Abstract
Objective
The aim of this study was to determine how gait speed and frontal lobe functionsin community-dwelling older adults in Korea.
Design
This was a cross-sectional study.
Setting
The study used data from the Korean Frailty and Aging Cohort Survey (KFACS), a multi-center longitudinal study addressing 10 centers across urban, rural, and suburban communities in Korea, between 2016 and 2017.
Participants
A total of 1552 older adults who underwent both gait speed tests and cognitive functions tests during the investigation of the KFACS.
Measurements
Gait speed was assessed by asking participants to walk from a starting point to a point 4 meters away at a normal gait. Cognitive functions were evaluated using various standardized cognitive functions tests.
Results
Gait speed was slower when participants were older or less educated The percentage of women, higher BMI, people with lower incomes, singles, smokers, and drinkers was high in the slower gait group. Also, all cognitive function scores were low and depression score was high in the group with slower walking speed. The slower walking speed showed low physical activity score and high prevalence of hypertension, osteoarthritis and osteoporosis. Among the seven cognitive functions (MMSE, memory, TMT, Recall, Recognition, digit span, and Fab), only TMT showed no significant difference between different gait speed groups. The other six cognitive functions showed higher results in the fastest gait speed group (T3), Participants in middle gait speed group (T2) also showed higher results in five of the seven cognitive function scores as well (Memory, Recall, Recognition, digit span, and Fab).
Conclusion
In this study, we found correlation between the slower gait speeds and the decrease in cognitive function, and especially the frontal lobe dysfunction was most prominent of all cognitive dysfunctions.
Key words: Gait, cognitive function, frontal lobe function, elderly
Background
Lately, the prevalence of dementia, which occurs mostly in elderly population, has been increasing due to rapid aging in Korea. Therefore, interests in the development of sensitive predictors of dementia and mild cognitive impairment, an early clinical stage of cognitive impairment, are increasing. Many studies have suggested that gait disturbance should be used as a predictor of cardiovascular disease as well as dementia and that gait disorder alone could be an early sign of neurodegenerative disease. In order to establish the relationship between cognitive function and gait speed there have been various studies in Western Europe and North America that have suggested walking speed can be used as an index of cognitive function and current health status. However, such studies investigating this correlation are lacking in Korea.
In the past, gait used to be considered as a simple repetition of movement, but recently there have been findings that suggest that high levels of cognitive functions including executive functions are involved in gait and that gait dynamics are a result of various cognitive functions and motor functions (1). Normal gait requires a strategic planning for the fastest route and a sustained interrelationship between the internal factors and the environment. Proper performance of sensorimotor system is also necessary to maintain safety and efficacy. Executive control dimension is also a necessity for integrating and determining behavior aspects of gait. Other factors involved in gait includes navigation, visuospatial perception, cognitive dimension, etc.
Such relationship between high brain function and gait has been investigated in several studies. In those studies, Abilities of elderly, who are ill or taking medication, to integrate cognitive abilities and gait were noticeably deteriorated, and the gait strides were found inconsistent (2). Such elderly were at increased risk for falls, and the gait disturbances of patients with Parkinson's disease or stroke were worse (3). Likewise, people with dementia, the gait strategy for safety does not work properly, which is known to be one of imperative functions of frontal lobe.
Based on the prospects that gait is related to the functions of the frontal lobe, the possibilities of gait disturbance's role as a predictor of frontal lobe dysfunction in elderly have been raised, and the importance of cognitive aspects of gait disorder has been investigated in various types of dementia studies (4). Therefore, it is imperative to be cognitive of the possibilities that the gait abnormality alone in the elderly population could be a sign of frontal lobe dysfunction rather than natural degeneration of the motor function by normal aging (5).
We focused more on the frontal functions that integrate the automatic and voluntary movement necessary for gait and predicted that the frontal lobe function would be reduced in people with slower gait along with the other cognitive functions (6). Thus, the purpose of this study was set to investigate the relationship between gait changes and cognitive impairment and to confirm which areas of cognitive impairment would be particularly deteriorated in the group with decreased gait speed (7).
