The effects of balance and gait function on quality of life of stroke patients

Abstract

BACKGROUND:

Stroke patients have a lower quality of life than other people.

OBJECTIVE:

The purpose of this study was to examine the effect of balance and gait function of stroke patients on their quality of life.

METHODS:

Twenty-seven subjects participated in the experiment. Balance ability was assessed using a SpaceBalance 3D and a Berg Balance Scale (BBS). Gait function was measured with a Biodex Gait Trainer 2 treadmill system. The quality of life of the subjects was assessed through the Stroke specific Quality of Life Scale (SS-QOL).

RESULTS:

Correlation analysis between balance and quality of life showed that weight bearing distribution and BBS are positive correlated with quality of life. In addition, gait speed, step length of the paretic limb, and step length of the non-paretic limb were also found to be correlated with quality of life.

CONCLUSION:

Balance and gait function must all be considered in order to improve the quality of life of stroke patients.

Keywords

Balance gait quality of life stroke

1. Introduction

Stroke patients have a lower quality of life than other people (Gunaydin, Karatepe, Kaya & Ulutas, 2011). This is because of emotional and physical changes (Clarke, Lawrence & Black, 2000). These factors, which stroke patients must face, are problematic in everyday life, like driving and work skills, affecting the quality of life of each individual (Gunaydin et al., 2011). In particular, reduced balance and gait function, together with social isolation within the community, affects the quality of life (Ada, Dean, Hall, Bampton & Crompton, 2003; Dean, Richards & Malouin, 2000). This suggests that improving balance and gait function will improve the quality of life of stroke patients (Garland, Ivanova & Mochizuki, 2007).

Many research is being carried out to improve the quality of life of stroke patients. An examination of analytical research on the factors related to the quality of life of stroke patients shows that emotional factors are more important than physical factors. In particular, it was reported that quality of life changes depending on the influence of depression and social activities of stroke patients (Niemi, Laaksonen, Kotila & Waltimo, 1988). In contrast, King (1996) reported that the main factor involved in the quality of life of stroke patients was physical functioning. In a study which examined changes in quality of life by improving physical function, it was reported that fifty stroke patients who did strength training on the paretic side, improved muscle strength on both the paretic and non-paretic sides, which in turn improved balance and gait function and quality of life (Şen, Demir, Ekiz, & Özgirgin, 2015). In addition, research results show a correlation between balance ability and quality of life. It was reported that the increase in falls associated with loss of balance reduces the quality of life (Schmid et al., 2013).

These studies demonstrate the relationship between stroke patients’ balance ability and their quality of life. However, most previous studies have focused only on balance and gait training for stroke patients to improve their quality of life. Furthermore, the gait of stroke patients when walking, shows variations in spatio-temporal elements and kinematic elements due to musculoskeletal problems associated with lesions. In particular, the difference between the paretic and non-paretic lower limbs, and reductions in lower limb support time, gait speed and endurance all cause problems (Balasubramanian, Bowden, Neptune & Kautz, 2007; Jung, Lee, Charalambous & Vrongistinos, 2010; Kim & Eng, 2003). However research on how these spatial and temporal variables on gait function affect quality of life is rare.

Therefore, in this study, the relationship between stroke patients’ balance ability and various gait parameters and quality of life was investigated in order to provide information on what factors should be considered for improving the quality of life of stroke patients when providing therapeutic intervention to stroke patients in clinical settings.

2. Methods

2.1. Participants

Twenty seven stroke patients, who were receiving rehabilitation treatment between January and February 2017. The subjects informed written consent for participation was obtained. The study was conducted in accordance with the Declaration of Helsinki. Table 1 summarizes the subjects general characteristics.

Table 1
General characteristics of subjects (N = 27)

Age (years) 52.7±9.7 a

Gender
Male
Female
17(63%)
10(37%)

Time since stroke (months) 12.1±4.2

Type of lesion
Hemorrhagic
Infarction
8(30%)
19(70%)

Side of lesion
Right
Left
12(44%)
15(56%)

Height (cm) 166.3±8.9

Weight (kg) 66±9.4

^aMean±SD.

The inclusion criteria for participating in the study were as follows: 1) Subjects were able to walk ten meters without walking aids. 2) Subjects had no visual and auditory impairments such as amblyopia, vertigo, and vestibular disorders. 3) Subjects had no orthopedic problems that could affect gait in the lower limbs. 4) Subjects scored 24 or higher on the Korean version of Mini-Mental State Examination (MMSE-K). 5) Subjects had no abnormal blood pressure, pulse, and breathing after walking for six minutes. Subjects were excluded from the study if they had a medical problem that would interfere with the research such as unilateral neglect.

