Jung et al.
Journal of Physiological Anthropology(2023) 42:16
https://doi.org/10.1186/s40101-023-00334-3

ORIGINAL ARTICLE

Journal of
Physiological Anthropology

Open Access

Association of sarcopenia, pre‑sarcopenia,
and dynapenia with the onset and progressionof locomotive syndrome in Japanese older
adults: a cross‑sectional study
Hungu Jung1,2,3, Shigeharu Tanaka1,4, Shusei Kataoka5 and Ryo Tanaka1*

Abstract
Background Sarcopenia commonly occurs in older adults with motor disorders requiring long-term care,and the clinical features of sarcopenia are associated with locomotive syndrome. Dynapenia is the age-related lossof muscle strength. However, the association of sarcopenia and dynapenia with the onset and progression of locomotive syndrome in older adults remains unknown. The current study aimed to determine the association of sarcopenia,
pre-sarcopenia, and dynapenia with the onset and progression of locomotive syndrome in Japanese older adults.
Methods This study included older females (n = 264, 73.9 ± 5.8 years) and males (n = 92, 76.3 ± 6.1 years). Sarcopenia
was defined as low muscle function and mass; pre-sarcopenia was defined as low muscle mass with normal muscle
function; and dynapenia was defined as low muscle function without low muscle mass. Locomotive syndrome (stage0–2) severity was determined using the stand-up test, the two-step test, and the 25-question geriatric locomotivefunction scale. Logistic regression analysis was performed to determine the relationship between sarcopenia category
and locomotive syndrome stages.
Results Age (1.208, 95% confidence interval (CI) 1.124–1.298), sex (2.455, 95% CI 1.241–4.856), and BMI (1.211, 95%
CI 1.077–1.361) were significant variables for determining locomotive syndrome stage ≥ 1, whereas pre-sarcopenia(0.543, 95% CI 0.331–0.891) and sarcopenia (1.664, 95% CI 1.005–2.755) were significant variables for determining
locomotive syndrome stage 2.
Conclusions Only sarcopenia was associated with locomotive syndrome progression, while low muscle mass or low
muscle function was not associated with locomotive syndrome. Gaining muscle mass accompanied by an increased
muscle function for older adults is warranted to prevent locomotive syndrome progression in the super-aged society.
Keywords Locomotive syndrome, Muscle function, Muscle mass, Older adults, Sarcopenia*Correspondence:
Ryo Tanaka
ryotana@hiroshima-u.ac.jp
Full list of author information is available at the end of the article© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of thislicence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​
mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Jung et al. Journal of Physiological Anthropology(2023) 42:16

Background
Locomotive function impairment is a cause of healthdisparities among older adults aged ≥ 65 years [1]. Olderadults who experience difficulty walking, climbing stairs,
going to the shop, or doing housework are at higher riskof requiring nursing services compared to those who do
not experience the same difficulties [2]. In this context,
the Japanese Orthopaedic Association (JOA) in 2007
proposed the concept of locomotive syndrome (LS) [3],which is associated with musculoskeletal disorders [1].
Aging has been associated with changes in body composition, such as skeletal muscle mass and body massindex (BMI). Accordingly, BMI has been associated withmortality, with individuals having an increased BMI withmuscle mass loss being at a higher risk of death [4]. Sarcopenia and pre-sarcopenia are conditions characterized
by changes in body composition and muscle function,
particularly muscle mass loss, declined motor ability,
or loss of muscle function, in older adults [5]. Previous
reports have demonstrated that sarcopenia was common in older adults with motor disorders requiring longterm care [6] and that the clinical features of sarcopenia
were subsequently associated with LS [7]. Gaining muscle mass in older adults may does not prevent muscle
strength loss with aging, considering that muscle strength
is lost at a considerably faster rate than muscle mass [8].
Clark and Manini [9] had proposed the term “dynapenia”
to describe age-related loss of muscle strength against
sarcopenia, which can be used in its original context todescribe age-related loss of muscle mass. Muscle strength
loss is an essential factor of LS [7]. To the best of ourknowledge, the impact of muscle mass and/or function
loss, including strength loss, in older adults with LS has
yet to be investigated. Moreover, the association of sarcopenia, pre-sarcopenia, and dynapenia with the onset andprogression of LS in older adults remains unclear. Confirming the extent of the association would certainly help
prevent the onset and progression of LS due to musculoskeletal disorders in older adults.
Therefore, the current study aimed to determine theassociation of sarcopenia, pre-sarcopenia, and dynapenia with the onset and progression of LS in older adults.
We hypothesized that muscle mass and/or function loss
would be strongly linked to older adults with LS.
Methods
Study design

This cross-sectional study included Japanese communitydwelling older adults. All parameters were essential forassessing the subjects’ functional status and were notharmful. All procedures were conducted in accordancewith the Ethical Principles for Medical Research Involving Human Subjects of 1975 stated in the World Medical

