Open Journal of Therapy and Rehabilitation, 2022, 10, 1-8
https://www.scirp.org/journal/ojtr
ISSN Online: 2332-1830
ISSN Print: 2332-1822

Correlations between Motor Ability with Gait
Speed and Cognitive Functions in
Rehabilitation Users
Hiroya Miyabara1*, Seigo Koura1, Moemi Matsuo1, Makoto Uchinoura2, Yuki Kishikawa1,
Yuji Yamaguchi1, Youhei Komatsu1, Seijiro Nishimura2, Shinichi Shibata2, Hajime Shibata2
Faculty of Rehabilitation, Nishikyusyu University, Kanzaki, City, Japan
Kurume Rehabilitation Hospital, Kurume City, Japan1
2

How to cite this paper: Miyabara, H., Koura, S., Matsuo, M., Uchinoura, M., Kishikawa, Y., Yamaguchi, Y., Komatsu, Y., Nishimura, S., Shibata, S. and Shibata, H. (2022)
Correlations between Motor Ability with Gait
Speed and Cognitive Functions in Rehabilitation Users. Open Journal of Therapy andRehabilitation, 10, 1-8.
https://doi.org/10.4236/ojtr.2022.101001
Received: November 25, 2021
Accepted: January 3, 2022
Published: January 6, 2022
Copyright © 2022 by author(s) and
Scientific Research Publishing Inc.
This work is licensed under the Creative
Commons Attribution International
License (CC BY 4.0).
http://creativecommons.org/licenses/by/4.0/
Open Access

Abstract
Purpose: To compare and examine motor and cognitive functions in people
who require support, and in healthy elders. Method: The variables of age,
BMI, educational background, blood pressure, grip strength, knee extension,
gait speed, MMSE, and subjective health feeling for 36 rehabilitation users
and 22 healthy elders were assessed. We compared and examined motor andcognitive functions in rehabilitation users who need support and healthy elders. Results: The percentage of MMSE scores with 27 points or higher andthat of subjective health feeling with 3 points or higher were significantly
higher in healthy elders than in rehabilitation users. Systolic and diastolic bloodpressure were significantly higher in rehabilitation users than in healthy elders. Gait speed and MMSE scores were significantly higher in healthy elders
than rehabilitation users. Conclusion: Gait speed could be used for physicalfitness in elders. Gait speed was the best physical fitness measurement for elders. Gait speed of rehabilitation users was strongly related to MMSE scores.
Gait speed could be a determinant of MMSE scores.

Keywords
Elderly, Gait Speed, Motor Ability, Rehabilitation Users,
The Long-Term Care Insurance

1. Introduction
The gait speed test is an easy assessment tool that widely used for the aging researches [1]. Moreover, it can predict a future decrease in activities of daily livDOI: 10.4236/ojtr.2022.101001 Jan. 6, 2022

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H. Miyabara et al.

ing (ADL), and also elderly people’s motor functions including muscle strength,balance and flexibility are able to represent walking velocity [2]. In addition, it
was reported that elderly people’s functional capacity was predictable by their
gait speed [3]. Furthermore, the decrease in gait speed is a common process inaging and is often associated with several adverse health effects, such as weakness [4], falls [5], hospitalizations [6] and poor quality of life [7]. Gait speed has
been directly related to cognitive abilities of an individual [8] [9] and it is considered an indicator of elderly who are at high risk for the cognitive decline [10][11].
Based on these, it might be possible that gait speed can be a predictive factor
of inclusive physical functions. In the present study, we examined relations between gait speed, motor ability and cognitive functions in rehabilitation users
who need supports and in healthy elders to clarify the facts. Thus, the objectiveof present study is to clarify the relationship between gait speed and motor ability, Mini-Mental State Examination (MMSE) for 36 elderly persons who use
day-service rehabilitation.

2. Subject and Methods
2.1. Participants
Thirty-six rehabilitation users (81.3 ± 5.7 years; 11 males and 26 females) and 22
healthy elders (79.1 ± 4.6 years; 7 males and 15 females) participated in thisstudy. 59 subjects accepted the invitation of which 58 subjects could be includedin the present study. The remaining 1 subjects were excluded owing to missing
details about physical activity (n = 1).
The present investigation was approved by Kurume Rehabilitation Hospital
Ethical Review Board for Medical Research Involving Human Subjects (ethicalnumber: 21-001). Collected data included the socio-demographic characteristics(e.g., gender, age, educational background), anthropometric measurements (e.g.,height, weight). Body mass index (BMI) was calculated by dividing the weight inkilogram by height in meter squared (Table 1).