Methods
Study population and protocol
The study subjects were among participants from 70 to 84 years old who participated in the Korean Frailty and Aging Cohort Study (KFACS). The KFACS is a national, multi-center, large-scale cohort study initiated in 2016 with the target number of 3,000 adults aged from 70 to 84 years old, stratified by age and gender. It aims to identify risk factors for frailty and measures to prevent it in the community-dwelling older adults (8).
Measures
Gait speed was assessed by asking participants to walk from a starting point to a point 4 meters away at a normal gait. Time (in seconds) was recorded with a stopwatch for 2 trials, and the faster time was recorded. After calculating participants' gait speed in meters per seconds, they were divided in three groups according to speed (T1=0.17–0.99 m/s, T2=1.00–1.25 m/s, T3=1.26–3.45 m/s). The K-MMSE score were divided into two groups. Participants with a score of 22 or below was classified as cognitive dysfunction group. Likewise, people with a score or 16 or below on memory tests, 24 or below on TMT tests, 5 or below on recall tests, 8 or below on recognitions tests, 10 or below on digit pan tests, 12 or below on Fab (Frontal assessment battery) tests were classified as dysfunction. Depression status was assessed by SGDS (Short Geriatric Depression Scale) questionnaire, and participants with a score of 8 or above out of 15 were classified as depressed. Socioeconomic status was divided into two groups based on their monthly income, and the cut-off value used was 2,000,000. Participants' abilities for physical activity were evaluated based on MET (Metabolic Equivalent of Task) and SPPB (Short Physical Performance Battery).
Statistical methods
Characteristics at baseline and presence of health conditions were compared between different gait speed groups using the ANOVA test for continuous variables and Pearson square test for categorical variables. The outcomes were reported as the relative risk and the risk difference with 95% confidence intervals and P values. Logistic regression model was used to investigate the correlation with cognitive function
Results
Gait speed was slower when participants were older or less educated The percentage of women, higher BMI, people with lower incomes, singles, smokers, and drinkers was high in the slower gait group. Also, all cognitive function scores were low and depression score was high in the group with slower walking speed. The slower walking speed showed low physical activity score and high prevalence of hypertension, osteoarthritis and osteoporosis. (Table 1)
Table 1.
General characteristics between gait speed groups (N=1,552)
| Baseline characteristic | Gait speed (m/s) | Total (1,552)) | p-value | ||
|---|---|---|---|---|---|
| T1 (460) 0.17–0.99 | T2 (657) 1.00–1.25 | T3 (435) 1.26–3.45 | |||
| Age | 77.77 | 75.97 | 74.77 | 76.17 | 0.000 |
| Education (yr) | 148 (32.2%) | 350 (53.3%) | 295 (67.8%) | 793 (51.1%) | 0.000 |
| Sex, female (%) | 301 (65.4%) | 350 (53.3%) | 171 (39.3%) | 822 (%) | 0.000 |
| BMI (kg/m2) | 24.5 | 24.6 | 23.9 | 24.4 | 0.001 |
| SES1; income > 2,000,000 | 67 (16.2%) | 182 (30.6%) | 155 (38.3%) | 404 (28.6%) | 0.000 |