Page 2 of 9

Association Declaration of Helsinki. This research has
been approved by the institutional review board of theauthors’ affiliated institutions (approval number: 02–05).
Setting

Participants were recruited from the staff of regional
comprehensive support centers, community centers, andgymnasiums throughout Hiroshima Prefecture, Japan. A
flyer with an outline of this study was also used for subject recruitment. Subject recruitment and data measurements were performed between November 2020 and
December 2021.
ParticipantsCommunity-dwelling individuals aged ≥ 65 years andindividuals with independent mobility were included inthis study. All participants provided written informed
consent before participating. Whereas, individuals
with suspected cognitive dysfunction and severe illness(unstable cardiovascular disease, stroke, serious breathing impairment, Parkinson’s disease, diabetic peripheral
neuropathy, injury to the spinal cord, or rheumatoid
arthritis) were excluded from this study to ensure theaccuracy of responses to the questionnaire survey andprevent falls during measurement and worsening of diseases, respectively.
Sarcopenia category

Participants were classified into the normal, pre-sarcopenia, dynapenia, and sarcopenia groups according to aprevious study [10] (Fig. 1). According to the diagnostic
algorithm established by the Asian Working Group for
Sarcopenia, sarcopenia was defined as the presence ofboth low muscle mass, as measured using the skeletal
mass index (SMI), and low muscle function, as measured
using hand grip and walking speed [11]. Pre-sarcopenia
was defined as the presence of low muscle mass without low physical performance or low muscle strength
based on the European Working Group on Sarcopenia in
Older People (EWGSOP) definition [12]. Dynapenia wasdefined as the presence of low muscle function without
low muscle mass [10].
Skeletal muscle mass index

SMI, a skeletal muscle mass index, was measured throughmultifrequency bioelectrical impedance analysis (MFBIA; InBody 270, Tokyo, Japan) [13]. InBody270 estimates SMI in absolute values (kg), which is subsequently
calculated by height squared (­m2). The technique also
estimates body fat. The height was referred to as the mostrecent value of the subject. SMI measurements begin
at 10 am or 2 pm for the convenience of participants.
These time points may be 1–3 h after meals. The indoor

Jung et al. Journal of Physiological Anthropology(2023) 42:16

Page 3 of 9

Fig. 1 Methods of categorization based on skeletal mass index (SMI) and muscle function

temperature was set to keep a comfortable temperatureby heating or cooling, depending on the season. The MFBIA instrument is a common method used to measurebody composition, such as SMI. Body mass index (BMI)
was divided by the height in meters squared. This tool isinstantaneous, versatile, convenient, and noninvasive formeasuring bioelectrical impedance.
Measurements of physical performances

Walking time is a reliable and valid method for measuring walking speed [14]. The test subjects walked along a
5-m path as instructed. A spare path of 1 m was provided
for walking. The following instruction was provided foruniformity: “Walk forward at normal speed.” The subjects
were only measured once.
Measuring hand-grip strength using a hand-helddynamometer has been reported to be reliable and valid[15]. In this study, a grip strength meter (TKK 5401
Grip-D; Takei, Niigata, Japan) was utilized for measuring grip strength. The test subjects held the grip strength
meter with the pointer facing outward. The interphalangeal joints of the fingers were adjusted so that they were
nearly at right angles prior to measurement. Measurements were recorded in kilograms. The average of eachhand was used for subsequent analysis.

Previous studies have confirmed that this test had good
validity, reliability, and feasibility [16, 17].
In the stand-up test, an individual who was able tostand from a 40-cm platform using both legs and standfrom the same height using a single leg (both right andleft side) was determined not to have LS (stage 0). An
individual with LS stage 1 could not stand on a 40-cm
platform with either leg, but could stand on a 20-cm platform with both legs. It was determined that an individualwith LS stage 2 could not stand on a 20-cm platform withboth legs but could stand on a 30-cm platform.
In the two-step test, the distance between the firststanding line and the landing point’s toe was determined. This test was conducted twice, with the better
result being recorded. The two-step test score was calculated by dividing the distance (cm) by the height (cm).
Using this test, severity was categorized as follows: stage
0, 1.3 ≤ two-step test score; stage 1, 1.1 ≤ two-step testscore < 1.3; and stage 2, two-step test score < 1.1.
Using GLFS-25, severity was categorized based on thefollowing criteria: stage 0, 7 points < GLFS-25 score; stage
1, 7 points ≤ GLFS-25 score < 16 points; and stage 2, 16
points ≤ GLFS-25 score.
The final LS severity was determined after completing
all three tests. Among the severity stages determined by
the outcomes of three tests, the most severe stage wasselected for further analysis.

Categorical outcome

The main outcome measure was LS severity, which wasassessed using the LS risk test developed to detect motor
dysfunction closely associated with disability. This test
consists of the stand-up test, two-step test, and 25-question geriatric locomotive function scale, a self-administered questionnaire (GLFS-25) [16] proposed by the JOA.

