Literature DB >> 24571923

Association of lower limb muscle mass and energy expenditure with visceral fat mass in healthy men.

Shusuke Yagi1, Muneyuki Kadota1, Ken-Ichi Aihara2, Koji Nishikawa3, Tomoya Hara1, Takayuki Ise1, Yuka Ueda1, Takashi Iwase1, Masashi Akaike4, Michio Shimabukuro5, Shinsuke Katoh3, Masataka Sata1.   

Abstract

BACKGROUND: A high-calorie diet and physical inactivity, an imbalance between caloric intake and energy consumption, are major causes of metabolic syndrome (MetS), which manifests as accumulation of visceral fat and insulin resistance. However, the lifestyle-related factors associated with visceral fat mass in healthy men are not fully understood.
METHODS: We evaluated visceral fat area (VFA), skeletal muscle mass, caloric intake, and energy expenditure in 67 healthy male participants (mean age, 36.9 ± 8.8 years; body mass index 23.4 ± 2.5 kg/m2).
RESULTS: Multiple regression analysis showed that the total skeletal muscle mass (P < 0.001) were negatively and age (P < 0.001) were positively associated with VFA. Lower limb muscle mass (P < 0.001) was strongly associated with VFA. However, total caloric intake, total energy expenditure, and energy expenditure during exercise were not associated with VFA.
CONCLUSIONS: Skeletal muscle mass especially lower limb muscle mass negatively contributes to visceral fat mass in healthy men. Therefore, maintaining lower limb muscular fitness through daily activity may be a useful strategy for controlling visceral obesity and metabolic syndrome.

Entities:  

Year:  2014        PMID: 24571923      PMCID: PMC3945716          DOI: 10.1186/1758-5996-6-27

Source DB:  PubMed          Journal:  Diabetol Metab Syndr        ISSN: 1758-5996            Impact factor:   3.320


Introduction

The imbalance between caloric intake and energy consumption, high-calorie diets and physical inactivity, are major causes of metabolic syndrome (MetS), which manifests as accumulation of visceral fat and insulin resistance [1]. The prevention of MetS is an important issue, as it is a major cause of cardiovascular disease (CVD) [2,3]. Lifestyle intervention including caloric restriction and exercise is the preferred approach to reduce the incidence of MetS [4,5]. Exercise not only increases energy consumption but also improves muscle metabolism through increased glucose uptake in skeletal muscles [6]. In addition, exercise enhances skeletal muscle mass, suggesting that skeletal muscle mass could be a parameter of exercise duration and intensity. Exercise prevents visceral obesity [7]; however, the relashonship between viseral obesity and skeletal muscle mass remains unclear. The American Heart Association therefore recommends weight reduction to a BMI of <25 kg/m2) with exercise duration of at least 30 min performed 5 times a week at moderate intensity [1]; however, it is unclear which exercise should be used and which skeletal muscles should be targeted to effectively reduce visceral fat mass in healthy subjects. Since the prevalence of MetS is increasing worldwide, healthy subjects are potentially at risk of MetS [8-10]. Therefore, it is important to identify the risk factors for visceral fat obesity in healthy subjects to prevent MetS. In order to clarify these issues, we evaluated visceral fat mass, skeletal muscle mass, caloric intake, and energy consumption in healthy Japanese men and identified lifestyle-related factors associated with visceral fat mass.

Methods

We recruited 67 healthy male volunteers aged between 20 and 85 years (mean age, 36.9 ± 8.8 years; body mass index (BMI) 23.4 ± 2.5 kg/m2). Visceral fat area (VFA) and subcutaneous fat area (SFA) were measured using a fat area analyzer (Dual Scan HDS-2000®; Omron, Japan) [11,12]. Studies have shown that the correlation coefficient between VFA measured by the fat area analyzer and VFA measured by computed tomography was r = 0.88 (p < 0.001) [12]. The repeatability of the fat area analyzer was evaluated by the Bland–Altman plot, which has been described elsewhere [12]. These data indicate that this indirect measurement of VFA has a high correlation coefficient with VFA evaluated by computed tomography and does not involve X-ray exposure. Because VFA and SFA were compared with obesity-related variables, which were adjusted with body size represented by body surface area or body weight, VFA and SFA were indexed with body surface area (BSA) as visceral fat area index (VFAI) and subcutaneous fat area index (SFAI), respectively. Skeletal muscle mass was measured with a body composition analyzer (Inbody 7200®; Biospace, Korea) [13]. Body weight and waist circumstance were measured, and BMI was calculated as an index of obesity. Energy expenditure and total caloric intake was calculated using a questionnaire for food and exercise frequency. Energy expenditure during exercise was defined as energy consumed during exercise per day. Total energy expenditure was defined as energy consumed for daily activity, which includes energy expenditure during exercise. Total caloric intake, energy expenditure during exercise, and total energy expenditure were assessed for 7 days. These values were then averaged per day [14,15]. The study protocol was approved by the Ethics Committee at the Tokushima University Hospital.

