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. 2025 Jan 3;39(1):381–389. doi: 10.21873/invivo.13839

Metabolic Syndrome and Somatic Composition: A Large Cross-sectional Analysis

MASAHIRO MATSUI 1, AKIRA FUKUDA 2, SAORI ONISHI 1, KOSUKE USHIRO 1, TOMOHIRO NISHIKAWA 1, AKIRA ASAI 1, SOO KI KIM 3, HIROKI NISHIKAWA 1
PMCID: PMC11705143  PMID: 39740891

Abstract

Background/Aim

To elucidate the relationship between metabolic syndrome (Mets) and somatic composition [fat mass, fat-free (FF) mass, and fat to fat-free (F-FF) ratio] among health checkup recipients (7,776 males and 10,121 females).

Patients and Methods

We classified study subjects into four types considering Japanese criteria for Mets; Type A is for males with waist circumference (WC) <85 cm and females with WC <90 cm, Type B is for males with WC ≥85 cm and females with WC ≥90 cm, but without any metabolic abnormalities, Type C is for males with WC ≥85 cm and females with WC ≥90 cm and one metabolic disorder (pre-Mets), and Type D is Mets. We compared baseline characteristics among types of A, B, C, and D.

Results

F index, FF index, and F-FF ratio showed an increasing trend with increasing risk factors for Mets in both sexes.

Conclusion

This study demonstrates a clear correlation between somatic composition and the severity of metabolic syndrome (Mets). As Mets risk factors increase, fat mass, fat-free mass, and the fat-to-fat-free ratio also rise, indicating that body composition shifts with disease progression. These findings emphasize the need for early intervention, such as exercise and diet, to manage somatic composition imbalances and reduce complications like insulin resistance.

Keywords: Metabolic syndrome, somatic composition, fat mass, fat-free mass, fat mass to fat-free mass ratio

Metabolic syndrome (Mets) refers to a condition in which, in addition to excessive accumulation of visceral fat, elevated blood pressure, high fasting blood glucose, and lipid abnormalities are observed (1,2). In Mets, the focus is on visceral fat obesity, and the most important criterion for Mets is the waist circumference (WC), which correlates well with visceral fat accumulation. Therefore, there are a certain number of people who develop Mets even if their body mass index (BMI) is low (1,2). In Japan, approximately 30% of males and 10% of females who undergo health checkups have metastasis (Mets). This condition increases the risk of developing cardiovascular events and other related health issues (1). Patients with Mets often have increased ectopic fat deposition, including in the abdominal cavity, that is characterized by enlarged adipocytes and abnormalities in adipocyte-derived endocrine factors called adipokines (3). Overnutrition, especially in adulthood and beyond, can easily lead to visceral fat accumulation, a condition associated with chronic inflammation, hypoxia, and hyperoxidative stress, leading to hypoadiponectinemia (4-6). Adiponectin activates lipolytic enzymes and supports the consumption of glucose and fat (6). Furthermore, sex differences in fat and skeletal muscle distribution contribute substantially to sex differences in tissue-specific insulin sensitivity and cardiometabolic health (7).

Skeletal muscle is the largest glucose metabolizing organ in the human body, processing approximately 80% of glucose (8-12). In the case of abnormal glucose metabolism, glucose uptake into skeletal muscle is significantly reduced compared to other organs (9). However, the relationship between Mets and skeletal muscle partly remains unclear. There is concern that reduced skeletal muscle mass and skeletal muscle quality may lead to reduced muscle contractile and metabolic functions, leading to the development of Mets (13,14). However, there are a variety of cases, ranging from athletes with Mets (such as Sumo wrestler in Japan), who have both high body fat mass and skeletal muscle mass, to those with high fat mass but low skeletal muscle mass, as seen in patients with sarcopenic obesity (15-18). Therefore, it is clinically relevant to elucidate the relevance between Mets and skeletal muscle. Appropriate intervention such as exercise would be especially important for those with reduced skeletal muscle mass as in patients with Mets. The purpose of the present research was to elucidate the relationship between Mets and somatic composition, including skeletal muscle, among health checkup recipients.

