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Increasing postural sway in balance test is related to locomotive syndrome risk: A cross-sectional study
Journal of Orthopaedic Science xxx (xxxx) xxx
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Original Article
Increasing postural sway in balance test is related to locomotive syndrome risk: A cross-sectional study Satoshi Tanaka a, Kei Ando a, Kazuyoshi Kobayashi a, Tetsuro Hida b, Taisuke Seki a, Takashi Hamada a, Kenyu Ito a, Mikito Tsushima a, Masayoshi Morozumi a, Masaaki Machino a, Kyotaro Ota a, Naoki Ishiguro a, Yukiharu Hasegawa c, Shiro Imagama a, * a
Department of Orthopaedic Surgery, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan Department of Orthopaedic Surgery, Japanese Red Cross Nagoya Daini Hospital, Nagoya, Japan c Department of Rehabilitation, Kansai University of Welfare Science, Osaka, Japan b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 17 June 2018 Received in revised form 24 January 2019 Accepted 25 January 2019 Available online xxx
Background: Locomotive syndrome risk level has been recently proposed to evaluate physical ability. Impaired balance control is one of the most important risk factors for falls. However, the relationship between locomotive syndrome risk and postural sway according to the balance test is unclear. This study aimed to investigate the relationship between locomotive syndrome risk and balance test results, including muscle mass and physical function, in a large-scale prospective general health checkup. Methods: We enrolled 292 participants who underwent a basic health checkup and conducted a twostep test, stand-up test, evaluation using a 25-question geriatric locomotive function scale for the locomotive syndrome risk test, balance test, appendicular skeletal muscle mass measurement by bioelectrical impedance analysis, evaluation of physical function by the timed-up-and-go test, and back muscle and grip strength evaluation. A statistical comparative study was then conducted between normal and locomotive syndrome risk groups. Subsequently, significant factors for locomotive syndrome risk were investigated by multivariate analysis. Results: The comparative study was conducted by adjusting age and sex using a generalized linear model. No significant difference in muscle mass existed, but postural sway in the balance test significantly increased in the people at locomotive syndrome risk. Among the four posturographic variables by balance test, increase in back-and-forth sway was the most remarkable variable associated with locomotive syndrome risk together with back muscle strength, body mass index, and the timed-up-and-go test by logistic regression analysis. This posturographic variable was significantly related to the timedup-and-go test and leg skeletal muscle mass by multiple regression analysis. Conclusions: A relationship was recognized between locomotive syndrome risk and postural sway. In particular, increase in back-and-forth sway was an important factor for locomotive syndrome risk. If the balance test shows an increase in back-and-forth sway, attention should be paid to locomotive syndrome risk for possible intervention and early treatment. © 2019 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.
1. Introduction
* Corresponding author. Department of Orthopaedic Surgery, Nagoya University Graduate School of Medicine, 65 Tsurumai Showa-ward, Nagoya, Aichi, 466-8550, Japan. Fax: þ81 52 744 2260. E-mail address: [email protected] (S. Imagama).
Musculoskeletal problems are becoming increasingly prevalent with the aging of the population. In addition, severe cases and multiple disease complications are often difficult to manage by applying existing guidelines. A new approach is necessary so that these problems are recognized by more people and appropriate intervention is obtained.
https://doi.org/10.1016/j.jos.2019.01.011 0949-2658/© 2019 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.
Please cite this article as: Tanaka S et al., Increasing postural sway in balance test is related to locomotive syndrome risk: A cross-sectional study, Journal of Orthopaedic Science, https://doi.org/10.1016/j.jos.2019.01.011
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S. Tanaka et al. / Journal of Orthopaedic Science xxx (xxxx) xxx
In 2007, the Japanese Orthopaedic Association (JOA) proposed the concept of “locomotive syndrome” (LS). LS is a condition in high-risk individuals with musculoskeletal disease who are likely to require nursing care at some point [1]. The JOA as a method of evaluating the risk of LS proposed the following tests in 2013: the two-step test, stand-up test, and 25-question geriatric locomotive function scale (GLFS) [2]. On the basis of the test results, the mobility and stage of LS can be determined. The LS risk level is categorized into two stages, 1 and 2. Risk level 1 indicates that the movement function has started to decline and that measures to prevent deterioration to LS should be instituted [3,4]. Therefore, early diagnosis of LS risk level is important to allow treatment of these conditions, and investigating the relation with LS risk from a broad perspective is necessary. Impaired balance control is one of the most important risk factors for falls [5e7]. Numerous studies have reported that elderly persons manifest deteriorating balance function, as evidenced by increased postural sway on the movement of the center of the pressure (COP) [8,9]. Postural stability is controlled by the motor, sensory, and cognitive systems [10]. Elderly persons show significant increases in the absolute latency of distal muscle response and impairment of sensory integration abilities under conditions of reduced or conflicting sensory information [11]. They also have decreased muscle strength and mass [12,13]. Moreover, sensory systems show age-related functional declines that affect balance control [11,14]. Recently, body composition analysis by bioelectrical impedance analysis (BIA), which can easily measure muscle mass and balance test, is commonly performed in general health checkups. However, the association between balance test and LS risk has not been clarified to date. Therefore, in this study, we aimed to investigate the relationship between LS risk and balance test with muscle mass and physical function and to analyze the significant factors for LS risk by multivariate analysis in a large-scale prospective general health checkup.
2.2. LS risk test The LS risk test consists of three parts: stand-up test, two-step test, and GLFS-25. These three tests were performed in the same way as described in previous studies [3,18,19]. The JOA defines two stages in the LS risk test. LS risk stage 1 is defined as a two-step test score <1.3, difficulty with one-leg standing from a 40-cm seat in the stand-up test (either leg), or a 25-question GLFS score 7; subjects meeting any of these criteria were diagnosed as starting to have decline in mobility. LS risk stage 2 is defined as a two-step test score <1.1, difficulty with standing from a 20-cm seat using both legs in the stand-up test, or a 25-question GLFS score 16; subjects meeting any of these criteria were diagnosed with progression of decline in mobility. In this study, subjects who met the criteria for LS risk test stage 1 or 2 were defined as LS risk subjects, and the other subjects were normal [18]. 2.3. Back muscle and grip strengths We examined back muscle strength as the maximum isometric strength of the trunk muscles in a standing position with 30 lumbar flexion by using a digital back muscle strength meter (T.K.K. 5102; Takei Co., Japan) and performing one measurement [13]. We tested grip strength in a standing position once for each hand by using a Toei Light hand-grip dynamometer (Toei Light Co., Ltd, Saitama, Japan) [20]. The average value was used to characterize the subject's grip strength. 2.4. TUG We measured the time taken by a subject to rise from a standard chair (46-cm seat height), walk a distance of 3 m, turn around, walk back to the chair, and sit down [21]. Each subject performed the test two times, both at maximum pace, and the mean score was used for analyses.