Statistical analysis

For continuous variables, each value is expressed as the mean ± SD. Single regression analysis was used to assess the correlation between VFA and obesity-related parameters. The degree of association among independent variables, including VFAI, age, skeletal muscle mass, energy expenditure, caloric intake, and parts of skeletal muscles, was assessed by multiple regression analyses (stepwise regression model). All statistical analyses were performed using SPSS software. Statistical significance was defined as P < 0.05.

Results

Clinical characteristics of subjects

The clinical characteristics of the subjects are presented in Table 1.
Table 1

Clinical characteristics of subjects

Variables (n = 67)Mean ± SD
Age (years)
36.9 ± 8.8
BW (kg)
69.2 ± 8.3
BMI (kg/m2)
23.4 ± 2.5
Waist circumference (cm2)
84.2 ± 7.4
VFA (cm2)
75.0 ± 29.5
VFAI (cm2)
41.0 ± 14.7
SFA (cm2)
160.3 ± 56.9
SFAI (cm2)
87.6 ± 27.7
Fat weight (kg)
15.1 ± 5.3
Fat weight/BW (%)
21.5 ± 5.6
Skeletal muscle weight
 
Total body (kg)
30.4 ± 3.0
Total body/BW(%)
44.3 ± 0.03
Upper limbs, (kg)
5.8 ± 0.7
Upper limbs/BW, (%)
8.3 ± 0.7
Lower limbs (kg)
17.5 ± 1.9
Lower limbs/BW (%)
25.5 ± 2.3
Truncal muscle (kg)
7.1 ± 0.9
Truncal muscle/BW (%)10.3 ± 1.3

BW, body weight; BMI, body mass index; VFA, visceral fat area; VFAI, visceral fat area index; SFA, subcutaneous fat area; SFAI, subcutaneous fat area index.

Clinical characteristics of subjects BW, body weight; BMI, body mass index; VFA, visceral fat area; VFAI, visceral fat area index; SFA, subcutaneous fat area; SFAI, subcutaneous fat area index.

VFAI is inversely associated with skeletal muscle mass and energy expenditure

The VFAI was positively associated with waist circumference, BMI, SFAI (Figure 1), and age (Figure 2), but was negatively associated with upper, lower and total skeletal muscle mass (Figure 2). The SFAI was negatively associated with total skeletal muscle mass (Figure 2). Neither SFAI nor skeletal muscle mass was associated with age (data not shown).
Figure 1

Waist circumference, BMI, and SFA are associated with VFA. VFA: visceral fat area, BMI: body mass index, SFA: subcutaneous fat area, BSA: body surface area.

Figure 2

Age is positively associated with increased VFA, while total skeletal muscle mass is negatively associated with both VFA and SFA. Upper and lower skeletal muscle mass are negatively associated with VFA. VFA: visceral fat area, SFA: subcutaneous fat area, BSA: body surface area, BW: body weight.

Waist circumference, BMI, and SFA are associated with VFA. VFA: visceral fat area, BMI: body mass index, SFA: subcutaneous fat area, BSA: body surface area. Age is positively associated with increased VFA, while total skeletal muscle mass is negatively associated with both VFA and SFA. Upper and lower skeletal muscle mass are negatively associated with VFA. VFA: visceral fat area, SFA: subcutaneous fat area, BSA: body surface area, BW: body weight. The VFAI was negatively associated with total energy expenditure and energy expenditure during exercise (Figure 3), but there was no relationship between total caloric intake and VFAI (data not shown).
Figure 3

Total energy expenditure for daily-life activity and energy expenditure during exercise are negatively associated with increased VFA. VFA: visceral fat area, BSA: body surface area, BW: body weight.

