cognitive and balance declines and examine how interventions for each deficit influence outcomes in both cognitive and physical domains.

Footnotes

ACKNOWLEDGMENTS

We would like to thank all participants and their caregivers who participated in this study. We would like to acknowledge Lyndell Webster, Sandra O’Rourke, Beatrice John, and Keri Lockwood for their contribution to subject recruitment and data collection, and hospital clinic staff for referring participants, in particular, Prof. Gideon Caplan, Dr. Thi-Yen Hill, Dr. Danielle Lasschuit, Dr. Lyndal Newton, and Prof. Mark Latt.

This work was supported by the Australian Na-tional Health and Medical Research Council (NHMRC) reference number 1060191. SRL receives salary funding from the NHMRC.

Authors’ disclosures available online ().

References

AIHW (2012) Dementia in Australia. Australian Institute of Health and Welfare, Canberra.

Taylor

, Boripuntakul

, Toson

, Close

JCT

, Lord

, Kochan

, Sachdev

, Brodaty

, Delbaere

(2019) The role of cognitive function and physical activity in physical decline in older adults across the cognitive spectrum. Aging Ment Health 23, 863–871.

Taylor

, Delbaere

, Lord

, Mikolaizak

, Brodaty

, Close

(2014) Neuropsychological, physical, and functional mobility measures associated with falls in cognitively impaired older adults. J Gerontol A Biol Sci Med Sci 69, 987–995.

Harvey

, Mitchell

, Brodaty

, Draper

, Close

(2016) The influence of dementia on injury-related hospitalisations and outcomes in older adults. Injury 47, 226–234.

Taylor

, Delbaere

, Lord

, Mikolaizak

, Close

JCT

(2013) Physical impairments in cognitively impaired older people: Implications for risk of falls. Int Psychogeriatr 25, 148–156.

Sant’Anna

, Silva

, Rodrigues

ACMA

, Plácido

, Ferreira

, Meereis

ECW

, Praxedes

, Marinho

, Laks

, Monteiro-Junior

, Deslandes

(2019) Posturographic analysis of older adults without dementia and patients with alzheimer’s disease a cross-sectional study. Dement Neuropsychol 13, 196–202.

Bruce-Keller

, Brouillette

, Tudor-Locke

, Foil

, Gahan

, Nye

, Guillory

, Keller

(2012) Relationship between cognitive domains, physical performance, and gait in elderly and demented subjects. J Alzheimers Dis 30, 899–908.

Mesbah

, Perry

, Hill

, Kaur

, Hale

(2017) Postural stability in older adults with Alzheimer disease. Phys Ther 97, 290–309.

Taylor

, Lord

, Delbaere

, Kurrle

, Mikolaizak

, Close

JCT

(2017) Reaction time and postural sway modify the effect of executive function on risk of falls in older people with mild to moderate cognitive impairment. Am J Geriatr Psychiatry 25, 397–406.

10.

Tangen

, Engedal

, Bergland

, Moger

, Mengshoel

(2014) Relationships between balance and cognition in patients with subjective cognitive impairment, mild cognitive impairment, and Alzheimer disease. Phys Ther 94, 1123–1134.

11.

Bruce-Keller

, Brouillette

, Tudor-Locke

, Foil

, Gahan

, Correa

, Nye

, Keller

(2012) Assessment of cognition, physical performance, and gait in the context of mild cognitive impairment and dementia. J Am Geriatr Soc 60, 176–177.

12.

Lee

, Kang

, Park

(2020) Relationship between balance, gait, and activities of daily living in older adults with dementia. Geriatr Orthop Surg Rehabil 11, 2151459320929578.

13.

Morris

, Lord

, Bunce

, Burn

, Rochester

(2016) Gait and cognition: Mapping the global and discrete relationships in ageing and neurodegenerative disease. Neurosci Biobehav Rev 64, 326–345.

14.

Demnitz

, Esser

, Dawes

, Valkanova

, Johansen-Berg

, Ebmeier

, Sexton

(2016) A systematic review and meta-analysis of cross-sectional studies examining the relationship between mobility and cognition in healthy older adults. Gait Posture 50, 164–174.

15.

Woollacott

, Shumway-Cook

(2002) Attention and the control of posture and gait: A review of an emerging area of research. Gait Posture 16, 1–14.

16.

Taylor

, Close

JCT

(2018) Chapter 19 - Dementia. In Handbook of Clinical Neurology, Day BL, Lord SR, eds. Elsevier, pp. 303–321.

17.

Kueper

, Speechley

, Lingum

, Montero-Odasso

(2017) Motor function and incident dementia: A systematic review and meta-analysis. Age Ageing 46, 729–738.

18.

Dommershuijsen

, Isik

, Darweesh

SKL

, van der Geest

, Ikram

(2019) Unravelling the association between gait and mortality - one step at a time. J Gerontol A Biol Sci Med Sci 75, 1184–1190.

19.

, Wesson

, Sherrington

, Hill

, Kurrle

, Lord

, Brodaty

, Howard

, Gitlin

, O’Rourke

, Clemson

(2014) Can a tailored exercise and home hazard reduction program reduce the rate of falls in community dwelling older people with cognitive impairment: Protocol paper for the i-FOCIS randomised controlled trial. BMC Geriatrics 14, 89.

20.

Taylor

, Wesson

, Sherrington

, Hill

, Kurrle

, Lord

, Brodaty

, Howard

, O’Rourke

, Clemson

, Payne

, Toson

, Webster

, Savage

, Zelma

, Koch

, John

, Lockwood

, Close JCT (2021) Tailored exercise and home hazard reduction program for fall prevention in older people with cognitive impairment: The i-FOCIS randomized controlled trial. J Gerontol A Biol Sci Med Sci 76, 655–665.

21.

Hsieh

, Schubert

, Hoon

, Mioshi

, Hodges

(2013) Validation of the Addenbrooke’s Cognitive Examination III in frontotemporal dementia and Alzheimer’s disease. Dement Geriatr Cogn Disord 36, 242–250.

22.

Hsieh

, McGrory

, Leslie

, Dawson

, Ahmed

, Butler

, Rowe

, Mioshi

, Hodges

(2015) The Mini-Addenbrooke’s Cognitive Examination: A new assessment tool for dementia. Dement Geriatr Cogn Disord 39, 1–11.

23.

Delbaere

, Hauer

, Lord

(2010) Evaluation of the incidental and planned activity questionnaire for older people. Br J Sports Med 44, 1029–1034.

24.

Dubois

, Slachevsky

, Litvan

, Pillon

(2000) The FAB: A Frontal Assessment Battery at bedside. Neurology 55, 1621–1626.

25.

Yesavage

, Sheikh

(1986) 9/Geriatric Depression Scale (GDS). Clin Gerontol 5, 165–173.

26.

Lord

, Menz

, Tiedemann

(2003) A physiological profile approach to falls risk assessment and prevention. Phys Ther 83, 237–252.

27.

Sturnieks

, Arnold

, Lord

(2011) Validity and reliability of the Swaymeter device for measuring postural sway. BMC Geriatr 11, 63.

28.

Lord

, Ward

, Williams

(1996) Exercise effect on dynamic stability in older women: A randomized controlled trial. Arch Phys Med Rehabil 77, 232–236.

29.

Toots

ATM

, Taylor

, Lord

, Close

JCT

(2019) Associations between gait speed and cognitive domains in older people with cognitive impairment. J Alzheimers Dis 71, S15–S21.