2.2. Methods
We measured height and weight as the physique items and hand grip strength,
gait speed test as motor ability items. We evaluated hand grip strength by a mechanical dynamometer with a dominant hand. We asked participants to walk on
the straight walkway which consists of 11 m in length on the flat floor once attheir preferred velocity. Gait speed was measured over a 5 m distance which was
between 3 m to 8 m from the start line.
Cognitive function was assessed using a 30-question of MMSE; each correctly
answered question was awarded one point, whereas incorrect or no answers wereawarded zero points. The total score ranged from 0 to 30 points.
This work was supported by the Kabutoyama MS Limited company R, Japan(Kurume Rehabilitation Hospital, NO. 21-001).
DOI: 10.4236/ojtr.2022.101001

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Table 1. Demographic characteristics of participants.
Rehabilitation users(n = 36)

Healthy elders(n = 22)Male

11 (31)7 (32)

Female25 (69)15 (68)Junior school

17 (47)

2 (10)High school

19 (53)14 (63)

University―

6 (27)

Needs 128 (78)―

Needs 28 (22)―

Cerebrovascular disorders

8 (22.2)―

Bone and joint disorders

5 (13.8)―

Heart disorders

1 (2.8)―Hypertension

17 (47.2)

17 (47.3)

Diabetes mellitus

4 (11.1)―

Hyperlipidemia

1 (2.8)―Characteristics
Gender

Educational background

Level of care needed

Types of diseases

Numbers (%).

2.3. Statistics
IBM SPSS Statistics version 26.0 (SPSS Inc., Chicago, IL, USA) was used for statistical analysis. In this study, all continuous variables are presented as the mean ±standard deviation (SD) and categorical data are presented as numbers (percentages). Pair analyses were carried out using unpaired Student’s t-tests. Correlations were analyzed by Pearson’s correlation coefficient among continuous variables. After all, multiple regression analysis was performed for gait speed. The
level of significance was set as P < 0.05*.

3. Results
Table 1 provides an overview of the participants (rehabilitation users; 11 males
and 25 females and healthy elders; 7 males and 15 females). The mean age of thesample was 81.3 years. Seventy-eight percentages of rehabilitation users (78%)
were needed support 1 and forty-seven (47%) were with hypertension. Rehabilitation users had significantly higher systolic blood pressure (p < 0.05) and diastolic blood pressure (p < 0.05) than healthy elders. Healthy elders had significantly faster gait speed (p < 0.05) and better MMSE scores (p < 0.05) than rehabilitation users (Table 2). Gait speed of rehabilitation users showed significant
correlation with MMSE scores (r = 0.50, p < 0.01) (Table 3). Table 4 shows the
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H. Miyabara et al.
Table 2. Comparison of variables between rehabilitation users and elder.
Variables

Rehabilitation users(n = 36)

Healthy elders
P-value(n = 22)Age (year)

81.3 ± 5.7

79.1 ± 4.6

0.13

BMI (kg/m2)

23.9 ± 3.9

23.6 ± 2.6

0.75

Education (year)

10.9 ± 1.5

10.4 ± 1.5

0.40

Systolic blood pressure (mm/Hg)

142.3 ± 19.3

127.5 ± 16.6

0.01*

Diastolic blood pressure (mm/Hg)

80.6 ± 8.3

73.3 ± 10.0

0.01*

Grip strength (kg)23.8 ± 7.7

27.0 ± 9.3

0.20Knee extension strength (kg)13.1 ± 10.6

15.3 ± 8.2

0.45

Gait speed (m/second)

1.38 ± 0.4

2.48 ± 0.4

0.01

MMSE (score)

26.3 ± 3.0

28.8 ± 1.5

0.01

Notes: Values are means and SDs, BMI = body mass index; MMSE = mini-mental state
examinations. *P < 0.05 by unpaired student’s t-tests.
Table 3. Correlation coefficient between gait speed and variables.
Rehabilitation users

Variables

Healthy elders

Gait speed (ρ)

P-value

Gait speed (ρ)

P-value

Age

−0.33

0.07

0.29

0.27

BMI

0.22

0.25

0.28

0.29

Systolic blood pressure

0.12

0.50

0.20

0.44

Diastolic blood pressure

0.20

0.28

0.35

0.18

Grip strength

0.35

0.06

−0.25

0.34

Knee extension strength

0.35

0.62

0.11

0.67

MMSE

0.50

0.001*

0.08

0.77

Notes: Values are means and SDs, BMI = body mass index; MMSE = mini-mental state
examinations. *P < 0.05 by person’s correlation coefficient.
Table 4. Multiple regression analysis for gait speed.
Rehabilitation users

