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. 2021 Aug 17;16(8):e0256083. doi: 10.1371/journal.pone.0256083

Association of obesity, visceral adiposity, and sarcopenia with an increased risk of metabolic syndrome: A retrospective study

Su Hwan Kim 1,2,#, Hyoun Woo Kang 1,#, Ji Bong Jeong 1,*, Dong Seok Lee 1,2, Dong-Won Ahn 1, Ji Won Kim 1, Byeong Gwan Kim 1, Kook Lae Lee 1, Sohee Oh 3, Soon Ho Yoon 4, Sang Joon Park 4
Editor: Mauro Lombardo5
PMCID: PMC8370618  PMID: 34403431

Abstract

Aims

Metabolic syndrome (MS) is a global health problem associated with an increased risk of diabetes mellitus (DM), cardiovascular disease (CVD), and cancer. Body composition parameters, including obesity, visceral adiposity, and sarcopenia contribute to the development of MS and CVD. Previous studies have investigated the association of individual body composition parameters with MS. Studies analyzing the association between multiple body composition parameters and MS have been rare. We aimed to investigate the association between MS and multiple body composition parameters, including obesity, visceral adiposity, and sarcopenia.

Methods

A total of 13,620 subjects who underwent voluntary routine checkups at the Health Care Center of our institution between October 2014 and December 2019 were enrolled. Only data from the first examination of subjects who underwent repeated checkups were included. Clinical and laboratory data were collected. Skeletal muscle mass and visceral fat area (VFA) were measured using bioelectrical impedance analysis. Appendicular skeletal muscle mass (ASM) was divided by body weight (in kg) and expressed as a percentage (calculated as, ASM% = ASM × 100/Weight). Data were compared between the groups based on obesity, VFA, and ASM%. Logistic regression analysis was performed to determine the risk of MS in each group.

Results

Body mass index and VFA were significantly higher in subjects with MS than in those without MS. ASM% was significantly lower in subjects with MS than in those without MS. Subjects with obesity, visceral adiposity, or sarcopenia had a higher prevalence of MS than those without. As the number of metabolic components increased from 0 to 5, we identified a decreasing trend of ASM% and an increasing trend of VFA and BMI (P for trend < 0.001 for all). In the paired analyses, all the three body composition parameters showed additive effects in predicting MS. In the logistic regression analysis, the three parameters were associated with an increased risk of MS after adjustment for age, sex, hypertension, DM, dyslipidemia, smoking, alcohol intake, and C-reactive protein.

Conclusions

Obesity, visceral adiposity, and sarcopenia showed additive effects on MS prediction. Subjects with obesity, visceral adiposity, or sarcopenia were significantly associated with the increased risk of MS after adjustment for multiple confounders. Increasing skeletal muscle and reducing visceral fat may be strategies for the prevention or treatment of MS.

Introduction

Metabolic syndrome (MS) has become a global health problem and is associated with an increased risk of diabetes mellitus (DM) [1]. MS also increases the risk of cardiovascular disease (CVD) [2,3], cancer, and mortality [4–6].

Visceral adiposity is considered to contribute to the development of MS [7–13]. Visceral adiposity is also known to be a risk factor for DM [14], CVD [15], non-alcoholic fatty liver disease (NAFLD) [16], reflux esophagitis [17], and cancer [18]. Waist circumference (WC) can be used to measure visceral adiposity. However, WC is only a surrogate of visceral adiposity and does not measure visceral adiposity precisely. Another limitation of WC measurement is its poor reproducibility [19]. Recent studies that measured visceral adiposity using bioelectrical impedance analysis (BIA) showed that visceral adiposity is associated with MS [8,10,11,13]. BIA can measure body fat and muscle mass easily and is cost-effective; thus, BIA is widely used.

It is known that obesity is related to MS, hypertension (HT), DM, dyslipidemia (DL), and CVD [20–24]. However, body mass index (BMI), which is an indicator of obesity, does not precisely reflect the amount of body fat and is limited in predicting obesity-related diseases [25].

Sarcopenia is the progressive loss of skeletal muscle mass [26,27]. With aging of the population globally, sarcopenia has become a global issue [28,29]. Loss of skeletal muscle mass is a known risk factor for MS [30–32], NAFLD [33,34], carotid atherosclerosis, and CVD [28,35,36]. Skeletal muscle is the main site of glucose uptake and utilization [37]; thus, sarcopenia increases insulin resistance and thereby induces DM and MS [32]. Sarcopenia limits physical activity and independent daily living [38]. Sarcopenia has been reported to increase morbidity [39], disability [40], medical costs [41], and mortality [42].

Many studies have investigated the association of individual body composition parameters with MS. However, few studies have analyzed the association between multiple body composition parameters and MS [43–45]. We aimed to investigate the association between MS and multiple body composition parameters, including obesity, visceral adiposity, and sarcopenia.

Materials and methods

Study population

A total of 20,998 subjects underwent voluntary routine checkups at our Institutional Health Care Center between October 2014 and December 2019. After excluding 4,621 subjects who underwent repeated checkups, only data from the first examination were included. After excluding 2,627 subjects with insufficient data and 130 subjects with a history of malignancy, 13,620 subjects were enrolled, similar to a previous study (Fig 1) [46]. The data were fully anonymized before obtaining them. This study was approved by the Institutional Review Board of Boramae Medical Center (IRB No. 10-2020-234). The requirement for written informed consent was waived due to the retrospective nature of our study. The study was conducted in accordance with the Declaration of Helsinki.

Fig 1. Enrollment flow chart of patients.

