Factors associated with muscle mass

Abstract

Background:Sarcopenia is a common elderly syndrome that increases the risk of falls and fractures, affects the ability to live daily and reduces quality of life.The present study try to explore the factors associated with muscle mass by using Dual-energy X-ray absorptiometry(DXA) in Chinese postmenopausal women.
Methods: The clinical information of 234 postmenopausal women, ages 50 to 79, was included in this study. Every subject's height, weight, calf circumference (CC), and grip strength were recorded. The body mass index, or BMI, was computed. All subjects' DXA characteristics, such as their total mass, lean mass, fat mass, T value, and relative skeletal muscle index (RSMI), were also noted. Based on RSMI, the patients were separated into two groups: those with sarcopenia and those without. An analysis was conducted on the variations in grip strength, CC, DXA parameters, and demographic data between the two groups. The relationship between a number of variables and RSMI was investigated using bivariate correlation analysis. The link between each index and RSMI was examined using both univariate and multiple linear regression analysis, and a regression equation was produced.
Results:The study revealed that the sarcopenia group had significantly reduced BMI, grip strength, CC, RSMI, T value, total mass, lean mass, and fat mass compared to the non-sarcopenia group (P<0.05). Weight, fat mass, and CC had moderate correlations with RSMI (r=0.696, r=0.507, r=0.638, respectively, P < 0.05); T value and grip strength had weak correlations with RSMI (r=0.280, r=0.265, respectively, P < 0.05); BMI, total mass, and lean mass had strong correlations with RSMI (r=0.736, r=0.726, r=0.782, respectively, P < 0.05). The results of multiple linear regression analysis indicated that BMI (r=0.120, P<0.001) and CC (r=0.078, P<0.001) were the key variables linked to the muscle mass of postmenopausal women. We have RSMI = 0.473 + 0.120×BMI + 0.078×CC as the regression equation.
Conclusions: Compared to patients without sarcopenia, people with sarcopenia have lower BMIs, grip strengths, CCs, T values, total masses, lean masses, and fat masses. In postmenopausal women, there is a positive correlation between muscle mass and BMI and CC.

Full text

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Factors associated with muscle mass
Xiao Zhu
Third Hospital of Hebei Medical University
Yongli Zheng
Third Hospital of Hebei Medical University
Lei Gao
Third Hospital of Hebei Medical University
Ying Liu
Third Hospital of Hebei Medical University
Yan Wang
Third Hospital of Hebei Medical University
Wei Zhang
Third Hospital of Hebei Medical University
Ting ting Hu
Third Hospital of Hebei Medical University
Meiling Yang
Third Hospital of Hebei Medical University
Research Article
Keywords: Postmenopausal, Sarcopenia, Strength, BMI, Calf circumference
Posted Date: May 8th, 2024
DOI: https://doi.org/10.21203/rs.3.rs-4340017/v1
License:   This work is licensed under a Creative Commons Attribution 4.0 International License. 
Read Full License
Additional Declarations: No competing interests reported.