Patients and Methods

Patients and our study. Between February 2022 and May 2023, a total of 17897 consecutive cases with possible diagnosis of Mets and data on somatic composition were found in our medical records and were analyzed in a retrospective manner. All study subjects were tested at the Osaka Medical and Pharmaceutical University (OMPU) Health Sciences Clinic. Our method of measuring somatic composition is as previously described (19). Fat mass (FM, kg) and fat-free mass (FFM, kg) were measured and analyzed in the current analysis. F index was indicated by fat mass divided by height squared (kg/m2). FF index was indicated by fat-free mass divided by height squared (kg/m2). Fat mass to fat-free mass (F-FF) ratio was indicated by F index divided by FF index. In accordance with previous reports, skeletal muscle loss was defined as FF index <18 kg/m2 for males and FF index <15 kg/m2 for females (20).

In Japan, “metabolic syndrome” is diagnosed when WC is 85 cm or more for males and 90 cm or more for females, and when two or more of three items (i.e., blood pressure, blood glucose, and lipids) are outside the reference values (2). Reference values are as follows: (A) systolic blood pressure (BP) ≥130 mmHg and/or diastolic BP ≥85 mmHg; (B) fasting blood glucose ≥110 mg/dl; (C) triglyceride level ≥150 mg/dl and/or HDL ≤40 mg/dl. Subjects receiving pharmacotherapy for hypertriglyceridemia, low HDL cholesterol, hypertension, or diabetes are included in each category. We classified our study subjects into the following four types: Type A is for males with WC <85 cm and females with WC <90 cm; Type B is for males with WC ≥85 cm and females with WC ≥90 cm, but without any metabolic abnormalities; Type C is for males with WC ≥85 cm and females with WC ≥90 cm and one metabolic disorder (pre-metabolic syndrome); Type D is for males with WC ≥85 cm and females with WC ≥90 cm and two or more metabolic abnormalities (i.e., Mets).

We compared baseline characteristics among types of A, B, C, and D. Next, factors linked to skeletal muscle loss were investigated. The current research conformed to the principles of the Declaration of Helsinki and was approved by the ethics committee of OMPU hospital (approval no. 2024-034, and date of approval: 13th June, 2024). An opt-out approach was utilized to get informed consent from study subjects, and personal information was fully protected in the data collection.

Statistics. In the two-group comparisons (continuous variables), unpaired t-test or Mann-Whitney U-test was used, as appropriate. In the multiple-group comparisons (continuous variables), analysis of variance (ANOVA) or the Kruskal-Wallis test was used, as appropriate. In the group comparison (nominal variables), Fisher’s exact test was used. Multivariate logistic regression analysis was used to choose candidate variables. Data are shown as number or median [interquartile range (IQR)] with statistical significance set at p<0.05. JMP 17.0 software (SAS Institute, Cary, NC, USA) was used for statistical analysis.

Results

Baseline features. Baseline features in the current research are demonstrated in Table I. The median (IQR) age (years) in males (n=7,776) and females (n=10,121) was 52 (44-62) and 50 (43-58) (p<0.0001). The median (IQR) BMI (kg/m2) in males and females was 23.5 (21.5-25.7) and 21.1 (19.3-23.5), respectively (p<0.0001). The median (IQR) WC (cm) in males and females was 84.5 (79-91) and 76.5 (71-84), respectively (p<0.0001). The proportion of subjects with WC ≥85 cm in males was 48.9% (3,805/7,776), while that with WC ≥90 cm in females was 11.8% (1,197/10,121) (p<0.0001). The median (IQR) alanine aminotransferase (ALT, IU/l) in males and females was 21 (16-31) and 15 (12-19) (p<0.0001). The median (IQR) F index (kg/m2) in males and females was 5.120 (3.915-6.538) and 6.093 (4.719-7.900) (p<0.0001). The median (IQR) FF index (kg/m2) in males and females was 18.404 (17.500-19.368) and 15.090 (14.467-15.742) (p<0.0001). The median (IQR) F-FF ratio in males and females was 0.279 (0.221-0.344) and 0.407 (0.324-0.508) (p<0.0001). Type A, B, C, and D was found in 3,971/793/1,424/1,588 for males and 8,924/349/480/368 for females, respectively (p<0.0001).