Fig 1

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Data collection

The participants visited our health care center after an overnight 12-hour fast. Clinical information and blood laboratory data were collected during the health checkup. Height and weight were measured with the participants in a standing position wearing a light examination gown and no shoes. WC was measured at the umbilicus level with the participants in a standing position. Body composition analysis was performed using Inbody 720 (Biospace Co., Seoul, Korea) by a trained nurse following the manufacturer’s protocol [47]. Using Inbody 720, skeletal muscle mass and visceral fat area (VFA) were automatically calculated. Clinical information was collected and included for the following parameters: age, sex, systolic and diastolic blood pressure (BP), smoking, alcohol intake, and medical history, including HT and DM. The following laboratory blood investigations were performed: total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), glucose, aspartate aminotransferase (AST), alanine aminotransferase (ALT), uric acid, insulin level, and C-reactive protein (CRP).

Definitions

BMI was defined as weight (in kg) divided by height squared (in m2); obesity was defined as BMI ≥ 25 kg/m2 based on the criteria for the Asia-Pacific region [45,48]. Subjects were divided into obese (BMI ≥ 25 kg/m2) and non-obese (BMI < 25 kg/m2) groups.

VFA was measured using Inbody 720 and used to assess visceral adiposity. Subjects with VFA ≥100 cm2 were placed in the visceral adiposity group [11,43,49]. Subjects with VFA <100 cm2 were placed in the group without visceral adiposity.

Appendicular skeletal muscle mass (ASM) was calculated as the sum of the lean skeletal muscle mass of the bilateral upper and lower limbs. ASM was divided by body weight (in kg) and expressed as a percentage (calculated as, ASM% = ASM × 100/Weight). Sarcopenia was defined as ASM% < 29.0 in males and < 22.9 in females [50,51]. Subjects were placed in the sarcopenia and non-sarcopenia groups, accordingly. Obesity, visceral adiposity, and sarcopenia were considered as prognostic body composition parameters.

HT was defined as systolic BP ≥ 140 mmHg, diastolic BP ≥ 90 mmHg, or the use of antihypertensive medications. DM was defined as fasting plasma glucose ≥ 126 mg/dL, glycated hemoglobin level ≥ 6.5%, or the use of anti-diabetic medications including insulin. DL was defined as TG level ≥ 150 mg/dL, HDL-C in males < 40 mg/dL and in females < 50 mg/dL, or the use of medications.

MS was defined when three or more of the following criteria were met: 1) WC in males ≥ 102 cm and in females ≥ 88 cm; 2) TG level ≥ 150 mg/dL or the use of medications; 3) HDL-C in males < 40 mg/dL and in females < 50 mg/dL, or the use of medications; 4) systolic BP ≥ 130 mmHg, diastolic BP ≥ 85 mmHg, or the use of antihypertensive medications; and 5) fasting plasma glucose ≥ 100 mg/dL or the use of anti-diabetic medications including insulin [52,53]. Severe MS was defined when four or more of the above criteria were met.

The homeostatic model assessment of insulin resistance (HOMA-IR) was calculated as [fasting glucose (mg/dL) × fasting insulin (μU/mL)]/405 [54].

Comparison of Inbody 720 and computed tomography data

To verify the data of VFA and skeletal muscle mass as measured by Inbody 720, data were correlatively analyzed in subjects who underwent body composition analysis by BIA and computed tomography (CT) on the same day. Using CT, VFA and total abdominal muscle area (TAMA) were measured at the L3 vertebral level, which showed the highest correlation with visceral fat volume and whole-body skeletal muscle in previous studies [55,56].

All abdominal CT scans were performed using a 64-slice multi-detector CT scanner (Brilliance 64 scanners; Philips Healthcare, Amsterdam, Netherlands). Pre-contrast CT images were analyzed using a commercially available segmentation software program (MEDIP Deep Catch v1.0.0.0, MEDICALIP Co. Ltd., Seoul, South Korea) to measure TAMA. After automatic segmentation, the reader selected the level of the inferior endplate of the L3 vertebra and extracted the TAMA and VFA at the corresponding levels as previously described [46,57,58].

Statistical analysis

Continuous variables were expressed as mean ± standard deviation. Categorical variables were presented as numbers and percentages. The Student’s t-test and chi-square test were performed to compare quantitative and categorical variables, respectively. The linear trend between the number of MS components and categorical variables (obesity, visceral adiposity, and sarcopenia) was examined using the Cochran-Armitage trend test. The linear trend between the number of MS components and continuous variables (BMI, VFA, ASM%) was examined using analysis of variance with linear contrast. Logistic regression analysis was performed to determine the risk of MS. Crude odds ratios (ORs) were calculated for obesity, visceral adiposity, and sarcopenia at baseline. Model 1 was adjusted for age and sex; model 2 was adjusted for age, sex, HT, DM, and DL; model 3 was adjusted for age, sex, HT, DM, DL, smoking, and alcohol intake; and model 4 was adjusted for age, sex, HT, DM, DL, smoking, alcohol intake, and CRP levels. Pearson correlation analysis was performed between the BIA and CT scan data. Statistical significance was set at P < 0.05. All statistical analyses were conducted using the IBM SPSS 26 statistical software (IBM Corp., Armonk, NY, USA).

Results

Baseline characteristics of the study population

Among the 13,620 subjects who underwent routine health checkups, 7,422 and 6,198 were males and females, respectively. A total of 2,238 subjects were diagnosed with MS. Clinical characteristics according to the presence of MS are presented in Table 1 [46]. Clinical and anthropometric characteristics were significantly different based on the presence of MS. BMI and VFA were significantly higher in subjects with MS than in those without MS. ASM% was significantly lower in subjects with MS than that in those without MS.