Total energy expenditure for daily-life activity and energy expenditure during exercise are negatively associated with increased VFA. VFA: visceral fat area, BSA: body surface area, BW: body weight. Stepwise multiple regression analysis showed that total skeletal muscle mass was a negative and age was a positive determinant of VFAI; however, total caloric intake, total energy expenditure, and energy expenditure during exercise were statistically excluded (Table 2).
Table 2

Multiple regression analysis for determinants of visceral fat area

VariablesCoefficient95% Confidence intervalStandardized coefficient P value
Total skeletal muscle mass
−295
−404 to −187
−0.51
<0.001
Age0.630.32 to 0.940.38<0.001

R2 = 0.45, P < 0.001.

Multiple regression analysis for determinants of visceral fat area R2 = 0.45, P < 0.001.

VFAI is inversely associated with lower limb skeletal muscle mass

In order to clarify which part of skeletal muscle, including upper limb, lower limb, and truncal skeletal muscle, influences the volume of visceral fat, we performed stepwise multiple regression analysis. Although lower limb skeletal muscle mass was a negative and age was a positive determinant of VFA, upper limb and truncal skeletal muscle mass were statistically excluded (Table 3).
Table 3

Multiple regression analysis for determinants of visceral fat area

VariablesCoefficient95% Confidence intervalStandardized coefficient P value
Age
0.52
0.20 to 0.84
0.31
<0.01
Lower limb muscle weight
−6.78
−9.19 to −4.36
−0.53
<0.001
Upper limb muscle weight
-
-
-
-
Truncal muscle weight----

R2 = 0.46, P < 0.001.

Multiple regression analysis for determinants of visceral fat area R2 = 0.46, P < 0.001.

Discussion

The lifestyle-related factors associated with visceral fat mass has been unknown. In this study, we showed that skeletal muscle mass especially lower limb muscle mass are negatively associated with VFAI. We showed that the VFAI is positively associated with age and negatively associated with skeletal muscle mass. VFA is positively associated with number of metabolic risk factors in the elderly [16], and skeletal muscle mass is inversely associated with age [17,18]. However, our data showed that skeletal muscle mass was not associated with age, which is supported by the evidence that muscular strength is inversely associated with the incidence of MetS, independently of age [19]. Although the age outliers might have affected the results (Additional file 1), they nevertheless indicate that the decrease in skeletal muscle mass can be prevented by physical activity. Decreased skeletal muscle mass leads to physical inactivity [20]. Conversely, physical inactivity leads to decreased skeletal muscle mass [20]. Decreased skeletal muscle mass and strength is associated with increased morality [21,22]. Sarcopenic obesity is also associated with hypertension, independent of abdominal obesity [23]. Increasing skeletal muscle mass and strength via daily exercise may therefore prevent MetS and prolong life span. In addition, in patients with metabolic syndrome, visceral fat accumulation is accompanied by excess lipid deposition in skeletal muscle, which may contribute to impaired glucose uptake leading to insulin resistance [24]. Improved skeletal muscle functions (including metabolic system) through exercise may contribute to the prevention of MetS [25]. The American Heart Association recommends daily exercise to prevent the accumulation of abdominal fat [1]. Although some subjects exercised in their spare time, our results showed that the association between total energy expenditure during daily activity and VFAI was stronger than the association between energy expenditure during exercise and VFAI. Because the duration of energy expenditure during exercise is relatively short, it may be insufficient for reducing VFA. Therefore, the length of continuous caloric consumption is important for reducing VFA. Enhanced energy expenditure combined with daily exercise is essential for reducing the volume of visceral fat. Lower limb muscle mass is a determinant of VFAI. Lower limb muscle including the quadriceps forms the largest muscle mass in the body and may therefore contribute to decreased VFA to a greater extent than upper limb or truncal muscle. Lower limb muscle mass and performance in gait are also important because they are associated with reduced mobility, a poor quality of life, CVD, and death [26-28]. Increased physical activity and daily lower body exercise (e.g., brisk walking, cycling, and stair climbing) may be the most useful way to reduce visceral fat and improve mortality. Increased daily activity in young- and middle-aged men may prevent MetS and CVD by decreasing the volume of visceral fat. In conclusion, skeletal muscle mass especially lower limb muscle mass negatively contributed to VFA in healthy men. Maintaining lower limb muscular fitness through daily exercise may therefore be a useful strategy for controlling visceral obesity and MetS.