Statistical analysis

The Shapiro–Wilk test was used to verify the normalityof data distribution, whereas Levene’s test was used toassess the homogeneity of variance. Independent sample t-tests were conducted when the data were homogeneous and normally distributed to compare variables
between sexes, whereas Mann–Whitney U tests wereJung et al. Journal of Physiological Anthropology(2023) 42:16

applied whenever normality and homogeneity of variance were absent. Differences in the proportion of LS
stages between sarcopenia categories were tested using
chi-square tests. Analysis of variance (ANOVA) for background information was conducted separately for males
and females to determine the subject characteristics
across each sarcopenia category. The post-hoc test was
performed using the Tukey method. Logistic regression
analysis using forced entry method was performed todetermine the relationship between sarcopenia category
and LS. Sarcopenia category was entered into the regression model as independent variables. In logistic regression analysis, we used the deviation contrasts to compare
the effect of each category (pre-sarcopenia, dynapenia,
or sarcopenia) except the reference category (normal) to
the overall effect. To adjust for the relationship between
sarcopenia category and LS severity, age, sex, and BMI
was included in the regression model as a confounding variable. In model 1, the dependent variable was thebinary value of LS severity, which was either 0 or ≥ 1. The
dependent variable in model 2 was a binary variable withan LS severity of ≤ 1 or 2. The significance level was set
p < 0.05. SPSS (Version 18, SPSS, JAPAN) was used for all
statistical analyses.
Sample size

We followed standard methods for estimating the sample size using multiple logistic regression, with at least
10 outcomes needed for each included independent variable [18]. The number of variables to be fed into the independent variables of our logistic regression model wassix (age, sex, BMI, pre-sarcopenia, dynapenia, and sarcopenia). Assuming an 20% prevalence of LS stage 0 basedon a previous study showing an 19.0% prevalence of LS
stage 0 (females, 18.7%; males, 19.6%) [19], 300 subjects(among whom 60 had LS stage 0) were required to appropriately perform logistic regression with six variables.

Results
A total of 356 subjects participated in this study. The subjects’ background information is summarized in Tables 1
and 2. Females and males were significantly different inall variables (p < 0.05). ANOVA showed that all variables
differed significantly according to sarcopenia category inboth females and males. BMI in the dynapenia and normal groups in both females and males was significantly
higher than in the pre-sarcopenia and sarcopenia groups(p < 0.05). The sarcopenia group was older than the presarcopenia and normal groups in females while the sarcopenia group was older than the dynapenia group in males(p < 0.05).

Page 4 of 9

The results of logistic regression analysis are shown in
Table 3. In model 1 (dependent variable; LS stage ≥ 1),
age (p < 0.001), sex (p = 0.010), and BMI (p = 0.001) wereidentified as significant independent variables. In model
2 (dependent variable; LS stage 2), the sarcopenia category (p = 0.026) was determined to be a significant independent variable, with the odds ratios for pre-sarcopenia(0.543, 95% confidence interval (CI) 0.331–0.891) andsarcopenia (1.664, 95% CI 1.005–2.755) being significant.

Discussion
The current study investigated the association of sarcopenia, pre-sarcopenia, and dynapenia with the onset
and progression of LS on a community of Japanese older
adults. Our results revealed that in a logistic regression
analysis using the results of the overall judgment with thethree tests, the standard method to assess LS severity,age, sex, and BMI are significant variables for LS stage ≥ 1
as are pre-sarcopenia and sarcopenia for LS stage 2.
Musculoskeletal disorders were found to be associatedwith LS [7]. Sarcopenia characterized by muscle massloss frequently occurred in older adults and was associated with a greater risk of incident disability [5, 6]. Recent
studies have reported that sarcopenia can completelyreflect serious health problems among older adults andthat most older adults with sarcopenia had LS [19, 20].
LS with sarcopenia was found to be an essential factor inearly identification of older adults who are at a higher riskof deterioration in health status and subsequent disability [21]. Considering the need for preventing disability offunctional capacity, detailed evaluation of advancing LS
stage is imperative. However, no study on communitydwelling older adults had examined the relationshipbetween the classification of sarcopenia, pre-sarcopenia,
and dynapenia by loss of muscle mass and/or function
and the onset and progression of LS. Thus, this is the firststudy to report on the association of sarcopenia, pre-sarcopenia, and dynapenia with the onset and progressionof LS.
BMI was a significant factor for the onset of LS, but
it cannot be distinguished by the components of bodyweight, such as fat mass, muscle mass, bone, and organs.
Sex was related to the onset of LS; i.e., females are more
likely to have LS due to the difference in physical function between sexes, e.g., low muscle mass and weak muscle strength [22]. However, age was a significant factor forthe onset of LS as females have more life extensity thanmales [23]. Therefore, we fully agree on the importanceof preventing the onset of LS in super-aging societies,
such as Japan.
The current study found that pre-sarcopenia was asignificant variable of LS stage 2 with an OR of < 1, indicating that older adults with normal muscle functionJung et al. Journal of Physiological Anthropology(2023) 42:16