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Abstract
Background:Sarcopenia is a common elderly syndrome that increases the risk of falls and fractures,
affects the ability to live daily and reduces quality of life.The present study try to explore the factors
associated with muscle mass by using Dual-energy X-ray absorptiometry(DXA) in Chinese
postmenopausal women.
Methods: The clinical information of 234 postmenopausal women, ages 50 to 79, was included in this
study. Every subject's height, weight, calf circumference (CC), and grip strength were recorded. The body
mass index, or BMI, was computed. All subjects' DXA characteristics, such as their total mass, lean
mass, fat mass, T value, and relative skeletal muscle index (RSMI), were also noted. Based on RSMI, the
patients were separated into two groups: those with sarcopenia and those without. An analysis was
conducted on the variations in grip strength, CC, DXA parameters, and demographic data between the
two groups. The relationship between a number of variables and RSMI was investigated using bivariate
correlation analysis. The link between each index and RSMI was examined using both univariate and
multiple linear regression analysis, and a regression equation was produced.
Results:The study revealed that the sarcopenia group had signicantly reduced BMI, grip strength, CC,
RSMI, T value, total mass, lean mass, and fat mass compared to the non-sarcopenia group (P<0.05).
Weight, fat mass, and CC had moderate correlations with RSMI (r=0.696, r=0.507, r=0.638, respectively, P
< 0.05); T value and grip strength had weak correlations with RSMI (r=0.280, r=0.265, respectively, P <
0.05); BMI, total mass, and lean mass had strong correlations with RSMI (r=0.736, r=0.726, r=0.782,
respectively, P < 0.05). The results of multiple linear regression analysis indicated that BMI (r=0.120,
P<0.001) and CC (r=0.078, P<0.001) were the key variables linked to the muscle mass of
postmenopausal women. We have RSMI = 0.473 + 0.120×BMI + 0.078×CC as the regression equation.
Conclusions: Compared to patients without sarcopenia, people with sarcopenia have lower BMIs, grip
strengths, CCs, T values, total masses, lean masses, and fat masses. In postmenopausal women, there
is a positive correlation between muscle mass and BMI and CC.
Background
A complex disease that primarily affects the elderly, sarcopenia causes a progressive decrease of
muscle mass and function[1]. The United Nations estimates that 985million women globally were over
50 in 2020, and that number is projected to increase to 1.65billion by 2050[2]. It is often recognized that
China is among the nations with the fastest rates of aging in the world, with an annual rise in the
prevalence of sarcopenia that has a major negative impact on the health and standard of living of the
elderly[3–5].The current study aims to investigate the factors associated with muscle mass in Chinese
postmenopausal women using DXA, as there are many studies currently conducted on the related
factors of bone and bone density in these women. This helps to prevent or delay adverse health

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outcomes that place a signicant burden on patients and healthcare systems, as well as to lessen the
occurrence and development of sarcopenia.
Materials and Methods
1.1 Patient Population
255 postmenopausal women who were admitted to Hebei Medical University's Third Hospital between
September 2021 and October 2022 had their clinical data gathered. The inclusion criteria included
postmenopausal females, who can cooperate with basic data collection and DXA
examination.Postmenopausal was described as not having a menstrual period for at least a year. The
exclusion criteria included a history of hysterectomy, a malignant tumor, a vertebral compression
fracture, a history of smoking and alcohol consumption, a history of drug use that affects bone
metabolism (e.g, warfarin, bisphosphonates, sex steroids), a history of renal failure, hyperthyroidism,
hyperparathyroidism, and a history of paralysis from other diseases.21 of the 255 people who were
enrolled in the study were not included because of incomplete data. In the end, 234 people were signed
up for this research. The Institutional Review Board of the Faculty of Medicine at Hebei Medical
University's Third Hospital gave its approval to this study (Ethical Approval number: Radiology Section
2021-045-1). Before beginning any procedures, the subjects gave their written, informed consent. Every
technique was used in compliance with all applicable rules and regulations.
1.2 Data collection
Recorded were age, height, weight, and CC. BMI was computed as follows: weight (kg) / height (m)2.The
Jamar 5030J1 Hydraulic Hand Dynamometer (Serial Number: 20190815339) was used to measure the
muscle strength.DXAwhole body scan was performed with the LUNAR Prodigy (GE-Lunar Corp)
densitometer by a trained DXA technician to assess the total mass, fat mass, lean mass, and T value of
various regions of interest. Assuming that all non-fat and non-bone tissue is skeletal muscle, the RSMI
was computed as the total lean mass in the arms and legs (all four extremities) divided by height
squared (m2).The Asian Working Group for Sarcopenia (AWGS-2019) has updated its diagnostic criteria
for sarcopenia, using RSMI—the key measure of muscle mass—in conjunction with loss of muscle
strength[6].The 2019 AWGS cutoffs for low muscle mass in the diagnosis of sarcopenia are < 5.4 kg/m2
in women and < 7.0 kg/m2 in men based on DXA.A BMD value between − 1.0 and − 2.5 standard
deviation (SD) of that for a young, healthy adult, or a T-score between − 2.5 and − 1.0, is considered
osteopenia, according to WHO guidelines, whereas a BMD score of ≤ − 2.5 SD is considered
osteoporosis[7].
1.3 Statistical analysis
SPSS Statistic version 26.0 was used to conduct the statistical analysis.The study's quantitative
variables were statistically described using mean ± standard deviation (SD) for data with a normal
distribution and medians (interquartile range; IQR) for data with a non-normal distribution. The data were