| Living alone | 213 (46.3%) | 218 (33.2%) | 118 (27.1%) | 549 (35.4%) | 0.000 |
| Smoker | 321 (69.8%) | 412 (62.7%) | 232 (53.3%) | 965 (62.2%) | 0.000 |
| Alcohol drinker | 166 (36.1%) | 180 (27.4%) | 89 (20.5%) | 435 (28.0%) | 0.000 |
| Cognitive function | |||||
| MMSE-score | 23.81 | 25.74 | 26.62 | 25.42 | 0.000 |
| Memory score | 14.70 | 17.02 | 17.89 | 16.58 | 0.000 |
| TMT12 | 23.97 | 24.71 | 24.90 | 24.53 | 0.000 |
| Recall-score | 4.67 | 5.64 | 6.03 | 5.46 | 0.000 |
| Recog-score | 7.85 | 8.72 | 8.90 | 8.51 | 0.000 |
| Span-score | 8.90 | 10.76 | 12.10 | 10.58 | 0.000 |
| Fab-score | 11.83 | 13.43 | 14.42 | 13.23 | 0.000 |
| Depression; SGDSK-score | 131 (28.5%) | 93 (14.2%) | 27 (6.2%) | 251 (16.2%) | 0.000 |
| Physical activity score | |||||
| PA (MET-hr) | 166 (36.8%) | 350 (53.8%) | 252 (58.5%) | 768 (50.1%) | 0.000 |
| Comorbidities | |||||
| HTN | 309 (67.2%) | 384 (58.4%) | 206 (47.4%) | 899 (57.9%) | 0.000 |
| Dyslipidemia | 142 (30.9%) | 203 (30.9%) | 116 (26.7%) | 461 (29.7%) | 0.030 |
| Angina | 39 (8.5%) | 50 (7.6%) | 18 (4.1%) | 107 (6.9%) | 0.015 |
| OA4 | 165 (35.9%) | 172 (26.2%) | 77 (17.7%) | 414 (26.7%) | 0.000 |
| Osteoporosis | 109 (23.7%) | 102 (15.5%) | 38 (15.3%) | 249 (16.0%) | 0.000 |
| DM5 | 114 (24.8%) | 132 (20.1%) | 80 (18.4%) | 326 (21.0%) | 0.134 |
| Kidney disease | 14 (3.0%) | 10 (1.5%) | 4 (0.9%) | 28 (1.8%) | 0.043 |
1. Socioeconomic status; 2. Trail making test; 3. Short Physical Performance Battery; 4. Osteoarthritis; 5) Diabetes mellitus
Among the seven cognitive functions (MMSE, memory, TMT, Recall, Recognition, digit span, and Fab), only TMT showed no significant difference between different gait speed groups. The other six cognitive functions showed higher results in the fastest gait speed group (T3), Participants in middle gait speed group (T2) also showed higher results in five of the seven cognitive function scores as well (Memory, Recall, Recognition, digit span, and Fab). (Table 2)
Table 2.
Adjusted results of Logistic Regression (N=1,552)
| Characteristics | OR | 95% CI | P value | |
|---|---|---|---|---|
| MMSE | T1 | |||
| T2 | 0.738 | (0.534~1.021) | 0.066 | |
| T3 | 0.429 | (0.278~0.661) | 0.000 | |
| Age | 1.074 | (1.033~1.115) | 0.000 | |
| Sex | 0.873 | (0.525~1.452) | 0.601 | |
| BMI | 0.927 | (0.683~1.257) | 0.626 | |
| Education | 0.227 | (0.162~0.318) | 0.000 | |
| Depression | 1.429 | (1.013~2.014) | 0.042 | |
| SES (Income > 2,000,000) | 0.570 | (0.372~0.875) | 0.010 | |
| Living alone | 0.787 | (0.566~1.094) | 0.154 | |
| Smoker | 0.791 | (0.492~1.271) | 0.332 | |
| Alcohol drinker | 0.947 | (0.687~1.306) | 0.740 | |
| PA | 0.850 | (0.637~1.134) | 0.269 | |
| HTN | 0.763 | (0.566~1.1027) | 0.074 | |
| Dyslipidemia | 0.951 | (0.822~1.099) | 0.494 | |
| Angina | 1.164 | (1.053~1.286) | 0.003 | |
| OA | 0.869 | (0.715~1.056) | 0.159 | |
| Osteoporosis | 0.996 | (0.887~1.118) | 0.943 | |
| DM | 0.870 | (0.697~1.084) | 0.214 | |
| Kidney disease | 1.239 | (0.968~1.587) | 0.089 | |
| Memory | T1 | |||
| T2 | 0.599 | (0.450~0.798) | 0.000 | |
| T3 | 0.466 | (0.333~0.651) | 0.000 | |
| Age | 1.099 | (1.065~1.134) | 0.000 | |
| Sex | 0.546 | (0.362~0.823) | 0.004 | |
| BMI | 0.790 | (0.614~1.017) | 0.068 | |