Page 5 of 9

Table 1 The background information of the subject (women)
Sarcopenia category

Overall

Sarcopenia

Pre-sarcopenia

Dynapenia

NormalNumber

264

41

77

32

114

Age, year

73.9

78.0

73.8

76.2

71.8

< 0.001

(5.8)

(6.6)

(5.2)

(6.7)

(4.5)

P, N < S
N<D

152.9

149.5

152.0

151.8

155.0

< 0.001

(5.4)

(4.8)

(4.7)

(6.4)

(4.9)

S, P, D < N
S<PWeight, kg

52.9

46.9

48.2

56.0

57.3

< 0.001

(8.0)

(6.4)

(5.0)

(8.2)

(6.9)

S, P < D, N

BMI, kg/m2

22.6

21.0

20.9

24.4

23.9

< 0.001

(3.2)

(2.7)

(2.3)

(3.7)

(2.8)

S, P < D, N

5.8

5.2

5.3

6.0

6.2

< 0.001

(0.6)

(0.3)

(0.2)

(0.3)

(0.4)

S, P < D, N

1.3

1.0

1.4

1.0

1.3

< 0.001

(0.3)

(0.3)

(0.2)

(0.3)

(0.2)

S, D < P, N

21.0

17.5

21.4

16.7

23.7

< 0.001

(4.3)

(2.8)

(2.1)

(5.3)

(3.6)

S, D < P < N

46

4

16

5

21

0.043†

17.4%

9.8%

20.8%

15.6%

18.4%

151

21

49

14

67

57.2%

51.2%

63.6%

43.8%

58.8%

Height, cm

SMI, kg/m2
Walking speed, m/sec
Hand grip, kg
LS Stage 0, number
LS Stage 1, number
LS Stage 2, number

67

16

12

13

26

25.4%

39.0%

15.6%

40.6%

22.8%

P value

Upper row; average, lower row; (standard deviation)
P value (analysis of variance)
Data under the P values are the results of post-hoc test (Tukey)†

P-value (chi-square test)

LS locomotive syndrome, S sarcopenia, P pre-sarcopenia, D dynapenia, N normalmight not be diagnosed with LS stage 2. Individuals withpre-sarcopenia have normal muscle function evaluatedusing a 5-m walking speed and hand grip strength. Baseline walking speeds of ≥ 1.07 m/s in men and ≥ 1.02 m/s
in women have been used for the clinical determination without a possibility for having a disability requiring long-term care within the Japanese population [24].
One study showed that grip strength was associated withmobility [25]. Specific grip strength thresholds have beenused to identify older adults who likely have walking limitations, with walking speeds as slow as < 0.80 m/s [25].
Grip strength thresholds for older men (23.2–39.0 kg)
and women (15.9–22.0 kg) have been reported [25]. In
the current study, subjects with pre-sarcopenia showed
a walking speed of 1.2 and 1.4 m/s and grip strength of
31.5 and 21.4 kg in older men and women, respectively,
suggesting that keeping higher walking speed and normal grip strength could help prevent the progressionof LS. Furthermore, our results showed that those withpre-sarcopenia displayed significantly lower weight and
BMI than those in the normal and dynapenia groups,

which can positively contribute to locomotion. EWGSOP
defined pre-sarcopenia as a conceptual staging of sarcopenia representing the age-related decrease in muscle
mass, indicating that pre-sarcopenia can develop into
sarcopenia with weak low muscle function [12]. From
this perspective, our results only indicate that despite adecrease in muscle mass, normal muscle function could
help prevent the progression of LS.
Dynapenia was not a significant factor for LS stage 2,
indicating that low muscle function alone may not be
associated with LS progression, like low muscle mass
alone did not contribute to LS stage 2. Dynapenia wasa stronger predictor for falls, mortality, and activities
of daily living in community-dwelling older adults [26–28]. Weak muscle strength, as one of low muscle function, compared with muscle mass, was more strongly
associated with poor physical performance [29]. A longitudinal study reported that muscle strength decline
in older adults is more rapid than the concomitantloss of muscle mass, indicating a reduction in muscle
quality [30]. They also noted that maintenance or evenJung et al. Journal of Physiological Anthropology(2023) 42:16

Page 6 of 9

Table 2 The background information of the subject (men)Sarcopenia category

Overall

Sarcopenia

Pre-sarcopenia

Dynapenia

NormalP value

Number

92

17

19

17

39

Age, year

76.3

82.7

78.1

75.1

73.0

< 0.001

(6.1)

(4.9)

(6.8)

(5.4)

(3.6)