Table 1. Clinical characteristics according to metabolic syndrome [46].

Variables All (N = 13620) p value
No metabolic syndrome Metabolic syndrome
N = 11382 (83.6%) N = 2238 (16.4%)
Age (years) 46.79±12.85 54.91±12.20 <0.001
Weight (kg) 64.33±11.91 73.62±14.80 <0.001
BMI (kg/m 2 ) 23.13±3.03 26.62±3.75 <0.001
WC (cm) 81.94±8.94 91.83±9.36 <0.001
Systolic BP (mmHg) 115.35±14.95 128.26±15.35 <0.001
Diastolic BP (mmHg) 78.04±10.57 84.48±11.42 <0.001
Visceral fat area (cm 2 ) 85.75±31.48 120.65±38.49 <0.001
ASM (kg) 19.58±4.75 20.96±5.21 <0.001
ASM% 30.25±3.55 28.33±3.56 <0.001
Cholesterol (mg/dL) 196.87±34.79 193.76±42.60 0.001
HDL-C (mg/dL) 58.45±13.96 45.97±10.94 <0.001
LDL-C (mg/dL) 119.15±32.71 113.18±37.60 <0.001
Triglyceride (mg/dL) 96.88±59.40 179.16±111.09 <0.001
Glucose (mg/dL) 90.70±15.17 113.48±28.63 <0.001
AST (IU/L) 26.48±17.52 33.58±20.49 <0.001
ALT (IU/L) 25.49±22.45 39.10±31.98 <0.001
Uric acid (mg/dL) 5.17±1.29 5.64±1.47 <0.001
HbA1c (%) 5.50±0.54 6.24±1.10 <0.001
Insulin 8.55±3.87 13.42±8.87 <0.001
HOMA-IR 2.02±1.11 3.80±2.33 <0.001
C-reactive protein (mg/dL) 0.13±0.44 0.22±0.55 <0.001
Hypertension (%) 2594 (22.8) 1636 (73.1) <0.001
Diabetes mellitus (%) 433 (3.8) 706 (31.5) <0.001
Smoking (%) 1897 (16.7) 484 (21.6) <0.001
Alcohol intake (%) 6096 (53.6) 1128 (50.4) 0.006
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Values are presented as mean ± standard deviation (SD) or number (%).

BMI, body mass index; WC, waist circumference; BP, blood pressure.

ASM, appendicular skeletal muscle; ASM%, appendicular skeletal muscle percentage.

HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol.

AST, aspartate aminotransferase; ALT, alanine aminotransferase.

HOMA-IR, homeostatic model assessment of insulin resistance.

The subjects were divided into two groups according to obesity, VFA, and ASM% (Table 2) [46]. Subjects with obesity, visceral adiposity, or sarcopenia were significantly older and had higher LDL-C, TG, CRP, and glucose levels, and HOMA-IR than those without. Subjects with obesity, visceral adiposity, or sarcopenia had a higher prevalence of HT, DM, and MS than those without.

Table 2. Clinical characteristics according to obesity, visceral adiposity, and sarcopenia [46].