| Education | 0.518 | (0.396~0.679) | 0.000 | |
| Depression | 1.520 | (1.096~2.108) | 0.012 | |
| SES (Income > 2,000,000) | 0.772 | (0.580~1.027) | 0.075 | |
| Living alone | 0.851 | (0.637~1.135) | 0.271 | |
| Smoker | 1.218 | (0.845~1.757) | 0.290 | |
| Alcohol drinker | 0.948 | (0.716~1.255) | 0.709 | |
| PA | 0.770 | (0.608~0.975) | 0.030 | |
| HTN | 1.017 | (0.799~1.295) | 0.890 | |
| Dyslipidemia | 0.942 | (0.833~1.066) | 0.344 | |
| Angina | 1.006 | (0.917~1.105) | 0.896 | |
| OA | 0.945 | (0.804~1.111) | 0.495 | |
| Osteoporosis | 0.960 | (0.858~1.073) | 0.471 | |
| DM | 0.996 | (0.821~1.209) | 0.970 | |
| Kidney disease | 1.172 | (0.945~1.455) | 0.149 | |
| TMT (Trail Making Test) | T1 | |||
| T2 | 1.052 | (0.783~1.414) | 0.737 | |
| T3 | 1.131 | (0.796~1.607) | 0.491 | |
| Age | 1.028 | (0.995~1.063) | 0.096 | |
| Sex | 3.494 | (2.199~5.552) | 0.000 | |
| BMI | 1.060 | (0.814~1.381) | 0.666 | |
| Education | 0.468 | (0.356~0.614) | 0.000 | |
| Depression | 1.043 | (0.757~1.438) | 0.797 | |
| SES (Income > 2,000,000) | 0.721 | (0.528~0.986) | 0.041 | |
| Living alone | 0.974 | (0.732~1.295) | 0.854 | |
| Smoker | 1.559 | (1.010~2.408) | 0.045 | |
| Alcohol drinker | 1.130 | (0.855~1.495) | 0.390 | |
| PA | 1.103 | (0.863~1.411) | 0.432 | |
| HTN | 0.992 | (0.771~1.276) | 0.950 | |
| Dyslipidemia | 0.966 | (0.847~1.102) | 0.604 | |
| Angina | 0.952 | (0.865~1.047) | 0.309 | |
| OA | 1.020 | (0.864~1.204) | 0.814 | |
| Osteoporosis | 0.987 | (0.881~1.105) | 0.819 | |
| DM | 1.166 | (0.938~1.450) | 0.165 | |
| Kidney disease | 1.177 | (0.934~1.483) | 0.166 | |
| Recall | T1 | |||
| T2 | 0.633 | (0.477~0.839) | 0.001 | |
| T3 | 0.537 | (0.388~0.745) | 0.000 | |
| Age | 1.087 | (1.054~1.121) | 0.000 | |
| Sex | 0.722 | (0.484~1.076) | 0.110 | |
| BMI | 0.800 | (0.625~1.024) | 0.077 | |
| Education | 0.607 | (0.467~0.789) | 0.000 | |
| Depression | 1.398 | (1.014~1.929) | 0.041 | |
| SES (Income > 2,000,000) | 0.934 | (0.708~1.233) | 0.630 | |
| Living alone | 0.785 | (0.593~1.040) | 0.092 | |
| Smoker | 1.118 | (0.781~1.602) | 0.542 | |
| Alcohol drinker | 0.786 | (0.598~1.033) | 0.084 | |
| PA | 0.834 | (0.662~1.050) | 0.123 | |
| HTN | 1.102 | (0.871~1.395) | 0.418 | |
| Dyslipidemia | 0.873 | (0.771~0.989) | 0.032 | |
| Angina | 1.014 | (0.924~1.111) | 0.774 | |
| OA | 0.928 | (0.791~1.090) | 0.364 | |
| Osteoporosis | 0.951 | (0.853~1.061) | 0.368 | |
| DM | 1.041 | (0.860~1.261) | 0.679 | |
| Kidney disease | 1.133 | (0.921~0.921) | 0.239 | |
| Recognition | T1 | |||
| T2 | 0.591 | (0.446~0.782) | 0.000 | |
| T3 | 0.592 | (0.425~0.825) | 0.002 | |
| Age | 1.064 | (1.032~1.098) | 0.000 | |
| Sex | 0.911 | (0.607~1.367) | 0.653 | |
| BMI | 1.012 | (0.786~1.303) | 0.927 | |
| Education | 0.709 | (0.543~0.927) | 0.012 | |
| Depression | 1.164 | (0.849~1.595) | 0.345 | |
| SES (Income > 2,000,000) | 0.984 | (0.736~1.315) | 0.914 | |
| Living alone | 0.878 | (0.661~1.165) | 0.367 | |
| Smoker | 0.907 | (0.629~1.307) | 0.599 | |
| Alcohol drinker | 1.089 | (0.826~1.436) | 0.545 | |
| PA | 0.929 | (0.734~1.177) | 0.544 | |
| HTN | 1.225 | (0.962~1.561) | 0.100 | |
| Dyslipidemia | 0.962 | (0.850~1.089) | 0.541 | |
| Angina | 0.965 | (0.878~1.061) | 0.463 | |
| OA | 0.967 | (0.817~1.144) | 0.693 | |