2. Materials and methods 2.5. Body composition and muscle mass measurement 2.1. Participants The participants were healthy Japanese volunteers who attended a basic health checkup supported by the local government in 2016. This checkup has been held annually since 1982 in the town of Yakumo in a rural area of southern Hokkaido, Japan and comprises voluntary orthopedic and physical function examinations, as well as internal medical examinations [15e17]. The inclusion criteria for this study were as follows: answers to all questions in the GLFS-25 [2]; LS risk test and physical function measurements by grip strength, back muscle strength, and timed up-and-go test (TUG); availability of BIA measurements; and ability to stand independently for more than 1 min to undergo balance test by platform measurements. Exclusion criteria were as follows: with a history of spinal or knee surgery, severe knee injury, knee osteoarthritis, or spinal compression fracture and severe disability in walking and standing, and the presence of equilibrium disturbance due to dysfunction of the central or peripheral nervous systems. Among 555 individuals who participated in the annual health checkup in 2016, 295 participants underwent LS risk test, BIA measurements, and balance test. Of these 295 participants, 293 completed physical performance test, of whom 1 was subsequently excluded due to the above-mentioned criteria. Therefore, 292 participants were finally included in the study. The study protocol was approved by the ethics committee in human research and the institutional review board of our university. All participants provided written informed consent. The study procedures were carried out in accordance with the principles of the Declaration of Helsinki.
For body composition analysis, body mass index (BMI), percent body fat (PBF), and appendicular skeletal muscle mass (aSMI) as muscle mass were measured using BIA. The Inbody 770 BIA unit (Inbody Co., Ltd, Seoul, Korea), which differentiates tissues (such as fat, muscle, and bone) on the basis of their electrical impedance, was used [22]. Individuals grasped the handles of the analyzer, in which electrodes are embedded, and stood on the platform, with the sole of the feet in contact with electrodes (two electrodes for each foot and hand). The accuracy of this method is comparable to that of the computed tomography cross-sectional area [23]. The aSMI was calculated using the following formula: aSMI ¼ arm and leg skeletal muscle mass (kg)/height2 (m2) [24]. 2.6. Balance test procedure Static postural stability was assessed using a stable force platform (Gravicoda GW-7; Anima, Tokyo, Japan). The machine is designed to assess the movement of COP from three verticality load sensors placed on corners of an isosceles triangle as that of the center of gravity in a horizontal plane. The balance test procedure was described in detail in a previous article [8,25]. Briefly, the recording was carried out in the corner of a gymnastics hall. All participants were instructed to stand steadily on the foot plate without their shoes and with their arms at their sides and feet close together. The examination was performed twice, each lasting 30 s, under eyes-open and eyes-closed conditions. The authors evaluated the following posturographic variables to assess postural
Please cite this article as: Tanaka S et al., Increasing postural sway in balance test is related to locomotive syndrome risk: A cross-sectional study, Journal of Orthopaedic Science, https://doi.org/10.1016/j.jos.2019.01.011
S. Tanaka et al. / Journal of Orthopaedic Science xxx (xxxx) xxx
stability: envelopment area tracing by the movement of the COP (E AREA), distance of the movement of the COP (LNG), distance of the movement of the COP in the left-right direction (X LNG), and distance of the movement of the COP in the front-back direction (Y LNG). In this study, we examined using the data obtained at eyesopen condition. 2.7. Statistical analysis Statistical analyses were conducted with SPSS v.25.0 for Mac (SPSS Inc., Chicago, IL, USA). Continuous variables are expressed as means (standard deviation: SD), and categorical variables as percentages. The Mann-Whitney U test was used to examine the difference in variables between male and female participants. To investigate the important factors related to LS risk, these variables were compared between normal and LS risk groups using MannWhitney U test, Fisher's exact test, and general linear model (GLM). GLM analysis was adjusted for the age and sex, which are known factors related to LS [26,27]. The relationships between these variables and LS risk stages were investigated using the Tukey-Kramer test and Fisher's exact test. To determine the factors associated with LS risk among the parameters that exhibited differences (p < 0.20) in the analyses conducted after GLM adjustment, logistic regression analysis with the step-wise method was performed using the aforementioned variables as covariates in addition to age and sex. To examine the relationships between the posturographic variables and other variables (muscle mass and physical functions), multiple regression analysis was performed. A p value < 0.05 was considered significant in all analyses. 3. Results The average age of the 292 participants was 64.1 years (range: 40e88; SD: 10.3), 122 were males and 170 were females, and the average BMI was 23.5 kg/m2. General demographic, balance test, and GLFS-25 data are listed in Table 1. The prevalence of LS risk in males and females was 49.2% (60 of 122) and 65.9% (112 of 170), respectively. Table 2 shows data on muscle mass and physical function, and a significant difference exists between males and females in all variables. Age, sex, BMI, PBF, LNG, Y LNG, E AREA, back muscle strength, grip strength, and TUG showed significant differences between normal and LS risk groups (Table 3), whereas all muscle mass was not significantly different. Furthermore, after controlling for age
Table 1 Demographic, balance test, and GLFS-25 data of the participants. Variables
Total
Male
Female
Number of participants Age (years) BMI (kg/m2) PBF (%) LNG (cm) X LNG (cm) Y LNG (cm) E AREA (cm2) GLFS-25 Prevalence of LS risk
292 64.1 (10.3) 23.5 (3.5) 29.1 (6.6) 51.5 (17.8) 34.2 (11.3) 31.1 (13.2) 2.7 (1.5) 8.2 (8.6) 58.9%
122 65.6 (9.6) 24.4 (3.3) 24.6 (4.7) 57.3 (20.7) 37.8 (12.8) 34.8 (15.8) 3.1 (1.7) 6.8 (8.4) 49.2%
170 63.1 (10.7) 22.9 (3.5) 32.4 (5.8) 47.3 (14.1) 31.6 (9.2) 28.5 (10.1) 2.5 (1.3) 9.2 (8.7) 65.9%
Parameter values are shown as mean (standard deviation) or numbers. LS risk includes the participants of LS risk levels 1 and 2. BMI, body mass index; PBF, percent body fat; LNG, distance of the movement of the center of pressure; X LNG, distance of the movement of the center of the pressure in the left-right direction; Y LNG, distance of the movement of the center of the pressure in the front-back direction; E AREA, envelopment area tracing by the movement of the center of pressure; GLFS-25, 25-question geriatric locomotive function scale; LS, locomotive syndrome.