N < P, D < S

Height, cm

Weight, kg
BMI, kg/m2
SMI, kg/m2
Walking speed, m/sec
Hand grip, kg

164.1

158.3

164.3

162.7

167.1

< 0.001

(6.3)

(5.4)

(5.4)

(5.3)

(5.6)

D, S < N
S<P

63.0

55.4

57.4

67.3

67.3

< 0.001

(9.1)

(6.7)

(6.3)

(6.3)

(8.8)

S, P < D, N

23.4

22.1

21.3

25.4

24.1

< 0.001

(2.8)

(2.1)

(2.1)

(2.2)

(2.7)

S, P < D, N

7.1

6.4

6.5

7.5

7.6

< 0.001

(0.7)

(0.5)

(0.3)

(0.5)

(0.5)

S, P < D, N

1.2

1.1

1.2

0.9

1.3

< 0.001

(0.2)

(0.3)

(0.2)

(0.1)

(0.2)

D, S < P, N

33.1

25.7

31.5

35.3

36.1

< 0.001

(6.3)

(5.3)

(3.2)

(6.9)

(4.6)

S<P<N
S<D

LS Stage 0, number

20

2

3

3

12

0.006†

21.7%

11.8%

15.8%

17.7%

30.8%

LS Stage 1, number

47

4

12

9

22

51.1%

23.5%

63.2%

52.9%

56.4%

LS Stage 2, number

25

11

4

5

5

27.2%

64.7%

21.0%

29.4%

12.8%

Upper row; average, lower row; (standard deviation)
P value (analysis of variance)
Data under the P values are the results of post-hoc test (Tukey)†

P value (chi-square test)

LS locomotive syndrome, S sarcopenia, P pre-sarcopenia, D dynapenia, N normal

Table 3 Results of logistic regression analysis
Independent variables

Dependent variables

Model 1 (LS stage ≥ 1)
OR

Model 2 (LS stage 2)

95% CI
Lower limit

P valueOR

Upper limit

95% CI
Lower limit

P value
Upper limit

Age

1.208

1.124

1.298

< 0.001

1.098

1.048

1.151

0.001

Sex (1 = female)

2.455

1.241

4.856

0.010

1.268

0.708

2.272

0.425

BMI

1.211

1.077

1.361

0.001

1.040

0.946

1.142

Sarcopenia Category(Reference: Normal)

0.820

0.418
0.026

Pre-sarcopenia

1.200

0.680

2.117

0.530

0.543

0.331

0.891

0.016

Dynapenia

0.746

0.392

1.538

0.427

1.345

0.789

2.292

0.275

Sarcopenia

1.222

0.567

2.635

0.610

1.664

1.005

2.755

0.048

LS locomotive syndrome, OR odd ratio, CI confidence intervalmuscle mass gain for the older adults did not necessarily prevent muscle strength loss [30]. This paradoxicallyemphasizes a need for muscle mass gain accompanied
by increased muscle strength.

Muscle weakness can decrease physical function,
diminish physical activity, and sometimes mobility disability [22, 29, 31], which is associated with low muscle
mass [30]. Therefore, attention should also be given toJung et al. Journal of Physiological Anthropology(2023) 42:16

older adults with dynapenia. Moreover, the hand grip
strength test is more objective and safe, which indirectly
evaluates locomotion ability [25].
In previous studies, the majority of older adults withsarcopenia were diagnosed with LS [19, 21]. In accordance with this, the current study added new evidence
that sarcopenia was a significant factor for LS stage 2 but
was unrelated to the onset of LS. The stand-up test, twostep test, and GLFS-25 assessing LS severity were highly
correlated with lower extremity muscle strength, gaitfunction, and activities of daily living, respectively [32].
In addition, our results revealed that low muscle massand function were strongly associated with advanced LSseverity, indicating that it is essential for increasing muscle mass and function in order to prevent the progressionof LS.
However, older adults without sarcopenia, pre-sarcopenia, or dynapenia, were diagnosed with LS in our study:
93 females (LS stage 1, 67; LS stage 2, 26) and 27 males(LS stage 1, 22; LS stage 2, 5). This indicates that LS canoccur or develop even in an older adult without losing
muscle mass and/or function. A previous study reported
that reduced static postural and balance ability assessedusing a single-leg standing test was a predictive factor
for the onset and progression of LS [33]. Therefore, otherpathologies independent of low muscle mass and function should be investigated.
Our results have important practical implications forthe risk of LS. Early detection of low muscle function
is crucial for preventing the development of sarcopenia
among older adults, consequently considerably reducing the likelihood of developing severe LS associatedwith functional disabilities and need for care service [34].
Furthermore, loss of muscle mass and function should
be prioritized during evaluation. Therefore, exercise
intervention programs for older adults should be recommended to gain muscle mass with an increase in muscle
function, which would prevent the prevalence of sarcopenia and the progression of LS severity in older adults.
This study had several limitations. First, the results
obtained from Japanese older adults cannot be generalized to all older adult populations given the differencesin hand grip strength among races [35]. Second, given
the cross-sectional nature of this study, the influence ofsarcopenia, pre-sarcopenia, and dynapenia on LS overtime may be difficult to elucidate within a specified
period of physical ability decreasing by age. Further longitudinal studies are thus essential to evaluate the influence of sarcopenia, pre-sarcopenia, and dynapenia on
LS over time. Third, this study defined dynapenia as low
muscle function without low muscle mass; however, nointernationally accepted definition of dynapenia has yet
been established. Fourth, pre-sarcopenia was definedPage 7 of 9