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examined to see if they t the normal distribution using the Shapiro-Wilk test. Based on RSMI, the
patients were separated into groups: those with sarcopenia and those without.
Results
1. The demographic data,CC and grip strength of
participants
There was no difference in age or height between the two groups, however there were signicant
differences in BMI, weight, grip strength, and CC in the sarcopenia group compared to the non-
sarcopenia group (P < 0.05) (Table1).
Table 1
Baseline characteristics of participants
All participants sarcopenia group non-sarcopenia group
P
No. of participants(%) 234 39(16.6%) 195(83.4%) 
Age(years) 64.00(57.00,68.00) 63.56 ± 7.62 64.00(57.00,68.00) 0.454
Height(m) 1.60(1.56,1.63) 1.58(1.56,1,60) 1.60(1.56,1,63) 0.592
Weight(kg) 61.03 ± 8.48 51.65 ± 4.84 62.90 ± 7.78 < 0.001
BMI(kg/m2)23.98 ± 3.22 20.65 ± 1.96 24.64 ± 3.01 < 0.001
CC(cm) 35.40 ± 2.83 32.52 ± 2.31 36.00(34.50,37.30) < 0.001
grip strength(kg) 21.00(18.00,25.00) 19.12 ± 4.24 22.00(18.00,26.00) 0.001
Table1 Baseline characteristics of participants
2.Comparison of DXA parameters between sarcopenia group and non-sarcopenia group.
Patients in the sarcopenia group had reduced RSMI, T value, total mass, lean mass, and fat mass (P <
0.05) in comparison to the non-sarcopenia group (Table2).

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Table 2
Comparison of DXA parameters between different groups.
All participants sarcopenia group non-sarcopenia group
P
T value -1.72 ± 1.13 -2.30 ± 1.05 -1.60 ± 1.11 < 0.001
total mass(kg) 60.57 ± 8.52 50.96 ± 4.63 62.50 ± 7.78 < 0.001
lean mass(kg) 35.68(33.30,38.51) 30.74 ± 2.11 36.28(34.42, 38.87) < 0.001
fat mass(kg) 22.91 ± 5.74 18.55 ± 4.04 23.78 ± 5.63 < 0.001
RSMI(kg/m2)6.08 ± 0.70 5.17(5.01,5.32) 6.18(5.86,6.59) < 0.001
Values are presented as median (interquartile range). Kruskal–Wallis test was used for analysis
Table2DXA parameter comparisons amongst several groups.
The interquartile range, or median, is used to show values. For analysis, the Kruskal-Wallis test was
employed.
3.Correlation between RSMI and various factors in postmenopausal women.
The relationship between a number of variables and RSMI was investigated using bivariate correlation
analysis. Figure1 demonstrated that RSMI was signicantly correlated with BMI, total mass, and lean
mass (r = 0.736, r = 0.726, r = 0.782, respectively, P < 0.05); moderately correlated with weight, fat mass,
and CC (r = 0.696, r = 0.507, r = 0.638, respectively, P < 0.05); weakly correlated with T value and grip
strength (r = 0.280, r = 0.265, respectively, P < 0.05); and not signicantly correlated with age and height
(P > 0.05).
Figure1 Scatter plot of correlation between BMI (a), weight(b), total mass(c), lean mass(d), fat mass(e),
calf circumference(f), T value(g), grip strength(h) with RSMI
RSMI of postmenopausal women was used as the dependent variable for univariable and multiple linear
regression analysis; results with VIF values between 0 and 10, no multicollinearity, and P < 0.05 were
selected. BMI, weight, T value, CC, total mass, and fat mass were collected as independent variables.
Multiple regression analysis revealed that in postmenopausal women, BMI (P < 0.001) and CC (P < 0.001)
were important and independent determinants of muscle mass. RSMI = 0.473 + 0.120×BMI + 0.078×CC is
the regression equation.
Table3 Analysis of the effects of associated factors on muscle mass in postmenopausal women using
univariate and multivariate linear regression.