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Table 2 Muscle mass and physical function measurements. Variables
Total
Male
Female
p-value
Number of participants aSMI (kg/m2) Arm SMI (kg/m2) Leg SMI (kg/m2) Back muscle strength (kg) Grip strength (kg) TUG (s)
292 6.68 (1.0) 1.65 (0.4) 5.03 (0.7) 65.7 (26.9) 26.6 (8.4) 6.4 (1.1)
122 7.52 (0.8) 1.97 (0.3) 5.55 (0.6) 86.8 (25.7) 34.4 (6.3) 6.2 (1.1)
170 6.09 (0.7) 1.43 (0.2) 4.66 (0.5) 50.5 (14.8) 21.0 (4.3) 6.4 (1.1)
<0.001 *** <0.001 *** <0.001 *** <0.001 *** <0.001 *** 0.031 *
*< 0.05, ***< 0.001, Mann-Whitney U test. Parameter values are shown as mean (standard deviation) or numbers. aSMI, appendicular skeletal muscle index; TUG, timed up-and-go. Bold values indicate significant difference.
and sex, in addition to the above variables, X LNG also showed a significant difference between the two groups. Comparisons among normal, LS risk stage 1, and LS risk stage 2 are shown in Table 4. Age, sex, BMI, PBF, Y LNG, back muscle strength, grip strength, and TUG were significantly different between stage 1 and no risk. In the comparison between no risk and stage 2, age, sex, LNG, Y LNG, E AREA, back muscle strength, grip strength, and TUG were significantly different. Furthermore, LNG, Y LNG, back muscle strength, grip strength, and TUG were significantly different between stages 1 and 2. A summary of logistic regression analysis for important factors related to LS risk is shown in Table 5. Covariates included age, sex, and factors associated with LS risk that were different (p < 0.20) in the GLM analysis. This analysis showed that back muscle strength (odds ratio [OR] ¼ 0.971; p < 0.001), BMI (OR ¼ 1.15; p ¼ 0.002), Y LNG (OR ¼ 1.04; p ¼ 0.007), and TUG (OR ¼ 1.42; p ¼ 0.029) were significant factors for LS risk. The results of multiple regression analysis revealed that TUG and leg SMI were significantly related to Y LNG (Table 6). 4. Discussion This study investigated the relationship between the presence or absence of LS risk and postural stability by balance test in a prospective large-scale general population. The results of this study showed that among the four posturographic variables measured by the balance test, Y LNG was most related to LS risk. Various factors related to LS have been reported [20,26,27]. A previous study reported that serum cystatin C can be an early predictor for LS risk [18], but LS risk has received relatively little attention. Elderly and women were reported as risk factors for LS. Recent studies have also indicated that muscle mass is predictive of LS [28,29]. Regarding postural stability, previous studies reported on the increase in COP values with increase in age [6,30]. A study also showed that COP values depend on sex; males were found to be more upset than females in a large number of community-dwelling people [8]. Therefore, in this study, the relationship between LS risk and postural stability was analyzed in detail including aSMI by BIA and physical function. In addition, after controlling for age and sex by GLM, comparison was also made considering factors that can be more biased. The results of this study showed that the LS risk group was also significantly older than the normal group, and LS risk was more likely to occur in females than in males. Among the four posturographic variables by balance test, only LNG, Y LNG, and E AREA were significantly higher in the LS risk group. Since LNG and E AREA were indicators showing total postural sway and Y LNG was considered to indicate postural sway in the front-back direction, the postural sway significantly increased in the LS risk group. With regard to muscle mass and physical function, physical function was
Please cite this article as: Tanaka S et al., Increasing postural sway in balance test is related to locomotive syndrome risk: A cross-sectional study, Journal of Orthopaedic Science, https://doi.org/10.1016/j.jos.2019.01.011
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S. Tanaka et al. / Journal of Orthopaedic Science xxx (xxxx) xxx
Table 3 Comparison between normal and LS risk groups. Variables
Age (years) Sex (male/female) BMI (kg/m2) PBF (%) LNG (cm) X LNG (cm) Y LNG (cm) E AREA (cm2) aSMI (kg/m2) Arm SMI (kg/m2) Leg SMI (kg/m2) Back muscle strength (kg) Grip strength (kg) TUG (s)
Non-adjusted
p-value
Normal (N ¼ 120)
LS risk (N ¼ 172)
62.1 (10.2) 62/58 22.9 (3.2) 27.1 (6.0) 48.0 (15.8) 32.9 (10.5) 28.0 (10.8) 2.5 (1.3) 6.77 (1.0) 1.69 (0.4) 5.08 (0.7) 76.2 (29.5) 29.0 (9.0) 6.0 (0.9)
65.6 (10.2) 60/112 23.9 (3.6) 30.5 (6.6) 53.9 (18.8) 35.1 (11.7) 33.3 (14.2) 2.9 (1.6) 6.62 (1.0) 1.63 (0.4) 4.99 (0.7) 58.3 (22.2) 24.9 (7.5) 6.6 (1.2)
0.013 * 0.006 ** 0.006 ** <0.001 *** 0.001 ** 0.056 <0.001 *** 0.002 ** 0.27 0.28 0.28 <0.001 *** <0.001 *** <0.001 ***
Age and sex-adjusted
p-value
Normal (N ¼ 120)
LS risk (N ¼ 172)
22.9 (0.4) 27.4 (0.6) 46.9 (1.9) 32.4 (1.2) 27.1 (1.4) 2.4 (0.2) 6.72 (0.08) 1.67 (0.03) 5.05 (0.06) 74.5 (2.1) 28.5 (0.5) 5.9 (0.1)
23.9 (0.3) 30.0 (0.5) 54.8 (1.6) 35.9 (1.0) 33.7 (1.2) 3.1 (0.1) 6.63 (0.07) 1.63 (0.03) 5.00 (0.05) 59.7 (1.7) 25.8 (0.4) 6.6 (0.1)
0.047 * 0.001 ** 0.002 ** 0.031 * <0.001 *** 0.001 ** 0.43 0.36 0.50 <0.001 *** <0.001 *** <0.001 ***
*< 0.05, **< 0.01, ***< 0.001, Mann-Whitney U test, Fisher's exact test. Parameter values are shown as the mean (standard deviation) or numbers for non-adjusted data, and corrected mean (standard error) or numbers of the mean for age and sexadjusted data. LS, locomotive syndrome; BMI, body mass index; PBF, percent body fat; LNG, distance of the movement of the center of pressure; X LNG, distance of the movement of the center of the pressure in the left-right direction; Y LNG, distance of the movement of the center of the pressure in the front-back direction; E AREA, envelopment area tracing by the movement of the center of pressure; aSMI, appendicular skeletal muscle index; TUG, timed up-and-go. Bold values indicate significant difference.