| Osteoporosis | 0.881 | (0.777~0.995) | 0.046 | |
| DM | 1.025 | (0.841~1.248) | 0.809 | |
| Kidney disease | 1.106 | (0.904~1.353) | 0.330 | |
| Digit span | T1 | |||
| T2 | 0.599 | (0.444~0.809) | 0.001 | |
| T3 | 0.427 | (0.302~0.604) | 0.000 | |
| Age | 1.057 | (1.023~1.092) | 0.001 | |
| Sex | 1.245 | (0.820~1.889) | 0.304 | |
| BMI | 0.956 | (0.733~1.245) | 0.738 | |
| Education | 0.295 | (0.226~0.385) | 0.000 | |
| Depression | 1.463 | (1.037~2.065) | 0.030 | |
| SES (Income > 2,000,000) | 0.721 | (0.537~0.966) | 0.029 | |
| Living alone | 0.732 | (0.545~0.983) | 0.038 | |
| Smoker | 0.783 | (0.535~1.146) | 0.208 | |
| Alcohol drinker | 1.306 | (0.975~1.749) | 0.073 | |
| PA | 1.072 | (0.836~1.374) | 0.585 | |
| HTN | 0.940 | (0.730~1.210) | 0.629 | |
| Dyslipidemia | 0.950 | (0.834~1.081) | 0.435 | |
| Angina | 1.062 | (0.954~1.183) | 0.268 | |
| OA | 1.086 | (0.894~1.320) | 0.407 | |
| Osteoporosis | 0.920 | (0.820~1.032) | 0.154 | |
| DM | 0.804 | (0.647~1.001) | 0.051 | |
| Kidney disease | 1.305 | (0.941~1.809) | 0.110 | |
| Fab (Frontal assessment battery) | T1 | |||
| T2 | 0.529 | (0.393~0.712) | 0.000 | |
| T3 | 0.402 | (0.279~01579) | 0.000 | |
| Age | 1.051 | (1.015~1.087) | 0.005 | |
| Sex | 1.365 | (0.867~2.151) | 0.179 | |
| BMI | 0.853 | (0.648~1.123) | 0.257 | |
| Education | 0.285 | (0.215~0.378) | 0.000 | |
| Depression | 1.717 | (1.234~2.390) | 0.001 | |
| SES (Income > 2,000,000) | 0.723 | (0.517~1.012) | 0.059 | |
| Living alone | 0.851 | (0.630~1.148) | 0.290 | |
| Smoker | 0.964 | (0.631~1.471) | 0.865 | |
| Alcohol drinker | 1.136 | (0.845~1.528) | 0.397 | |
| PA | 1.013 | (0.783~1.312) | 0.919 | |
| HTN | 0.979 | (0.752~0.752) | 0.876 | |
| Dyslipidemia | 0.918 | (0.803~0.803) | 0.214 | |
| Angina | 1.113 | (1.006~1.006) | 0.038 | |
| OA | 1.022 | (0.866~0.866) | 0.794 | |
| Osteoporosis | 0.924 | (0.825~0.825) | 0.176 | |
| DM | 0.923 | (0.755~0.755) | 0.437 | |
| Kidney disease | 1.087 | (0.882~0.882) | 0.434 | |
In addition to walking speed, the MMSE showed a significant relationship with age, duration of education, and angina. Memory was significantly related to age, sex, and duration of education. Although TMT had no significant correlation with gait speed, it was significantly related to gender and the duration of education. The recall function and digit span were also significantly related to age and the duration of education as well. The recognition functions were significantly different among the different age groups. Lastly, Fab was the only cognitive function that was significantly related to the depression score besides age and the duration of education. (Table 2)
Discussion
Normal gait is not a simple repetition of movement, but it rather consists of several functions of different parts of the brain including the frontal lobe that establishes the destination and direction of regular motions of upper and lower extremities. (9) It also requires the basal ganglia to properly work for automatization and cerebellum which manages coordination. The spinal cords and peripheral nerves also must be mutually and fluently coordinated as well. A malfunction of any of these organs could result in gait abnormalities (10).