Variables All (N = 13620) p value All (N = 13620) p value All (N = 13620) p value
Non-obese Obesity None Visceral adiposity None Sarcopenia
N = 9164 (67.3%) N = 4456 (32.7%) N = 8657 (63.6%) N = 4963 (36.4%) N = 12554 (92.2%) N = 1066 (7.8%)
Age (years) 47.57±13.34 49.28±12.51 <0.001 46.65±13.19 50.70±12.53 <0.001 47.70±12.84 53.16±14.94 <0.001
Weight (kg) 60.03±9.05 77.85±11.23 <0.001 60.20±9.65 75.73±11.85 <0.001 64.85±11.96 77.73±16.92 <0.001
BMI (kg/m 2 ) 21.87±2.01 27.48±2.50 <0.001 22.17±2.51 26.39±3.12 <0.001 23.29±2.99 28.67±4.11 <0.001
WC (cm) 79.04±7.22 92.88±7.29 <0.001 79.12±7.68 91.34±7.86 <0.001 82.49±8.90 96.30±10.05 <0.001
Systolic BP (mmHg) 113.69±14.77 125.25±14.86 <0.001 113.12±14.59 125.06±14.83 <0.001 116.66±15.50 127.09±15.64 <0.001
Diastolic BP (mmHg) 76.86±10.31 83.70±10.87 <0.001 76.56±10.23 83.53±10.82 <0.001 78.69±10.82 83.87±11.69 <0.001
Visceral fat area (cm 2 ) 77.04±25.52 121.19±33.71 <0.001 70.69±18.47 127.76±27.10 <0.001 87.18±30.75 142.13±43.73 <0.001
ASM (kg) 18.44±4.35 22.62±4.62 <0.001 18.35±4.36 22.35±4.61 <0.001 19.76±4.80 20.43±5.38 <0.001
ASM% 30.44±3.64 28.90±3.36 <0.001 30.24±3.64 29.40±3.54 <0.001 30.26±3.49 26.07±2.90 <0.001
Cholesterol (mg/dL) 194.62±35.31 199.93±37.73 <0.001 193.69±34.69 201.02±38.26 <0.001 196.03±35.87 200.18±39.76 0.001
HDL-C (mg/dL) 59.68±14.46 49.65±11.18 <0.001 59.91±14.54 50.27±11.48 <0.001 57.03±14.30 49.01±11.66 <0.001
LDL-C (mg/dL) 116.13±32.69 122.53±35.05 <0.001 115.36±32.16 123.22±35.47 <0.001 117.81±33.26 122.86±37.16 <0.001
Triglyceride (mg/dL) 94.63±57.76 142.83±98.12 <0.001 92.69±57.60 141.30±94.43 <0.001 107.35±74.49 146.33±93.26 <0.001
Glucose (mg/dL) 91.64±17.76 100.22±22.79 <0.001 90.81±16.23 100.77±23.89 <0.001 93.66±19.16 103.61±25.96 <0.001
AST (IU/L) 25.82±16.37 31.41±21.06 <0.001 25.44±16.91 31.50±19.76 <0.001 27.01±17.79 35.13±21.44 <0.001
ALT (IU/L) 23.07±20.22 37.32±30.02 <0.001 22.45±20.88 36.93±28.16 <0.001 26.37±22.94 43.74±37.15 <0.001
Uric acid (mg/dL) 4.98±1.24 5.80±1.36 <0.001 4.94±1.24 5.78±1.33 <0.001 5.19±1.31 5.94±1.48 <0.001
HbA1c (%) 5.54±0.63 5.81±0.84 <0.001 5.51±0.58 5.83±0.86 <0.001 5.59±0.68 5.99±0.99 <0.001
Insulin 7.94±3.39 12.14±7.43 <0.001 7.70±3.14 12.18±7.26 <0.001 8.72±3.82 16.85±11.09 <0.001
HOMA-IR 1.95±1.22 3.11±1.93 <0.001 1.83±1.02 3.19±1.96 <0.001 2.17±1.22 4.37±2.84 <0.001
C-reactive protein (mg/dL) 0.13±0.48 0.19±0.41 <0.001 0.12±0.46 0.19±0.46 <0.001 0.14±0.46 0.28±0.49 <0.001
Metabolic syndrome (%) 770 (8.4) 1468 (32.9) <0.001 685 (7.9) 1553 (31.3) <0.001 1746 (13.9) 492 (46.2) <0.001
Hypertension (%) 2025 (22.1) 2205 (49.5) <0.001 1774 (20.5) 2456 (49.5) <0.001 3591 (28.6) 639 (59.9) <0.001
Diabetes mellitus (%) 574 (6.3) 565 (12.7) <0.001 465 (5.4) 674 (13.6) <0.001 947 (7.5) 192 (18.0) <0.001
Smoking (%) 1367 (14.9) 1014 (22.8) <0.001 1071 (12.4) 1310 (26.4) <0.001 2144 (17.1) 237 (22.2) <0.001
Alcohol intake (%) 4637 (50.6) 2587 (58.1) <0.001 4250 (49.1) 2974 (59.9) <0.001 6672 (53.1) 552 (51.8) 0.392
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Values are presented as mean ± standard deviation (SD) or number (%).

BMI, body mass index; WC, waist circumference; BP, blood pressure; ASM, appendicular skeletal muscle.

ASM%, appendicular skeletal muscle percentage; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol.

AST, aspartate aminotransferase; ALT, alanine aminotransferase; HOMA-IR, homeostatic model assessment of insulin resistance.

Metabolic parameters according to obesity, visceral adiposity, and sarcopenia

Table 3 shows the trend in the number of metabolic parameters between subjects with and those without obesity, visceral adiposity, or sarcopenia. The prevalence of obesity, visceral adiposity, or sarcopenia increased with the number of metabolic parameters (P < 0.001 for all). Fig 2A shows the differences in the prevalence of MS between subjects with and without obesity, visceral adiposity, or sarcopenia. The prevalence of MS was significantly higher in those with obesity, visceral adiposity, or sarcopenia than in those without (32.9% vs. 8.4%, 31.3% vs. 7.9%, and 46.2% vs. 13.9%, respectively, P < 0.001 for all). We also calculated the prevalence of severe MS based on the presence of either four or five criteria among the groups (Fig 2B). The prevalence of severe MS was significantly higher in those with obesity, visceral adiposity, or sarcopenia than in those without (12.6% vs. 1.8%, 11.6% vs. 1.7%, and 20.1% vs. 4.1%, respectively, P < 0.001 for all).

Table 3. Comparisons of number of metabolic parameters according to obesity, visceral adiposity, or sarcopenia.

Obesity P-value Visceral adiposity P-value Sarcopenia P-value
No Yes No Yes No Yes
Number of parameters N <0.001 <0.001 <0.001
0 4891 4343 (88.8) 548 (11.2) 4233 (86.5) 658 (13.5) 4819 (98.5) 72 (1.5)
1 3797 2636 (69.4) 1161 (30.6) 2458 (64.7) 1339 (35.3) 3584 (94.4) 213 (5.6)
2 2694 1415 (52.5) 1279 (47.5) 1281 (47.6) 1413 (52.4) 2405 (89.3) 289 (10.7)
3 1513 607 (40.1) 906 (59.9) 537 (35.5) 976 (64.5) 1235 (81.6) 278 (18.4)
4 605 158 (26.1) 447 (73.9) 139 (23.0) 466 (77.0) 446 (73.7) 159 (26.3)
5 120 5 (4.2) 115 (95.8) 9 (7.5) 111 (92.5) 65 (54.2) 55 (45.8)
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Fig 2.

Fig 2

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(A) The prevalence of MS in subjects with obesity, visceral adiposity, or sarcopenia was higher than that in subjects without these parameters (P < 0.001 for all). (B) The prevalence of severe MS in subjects with obesity, visceral adiposity, or sarcopenia was higher than that in subjects without them (P < 0.001 for all). MS, metabolic syndrome.