Table 4 Comparison among LS risk stages in total participants. Variables
Age (years) Sex (male/female) BMI (kg/m2) PBF (%) LNG (cm) X LNG (cm) Y LNG (cm) E AREA (cm2) aSMI (kg/m2) Arm SMI (kg/m2) Leg SMI (kg/m2) Back muscle strength (kg) Grip strength (kg) TUG (s)
LS risk stage
Significance (p)
No risk (N ¼ 120)
Stage 1 (N ¼ 133)
Stage 2 (N ¼ 39)
No risk vs. Stage 1
No risk vs. Stage 2
Stage 1 vs. Stage 2
ANOVA
62.1 (10.1) 62/58 22.9 (3.2) 27.1 (6.0) 48.0 (15.8) 32.9 (10.5) 28.0 (10.8) 2.5 (1.3) 6.8 (1.0) 1.7 (0.4) 5.1 (0.7) 76.2 (29.5) 29.0 (9.0) 6.0 (0.9)
65.1 (9.9) 50/83 24.1 (3.7) 30.8 (6.8) 52.1 (17.6) 34.5 (11.4) 31.6 (12.3) 2.9 (1.6) 6.7 (1.0) 1.6 (0.4) 5.0 (0.7) 60.8 (21.3) 25.8 (7.3) 6.4 (0.9)
67.2 (11.1) 10/29 23.4 (3.3) 29.7 (6.1) 60.1 (21.4) 37.0 (12.5) 38.9 (18.5) 3.1 (1.6) 6.4 (1.0) 1.6 (0.4) 4.9 (0.7) 49.7 (23.4) 21.9 (7.7) 7.2 (1.6)
0.048* 0.031* 0.017* <0.001*** 0.15 0.47 0.046* 0.069 0.77 0.69 0.83 <0.001*** 0.005** 0.001**
0.018* 0.005** 0.78 0.078 0.001** 0.11 <0.001*** 0.035* 0.16 0.21 0.17 <0.001*** <0.001*** <0.001***
0.50 0.19 0.44 0.63 0.033* 0.44 0.005** 0.59 0.36 0.48 0.32 0.044* 0.024* <0.001***
0.009** 0.007** 0.023* <0.001*** 0.001** 0.12 <0.001*** 0.017* 0.19 0.23 0.19 <0.001*** <0.001*** <0.001***
*p < 0.05, **p < 0.01, ***p < 0.001, Tukey-Kramer test, Fisher's exact test. Parameter values are shown as the mean (standard deviation) or numbers. LS, locomotive syndrome; BMI, body mass index; PBF, percent body fat; LNG, distance of the movement of the center of pressure; X LNG, distance of the movement of the center of the pressure in the left-right direction; Y LNG, distance of the movement of the center of the pressure in the front-back direction; E AREA, envelopment area tracing by the movement of the center of pressure; aSMI, appendicular skeletal muscle index; TUG, timed up-and-go; ANOVA, analysis of variance. Bold values indicate significant difference.
Table 5 Logistic regression model for prediction of LS risk. Variables
Coefficient (b)
Odds ratio
95% CI
p-value
Back muscle strength (kg) BMI (kg/m2) Y LNG (cm) TUG (s)
0.029 0.138 0.036 0.351
0.971 1.15 1.04 1.42
0.960e0.983 1.054e1.250 1.010e1.065 1.036e1.948
<0.001 *** 0.002 ** 0.007 ** 0.029 *
*< 0.05, **< 0.01, ***< 0.001. The dependent variable was LS risk. Covariates were age, sex, BMI, PBF, back muscle strength, grip strength, TUG, X LNG, Y LNG, and E AREA. LS, locomotive syndrome; CI, confidence interval; BMI, body mass index; Y LNG, distance of the movement of the center of the pressure in the front-back direction; TUG, timed up-and-go; X LNG, distance of the movement of the center of the pressure in the left-right direction; E AREA, envelopment area tracing by the movement of the center of pressure. Bold values indicate significant difference.
significantly lower in the LS risk group than in the normal group, but no significant difference was found in muscle mass, and almost the same result was obtained even after controlling for age and sex.
These results suggest that the evaluation of LS risk involves motor function but not muscle mass. Since the LS risk group also includes subjects close to the normal group, no significant difference may be
Please cite this article as: Tanaka S et al., Increasing postural sway in balance test is related to locomotive syndrome risk: A cross-sectional study, Journal of Orthopaedic Science, https://doi.org/10.1016/j.jos.2019.01.011
S. Tanaka et al. / Journal of Orthopaedic Science xxx (xxxx) xxx Table 6 Summary of multiple regression analysis for Y LNG. Independent variables
TUG (s) Leg SMI (kg/m2) Grip strength (kg) Arm SMI (kg/m2) Back muscle strength (kg)a
Y LNG Coefficient (b)
p-value
0.302 0.203 0.059 0.011 0.001
<0.001 *** <0.001 *** 0.47 0.93 0.99
***< 0.001. The dependent variable was Y LNG. The independent variables were arm SMI, leg SMI, back muscle strength, grip strength, and TUG. Y LNG, distance of the movement of the center of the pressure in the front-back direction; TUG, timed up-and-go; SMI, skeletal muscle index. Bold values indicate significant difference.
observed in muscle mass. The LS risk group showed decreased physical function before the muscle mass decreased. Logistic regression analysis of the important factors related to LS risk showed that weak back muscle strength, high BMI, high Y LNG, and slow TUG were significant factors. These results indicate that increasing back-and-forth sway was particularly important for LS risk among the postural sway. The Y LNG by balance test is a related factor of LS risk unaffected by age and sex, and it was shown that the higher the Y LNG, the higher the possibility of being LS risk. In addition, to investigate the relationship between Y LNG and muscle mass and physical function, multiple regression analysis showed that TUG and leg SMI were significantly associated with Y LNG. Variables, such as aSMI, arm SMI, grip strength, and back muscle strength including upper limbs and trunk elements, did not show significant association with Y LNG. In other words, Y LNG was speculated to be related to physical function and muscle mass of the lower limbs, which confirms the relationship with LS risk. This study has several limitations. First, it targeted residents in rural areas, and a possibility of bias exists because the living and working environments differ from those in urban areas. Furthermore, evaluation of comorbidities and mental health is not enough. Second, only few participants were included in the subgroup analysis for each age group. Third, this study was a cross-sectional study. A longitudinal study is necessary in the future. In summary, the LS risk group showed increased postural sway in the balance test after controlling for age and sex. Among the four posturographic variables by balance test, Y LNG was the most remarkable variable associated with LS risk. Furthermore, Y LNG was considered to be significantly related to muscle mass and physical function of the lower limbs, which strongly suggested an association with LS risk. If the balance test shows an increase in Y LNG, attention should be paid to LS risk for possible intervention and early treatment. Conflicts of interest None. Acknowledgments We are grateful to the staff of the Comprehensive Health Care Program held in Yakumo, Hokkaido, and Ms. Marie Miyazaki and Ms. Hiroko Ino of Nagoya University for their assistance throughout this study. References [1] Nakamura K. The concept and treatment of locomotive syndrome: its acceptance and spread in Japan. J Orthop Sci 2011 Sep;16(5):489e91.