Consent

Informed consent was obtained from the participants for the publication of this report and any accompanying images.

Abbreviations

MetS: Metabolic syndrome; CVD: Cardiovascular disease; VFA: Visceral fat area; SFA: Subcutaneous fat area; BMI: Body mass index; BSA: Body surface area; VFAI: Visceral fat area index; SFAI: Subcutaneous fat area index.

Competing interests

The authors declare that they have no competing interest.

Authors’ contributions

SY, MK, KN, TH, TIs, YU, and TIw collected data and SY analyzed the data and wrote the manuscript. KA, MA, MSh, SK, and MSa provided the suggestion for this study. All authors read and approved the final manuscript.

Additional file 1

Age distribution of participants. Click here for file
  27 in total

1.  Total energy expenditure and physical activity in young Scottish children: mixed longitudinal study.

Authors:  J J Reilly; D M Jackson; C Montgomery; L A Kelly; C Slater; S Grant; J Y Paton
Journal:  Lancet       Date:  2004-01-17       Impact factor: 79.321

2.  Lower extremity muscle mass predicts functional performance in mobility-limited elders.

Authors:  K F Reid; E N Naumova; R J Carabello; E M Phillips; R A Fielding
Journal:  J Nutr Health Aging       Date:  2008 Aug-Sep       Impact factor: 4.075

3.  Association of muscular strength with incidence of metabolic syndrome in men.

Authors:  Radim Jurca; Michael J Lamonte; Carolyn E Barlow; James B Kampert; Timothy S Church; Steven N Blair
Journal:  Med Sci Sports Exerc       Date:  2005-11       Impact factor: 5.411

Review 4.  Abdominal obesity and metabolic syndrome.

Authors:  Jean-Pierre Després; Isabelle Lemieux
Journal:  Nature       Date:  2006-12-14       Impact factor: 49.962

5.  Validity and reliability of body composition analysers in children and adults.

Authors:  Nicole E Jensky-Squires; Christina M Dieli-Conwright; Amerigo Rossuello; David N Erceg; Scott McCauley; E Todd Schroeder
Journal:  Br J Nutr       Date:  2008-03-18       Impact factor: 3.718

6.  Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People.

Authors:  Alfonso J Cruz-Jentoft; Jean Pierre Baeyens; Jürgen M Bauer; Yves Boirie; Tommy Cederholm; Francesco Landi; Finbarr C Martin; Jean-Pierre Michel; Yves Rolland; Stéphane M Schneider; Eva Topinková; Maurits Vandewoude; Mauro Zamboni
Journal:  Age Ageing       Date:  2010-04-13       Impact factor: 10.668

Review 7.  Exercise, GLUT4, and skeletal muscle glucose uptake.

Authors:  Erik A Richter; Mark Hargreaves
Journal:  Physiol Rev       Date:  2013-07       Impact factor: 37.312

8.  Sarcopenic obesity as an independent risk factor of hypertension.

Authors:  Seung Ha Park; Jae Hee Park; Pil Sang Song; Dong Kie Kim; Ki Hun Kim; Sang Hoon Seol; Hyun Kuk Kim; Hang Jea Jang; Jung Goo Lee; Ha Young Park; Jinse Park; Kyong Jin Shin; Doo il Kim; Young Soo Moon
Journal:  J Am Soc Hypertens       Date:  2013-07-30

Review 9.  The effect of exercise on visceral adipose tissue in overweight adults: a systematic review and meta-analysis.