The descriptive numerical values of BMI, VFA, and ASM% showed linear trends according to the number of metabolic parameters (Table 4). As the number of metabolic components increased from 0 to 5, a decreasing trend of ASM% and an increasing trend of BMI and VFA were identified (P < 0.001 for all).

Table 4. Descriptive numerical values of body mass index, visceral fat area, and ASM% according to the number of metabolic parameters.

Number of parameters 0 1 2 3 4 5 P-value
N 4891 3797 2694 1513 605 120
BMI (kg/m 2 ) 21.79±2.52 23.58±2.79 24.94±3.09 25.99±3.32 27.48±3.89 30.24±5.02 <0.001
Visceral fat area (cm 2 ) 71.04±25.71 90.94±28.82 105.15±31.78 115.94±36.02 127.85±41.27 143.67±40.47 <0.001
ASM% 30.49±3.56 30.30±3.56 29.75±3.49 28.91±3.47 27.55±3.39 24.88±2.68 <0.001
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BMI, body mass index; ASM%, appendicular skeletal muscle percentage.

P-value estimated from analysis of variance with linear contrast.

Additive effects of body composition parameters on metabolic syndrome

The number of metabolic parameters was calculated according to the numbers of prognostic body composition parameters, including obesity, visceral adiposity, and sarcopenia. Metabolic burden increased with an increase in the number of body composition parameters (P for trend < 0.001, Fig 3A). As the number of body composition parameters increased from 0 to 3, the prevalence of MS increased accordingly (5.9%, 18.0%, 33.6%, and 50.4%, respectively; P for trend < 0.001 in all; Fig 3B) On performing paired analyses between two body composition parameters, all three parameters, including obesity, visceral adiposity, and sarcopenia, showed additive effects in predicting MS (Fig 4A–4C).

Fig 3.

Fig 3

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(A) The number of metabolic parameters according to the number of unfavorable body composition parameters (obesity, visceral adiposity, and sarcopenia). (B) The prevalence of MS according to the number of unfavorable body composition parameters (obesity, visceral adiposity, and sarcopenia). (P for trend < 0.001 in all); MS, metabolic syndrome.

Fig 4.

Fig 4

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The prevalence of MS in paired analyses according to (A) obesity and visceral adiposity, (B) obesity and sarcopenia, and (C) visceral adiposity and sarcopenia; MS, metabolic syndrome.

Body composition parameters and metabolic syndrome

Obesity, visceral adiposity, and sarcopenia were significantly associated with the risk of MS (crude OR = 5.356, 5.300, and 5.306, respectively). After adjustment for age, sex, HT, DM, DL, smoking, alcohol intake, and CRP, ORs remained significant for obesity, visceral adiposity, and sarcopenia (adjusted OR = 4.235, 3.552, and 3.674, respectively; Table 5).

Table 5. Odds ratios of metabolic syndrome according to the presence of obesity, visceral adiposity, and sarcopenia.

Obesity Visceral adiposity Sarcopenia
OR 95% CI p value OR 95% CI p value OR 95% CI p value
Crude 5.356 4.862–5.900 <0.001 5.300 4.803–5.849 <0.001 5.306 4.656–6.046 <0.001
Model 1 5.637 5.084–6.249 <0.001 5.090 4.577–5.661 <0.001 4.414 3.847–5.065 <0.001
Model 2 4.259 3.704–4.898 <0.001 3.547 3.079–4.086 <0.001 3.774 3.111–4.577 <0.001
Model 3 4.260 3.705–4.899 <0.001 3.567 3.095–4.110 <0.001 3.778 3.114–4.583 <0.001
Model 4 4.235 3.682–4.872 <0.001 3.552 3.082–4.095 <0.001 3.674 3.027–4.460 <0.001
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Model 1: Adjusted for age and sex.

Model 2: Adjusted for age, sex, HT, DM, and DL.

Model 3: Adjusted for age, sex, HT, DM, DL, smoking, and alcohol intake.

Model 4: Adjusted for age, sex, HT, DM, DL, smoking, alcohol intake, and CRP levels.

HT, hypertension; DM, diabetes mellitus; DL, dyslipidemia; CRP, C-reactive protein; OR, odds ratio; CI, confidence interval.

Correlation of VFA and skeletal muscle mass between Inbody 720 and computed tomography

Among the enrolled subjects, CT scans were performed on 966 subjects on the same day as the Inbody 720 analysis. Thus, correlation analysis was conducted in 966 subjects, similar to a previous study [46]. VFA measured by Inbody 720 positively correlated with VFA measured by CT scan (R = 0.743, P < 0.001, Fig 5A). ASM measured using BIA was positively correlated with TAMA measured by CT scan (R = 0.890, P < 0.001, Fig 5B) as previously described [46].

Fig 5.

Fig 5

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(A) Correlation of VFA measured by Inbody 720 and CT scan (R = 0.743, P<0.001), (B) Correlation of ASM measured by Inbody 720 and TAMA at the L3 vertebral level measured by CT scan (R = 0.890, P < 0.001) [46]. VFA, visceral fat area; CT, computed tomography; ASM, appendicular skeletal muscle mass; TAMA, total abdominal muscle area.

Discussion

In the current study, we analyzed the association between body composition parameters (obesity, visceral adiposity, and sarcopenia) and MS. We demonstrated that obesity, visceral adiposity, and sarcopenia were significantly associated with MS. After adjusting for multiple confounders, including age, sex, HT, DM, DL, smoking, alcohol intake, and CRP levels, subjects with obesity, visceral adiposity, and sarcopenia were found to be associated with an increased risk for MS (Table 5). In addition, as the number of prognostic body composition parameters increased, the risk for MS additively increased (Figs 3 and 4). Our study shows an association between body composition parameters and the risk of MS in a healthy population who underwent routine health checkups.