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Journal of Orthopaedic Science journal homepage: http://www.elsevier.com/locate/jos
Original Article
Increasing postural sway in balance test is related to locomotive syndrome risk: A cross-sectional study Satoshi Tanaka a, Kei Ando a, Kazuyoshi Kobayashi a, Tetsuro Hida b, Taisuke Seki a, Takashi Hamada a, Kenyu Ito a, Mikito Tsushima a, Masayoshi Morozumi a, Masaaki Machino a, Kyotaro Ota a, Naoki Ishiguro a, Yukiharu Hasegawa c, Shiro Imagama a, * a
Department of Orthopaedic Surgery, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan Department of Orthopaedic Surgery, Japanese Red Cross Nagoya Daini Hospital, Nagoya, Japan c Department of Rehabilitation, Kansai University of Welfare Science, Osaka, Japan b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 17 June 2018 Received in revised form 24 January 2019 Accepted 25 January 2019 Available online xxx
Background: Locomotive syndrome risk level has been recently proposed to evaluate physical ability. Impaired balance control is one of the most important risk factors for falls. However, the relationship between locomotive syndrome risk and postural sway according to the balance test is unclear. This study aimed to investigate the relationship between locomotive syndrome risk and balance test results, including muscle mass and physical function, in a large-scale prospective general health checkup. Methods: We enrolled 292 participants who underwent a basic health checkup and conducted a twostep test, stand-up test, evaluation using a 25-question geriatric locomotive function scale for the locomotive syndrome risk test, balance test, appendicular skeletal muscle mass measurement by bioelectrical impedance analysis, evaluation of physical function by the timed-up-and-go test, and back muscle and grip strength evaluation. A statistical comparative study was then conducted between normal and locomotive syndrome risk groups. Subsequently, significant factors for locomotive syndrome risk were investigated by multivariate analysis. Results: The comparative study was conducted by adjusting age and sex using a generalized linear model. No significant difference in muscle mass existed, but postural sway in the balance test significantly increased in the people at locomotive syndrome risk. Among the four posturographic variables by balance test, increase in back-and-forth sway was the most remarkable variable associated with locomotive syndrome risk together with back muscle strength, body mass index, and the timed-up-and-go test by logistic regression analysis. This posturographic variable was significantly related to the timedup-and-go test and leg skeletal muscle mass by multiple regression analysis. Conclusions: A relationship was recognized between locomotive syndrome risk and postural sway. In particular, increase in back-and-forth sway was an important factor for locomotive syndrome risk. If the balance test shows an increase in back-and-forth sway, attention should be paid to locomotive syndrome risk for possible intervention and early treatment. © 2019 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.
1. Introduction
* Corresponding author. Department of Orthopaedic Surgery, Nagoya University Graduate School of Medicine, 65 Tsurumai Showa-ward, Nagoya, Aichi, 466-8550, Japan. Fax: þ81 52 744 2260. E-mail address: [email protected] (S. Imagama).
Musculoskeletal problems are becoming increasingly prevalent with the aging of the population. In addition, severe cases and multiple disease complications are often difficult to manage by applying existing guidelines. A new approach is necessary so that these problems are recognized by more people and appropriate intervention is obtained.
https://doi.org/10.1016/j.jos.2019.01.011 0949-2658/© 2019 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.
Please cite this article as: Tanaka S et al., Increasing postural sway in balance test is related to locomotive syndrome risk: A cross-sectional study, Journal of Orthopaedic Science, https://doi.org/10.1016/j.jos.2019.01.011
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In 2007, the Japanese Orthopaedic Association (JOA) proposed the concept of “locomotive syndrome” (LS). LS is a condition in high-risk individuals with musculoskeletal disease who are likely to require nursing care at some point [1]. The JOA as a method of evaluating the risk of LS proposed the following tests in 2013: the two-step test, stand-up test, and 25-question geriatric locomotive function scale (GLFS) [2]. On the basis of the test results, the mobility and stage of LS can be determined. The LS risk level is categorized into two stages, 1 and 2. Risk level 1 indicates that the movement function has started to decline and that measures to prevent deterioration to LS should be instituted [3,4]. Therefore, early diagnosis of LS risk level is important to allow treatment of these conditions, and investigating the relation with LS risk from a broad perspective is necessary. Impaired balance control is one of the most important risk factors for falls [5e7]. Numerous studies have reported that elderly persons manifest deteriorating balance function, as evidenced by increased postural sway on the movement of the center of the pressure (COP) [8,9]. Postural stability is controlled by the motor, sensory, and cognitive systems [10]. Elderly persons show significant increases in the absolute latency of distal muscle response and impairment of sensory integration abilities under conditions of reduced or conflicting sensory information [11]. They also have decreased muscle strength and mass [12,13]. Moreover, sensory systems show age-related functional declines that affect balance control [11,14]. Recently, body composition analysis by bioelectrical impedance analysis (BIA), which can easily measure muscle mass and balance test, is commonly performed in general health checkups. However, the association between balance test and LS risk has not been clarified to date. Therefore, in this study, we aimed to investigate the relationship between LS risk and balance test with muscle mass and physical function and to analyze the significant factors for LS risk by multivariate analysis in a large-scale prospective general health checkup.
2.2. LS risk test The LS risk test consists of three parts: stand-up test, two-step test, and GLFS-25. These three tests were performed in the same way as described in previous studies [3,18,19]. The JOA defines two stages in the LS risk test. LS risk stage 1 is defined as a two-step test score <1.3, difficulty with one-leg standing from a 40-cm seat in the stand-up test (either leg), or a 25-question GLFS score 7; subjects meeting any of these criteria were diagnosed as starting to have decline in mobility. LS risk stage 2 is defined as a two-step test score <1.1, difficulty with standing from a 20-cm seat using both legs in the stand-up test, or a 25-question GLFS score 16; subjects meeting any of these criteria were diagnosed with progression of decline in mobility. In this study, subjects who met the criteria for LS risk test stage 1 or 2 were defined as LS risk subjects, and the other subjects were normal [18]. 2.3. Back muscle and grip strengths We examined back muscle strength as the maximum isometric strength of the trunk muscles in a standing position with 30 lumbar flexion by using a digital back muscle strength meter (T.K.K. 5102; Takei Co., Japan) and performing one measurement [13]. We tested grip strength in a standing position once for each hand by using a Toei Light hand-grip dynamometer (Toei Light Co., Ltd, Saitama, Japan) [20]. The average value was used to characterize the subject's grip strength. 2.4. TUG We measured the time taken by a subject to rise from a standard chair (46-cm seat height), walk a distance of 3 m, turn around, walk back to the chair, and sit down [21]. Each subject performed the test two times, both at maximum pace, and the mean score was used for analyses.