Healthy elders

βP-valueβP-value

Age

−0.33

0.07

0.29

0.27

Grip strength

0.35

0.06

−0.25

0.34

MMSE

0.50

0.001*

0.08

0.77

Variables

Notes: MMSE = mini-mental state examinations. *P < 0.05 by multiple correlation coefficient. β: multiple correlation coefficient adjusted for the degrees of freedom. β = 0.50, P <0.001, R = 0.97, R2 = 0.94 (gait speed of rehabilitation users). β = 0.08, P = 0.08, R = 0.39,
R2 = 0.15 (gait speed of elders).
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results of the multiple regression models. Gait speed of rehabilitation users wasstrongly related to MMSE scores, and the determinant of gait speed was MMSE
scores.

4. Discussion
In the present study, we examined motor ability and cognitive functions among
rehabilitation users and healthy elders. The previous studies have shown thatgait speed was taking part in 44% smaller in Rehabilitation users compared withelders [12], and the study which compared cognitive performance and gait speedof elders have shown that rehabilitation users with lower mean cognitive scores
were also with lower gait speed [8] [9] [10] [11]. Regarding gait speed, the Brazilian study which investigated pre-frailty and factors associated with this condition, identified significant relationship between slowness of gait and low cognitive functions in elders, and suggested that gait speed could be considered as oneof the markers, which was able to be used to assess cognitive functions [13]. Considering them, the importance of cares for elders regarding instructing of physical exercise to avoid progressive loss of muscle mass and to maintain proper gait
sped were emphasized [14].
Younger individuals, walking is normally an automatic task, the, the cognitiveand conscious component of gait control becomes progressively more importantwith ageing, possibly to compensate for sensory-motor deficits [15] [16]. Paradoxically, however, decline in the both cognitive and physical function is common in elderly persons. The interrelated decline of cognition and mobility is
postulated to be due to underlying shared neural substrates [17] [18] [19]. For
example, neuroimaging studies have shown that gait and mobility deficits are
frequently encountered in elderly persons with atrophy of temporal lobe [17]and prefrontal area [18]. Additionally, both global cognition and gait speed havebeen associated with atrophy of corpus callosum [19]. Our findings are only partially supportive of these conclusions. In the linear regression model, usual gait
speed was only a borderline predictor of an accelerated cognitive (Table 4).
In the investigation results of characteristics in rehabilitation users, 47% werewith up to junior high school in the educational background, and the higher ratio of current medical history showed the results below; 1st was hypertension(47.2%), 2nd was cerebrovascular disorder (22.2%), and 3rd was osteoarthritis(13.8%). According to the classification of O’ Bryant et al., the percentage of
people requiring support was calculated with 26 points or less as MCI [20]. Thus,
more than half, 55.6% were with MCI. According to the Ministry of Health, Labor and Welfare in Japan, the worst cause of needs for long-term care according
to the degree of long-term care in 2010 was osteoarthritis (19.4%), cerebrovascular disorder (24.1%) with that requiring long-term care. Dementia was themost common condition, followed by 20.5% [20].
High blood pressure in certain circumstances and low blood pressure havebeen associated with cognitive decline and dementia in community-based stuDOI: 10.4236/ojtr.2022.101001

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H. Miyabara et al.

dies, suggested that blood pressure may serve as a viable target for primary or
secondary dementia prevention [21]. On the other hand, accumulating evidence
suggested that hypertension during midlife may be a risk factor for cognitive decline and dementia [22]. Although relationships of elevated blood pressure during the 7th, 8th and 9th decades of life with cognitive outcomes have not known
yet, several studies indicated that optimal blood pressure ranges for older adults
might have depended on earlier blood pressure characteristics [23].
Likewise, cognitive stimulation is essential for elders with hypertension, which
tend to have reduced gait speed and worse cognitive performance. As contributions of this research, it was expected that the results could guide geriatric nursing care about detection of changes in cognitive or physical performance of elders, coping with health events such as physical frailty syndrome. Moreover, it has
a potential to support discussion on planning of interventions that provide positive results for quality of life in this age group.

5. Conclusion
In summary, gait speed could be used for physical fitness in elderly. Gait speed
was the best physical fitness measure for elderly. Gait speed of Rehabilitation
users was strongly related to MMSE scores. The determinant at Gait speed was
MMSE scores.

Acknowledgements
The authors express sincere thanks to the members of the research and volunteers who participated as subjects.

Conflicts of Interest
The authors declare no conflicts of interest regarding the publication of this paper.

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