To the best of our knowledge, this is the largest study showing that unfavorable body composition parameters (obesity, visceral adiposity, and sarcopenia) additively increase the risk for MS. Previous studies have shown that visceral adiposity [7–11], sarcopenia [30–32], and obesity [20–23] were associated with an increased risk for MS. However, most of these studies analyzed the association of only a single body composition parameter with MS; studies analyzing the association between multiple body composition parameters and MS have been rare [43,45]. Lim et al. analyzed the association between MS and two parameters (sarcopenia and visceral adiposity). However, in the above-mentioned study, visceral adiposity was defined based on abdominal CT results. Moreover, ASM was measured by dual energy X-ray absorptiometry and the sample size was small (N = 565) [43]. Lu et al. analyzed the association between MS and two parameters (sarcopenia and obesity). In this study, BIA was utilized for the measurement of skeletal muscle mass; however, the sample size was also small (N = 600) [45].

The previous study of the same study population as this study (Fig 1) showed that sarcopenia diagnosed by BIA is independently associated with MS risk in a dose-response manner [46]. Our previous study focused on the relationship between sarcopenia and MS [46]. In contrast, the current study comprehensively analyzed the effects of obesity, visceral adiposity, and sarcopenia on the risk of MS. Our current study demonstrated that the risks for MS additively increased as the number of undesirable body composition parameters (obesity, visceral adiposity, and sarcopenia) increased from 0 to 3. By utilizing BIA for the measurements of skeletal muscle mass and VFA, as well as BMI, the population with a high risk for MS could be easily identified. Our study also showed that all three body composition parameters (obesity, visceral adiposity, and sarcopenia) were associated with increased MS risk after adjustments for age, sex, HT, DM, DL, smoking, alcohol intake, and CRP levels. In accordance with previous studies analyzing CRP and MS [59,60], CRP was adopted as a variable in our current study. In our study, as the number of metabolic components increased from 0 to 5, a decreasing trend of ASM% and an increasing trend of VFA and BMI were identified, which exhibited a dose-response manner.

Mechanisms that link sarcopenia and MS include insulin resistance and inflammation [61,62]. The skeletal muscle is the primary site of glucose utilization [37]; the role of sarcopenia in causing insulin resistance and DM has been described [32,63]. In our current study, HOMA-IR was significantly higher in the sarcopenia group than in the non-sarcopenic group. Another mechanism that links sarcopenia and MS is inflammation. The association between inflammation and sarcopenia has been reported [64,65]. Pro-inflammatory cytokines, such as interleukin (IL)-6 and tumor necrosis factor (TNF)-alpha, are associated with sarcopenia. In our current study, the sarcopenia group had higher CRP levels than the non-sarcopenic group, which supported the hypothesis that systemic inflammation serves as a link between sarcopenia and MS.

A link has been proposed between adipose tissue and skeletal muscle inflammation [66]. According to this mechanism, there is a positive feedback loop between visceral adiposity and sarcopenia. In obese subjects, adipose tissue is infiltrated by activated pro-inflammatory macrophages and is associated with an elevated production of pro-inflammatory molecules and adipokines [67,68]. The production of TNF-alpha, IL-6, and CRP from adipose tissue influences insulin resistance [69]. In our current study, the visceral adiposity group had higher CRP levels than the group without visceral adiposity, which supported the hypothesis that systemic inflammation serves as a link between visceral adiposity and MS.

CT has been considered the gold standard for measuring skeletal muscle mass [70]. Cross-sectional CT images of the lumbar skeletal muscle have provided good estimates of the total body skeletal muscle [71,72]. However, the recent use of CT for measuring body fat or muscle has been limited due to an increased risk for radiation exposure [11]. In our current study, BIA was used to measure ASM and VFA because BIA has been widely used owing to its accessibility, safety, and cost-efficiency [10,45,73,74]. Furthermore, to validate the data of VFA and skeletal muscle mass measured by Inbody 720, the correlation between BIA data and CT scans was analyzed in subjects who underwent body composition analysis using BIA and CT scans on the same day. VFA and TAMA at the L3 vertebral level measured by CT scan show a high correlation with visceral fat volume and whole-body skeletal muscle [55,56]. Recent studies reported that BIA-measured VFA indicated an increased risk for MS as precisely as CT-measured VFA [47,75]. Our study also showed a high positive correlation between BIA-measured ASM and CT-measured TAMA as previously described [46]. Moreover, a high correlation was also observed between BIA- and CT- measured VFA in our study (Fig 5).

In the current study, we used BIA to measure ASM and VFA similar to previous studies. However, the study size was relatively small in most of the earlier studies (N<1,500) [8,10,13,31,45]. Jeon et al. analyzed the risk for MS according to BIA-measured VFA; the study size was large, but skeletal muscle mass was not addressed [11]. The strength of our study is that we analyzed multiple body composition parameters, including VFA and ASM, in a large and healthy population. In addition, a significant association between body composition parameters and MS was confirmed after multivariable adjustments for age, sex, underlying diseases, smoking, alcohol intake, and inflammatory markers.

Our study had some limitations. First, as this was a cross-sectional, single-centered, retrospective study, the duration of MS was not assessed. It was difficult to assess the causal relationship between visceral fat, sarcopenia, and MS. Second, our study population was of an Asian ethnicity; thus, our study results cannot be generalized for all ethnicities. Third, our study population consisted of healthy subjects who underwent routine health checkups in a health care center. Thus, our study results are difficult to apply in non-healthy subjects. On the contrary, our study results are likely to be generalizable to a healthy population. Fourth, functional measurements of skeletal muscle, including handgrip testing or gait speed, were not performed. Surveys of exercise status were not included in the variables and could not be evaluated in our study. Finally, HOMA-IR results were available in only a small portion of the study population (N = 305); thus, significant results after adjustment for HOMA-IR could not be derived.