2. Materials and methods 2.5. Body composition and muscle mass measurement 2.1. Participants The participants were healthy Japanese volunteers who attended a basic health checkup supported by the local government in 2016. This checkup has been held annually since 1982 in the town of Yakumo in a rural area of southern Hokkaido, Japan and comprises voluntary orthopedic and physical function examinations, as well as internal medical examinations [15e17]. The inclusion criteria for this study were as follows: answers to all questions in the GLFS-25 [2]; LS risk test and physical function measurements by grip strength, back muscle strength, and timed up-and-go test (TUG); availability of BIA measurements; and ability to stand independently for more than 1 min to undergo balance test by platform measurements. Exclusion criteria were as follows: with a history of spinal or knee surgery, severe knee injury, knee osteoarthritis, or spinal compression fracture and severe disability in walking and standing, and the presence of equilibrium disturbance due to dysfunction of the central or peripheral nervous systems. Among 555 individuals who participated in the annual health checkup in 2016, 295 participants underwent LS risk test, BIA measurements, and balance test. Of these 295 participants, 293 completed physical performance test, of whom 1 was subsequently excluded due to the above-mentioned criteria. Therefore, 292 participants were finally included in the study. The study protocol was approved by the ethics committee in human research and the institutional review board of our university. All participants provided written informed consent. The study procedures were carried out in accordance with the principles of the Declaration of Helsinki.
For body composition analysis, body mass index (BMI), percent body fat (PBF), and appendicular skeletal muscle mass (aSMI) as muscle mass were measured using BIA. The Inbody 770 BIA unit (Inbody Co., Ltd, Seoul, Korea), which differentiates tissues (such as fat, muscle, and bone) on the basis of their electrical impedance, was used [22]. Individuals grasped the handles of the analyzer, in which electrodes are embedded, and stood on the platform, with the sole of the feet in contact with electrodes (two electrodes for each foot and hand). The accuracy of this method is comparable to that of the computed tomography cross-sectional area [23]. The aSMI was calculated using the following formula: aSMI ¼ arm and leg skeletal muscle mass (kg)/height2 (m2) [24]. 2.6. Balance test procedure Static postural stability was assessed using a stable force platform (Gravicoda GW-7; Anima, Tokyo, Japan). The machine is designed to assess the movement of COP from three verticality load sensors placed on corners of an isosceles triangle as that of the center of gravity in a horizontal plane. The balance test procedure was described in detail in a previous article [8,25]. Briefly, the recording was carried out in the corner of a gymnastics hall. All participants were instructed to stand steadily on the foot plate without their shoes and with their arms at their sides and feet close together. The examination was performed twice, each lasting 30 s, under eyes-open and eyes-closed conditions. The authors evaluated the following posturographic variables to assess postural
Please cite this article as: Tanaka S et al., Increasing postural sway in balance test is related to locomotive syndrome risk: A cross-sectional study, Journal of Orthopaedic Science, https://doi.org/10.1016/j.jos.2019.01.011
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stability: envelopment area tracing by the movement of the COP (E AREA), distance of the movement of the COP (LNG), distance of the movement of the COP in the left-right direction (X LNG), and distance of the movement of the COP in the front-back direction (Y LNG). In this study, we examined using the data obtained at eyesopen condition. 2.7. Statistical analysis Statistical analyses were conducted with SPSS v.25.0 for Mac (SPSS Inc., Chicago, IL, USA). Continuous variables are expressed as means (standard deviation: SD), and categorical variables as percentages. The Mann-Whitney U test was used to examine the difference in variables between male and female participants. To investigate the important factors related to LS risk, these variables were compared between normal and LS risk groups using MannWhitney U test, Fisher's exact test, and general linear model (GLM). GLM analysis was adjusted for the age and sex, which are known factors related to LS [26,27]. The relationships between these variables and LS risk stages were investigated using the Tukey-Kramer test and Fisher's exact test. To determine the factors associated with LS risk among the parameters that exhibited differences (p < 0.20) in the analyses conducted after GLM adjustment, logistic regression analysis with the step-wise method was performed using the aforementioned variables as covariates in addition to age and sex. To examine the relationships between the posturographic variables and other variables (muscle mass and physical functions), multiple regression analysis was performed. A p value < 0.05 was considered significant in all analyses. 3. Results The average age of the 292 participants was 64.1 years (range: 40e88; SD: 10.3), 122 were males and 170 were females, and the average BMI was 23.5 kg/m2. General demographic, balance test, and GLFS-25 data are listed in Table 1. The prevalence of LS risk in males and females was 49.2% (60 of 122) and 65.9% (112 of 170), respectively. Table 2 shows data on muscle mass and physical function, and a significant difference exists between males and females in all variables. Age, sex, BMI, PBF, LNG, Y LNG, E AREA, back muscle strength, grip strength, and TUG showed significant differences between normal and LS risk groups (Table 3), whereas all muscle mass was not significantly different. Furthermore, after controlling for age
Table 1 Demographic, balance test, and GLFS-25 data of the participants. Variables
Total
Male
Female
Number of participants Age (years) BMI (kg/m2) PBF (%) LNG (cm) X LNG (cm) Y LNG (cm) E AREA (cm2) GLFS-25 Prevalence of LS risk
292 64.1 (10.3) 23.5 (3.5) 29.1 (6.6) 51.5 (17.8) 34.2 (11.3) 31.1 (13.2) 2.7 (1.5) 8.2 (8.6) 58.9%
122 65.6 (9.6) 24.4 (3.3) 24.6 (4.7) 57.3 (20.7) 37.8 (12.8) 34.8 (15.8) 3.1 (1.7) 6.8 (8.4) 49.2%
170 63.1 (10.7) 22.9 (3.5) 32.4 (5.8) 47.3 (14.1) 31.6 (9.2) 28.5 (10.1) 2.5 (1.3) 9.2 (8.7) 65.9%
Parameter values are shown as mean (standard deviation) or numbers. LS risk includes the participants of LS risk levels 1 and 2. BMI, body mass index; PBF, percent body fat; LNG, distance of the movement of the center of pressure; X LNG, distance of the movement of the center of the pressure in the left-right direction; Y LNG, distance of the movement of the center of the pressure in the front-back direction; E AREA, envelopment area tracing by the movement of the center of pressure; GLFS-25, 25-question geriatric locomotive function scale; LS, locomotive syndrome.