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Table 3
Univariable and multivariable linear regression analysis of assotiated factors on muscle mass
in postmenopausal women.
Variables Univariate analysis Multivariate analysis 
 Coefcient
(95% CI)
P
Coefcient
(95% CI)
P
BMI(kg/m2)(0.193,0.239) < 0.001 (0.098,0.141) < 0.001
calf circumference(cm) (0.029,0.062) < 0.001 (0.052,0.103) < 0.001
weight(kg) (-0.099,-0.059) < 0.001  
fat mass(g) (0.000,0.000) < 0.001  
T value (-0.070,0.002) 0.062  
total mass(kg) (0.140,0.185) < 0.001  
Discussion
A widespread and progressive decrease of skeletal muscle mass and function (muscle strength and/or
physical performance) is known as sarcopenia.Age, sex, geography, ethnicity, medical history, health
status, psychological, social, and behavioral factors, as well as genetic, gut microbiota, other
comorbidities, and biochemical factors, are all linked to sarcopenia[8]. Sarcopenia is believed to entail a
number of pathophysiological processes that could have a negative impact on health, including
denervation, mitochondrial dysfunction, inammatory responses, and hormonal changes[9]. It raises the
risk of mortality, hospitalization, impairment, falls and fall-related injuries, and limitations on
independence[10].Using the Consensus Report of the Asian Working Group for Sarcoidosis(AWGS)
criteria, an epidemiological investigation with 6172 Chinese participants aged 60–94 years revealed
26.6% of the patients had sarcopenia[11].Estrogen reduction in postmenopausal women results in
endocrine and metabolic disruption, which increases the risk of decreasing muscle mass and
strength[12].Around the age of 50, women are more likely to develop sarcopenia, which results in a 12%
annual loss of muscle[13]..Sarcopenia was found to be as common in post-menopausal women as 31%,
according to one study[14]. All of the aforementioned ndings point to a signicant frequency of
sarcopenia; also, postmenopausal women who have sarcopenia are more likely to experience falls and
vertebral fractures[15]. Senior women's quality of life is severely impacted by sarcopenia, which also
places a signicant nancial strain on patients and healthcare systems.Studying the prevalence and
contributing variables of sarcopenia is so crucial.
According to the current study, postmenopausal women with sarcopenia had lower BMI, weight, and
total mass than postmenopausal women without sarcopenia.The results of the bivariate correlation
study demonstrated that, among postmenopausal women, muscle mass is positively connected with

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BMI, weight, and total mass; the greater these three variables, the greater the muscle mass. In
postmenopausal women, a further multiple linear regression analysis likewise revealed a strong positive
connection between BMI and muscle mass, with an increase in RSMI of 0.120 kg/m2 for every 1 kg/m2
rise in BMI. This study's conclusion is supported by numerous other investigations. For instance, Sung et
al.'s analysis of 466 patients' data[16] revealed an independent relationship between a greater BMI and a
lower likelihood of sarcopenia. Esteves and others [17]found that the probability of sarcopenia decreased
by 36% for every unit rise in BMI. A Chinese study found that while a high BMI protected against the loss
of skeletal muscle mass, it was a risk factor for sluggish gait speed[18].A different study involving 629
middle-aged and older Europeans found that patients with a BMI of greater than 30 kg/m2 had higher
muscle mass; additionally, middle-aged and elderly individuals without obesity had a 176.3 percent
higher risk of low muscle mass than those who were obese[19]. Higher BMI may also be a protective
factor against sarcopenia.This could be explained by the fact that an older person with a relatively high
body mass index is more likely to have a bigger amount of stored energy and a better nutritional state,
both of which improve prognosis.Thus, we came to the conclusion that postmenopausal women may
benet from having a higher BMI, weight, and total mass.
We found that the probability of sarcopenia decreased by 36% for every unit rise in BMI. A Chinese study
found that while a high BMI protected against the loss of skeletal muscle mass, it was a risk factor for
sluggish gait speed[18].A different study involving 629 middle-aged and older Europeans found that
patients with a BMI of greater than 30 kg/m2 had higher muscle mass, and that a higher BMI may protect
against sarcopenia; additionally, the risk of low muscle mass was 176.3 percent higher in middle-aged
and elderly individuals without obesity than in those with obesity[19]..This could be explained by the fact
that an older person with a relatively high body mass index is more likely to have a bigger amount of
stored energy and a better nutritional state, both of which improve prognosis.Thus, we came to the
conclusion that postmenopausal women may benet from having a higher BMI, weight, and total mass.
When it came to fat mass, the non-sarcopenia group had more fat mass than the sarcopenia group
did.The study's fat mass and muscle mass had a somewhat positive link, according to a subsequent
Pearson correlation analysis (r = 0.520). A larger amount of fat may, in some cases, defend against the
loss of muscle mass. However, this is debatable.According to some researchers, paracrine signals from
cytokines in obesity may cause muscle progenitor cells to develop into an adipocyte-like phenotype,
which would increase fatty inltration and decrease muscular renewal[20].One study on body
composition revealed that during premenopause and menopause, there was an increase in fat mass and
a decrease in the proportion of lean mass, which led to increased adiposity and fat redistribution
towards central-type obesity. After menopause, there was an average stabilization of body
composition[21].After peaking in the fourth decade, muscle mass starts to diminish, resulting in weight
growth that is primarily composed of fat rather than lean mass.It is believed that excess lipids "spill over"
to other tissues, particularly the skeletal muscles[22].Therefore, we need to be aware of the possibility of
sarcopenic obesity, a high-risk geriatric syndrome that is primarily seen in the aging population and puts