based on the EWGSOP in 2011 [12], which is not thecurrent definition. Moreover, EWGSOP2 in 2019 did
not argue about the definition of pre-sarcopenia, possibly aiming no merit in diagnosing pre-sarcopenia[36]. We demonstrated that an individual with pre-sarcopenia was not negatively associated with LS severity.
Fifth, we used BIA methods to analyze body composition, and not dual-energy X-ray absorptiometry (DXA),
which is the gold-standard technique. BIA methods
strongly correlate with DXA methods, as reported in
one study [37]. Thus, our results were considered reliable. Additionally, attention should be given to the dataobtained using BIA methods because muscle mass isunder or overestimated by BIA methods compared to
DXA methods [37]. Sixth, we did not measure calf circumference to diagnose sarcopenia or pre-sarcopenia.
Calf circumference is an anthropometric measurement
to identify early a sign of sarcopenia and was strongly
correlated with SMI [11, 38], thereby corroborating our
findings. Finally, we did not standardize conditions to
reduce the estimation error of participants’ body compositions: fasting or staying for 4 h with no food or
drink consumption, absence of exercise in the previous day, absence of alcohol or diuretic drinks, normal
hydration level, and a stable temperature of 23 ℃ [39,40]. This is because of the characteristics of older adultparticipants. They may reject implementing standardized conditions for their health or daily habit. Thus,
we set it up, considering their convenience and safety.
The data in the current study may differ from thoseobtained under standardized conditions.

Conclusions
Our results revealed age, sex, and BMI to be significantly
associated with the onset of LS. Only sarcopenia wasrelated to LS progression, while low muscle mass or low
muscle function was not associated with LS. Therefore,
gaining muscle mass accompanied by an increased muscle function for older adults is warranted to prevent LS
progression in the super-aged society.
Abbreviations
ANOVA	Analysis of variance
BMI	Body mass index
CI	Confidence interval
EWGSOP	European Working Group on Sarcopenia in Older People
GLFS-25	25-Question geriatric locomotive function scale
JOA	Japanese Orthopaedic Association
LS	Locomotive syndrome
SMI	Skeletal mass index
Acknowledgements
We would like to thank Ms. Sayumi Amagata, Ms. Tian Hui, Ms. Rinna Nakamura, and Ms. Manami Yamamoto who belong to Hiroshima University fordata collection.

Jung et al. Journal of Physiological Anthropology(2023) 42:16

Authors’ contributions
HJ and RT contributed to the study design, data acquisition, statisticalanalysis, interpretation of the results, and manuscript preparation. ST and SK
participated in the study and reviewed the manuscript. All authors read andapproved the final manuscript.
Funding
There was no financial support in this study.
Availability of data and materials
Not applicable.

Declarations
Ethics approval and consent to participate
The ethical committee of the Graduate School of Humanities and Social Sciences of Hiroshima University approved this study (approval number: 02–05).
All participants provided written informed consent.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1
Graduate School of Humanities and Social Sciences, Hiroshima University,
1‑7‑1 Kagamiyama, Higashi‑Hiroshima City, Hiroshima, Japan. 2 Departmentof Medicine for Integrated Approach to Social Inclusion, Graduate Schoolof Biomedical and Health Sciences, Hiroshima University, 1‑2‑3 Kasumi,
Minami‑Ku, Hiroshima City, Hiroshima, Japan. 3 Department of Sports, Healthand Well‑Being, Faculty of Human Health Science, Hiroshima Bunka Gakuen
University, 3‑3‑20 Heiseigahama, Saka‑cho Aki‑gun, Hiroshima, Japan.
4
Physical Therapy Major, School of Rehabilitation, Kanagawa Universityof Human Services, 1‑10‑1 Heiseicho, Kanagawa, Yokosuka City, Japan. 5 Schoolof Integrated Arts and Sciences, Hiroshima University, 1‑7‑1 Kagamiyama,
Higashi‑Hiroshima City, Hiroshima, Japan.
Received: 9 April 2023 Accepted: 23 July 2023