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Table 2 Muscle mass and physical function measurements. Variables
Total
Male
Female
p-value
Number of participants aSMI (kg/m2) Arm SMI (kg/m2) Leg SMI (kg/m2) Back muscle strength (kg) Grip strength (kg) TUG (s)
292 6.68 (1.0) 1.65 (0.4) 5.03 (0.7) 65.7 (26.9) 26.6 (8.4) 6.4 (1.1)
122 7.52 (0.8) 1.97 (0.3) 5.55 (0.6) 86.8 (25.7) 34.4 (6.3) 6.2 (1.1)
170 6.09 (0.7) 1.43 (0.2) 4.66 (0.5) 50.5 (14.8) 21.0 (4.3) 6.4 (1.1)
<0.001 *** <0.001 *** <0.001 *** <0.001 *** <0.001 *** 0.031 *
*< 0.05, ***< 0.001, Mann-Whitney U test. Parameter values are shown as mean (standard deviation) or numbers. aSMI, appendicular skeletal muscle index; TUG, timed up-and-go. Bold values indicate significant difference.
and sex, in addition to the above variables, X LNG also showed a significant difference between the two groups. Comparisons among normal, LS risk stage 1, and LS risk stage 2 are shown in Table 4. Age, sex, BMI, PBF, Y LNG, back muscle strength, grip strength, and TUG were significantly different between stage 1 and no risk. In the comparison between no risk and stage 2, age, sex, LNG, Y LNG, E AREA, back muscle strength, grip strength, and TUG were significantly different. Furthermore, LNG, Y LNG, back muscle strength, grip strength, and TUG were significantly different between stages 1 and 2. A summary of logistic regression analysis for important factors related to LS risk is shown in Table 5. Covariates included age, sex, and factors associated with LS risk that were different (p < 0.20) in the GLM analysis. This analysis showed that back muscle strength (odds ratio [OR] ¼ 0.971; p < 0.001), BMI (OR ¼ 1.15; p ¼ 0.002), Y LNG (OR ¼ 1.04; p ¼ 0.007), and TUG (OR ¼ 1.42; p ¼ 0.029) were significant factors for LS risk. The results of multiple regression analysis revealed that TUG and leg SMI were significantly related to Y LNG (Table 6). 4. Discussion This study investigated the relationship between the presence or absence of LS risk and postural stability by balance test in a prospective large-scale general population. The results of this study showed that among the four posturographic variables measured by the balance test, Y LNG was most related to LS risk. Various factors related to LS have been reported [20,26,27]. A previous study reported that serum cystatin C can be an early predictor for LS risk [18], but LS risk has received relatively little attention. Elderly and women were reported as risk factors for LS. Recent studies have also indicated that muscle mass is predictive of LS [28,29]. Regarding postural stability, previous studies reported on the increase in COP values with increase in age [6,30]. A study also showed that COP values depend on sex; males were found to be more upset than females in a large number of community-dwelling people [8]. Therefore, in this study, the relationship between LS risk and postural stability was analyzed in detail including aSMI by BIA and physical function. In addition, after controlling for age and sex by GLM, comparison was also made considering factors that can be more biased. The results of this study showed that the LS risk group was also significantly older than the normal group, and LS risk was more likely to occur in females than in males. Among the four posturographic variables by balance test, only LNG, Y LNG, and E AREA were significantly higher in the LS risk group. Since LNG and E AREA were indicators showing total postural sway and Y LNG was considered to indicate postural sway in the front-back direction, the postural sway significantly increased in the LS risk group. With regard to muscle mass and physical function, physical function was
Please cite this article as: Tanaka S et al., Increasing postural sway in balance test is related to locomotive syndrome risk: A cross-sectional study, Journal of Orthopaedic Science, https://doi.org/10.1016/j.jos.2019.01.011
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Table 3 Comparison between normal and LS risk groups. Variables
Age (years) Sex (male/female) BMI (kg/m2) PBF (%) LNG (cm) X LNG (cm) Y LNG (cm) E AREA (cm2) aSMI (kg/m2) Arm SMI (kg/m2) Leg SMI (kg/m2) Back muscle strength (kg) Grip strength (kg) TUG (s)
Non-adjusted
p-value
Normal (N ¼ 120)
LS risk (N ¼ 172)
62.1 (10.2) 62/58 22.9 (3.2) 27.1 (6.0) 48.0 (15.8) 32.9 (10.5) 28.0 (10.8) 2.5 (1.3) 6.77 (1.0) 1.69 (0.4) 5.08 (0.7) 76.2 (29.5) 29.0 (9.0) 6.0 (0.9)
65.6 (10.2) 60/112 23.9 (3.6) 30.5 (6.6) 53.9 (18.8) 35.1 (11.7) 33.3 (14.2) 2.9 (1.6) 6.62 (1.0) 1.63 (0.4) 4.99 (0.7) 58.3 (22.2) 24.9 (7.5) 6.6 (1.2)
0.013 * 0.006 ** 0.006 ** <0.001 *** 0.001 ** 0.056 <0.001 *** 0.002 ** 0.27 0.28 0.28 <0.001 *** <0.001 *** <0.001 ***
Age and sex-adjusted
p-value
Normal (N ¼ 120)
LS risk (N ¼ 172)
22.9 (0.4) 27.4 (0.6) 46.9 (1.9) 32.4 (1.2) 27.1 (1.4) 2.4 (0.2) 6.72 (0.08) 1.67 (0.03) 5.05 (0.06) 74.5 (2.1) 28.5 (0.5) 5.9 (0.1)
23.9 (0.3) 30.0 (0.5) 54.8 (1.6) 35.9 (1.0) 33.7 (1.2) 3.1 (0.1) 6.63 (0.07) 1.63 (0.03) 5.00 (0.05) 59.7 (1.7) 25.8 (0.4) 6.6 (0.1)
0.047 * 0.001 ** 0.002 ** 0.031 * <0.001 *** 0.001 ** 0.43 0.36 0.50 <0.001 *** <0.001 *** <0.001 ***
*< 0.05, **< 0.01, ***< 0.001, Mann-Whitney U test, Fisher's exact test. Parameter values are shown as the mean (standard deviation) or numbers for non-adjusted data, and corrected mean (standard error) or numbers of the mean for age and sexadjusted data. LS, locomotive syndrome; BMI, body mass index; PBF, percent body fat; LNG, distance of the movement of the center of pressure; X LNG, distance of the movement of the center of the pressure in the left-right direction; Y LNG, distance of the movement of the center of the pressure in the front-back direction; E AREA, envelopment area tracing by the movement of the center of pressure; aSMI, appendicular skeletal muscle index; TUG, timed up-and-go. Bold values indicate significant difference.