Of all parts of different functions involved, the executive function and attention which are mediated by the frontal lobe play an important role (11). Some studies that investigated the relationship between gait and executive function have shown that the prefrontal volume is associated with decreased gait. In addition, they also reported the association between the gray matter changes in the cognitive function area with gait change (12). Behavioral studies also showed that walking while performing dual tasks reduced walking speed and increased dysrythmicity (13). In healthy young adults, when performing difficult double tasks, the walking speed appeared to have decreased. The results of these studies can be interpreted as that all gait depends on the cognitive function, particularly on the ones associated with the frontal and prefrontal lobe (14).
In this study, we investigated the differences of cognitive functions according to different walking speed groups. We examined seven different cognitive functions among the different gait speed groups. Among the seven dependent variables, five of them were found to be significantly related to gait speed.
We predicted that the frontal lobe dysfunction would be most prominent among the various cognitive functions. This was confirmed by the fact that the frontal assessment battery (FB), which assesses the frontal lobe function, degraded to the greatest extent as gait speed decreased. MMSE showed a relatively large change in T3 group. T2 group, however, showed no significant differences compared to the normal gait group. Also, age, education level, and depression were the most influential variables in cognitive function (15).
Recent studies continuously report that a decrease in the executive function of the frontal lobe is responsible for postural instability (10). Thus, several studies have suggested that the mechanism associated with the decline of the frontal lobe may be related to the decrease in gait. In this study, we found a potential use for slower gait speed as a predictor of frontal lobe dysfunction (16). There is, however, also a possibility that the decline in gait speed is a result of simple frailty of the elderly population. Therefore, other exercise functions such as grip strength and muscle mass should be taken into account and judged comprehensively (17).
The limitations of this study were as follows. First, was that the analysis of gait speed was not differentiated by gender (18). However, Hall et al. (2004) and some other studies have shown that energy costs caused by walking are similar for males and females, thus we felt it would be unnecessary separately analyze the gait speed of male and female. Second, this study was cross-sectional, so we could not prove causal relationship.
In conclusion, we found that gait speed was significantly related with cognitive function, especially with frontal lobe function. So well designed further study including follow-up survey will be needed to find the causal relationship.
Conclusion
In this study, we found correlation between the slower gait speeds and the decrease in cognitive function, and especially the frontal lobe dysfunction was most prominent of all cognitive dysfunctions. Therefore, we recommend that geriatric rehabilitation should include not only gait training and strengthening of leg muscles, but also training with frontal and general cognitive function for better performance.
Acknowledgement
This research was supported by a grant of the Korea Health Technology R&D Project through the Korean Health Industry Development Institute (KHIDI), funded by the Ministry of Health and Welfare, Republic of Korea (grant number:HI15C3153).
Conflict of Interest
Dr. Seo has nothing to disclose
Ethical Standards
All parties involved in the act of publishing in The Journal of Nursing Home Research including the author, the journal editor, the peer reviewer and the publisher agree upon standards of expected ethical behavior.
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