In conclusion, our study demonstrated that obesity, visceral adiposity, and sarcopenia were significantly associated with MS. In addition, with the increase in unfavorable body composition parameters, there is an additive increased risk of MS. Increasing skeletal muscle and reducing visceral adiposity may act as strategies for the prevention or treatment of MS. Further studies are needed to assess the causal relationship between body composition parameters and MS.

Supporting information

S1 File. Data file.

(XLSX)

Click here for additional data file. (3.6MB, xlsx)

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

The authors received no specific funding for this work.

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Decision Letter 0

Mauro Lombardo

23 Jun 2021

PONE-D-21-15211

Association of obesity, visceral adiposity, and sarcopenia with an increased risk of metabolic syndrome: a retrospective study

PLOS ONE

Dear Dr. Jeong,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Academic Editor

PLOS ONE

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Additional Editor Comments (if provided):

Dear authors

Please improve the English in the paper.

Answer point-by-point to the reviews' observations

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The manuscript provides evidence of the association between body composition parameters (obesity, visceral adiposity, and sarcopenia) and metabolic syndrome in a large sample of subjects. The manuscript is technically sound and the data do support the conclusions however there are a few revisions or clarifications I would suggest the authors address.

Statistical Analysis/Study Population (Methods General):

•The authors indicated that data from 4,621 repeated checkups were excluded from the analyses it would have been interesting to assess how the body composition parameters may have predicted changes in MS status over time using the repeated visits from the 4,621 with repeat data as this data was available.

Results:

•The results are clear however, the authors should include the percentages for the total number of subjects (n=2238) with MS as well as the percentages for the total number of subjects who were in the obesity group, visceral adiposity group and sarcopenia group. I would further suggest either updating this in Table 1 and Table 2.

•Table 3 and the language describing table 3 is unclear, it states the prevalence of MS was significantly higher in those with obesity, visceral adiposity AND sarcopenia compared to those without however, the table appears to show these as mutually exclusive groups. That is to say, obesity vs none, visceral vs non, sarcopenia vs none NOT those with obesity, visceral adiposity AND sarcopenia I would assume the group of individuals whom may be categorized by all 3 conditions would be much smaller. Thus, I would suggest the authors use ‘or’ rather than ‘and’ to indicate these analyses were done separately for each of the 3 conditions.

•It is unclear which models were used to assess the results reported in Table 3 and 4—were these done using chi-squared or the students t-tests? As these are counts for the number of parameters the authors should be more clear on how these results were modeled in the statistical analyses section.

•Table 5 is clearly defined and easy to read as well as reported and described appropriately both in the analyses section as well as the results.

Overall, the manuscript is clear and describes the association between obesity, visceral adiposity, and sarcopenia in a large sample of individuals.

Reviewer #2: Comment for Authors

The authors have undertaken study to explore the association of multiple body composition parameters such as obesity, visceral adiposity and sarcopenia with metabolic syndrome. The sample size is large and study span of 5 year have resulted in robust data. Over all study represent a major portion of Asian population. Despite these merits the study is not novel and is just an extension of earlier study by Kim S H et al., “Association between sarcopenia level and metabolic syndrome” (PMID: 33739984).

GENERAL

English should be improved throughout the text. Sentence needs to be rephrased and lines should be numbered throughout the manuscript.

In discussion include a paragraph explaining the parameters that are included in the current study and merit of the current study over earlier study conducted by same author (PMID: 33739984).

Methods and Materials

Methods and material section is well written

Results

The table 1 and table 2 are duplication of table 1 of previous published article (PMID: 33739984) by the same author represented in different way.

The figure 5B of the current study is duplication of figure 5 of previous published article (PMID: 33739984).

Figure legends should be self-explanatory.

Novelty

The study is not novel

**********

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2021 Aug 17;16(8):e0256083. doi: 10.1371/journal.pone.0256083.r002

Author response to Decision Letter 0

22 Jul 2021

Response Letter

Editors, PLOS ONE

Thank you for allowing the revision of our manuscript: ID PONE-D-21-15211 entitled “Association of obesity, visceral adiposity, and sarcopenia with an increased risk of metabolic syndrome: a retrospective study” We revised our manuscript in accordance with the reviewers’ suggestions. Our responses to the comments are as follows.

Reviewer #1:

The manuscript provides evidence of the association between body composition parameters (obesity, visceral adiposity, and sarcopenia) and metabolic syndrome in a large sample of subjects. The manuscript is technically sound and the data do support the conclusions however there are a few revisions or clarifications I would suggest the authors address.

Comment 1>

1. The authors indicated that data from 4,621 repeated checkups were excluded from the analyses it would have been interesting to assess how the body composition parameters may have predicted changes in MS status over time using the repeated visits from the 4,621 with repeat data as this data was available.

Reply: Thank you for your valuable comments. It seems that causal relationship may be assessed by analyzing the data of subjects who underwent repeated health checkup. However, in this current study, we intended a cross-sectional study. We indeed have a plan to perform another study in the next step with the data of subjects who underwent repeated health checkup. As of now, it’s a pity that we can’t show you the repeat data, but we’ll be able to show you when the next paper is completed. We sincerely ask for your kind understanding.