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them at risk for consequences that could arise from both obesity and sarcopenia working together. It's
plausible that fat itself negatively affects muscle metabolism after removing the mechanical loading
effect of fat on bulk.
T value and muscle mass had a weak correlation in our study (r = 0.280). T value (P > 0.05) was not an
independent predictor of muscle mass in postmenopausal women, according to multiple regression
analysis. Despite extensive discussion, the connection between BMD and RSMI is still unclear. A natural
drop in estrogen during menopause is linked to a loss of muscle mass and bone density. Sarcopenia and
osteoporosis are intimately related to each other due to the important interaction between muscles and
bones. They also share similar risk factors.Because the link between RSMI and BMD was lost in the nal
regression models after accounting for BMI, several researchers have recently come to the conclusion
that RSMI was not connected with the BMD of the postmenopausal women assessed [17]. This contrasts
with other research that found a favorable correlation between RSMI and BMD across all sites [23–24].
Sarcopenia was as common as 39.3% among postmenopausal osteoporosis patients, according to a
study[25]. Researchers França CF et al. investigated the connection between postmenopausal women's
bone mass and geometry and found that sarcopenia is linked to low aBMD[26]. According to AHEDI et al.
[27], inactivity reduces muscle mass and function as well as the mechanical stimulation of bone density,
which in turn results in a decreased bone density and a diminished osteogenic effect.Physical forces as
well as the release of osteokines and myokines are how muscle and bone interact. According to Karasik
et al. [28], there is a gene-level linkage between muscle and osteoporosis and genes linked to muscle
metabolism, such as myocyte enhancer factor 2c, A-actin 3, and myostatin, which are also associated
with muscle loss.The prevalence of both conditions is expected to rise signicantly over the next few
decades due to the ageing population. These conditions together can have a negative impact on quality
of life by decreasing balance, increasing the risk of falls, and making patients more susceptible to
fragility fractures.As a result, more research on the relationship between these two illnesses is required
in the future in order to identify their shared targets and contributing variables.
Compared to the sarcopenia group, the non-sarcopenia group had greater grip strength.In this study,
there was a weak correlation (r = 0.265) between grip strength and muscle mass. Additionally, Ryo et al.
discovered a strong correlation between trunk muscle mass and both trunk exion and extension[30].
Numerous researchers have demonstrated that resistance exercise can increase muscle strength in
older individuals suffering from sarcopenia [31–32]. Muscle strength was found to be a more accurate
predictor of unfavorable outcomes than muscle mass, according to the European Working Group on
Sarcopenia in Older People 2 (EWGSOP2)[33]. The
pathophysiological process could be that cells use adhesion molecules to sense mechanical strain,
which then triggers biochemical reactions that alter fundamental cellular biology systems and perhaps
trigger the start of muscle hypertrophy[34]. As a result, postmenopausal women ought to intensify their
physical activity, particularly if they are already experiencing a reduction in muscle mass.