2.2. Procedures

In order to measure the static balance ability of all subjects, the weight bearing distribution of the paretic side was measured by subjects maintaining a standing position on a SpaceBalance 3D (SpaceBalance 3D, CyberMedic Co., Ltd., Iksan, Korea). The Berg Balance Scale (BBS) was used to measure dynamic balance ability. Measurement of spatio-temporal gait parameters was done with a Biodex Gait Trainer 2 (Biodex Medical System Inc., NY, USA). After walking, the quality of life of the subjects was assessed through completing the Stroke specific Quality of Life Scale (SS-QOL).

2.3. Assessment

SpaceBalance 3D was used to evaluate the balance ability of the subjects. This study evaluated the weight bearing distribution on the paretic side during static standing to confirm the weight bearing distribution of standing posture. The BBS is mainly used in clinical practice to measure the balance ability of stroke patients.

The Biodex Gait Trainer 2 was used to measure subjects gait parameters. This equipment consists of a floor that can measure gait parameters, a monitor which provides visual feedback, and speakers which provide auditory feedback. Measurable gait parameters are gait speed, gait cycle, paretic and non-paretic side step length, and weight bearing distribution of the paretic and non-paretic sides. Before measurements were taken, subjects practiced walking for three minutes in order to familiarize themselves with the Biodex Gait Trainer 2. General information about the subject was input into the Trainer, and gait training was performed for five minutes. The measured kinematic gait parameters by this equipment were statistically analyzed.

Questionnaires were used to assess the quality of life of stroke patients. The Stroke specific Quality of Life Scale (SS-QOL) is split up into twelve sections with forty nine items in total. The twelve sections are mobility, energy, upper extremity function, work/productivity, mood, self-care, social roles, family roles, vision, language, thinking, and personality (Williams, Weinberger, Harris, Clark & Biller, 1999).

3. Statistical analysis

PASW 18.0 version for window (PASW Inc., Chicago) was used for statistical analysis of the measured values of the subjects. Spearman’s correlation analysis was performed to analyze the correlation between subjects balance ability and gait parameters and quality of life. The significance level was set to 0.05.

4. Results

4.1. Correlation between balance and quality of life

The analysis of the correlation between subjects balance ability and quality of life showed that improvement in the weight bearing distribution on the paretic side was positively correlated with quality of life, as the correlation coefficient for weight bearing distribution on the paretic side was 0.548. The correlation analysis results for the BBS and quality of life showed that improvement in the BBS was associated with improvement in quality of life, as the correlation coefficient between the BBS and quality of life was 0.735 (p < .05) (Table 2).

Table 2
Correlation of balance and quality of life (N = 27)

	Weight distribution (affected)	BBS a
SS-QOL b	.548 *	.735 *

^*p < .05. ^aBerg Balance Scale. ^bStroke-Specific Quality of Life.

4.2. Correlation between gait parameters and quality of life

The correlation analysis results for the subjects gait parameters and quality of life showed there was a positive correlation between the quality of life components of mobility, upper extremity function, social roles, family roles, thinking, and among the gait parameters, those of gait speed, paretic side step length, and non-paretic side step length(p < .05). There was no correlation between the step cycle and weight bearing distribution and quality of life items while walking (p > .05)(Table 3).

5. Discussion

The purpose of this study was to examine the relationship between balance and gait function of stroke patients and quality of life, in order to present information on what factors should be considered in the rehabilitation of stroke patients to improve their quality of life.

Table 3
Correlation of gait parameters and quality of life (N = 27)

Gait speed Step cycle Step length (affected) Step length (unaffected) Time on each foot (affected) Time on each foot (unaffected)

Mobility .583 * .217 .507 * .489 * .211 -.211

Energy .228 -.132 .292 .237 -.119 .119

Upper extremity function .559 * .264 .431 * .498 * .189 -.189

Work/productivity .348 .119 .316 .337 .144 -.144

Mood .172 .442 * .100 .095 -.095 .095

Self care .561 * .032 .453 * .519 * .277 -.277

Social roles .522 * -.148 .548 * .553 * .123 -.123

Family roles .562 * .311 .510 * .474 * .289 -.289

Vision .358 -.016 .335 .366 -.027 .027

Language .175 -.168 .193 .158 .135 -.135

Thinking .484 * -.091 .470 * .512 * .150 -.150

Personality .046 .366 -.013 -.145 -.013 .013

Total score .536 * .192 .446 * .471 * .125 -.125

	Gait speed	Step cycle	Step length (affected)	Step length (unaffected)	Time on each foot (affected)	Time on each foot (unaffected)
Mobility	.583 *	.217	.507 *	.489 *	.211	-.211
Energy	.228	-.132	.292	.237	-.119	.119
Upper extremity function	.559 *	.264	.431 *	.498 *	.189	-.189
Work/productivity	.348	.119	.316	.337	.144	-.144
Mood	.172	.442 *	.100	.095	-.095	.095
Self care	.561 *	.032	.453 *	.519 *	.277	-.277
Social roles	.522 *	-.148	.548 *	.553 *	.123	-.123
Family roles	.562 *	.311	.510 *	.474 *	.289	-.289
Vision	.358	-.016	.335	.366	-.027	.027
Language	.175	-.168	.193	.158	.135	-.135
Thinking	.484 *	-.091	.470 *	.512 *	.150	-.150
Personality	.046	.366	-.013	-.145	-.013	.013
Total score	.536 *	.192	.446 *	.471 *	.125	-.125