References
1. Nakamura K. A “super-aged” society and the “locomotive syndrome.” J
Orthop Sci. 2008;13:1–2.
2. Ishii M, Kim Y, Suehara Y, Kawasaki T, Matsuoka J, Akaike K, et al. The recognition of locomotive syndrome in 2014: a cross-sectional study in theorthopeadic outpatients in Tokyo. Br J Med Med Res. 2015;6:606–16.
3. Nakamura K. The concept and treatment of locomotive syndrome: Its
acceptance and spread in Japan. J Orthop Sci. 2011;16:489–91.
4. Abramowitz MK, Hall CB, Amodu A, Sharma D, Androga L, Hawkins M.
Correction: Muscle mass, BMI, and mortality among adults in the UnitedStates: a population-based cohort study. PLoS ONE. 2018;13:1–16.
5. Chen LK, Liu LK, Woo J, Assantachai P, Auyeung TW, Bahyah KS, et al.
Sarcopenia in Asia: Consensus report of the Asian working group forsarcopenia. J Am Med Dir Assoc. 2014;15:95–101.
6. Landi F, Liperoti R, Fusco D, Mastropaolo S, Quattrociocchi D, Proia A, et al.
Prevalence and risk factors of sarcopenia among nursing home older
residents. J Gerontol Ser A Biol Sci Med Sci. 2012;67 A:48–55.
7. Ikemoto T, Arai YC. Locomotive syndrome: clinical perspectives. Clin
Interv Aging. 2018;13:819–27.
8. Manini TM, Clark BC. Dynapenia and aging : an update. 2012. p. 28–40.
9. Clark BC, Manini TM. Sarcopenia =/= Dynapenia. J Gerontol A Biol Sci
Med Sci. 2008;63:829–34.
10. Yamada M, Kimura Y, Ishiyama D, Nishio N, Abe Y, Kakehi T, et al. Differential characteristics of skeletal muscle in community-dwelling older adults.
J Am Med Dir Assoc. 2017;18:807.e9-807.e16.

Page 8 of 9

11. Chen LK, Woo J, Assantachai P, Auyeung TW, Chou MY, Iijima K, et al. Asian
Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia
Diagnosis and Treatment. J Am Med Dir Assoc. 2020;21:300-307.e2.
12. Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al.
Sarcopenia: European consensus on definition and diagnosis: Report of
the European Working Group on Sarcopenia in Older People. Age Ageing.
2010;39:412–23.
13. Czartoryski P, Garcia J, Manimaleth R, Napolitano P, Watters H, WeberC, et al. Body composition assessment: a comparison of the DXA,InBody270, and Omron. J Exerc Nutr. 2020;3:1.
14. Steffen TM, Hacker TA, Mollinger L. Age- and gender-related test
performance in community-dwelling elderly people: Six-Minute Walk
Test, Berg Balance Scale, Timed Up & Go Test, and gait speeds. Phys Ther.
2002;82:128–37.
15. Abizanda P, Navarro JL, García-Tomás MI, López-Jiménez E, MartínezSánchez E, Paterna G. Validity and usefulness of hand-held dynamometry
for measuring muscle strength in community-dwelling older persons.
Arch Gerontol Geriatr. 2012;54:21–7.
16. Seichi A, Hoshino Y, Doi T, Akai M, Tobimatsu Y, Iwaya T. Developmentof a screening tool for risk of locomotive syndrome in the elderly:
The 25-question Geriatric Locomotive Function Scale. J Orthop Sci.
2012;17:163–72.
17. Ogata T, Muranaga S, Ishibashi H, Ohe T, Izumida R, Yoshimura N, et al.
Development of a screening program to assess motor function in theadult population: a cross-sectional observational study. J Orthop Sci.
2015;20:888–95.
18. Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A simulation
study of the number of events per variable in logistic regression analysis.
J Clin Epidemiol. 1996;49:1373–9.
19. Yoshimura N, Muraki S, Iidaka T, Oka H, Horii C, Kawaguchi H, et al. Prevalence and co-existence of locomotive syndrome, sarcopenia, and frailty:
the third survey of Research on Osteoarthritis/Osteoporosis Against
Disability (ROAD) study. J Bone Miner Metab. 2019;37:1058–66.
20. Ohyama S, Hoshino M, Takahashi S, Hori Y, Yabu A, Kobayashi A, et al. Predictors of dropout from cohort study due to deterioration in health status, with focus on sarcopenia, locomotive syndrome, and frailty: from the
Shiraniwa Elderly Cohort (Shiraniwa) study. J Orthop Sci. 2021;26:167–72.
21. Nishimura T, Imai A, Fujimoto M, Kurihara T, Kagawa K, Nagata T, et al.
Adverse effects of the coexistence of locomotive syndrome andsarcopenia on the walking ability and performance of activities of dailyliving in Japanese elderly females: a cross-sectional study. J Phys Ther Sci.
2020;32:227–32.
22. Visser M, Goodpaster BH, Kritchevsky SB, Newman AB, Nevitt M, Rubin
SM, et al. Muscle mass, muscle strength, and muscle fat infiltration as predictors of incident mobility limitations in well-functioning older persons.
J Gerontol A Biol Sci Med Sci. 2005;60:324–33.
23. Kyu HH, Abate D, Abate KH, Abay SM, Abbafati C, Abbasi N, et al. Global,
regional, and national disability-adjusted life-years (DALYs) for 359
diseases and injuries and healthy life expectancy (HALE) for 195 countries
and territories, 1990–2017: a systematic analysis for the Global Burden of
Disease Study 2017. Lancet. 2018;392:1859–922.
24. Yoshimura N, Oka H, Muraki S, Akune T, Hirabayashi N, Matsuda S, et al.
Reference values for hand grip strength, muscle mass, walking time,and one-leg standing time as indices for locomotive syndrome andassociated disability: The second survey of the ROAD study. J Orthop Sci.
2011;16:768–77.
25. Bohannon RW. Grip strength: an indispensable biomarker for older adults.
Clin Interv Aging. 2019;14:1681–91.
26. Iwamura M, Kanauchi M. A cross-sectional study of the association
between dynapenia and higher-level functional capacity in daily living incommunity-dwelling older adults in Japan. BMC Geriatr. 2017;17:1–6.
27. Alexandre Tda S, Duarte YA, Santos JL, Wong R, Lebrão ML. Sarcopenia
according to the European Working Group on Sarcopenia in Older People (EWGSOP) versus dynapenia as a risk factor for mortality in the elderly.
J Nutr Health Aging France. 2014;18:751–6.
28. Scott D, Sanders KM, Aitken D, Hayes A, Ebeling PR, Jones G. Sarcopenic
obesity and dnapenic obesity: 5-year associations with falls risk in
middle-aged and older adults. Obesity. 2014;22:1568–74.
29. Kim M, Tsuji T, Kitano N, Yoon J, Soma Y, Jindo T, et al. Relationships between sarcopenia or Dynapenia and physical function inJung et al. Journal of Physiological Anthropology