Table I. Baseline features.

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Data are expressed as median (IQR). sBP: Systolic blood pressure; dBP: diastolic blood pressure; TG: triglyceride; FBS: fasting blood sugar; eGFR: estimated glomerular filtration rate; F-FF ratio: fat mass to fat-free mass ratio.

Comparison of baseline parameters for types of A, B, C, and D in males. In males, the median (IQR) age (years) for types of A, B, C, and D were 50 (42-61), 47 (41-55), 53 (46-62), and 57 (50-66), respectively (Figure 1A). The median (IQR) ALT (IU/l) for types of A, B, C, and D were 18 (14-24), 24 (18-34), 25 (19-36), and 29 (20-43), respectively (Figure 1B). The median (IQR) estimated glomerular filtration rate (eGFR, ml/min/1.73m2) for types of A, B, C, and D were 70.9 (62.9-79.5), 71.0 (64.1-80.3), 68.9 (61.1-77.7), and 66.8 (58.5-76.4) (Figure 1C). The median (IQR) F index (kg/m2) for types of A, B, C, and D were 3.97 (3.16-4.75), 6.02 (5.20-7.03), 6.43 (5.48-7.61), and 6.97 (5.95-8.49) (Figure 2A). The median (IQR) FF index (kg/m2) for types of A, B, C, and D were 17.65 (16.94-18.34), 19.04 (18.39-19.83), 19.24 (18.51-20.11), and 19.45 (18.58-20.46) (Figure 2B). The median (IQR) F-FF ratio for types of A, B, C, and D were 0.225 (0.183-0.263), 0.317 (0.279-0.364), 0.336 (0.297-0.386), and 0.363 (0.318-0.421) (Figure 2C). The prevalence of subjects with BMI <23 kg/m2 for types of A, B, C, and D were 76.05%, 12.86%, 8.78% and 6.17% (Figure 3A). The prevalence of subjects with FF index <18 kg/m2 for types of A, B, C, and D were 63.56%, 13.87%, 12.01% and 12.28% (Figure 3B).

Figure 1.

Figure 1

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Comparison of age (A), ALT (B) and eGFR (C) among types of A, B, C, and D in males (n=7776). Type A: WC <85 cm, Type B: WC ≥85 cm and no metabolic abnormalities, Type C: pre-metabolic syndrome, and Type D: Mets. (A) p-Values: comparison of A and B, p<0.0001; A and C, p<0.0001; A and D, p<0.0001; B and C, p<0.0001; B and D, p<0.0001; C and D, p<0.0001; overall p<0.0001. (B) p-Values: comparison of A and B, p<0.0001; A and C, p<0.0001; A and D, p<0.0001; B and C, p=0.0162; B and D, p<0.0001; C and D, p<0.0001; overall p<0.0001. (C) p-Values: comparison of A and B, p=0.1764; A and C, p<0.0001; A and D, p<0.0001; B and C, p<0.0001; B and D, p<0.0001; C and D, p<0.0001; overall p<0.0001.

Figure 2.

Figure 2

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Comparison of F index (A), FF index (B) and F-FF ratio (C) among types of A, B, C, and D in males (n=7,776). Type A: WC <85 cm, Type B: WC ≥85 cm and no metabolic abnormalities, Type C: pre-metabolic syndrome, and Type D: Mets. (A) p-Values: comparison of A and B, p<0.0001; A and C, p<0.0001; A and D, p<0.0001; B and C, p<0.0001; B and D, p<0.0001; C and D, p<0.0001; overall p<0.0001. (B) p-Values: comparison of A and B, p<0.0001; A and C, p<0.0001; A and D, p<0.0001; B and C, p<0.0001; B and D, p<0.0001; C and D, p<0.0001; overall p<0.0001. (C) p-Values: comparison of A and B, p<0.0001; A and C, p<0.0001; A and D, p<0.0001; B and C, p<0.0001; B and D, p<0.0001; C and D, p<0.0001; overall p<0.0001.