Authors:  Dirk Vissers; Wendy Hens; Jan Taeymans; Jean-Pierre Baeyens; Jacques Poortmans; Luc Van Gaal
Journal:  PLoS One       Date:  2013-02-08       Impact factor: 3.240

10.  Association between muscular strength and mortality in men: prospective cohort study.

Authors:  Jonatan R Ruiz; Xuemei Sui; Felipe Lobelo; James R Morrow; Allen W Jackson; Michael Sjöström; Steven N Blair
Journal:  BMJ       Date:  2008-07-01
View more
  12 in total

1.  Body fat distribution and incident cardiovascular disease in obese adults.

Authors:  Ian J Neeland; Aslan T Turer; Colby R Ayers; Jarett D Berry; Anand Rohatgi; Sandeep R Das; Amit Khera; Gloria L Vega; Darren K McGuire; Scott M Grundy; James A de Lemos
Journal:  J Am Coll Cardiol       Date:  2015-05-19       Impact factor: 24.094

2.  Influence of segmental body composition and adiposity hormones on resting metabolic rate and substrate utilization in overweight and obese adults.

Authors:  K R Hirsch; A E Smith-Ryan; M N M Blue; M G Mock; E T Trexler
Journal:  J Endocrinol Invest       Date:  2017-02-16       Impact factor: 4.256

3.  Sarcopenia is associated with an increased risk of advanced colorectal neoplasia.

Authors:  Youn Su Park; Ji Won Kim; Byeong Gwan Kim; Kook Lae Lee; Jae Kyung Lee; Joo Sung Kim; Seong-Joon Koh
Journal:  Int J Colorectal Dis       Date:  2016-12-24       Impact factor: 2.571

4.  Capsaicin induces browning of white adipose tissue and counters obesity by activating TRPV1 channel-dependent mechanisms.

Authors:  Padmamalini Baskaran; Vivek Krishnan; Jun Ren; Baskaran Thyagarajan
Journal:  Br J Pharmacol       Date:  2016-06-21       Impact factor: 8.739

5.  Loss of skeletal muscle mass and its predictors in type 2 diabetes patients under a multifaceted treatment approach.

Authors:  Norihiko Ohara; Isao Minami; Ryotaro Bouchi; Hajime Izumiyama; Koshi Hashimoto; Takanobu Yoshimoto; Yoshihiro Ogawa
Journal:  Diabetol Int       Date:  2017-07-13

6.  Associations of Low-Intensity Resistance Training with Body Composition and Lipid Profile in Obese Patients with Type 2 Diabetes.

Authors:  Hidetaka Hamasaki; Yu Kawashima; Yoshiki Tamada; Masashi Furuta; Hisayuki Katsuyama; Akahito Sako; Hidekatsu Yanai
Journal:  PLoS One       Date:  2015-07-15       Impact factor: 3.240

7.  Associations between lower extremity muscle mass and metabolic parameters related to obesity in Japanese obese patients with type 2 diabetes.

Authors:  Hidetaka Hamasaki; Yu Kawashima; Hiroki Adachi; Sumie Moriyama; Hisayuki Katsuyama; Akahito Sako; Hidekatsu Yanai
Journal:  PeerJ       Date:  2015-05-05       Impact factor: 2.984

8.  Canagliflozin reduces epicardial fat in patients with type 2 diabetes mellitus.

Authors:  Shusuke Yagi; Yukina Hirata; Takayuki Ise; Kenya Kusunose; Hirotsugu Yamada; Daiju Fukuda; Hotimah Masdan Salim; Gulinu Maimaituxun; Susumu Nishio; Yuriko Takagawa; Saori Hama; Tomomi Matsuura; Koji Yamaguchi; Takeshi Tobiume; Takeshi Soeki; Tetsuzo Wakatsuki; Ken-Ichi Aihara; Masashi Akaike; Michio Shimabukuro; Masataka Sata
Journal:  Diabetol Metab Syndr       Date:  2017-10-04       Impact factor: 3.320

9.  Cross-sectional study of the association between day-to-day home blood pressure variability and visceral fat area measured using the dual impedance method.

Authors:  Junko Kuwabara; Koichiro Kuwahara; Yoshihiro Kuwabara; Shinji Yasuno; Yasuaki Nakagawa; Kenji Ueshima; Takeshi Kimura
Journal:  PLoS One       Date:  2018-11-05       Impact factor: 3.240

10.  Association of Body Mass Index with Risk of Major Adverse Cardiovascular Events and Mortality in People with Diabetes.

Authors:  Dong Hun Lee; Kyoung Hwa Ha; Hyeon Chang Kim; Dae Jung Kim
Journal:  J Obes Metab Syndr       Date:  2018-03-30
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.