^*p < .05.

As a result, among the balance variables, weight bearing distribution on the non-paretic side and the BBS were shown to be correlated with quality of life. The result showing the paretic side’s weight bearing distribution and improvement in BBS, indicates improvement in quality of life. A common after effect of a stroke is falls due to a loss of balance, which leads to a lower quality of life (Schmid et al., 2009). In a study by Garland et al. (2007), an improvement in the balance ability of stroke patients was associated with improvement of quality of life. The results of this study also suggest that improvement in balance ability affects improvement in quality of life. This is because improvement in the weight bearing distribution of the paretic side and balance ability reduces the risk of falls in stroke patients and allows them to engage in daily life. Therefore, improving the balance ability of stroke patients should be fully considered in order to improve their quality of life.

The correlation analysis results for the gait parameters and quality of life showed that gait speed, step length on the paretic side, and step length on the non-paretic side were positively correlated with the quality of life components of mobility, upper extremity function, self-care, social roles, family roles, and thinking. There was a relationship between improved quality of life and increased gait speed and increased paretic side step length, and non-paretic side step length. Most gait training performed by stroke patients leads to an improvement in gait speed, and this improvement in gait parameters is related to the quality of life of stroke patients (Flansbjer, Downham & Lexell, 2006; Sharp & Brouwer, 1997). Improvement in gait speed is related to the step length of the paretic and non-paretic side, and increasing step length results in increased gait speed (Lin, Yang, Cheng & Wang, 2006). The reason that this increased gait speed improves quality of life is because as the gait speed increases, stroke patients say that this makes them feel more comfortable in their daily lives (Şen et al., 2015). This results of this study also showed that gait speed and quality of life were correlated. Improved gait speed in line with increased step length on both the paretic and non-paretic sides is an important factor in improving quality of life. It is suggested that this is due to patients engaging more comfortably in daily life and that they have reduced need for family and social roles.

Among the gait parameters, there was no correlation between the step cycle and weight bearing distribution and quality of life items while walking. Changes in stroke patients step cycle and weight bearing distribution during walking were shown to not affect quality of life. Among the gait parameters of stroke patients, cadence is closely related to gait speed, and when cadence increases, there is improvement in gait speed (Lin et al., 2006). In contrast, improvement in stroke patients’ cadence means that, with regard to weight bearing distribution while walking, the paretic side and non-paretic side step length becomes shorter. As weight distribution is not being done correctly during walking, there is a reduction in stance time and gait asymmetry reduces the step cycle (Park, Park, Kim & Woo, 2015). Based on these conflicting results in this study, step cycle and weight bearing distribution during walking, which was shown to be closely related to quality of life, does not affect gait speed, so it is considered that there is no correlation.

This stroke specific quality of life measurement tool consists of forty nine items in twelve sections including mobility, energy, upper extremity function, work/productivity, mood, self-care, social roles, family roles, vision, language, thinking, and personality. Because changes in balance and gait function in this study can influence only items that correspond to the quality of physical life in the twelve test areas, there can be limits to confirming correlations. Furthermore, since the tests were carried out on subjects while they were in hospital there may be a difference when they return to normal life after they are discharged. Since the measurement of the gait parameters only measured the functional gait variables and the spatial and temporal gait variables, further studies should be conducted on subjects who are engaged in daily life, and it will be necessary to research the correlation between different gait parameters and walking force.

6. Conclusion

In conclusion, balance and gait function are important factors in the quality of life of stroke patients. In order to provide clinical intervention with a focus on improving the quality of life of stroke patients, from among the balance and gait function parameters, improvement in gait speed, and step length of both the paretic and non-paretic sides should be considered.

Conflict of interest

None to report.

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Age (years)	52.7±9.7 a
Gender Male Female	17(63%) 10(37%)
Time since stroke (months)	12.1±4.2
Type of lesion Hemorrhagic Infarction	8(30%) 19(70%)
Side of lesion Right Left	12(44%) 15(56%)
Height (cm)	166.3±8.9
Weight (kg)	66±9.4