Figure 3.

Figure 3

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Comparison of the percentage decrease in BMI and FF index among types of A, B, C, and D in males. (A) Comparison of percentage of BMI <23 kg/m2 among types of A, B, C, and D in males. (B) Comparison of percentage of FF index <18 kg/m2 (skeletal muscle mass loss) among types of A, B, C, and D in males. Type A: WC <85 cm, Type B: WC ≥85 cm and no metabolic abnormalities, Type C: pre-metabolic syndrome, and Type D: Mets. (A) p-Values: comparison of A and B, p<0.0001; A and C, p<0.0001; A and D, p<0.0001; B and C, p=0.0027; B and D, p<0.0001; C and D, p=0.0066; overall p<0.0001. (B) p-Values: comparison of A and B, p<0.0001; A and C, p<0.0001; A and D, p<0.0001; B and C, p=0.2065; B and D, p=0.2979; C and D, p=0.8235; overall p<0.0001.

Comparison of baseline parameters for types of A, B, C and D in females. In females, the median (IQR) age (years) for types of A, B, C, and D were 50 (43-58), 50 (44-55), 53 (46.25-61), and 60 (53-66), respectively (Figure 4A). The median (IQR) ALT (IU/l) for types of A, B, C, and D were 14 (11-18), 16 (13-23), 20 (15-30), and 24 (17-34) (Figure 4B). The median (IQR) eGFR (ml/min/1.73 m2) for types of A, B, C, and D were 72.7 (64.4-82.2), 72.9 (66.0-81.5), 71.9 (64.2-81.45), and 70.8 (62.5-80.1) (Figure 4C). The median (IQR) F index (kg/m2) for types of A, B, C, and D were 5.73 (4.55-7.12), 11.23 (9.71-12.78), 11.73 (10.16-14.03), and 12.01 (10.15-13.97) (Figure 5A). The median (IQR) FF index (kg/m2) for types of A, B, C, and D were 14.96 (14.38-15.51), 16.55 (16.01-16.99), 16.56 (16.08-17.06), and 16.52 (16.05-17.04) (Figure 5B). The median (IQR) F-FF ratio for types of A, B, C, and D were 0.388 (0.313-0.466), 0.674 (0.605-0.764), 0.708 (0.626-0.831), and 0.722 (0.633-0.832) (Figure 5C). The prevalence of subjects with BMI <23 kg/m2 for types of A, B, C, and D were 79.82%, 2.01%, 1.04% and 3.26% (Figure 6A). The prevalence of subjects with FF index <15 kg/m2 for types of A, B, C, and D were 52.02%, 0.86%, 1.67%, and 2.72% (Figure 6B).

Figure 4.

Figure 4

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Comparison of age (A), ALT (B) and eGFR (C) among types of A, B, C, and D in females (n=10121). Type A: WC <90 cm, Type B: WC ≥90 cm and no metabolic abnormalities, Type C: pre-metabolic syndrome, and Type D: Mets. (A) p-Values: comparison of A and B, p=0.3364; A and C, p<0.0001; A and D, p<0.0001; B and C, p<0.0001; B and D, p<0.0001; C and D, p<0.0001; overall p<0.0001. (B) p-Values: comparison of A and B, p<0.0001; A and C, p<0.0001; A and D, p<0.0001; B and C, p<0.0001; B and D, p<0.0001; C and D, p<0.0001; overall p<0.0001. (C) p-Values: comparison of A and B, p=0.6041; A and C, p=0.4239; A and D, p=0.0066; B and C, p=0.3505; B and D, p=0.0214; C and D, p=0.1228; overall p=0.0410.

Figure 5.