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According to the current study, postmenopausal women with sarcopenia had lower CC than
postmenopausal women without sarcopenia.According to the bivariate correlation study, there was a
modest association (r = 0.638) between muscle mass and CC, meaning that the higher the CC, the
greater the muscle mass.In postmenopausal women, a subsequent multiple linear regression study
likewise revealed a strong positive connection between CC and muscle mass, with an increase in RSMI
of 0.078 kg/m2 for every centimeter rise in CC. Numerous studies have demonstrated a good correlation
between calf circumference and both muscle mass and the skeletal mass index (SMI)[35–36], making this
a quick and easy way to screen for sarcopenia. Similar to the current ndings for postmenopausal
women, Ryoko et al. showed that maximal CC was positively connected with DXA-measured ASM among
older women aged 63 years (IQR 54–68 years), (r = 0.73). Chikako et al. recently used magnetic
resonance imaging to investigate the association between CC and calf muscle mass; the ndings
indicate a good correlation (r = 0.892) between the two for females. MRI is thought to be an extremely
accurate imaging method that can distinguish between fat and other body soft tissues with
clarity[38].Sarcopenia development and occurrence are intimately linked to nutritional status, which can
be easily assessed by measuring the circumference of the calf.Thus, it is important to monitor the
circumference of the calf as a scientic reference for sarcopenia early screening.
Limitations
This study had certain drawbacks. First off, the sample size still has to be increased because the number
of recruited participants was rather small. Second, the results can be affected by the fact that DXA is not
the most precise technique for analyzing muscle mass. In the future, muscle measurement can be done
using CT and MRI. Thirdly, to make the research more thorough, lifestyle factors including physical
activity, protein intake, falls, frailty, and comorbidities should be taken into account.
Conclusions
Compared to patients without sarcopenia, people with sarcopenia have lower BMIs, grip strengths, CCs,
T values, total masses, lean masses, and fat masses. In postmenopausal women, there is a positive
correlation between muscle mass and BMI and CC.
Abbreviations
BMD: Bone mineral density; BMI: Body mass index; DXA: Dual-energy X-ray;CC:calf
circumference;RSMI:relative skeletal muscle index;AWGS :Consensus Report of the Asian Working Group
for Sarcoidosis.
Declarations
Ethics approval and consent to participate

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This study was reviewed and approved by Ethics Committee of the Third Hospital of Hebei Medical
University (Serial Number: 20190815339) and was conducted in accordance with the Helsinki
Declaration. The informed consent of all patients was obtained, and all patients agreed to participate in
the study.
Consent for publication
Not applicable
Availability of data and materials
All data generated or analyzed during this study are included in this published article and its
supplementary information les.
Competing interests
There is no conct of interest in this article.
Funding
No funds, grants, or other support was received
Authors' contributions
Xiaona Zhu drafted, reviewed and revised manuscript; Yongli Zheng interpreted results of experiments;
Ying Liu,Lei Gao analyzed data.Yan Wang reviewed, edited and revised manuscript;Wei Zhang concepted
and designed of research. Meiling Yang and Tingting Hu collected the data.All authors have approved the
manuscript for submission.
Acknowledgements
Thanks to all the authors of this article.
Authors' information
Xiaona Zhua,Yongli Zhenga,Ying Liub,Lei Gaob ,Yan Wangc,* ,Wei Zhanga,* , Meiling Yanga
Tingting Hua
aDepartment of Radiology, the Third Hospital of Hebei Medical University, No. 139 Ziqiang Road, Qiaoxi
District, Shijiazhuang 050051, Hebei Province, China.bDepartment of CT/MRI, the Third Hospital of Hebei
Medical University, No. 139 Ziqiang Road, Qiaoxi District, Shijiazhuang 050051, Hebei Province, China.
cDepartment of Endocrinology, the Third Hospital of Hebei Medical University, No. 139 Ziqiang Road,
Qiaoxi District, Shijiazhuang 050051, Hebei Province, China. * Co-Corresponding:Yan Wang and Wei
Zhang have contributed equally to this work and should be considered co - corresponding author.Yan

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Wang;Department of Endocrinology, the Third Hospital of Hebei Medical University, No. 139 Ziqiang
Road, Qiaoxi District, Shijiazhuang 050051, Hebei Province, China. E-mail addresses:
wangyan66200@163.com.Wei Zhang; Department of Radiology, the Third Hospital of Hebei Medical
University, No. 139 Ziqiang Road, Qiaoxi District, Shijiazhuang 050051, Hebei Province, China.E-mail
addresses:zw77988@163.com.

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Figures

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Figure 1
Scatter plot of correlation between BMI (a), weight(b), total mass(c), lean mass(d), fat mass(e), calf
circumference(f), T value(g), grip strength(h) with RSMI