Comment 2>

2. The results are clear however, the authors should include the percentages for the total number of subjects (n=2238) with MS as well as the percentages for the total number of subjects who were in the obesity group, visceral adiposity group and sarcopenia group. I would further suggest either updating this in Table 1 and Table 2

Reply: Thank you for your valuable comments. Based on your comments, we added the percentages of subjects with MS in Table 1. We also added the percentages of subjects in the obesity group, visceral adiposity group and sarcopenia group in Table 2.

Comment 3>

3. Table 3 and the language describing table 3 is unclear, it states the prevalence of MS was significantly higher in those with obesity, visceral adiposity AND sarcopenia compared to those without however, the table appears to show these as mutually exclusive groups. That is to say, obesity vs none, visceral vs non, sarcopenia vs none NOT those with obesity, visceral adiposity AND sarcopenia I would assume the group of individuals whom may be categorized by all 3 conditions would be much smaller. Thus, I would suggest the authors use ‘or’ rather than ‘and’ to indicate these analyses were done separately for each of the 3 conditions.

Reply: Thank you for your valuable comments. Based on your comments, we revised our manuscript. We used ‘or’ instead of ‘and’ to indicate these analyses were done separately for each of the 3 conditions.

Comment 4>

4. It is unclear which models were used to assess the results reported in Table 3 and 4—were these done using chi-squared or the students t-tests? As these are counts for the number of parameters the authors should be more clear on how these results were modeled in the statistical analyses section.

Reply: Thank you for your valuable comments. We added more specific contents in the statistical analyses section. In the results section, we revised some contents regarding Table 3 and Table 4.

Comment 5>

5. Table 5 is clearly defined and easy to read as well as reported and described appropriately both in the analyses section as well as the results.

Reply: Thank you for your valuable comments.

Reviewer #2:

The authors have undertaken study to explore the association of multiple body composition parameters such as obesity, visceral adiposity and sarcopenia with metabolic syndrome. The sample size is large and study span of 5 year have resulted in robust data. Over all study represent a major portion of Asian population. Despite these merits the study is not novel and is just an extension of earlier study by Kim S H et al., “Association between sarcopenia level and metabolic syndrome” (PMID: 33739984).

Comment 1>

1. English should be improved throughout the text. Sentence needs to be rephrased and lines should be numbered throughout the manuscript.

Reply: Thank you for your valuable comments. We rephrased some sentences and underwent additional English proofreading. And lines were numbered throughout the manuscript.

Comment 2>

2. In discussion include a paragraph explaining the parameters that are included in the current study and merit of the current study over earlier study conducted by same author (PMID: 33739984).

Reply: Thank you for your valuable comments. As you suggested, we added sentences explaining the parameters that are included in the current study and merit of the current study over earlier study. We revised our manuscript as follows.

Discussion – 3rd paragraph

The previous study of the same study population as this study (Figure 1) showed that sarcopenia diagnosed by BIA is independently associated with MS risk in a dose-response manner.46 Our previous study focused on the relationship between sarcopenia and MS.46 In contrast, the current study comprehensively analyzed the effects of obesity, visceral adiposity, and sarcopenia on the risk of MS. Our current study demonstrated that the risks for MS additively increased……

Comment 3>

3. The table 1 and table 2 are duplication of table 1 of previous published article (PMID: 33739984) by the same author represented in different way.

Reply: Thank you for your valuable comments. Our current study and the previous published article share the same study population (N=13620), but the research topic and analysis methods were completely different between the two studies. However, since Table 1 and Table 2 in our current study have some overlap with the contents of the Table 1 of the previous paper, we added such contents in the main text and cited the previous paper in Table 1 and Table 2.

Comment 4>

4. The figure 5B of the current study is duplication of figure 5 of previous published article (PMID: 33739984).

Reply: Thank you for your valuable comments. Although the research topic and analysis methods were completely different between the two studies, patients who performed both CT and Inbody on the same day were the same. Therefore, the graph that correlated CT and Inbody in this current study was the same as the graph in the previous study. We added such contents in the main text and cited the previous paper in the Figure 5B.

Comment 5>

5. Figure legends should be self-explanatory.

Reply: Thank you for your valuable comments. Based on your comments, we revised the Figure legend of Figure 2.

Comment 6>

6. The study is not novel.

Reply: Although this study is not novel, the sample size of our study is large and 5-year span resulted in robust data as you commented. And our data strongly support our conclusion. Thus, our study is thought to have sufficient merit. Thank you.

Thank you again for your insightful advice.

Yours sincerely,

Ji Bong Jeong, MD, PhD

Associate Professor

Department of Internal Medicine

Seoul Metropolitan Government Seoul National University Boramae Medical Center

20 Boramae-ro 5-gil, Dongjak-gu

Seoul 07061, Republic of Korea

Phone: +82-2-870-2222

Fax: +82-2-870-3863

E-mail: jibjeong@gmail.com

Attachment

Submitted filename: Response to reviewers.docx

Click here for additional data file. (22.5KB, docx)

Decision Letter 1

Mauro Lombardo

2 Aug 2021

Association of obesity, visceral adiposity, and sarcopenia with an increased risk of metabolic syndrome: a retrospective study

PONE-D-21-15211R1

Dear Dr. Jeong,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Mauro Lombardo

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: I Don't Know

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: (No Response)

Reviewer #2: All the Major comments have been addressed.

Minor comments

1) The manuscript could be structured more reader friendly and improve the language by giving the manuscript for professionals for editing.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Acceptance letter

Mauro Lombardo

5 Aug 2021

PONE-D-21-15211R1

Association of obesity, visceral adiposity, and sarcopenia with an increased risk of metabolic syndrome: a retrospective study

Dear Dr. Jeong:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Mauro Lombardo

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PLOS ONE

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