30.

31.

32.
33.

34.
35.
36.
37.
38.

39.
40.

(2023) 42:16

Page 9 of 9community- dwelling older adults. Japan J Test Eval Health Physical Educ.
2016;15:1–10 (in Japanese).
Goodpaster BH, Park SW, Harris TB, Kritchevsky SB, Nevitt M, Schwartz
AV, et al. The loss of skeletal muscle strength, mass, and quality in older
adults: The Health, Aging and Body Composition Study. J Gerontol Ser A
Biol Sci Med Sci. 2006;61:1059–64.
Gómez-Cabello A, Carnicero JA, Alonso-Bouzón C, Tresguerres JÁ, AlfaroAcha A, Ara I, et al. Age and gender, two key factors in the associations
between physical activity and strength during the ageing process.
Maturitas. 2014;78:106–12.
Nakamura K, Ogata T. Locomotive syndrome: definition and management. Clin Rev Bone Miner Metab Springer US. 2016;14:56–67.
Tanaka S, Jung H, Yamashina S, Inoue Y, Nakashima N, Tanaka R. Clinicalprediction rule for locomotive syndrome in older adults: a decision treemodel. J Orthop Sci. Elsevier Ltd; 2022.https://​doi.​org/​10.​1016/j.​jos.​2022.​
04.​008.
Iwaya T, Doi T, Seichi A, Hoshino Y, Ogata T, Akai M. Relationship between
physician-judged functioning level and self-reported disabilities in elderly
people with locomotive disorders. Qual Life Res. 2017;26:35–43.
Forrest KYZ, Williams AM, Leeds MJ, Robare JF, Bechard TJ. Patterns
and correlates of grip strength in older Americans. Curr Aging Sci.
2018;11:63–70.
Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, et al.
Sarcopenia: Revised European consensus on definition and diagnosis.
Age Ageing. 2019;48:16–31.
Ward LC. Segmental bioelectrical impedance analysis: an update. Curr
Opin Clin Nutr Metab Care. 2012;15:424–9.
Kawakami R, Murakami H, Sanada K, Tanaka N, Sawada SS, Tabata I, et al.
Calf circumference as a surrogate marker of muscle mass for diagnosing sarcopenia in Japanese men and women. Geriatr Gerontol Int.
2015;15:969–76.
Kyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M, Gómez JM, et al.
Bioelectrical impedance analysis - Part II: Utilization in clinical practice.
Clin Nutr. 2004;23:1430–53.
Leão C, Simões M, Silva B, Clemente FM, Bezerra P, Camões M. Body
composition evaluation issue among young elite football players: DXA
assessment. Sports. 2017;5:1–9.

Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Ready to submit your research ? Choose BMC and benefit from:• fast, convenient online submission• thorough peer review by experienced researchers in your field• rapid publication on acceptance• support for research data, including large and complex data types• gold Open Access which fosters wider collaboration and increased citations• maximum visibility for your research: over 100M website views per year
At BMC, research is always in progress.
Learn more biomedcentral.com/submissions