Table 4 Comparison among LS risk stages in total participants. Variables
Age (years) Sex (male/female) BMI (kg/m2) PBF (%) LNG (cm) X LNG (cm) Y LNG (cm) E AREA (cm2) aSMI (kg/m2) Arm SMI (kg/m2) Leg SMI (kg/m2) Back muscle strength (kg) Grip strength (kg) TUG (s)
LS risk stage
Significance (p)
No risk (N ¼ 120)
Stage 1 (N ¼ 133)
Stage 2 (N ¼ 39)
No risk vs. Stage 1
No risk vs. Stage 2
Stage 1 vs. Stage 2
ANOVA
62.1 (10.1) 62/58 22.9 (3.2) 27.1 (6.0) 48.0 (15.8) 32.9 (10.5) 28.0 (10.8) 2.5 (1.3) 6.8 (1.0) 1.7 (0.4) 5.1 (0.7) 76.2 (29.5) 29.0 (9.0) 6.0 (0.9)
65.1 (9.9) 50/83 24.1 (3.7) 30.8 (6.8) 52.1 (17.6) 34.5 (11.4) 31.6 (12.3) 2.9 (1.6) 6.7 (1.0) 1.6 (0.4) 5.0 (0.7) 60.8 (21.3) 25.8 (7.3) 6.4 (0.9)
67.2 (11.1) 10/29 23.4 (3.3) 29.7 (6.1) 60.1 (21.4) 37.0 (12.5) 38.9 (18.5) 3.1 (1.6) 6.4 (1.0) 1.6 (0.4) 4.9 (0.7) 49.7 (23.4) 21.9 (7.7) 7.2 (1.6)
0.048* 0.031* 0.017* <0.001*** 0.15 0.47 0.046* 0.069 0.77 0.69 0.83 <0.001*** 0.005** 0.001**
0.018* 0.005** 0.78 0.078 0.001** 0.11 <0.001*** 0.035* 0.16 0.21 0.17 <0.001*** <0.001*** <0.001***
0.50 0.19 0.44 0.63 0.033* 0.44 0.005** 0.59 0.36 0.48 0.32 0.044* 0.024* <0.001***
0.009** 0.007** 0.023* <0.001*** 0.001** 0.12 <0.001*** 0.017* 0.19 0.23 0.19 <0.001*** <0.001*** <0.001***
*p < 0.05, **p < 0.01, ***p < 0.001, Tukey-Kramer test, Fisher's exact test. Parameter values are shown as the mean (standard deviation) or numbers. LS, locomotive syndrome; BMI, body mass index; PBF, percent body fat; LNG, distance of the movement of the center of pressure; X LNG, distance of the movement of the center of the pressure in the left-right direction; Y LNG, distance of the movement of the center of the pressure in the front-back direction; E AREA, envelopment area tracing by the movement of the center of pressure; aSMI, appendicular skeletal muscle index; TUG, timed up-and-go; ANOVA, analysis of variance. Bold values indicate significant difference.
Table 5 Logistic regression model for prediction of LS risk. Variables
Coefficient (b)
Odds ratio
95% CI
p-value
Back muscle strength (kg) BMI (kg/m2) Y LNG (cm) TUG (s)
0.029 0.138 0.036 0.351
0.971 1.15 1.04 1.42
0.960e0.983 1.054e1.250 1.010e1.065 1.036e1.948
<0.001 *** 0.002 ** 0.007 ** 0.029 *
*< 0.05, **< 0.01, ***< 0.001. The dependent variable was LS risk. Covariates were age, sex, BMI, PBF, back muscle strength, grip strength, TUG, X LNG, Y LNG, and E AREA. LS, locomotive syndrome; CI, confidence interval; BMI, body mass index; Y LNG, distance of the movement of the center of the pressure in the front-back direction; TUG, timed up-and-go; X LNG, distance of the movement of the center of the pressure in the left-right direction; E AREA, envelopment area tracing by the movement of the center of pressure. Bold values indicate significant difference.
significantly lower in the LS risk group than in the normal group, but no significant difference was found in muscle mass, and almost the same result was obtained even after controlling for age and sex.
These results suggest that the evaluation of LS risk involves motor function but not muscle mass. Since the LS risk group also includes subjects close to the normal group, no significant difference may be
Please cite this article as: Tanaka S et al., Increasing postural sway in balance test is related to locomotive syndrome risk: A cross-sectional study, Journal of Orthopaedic Science, https://doi.org/10.1016/j.jos.2019.01.011
S. Tanaka et al. / Journal of Orthopaedic Science xxx (xxxx) xxx Table 6 Summary of multiple regression analysis for Y LNG. Independent variables
TUG (s) Leg SMI (kg/m2) Grip strength (kg) Arm SMI (kg/m2) Back muscle strength (kg)a
Y LNG Coefficient (b)
p-value
0.302 0.203 0.059 0.011 0.001
<0.001 *** <0.001 *** 0.47 0.93 0.99
***< 0.001. The dependent variable was Y LNG. The independent variables were arm SMI, leg SMI, back muscle strength, grip strength, and TUG. Y LNG, distance of the movement of the center of the pressure in the front-back direction; TUG, timed up-and-go; SMI, skeletal muscle index. Bold values indicate significant difference.
observed in muscle mass. The LS risk group showed decreased physical function before the muscle mass decreased. Logistic regression analysis of the important factors related to LS risk showed that weak back muscle strength, high BMI, high Y LNG, and slow TUG were significant factors. These results indicate that increasing back-and-forth sway was particularly important for LS risk among the postural sway. The Y LNG by balance test is a related factor of LS risk unaffected by age and sex, and it was shown that the higher the Y LNG, the higher the possibility of being LS risk. In addition, to investigate the relationship between Y LNG and muscle mass and physical function, multiple regression analysis showed that TUG and leg SMI were significantly associated with Y LNG. Variables, such as aSMI, arm SMI, grip strength, and back muscle strength including upper limbs and trunk elements, did not show significant association with Y LNG. In other words, Y LNG was speculated to be related to physical function and muscle mass of the lower limbs, which confirms the relationship with LS risk. This study has several limitations. First, it targeted residents in rural areas, and a possibility of bias exists because the living and working environments differ from those in urban areas. Furthermore, evaluation of comorbidities and mental health is not enough. Second, only few participants were included in the subgroup analysis for each age group. Third, this study was a cross-sectional study. A longitudinal study is necessary in the future. In summary, the LS risk group showed increased postural sway in the balance test after controlling for age and sex. Among the four posturographic variables by balance test, Y LNG was the most remarkable variable associated with LS risk. Furthermore, Y LNG was considered to be significantly related to muscle mass and physical function of the lower limbs, which strongly suggested an association with LS risk. If the balance test shows an increase in Y LNG, attention should be paid to LS risk for possible intervention and early treatment. Conflicts of interest None. Acknowledgments We are grateful to the staff of the Comprehensive Health Care Program held in Yakumo, Hokkaido, and Ms. Marie Miyazaki and Ms. Hiroko Ino of Nagoya University for their assistance throughout this study. References [1] Nakamura K. The concept and treatment of locomotive syndrome: its acceptance and spread in Japan. J Orthop Sci 2011 Sep;16(5):489e91.
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Please cite this article as: Tanaka S et al., Increasing postural sway in balance test is related to locomotive syndrome risk: A cross-sectional study, Journal of Orthopaedic Science, https://doi.org/10.1016/j.jos.2019.01.011