Figure 5

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Comparison of F index (A), FF index (B) and F-FF ratio (C) among types of A, B, C, and D in females (n=10121). Type A: WC <90 cm, Type B: WC ≥90 cm and no metabolic abnormalities, Type C: pre-metabolic syndrome, and Type D: Mets. (A) p-Values: comparison of A and B, p<0.0001; A and C, p<0.0001; A and D, p<0.0001; B and C, p=0.0007; B and D, p=0.0003; C and D, p=0.6849; overall p<0.0001. (B) p-Values: comparison of A and B, p<0.0001; A and C, p<0.0001; A and D, p<0.0001; B and C, p=0.4011; B and D, p=0.7635; C and D, p=0.6580; overall p<0.0001. (C) p-Values: comparison of A and B, p<0.0001; A and C, p<0.0001; A and D, p<0.0001; B and C, p<0.0001; B and D, p<0.0001; C and D, p=0.6245; overall p<0.0001.

Figure 6.

Figure 6

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Comparison of the percentage decrease in BMI and FF index among types of A, B, C, and D in females. (A) Comparison of percentage of BMI <23 kg/m2 among types of A, B, C, and D in females. (B) Comparison of percentage of FF index <15 kg/m2 (skeletal muscle mass loss) among types of A, B, C, and D in females. Type A: WC <90 cm, Type B: WC ≥90 cm and no metabolic abnormalities, Type C: pre-metabolic syndrome, and Type D: Mets. (A) p-Values: comparison of A and B, p<0.0001; A and C, p<0.0001; A and D, p<0.0001; B and C, p=0.3777; B and D, p=0.3561; C and D, p=0.0264; overall p<0.0001. (B) p-Values: comparison of A and B, p<0.0001; A and C, p<0.0001; A and D, p<0.0001; B and C, p=0.3731; B and D, p=0.0908; C and D, p=0.3404; overall p<0.0001.

Multivariate analyses of factors related to the FF index <18 kg/m2 in males and FF index <15 kg/m2 in females. Results for multivariate analyses of factors [age, BMI and our type classification (i.e., Type A, B, C, and D)] linked to the FF index <18 kg/m2 in males and FF index <15 kg/m2 in females are shown in Table II. In both males and females, as the disease progressed from Type A to D, the hazard ratio for skeletal muscle loss decreased progressively.

Table II. Multivariate analyses of factors (age, BMI and our type classification) linked to the FF index <18 kg/m2 in males and FF index <15 kg/m2 in females.

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BMI: Body mass index; CI: confidence interval.

Discussion

In Mets, obesity, especially visceral fat storage obesity, is upstream in the pathogenesis, and environmental factors, such as eating and exercise habits, are added to the genetic background, and a chain of each risk factors over time leads to the development of atherosclerotic and/or cerebrovascular diseases (21). However, as mentioned earlier, the precise relationship between Mets and somatic composition, especially skeletal muscle, is still partly unclear. In particular, Japanese are characterized by a higher number of non-obese steatotic liver patients compared to Westerners, with 20% of steatotic liver patients in Japan having non-obese steatotic liver (22). This has been pointed out to be related to a genetic polymorphism of PNPLA3 (23-25). In the present study, a large number of cases were classified into four groups according to risk factors for Mets, focusing on the association with somatic composition. To the best of our knowledge, there is no other such large study.

The results of the current research can be summarized as follows: In males, 1) age and ALT showed increasing trends with increasing risk factors for Mets, while eGFR showed decreasing trends; 2) F index, FF index, and F-FF ratio showed an increasing trend with increasing risk factors for Mets; 3) the proportion of subjects with BMI <23 kg/m2 decreased significantly with increasing risk factors for Mets; 4) The proportion of subjects with FF index <18 kg/m2 was significantly higher in Type A. Although there were no significant differences in the other groups, the hazard ratio for FF index <18 kg/m2 decreased significantly with increasing risk factors for Mets in the multivariate analysis. In females, 1) age and ALT showed an increasing trend and eGFR showed a decreasing trend with increasing risk factors for Mets; 2) F index, FF index, and F-FF ratio showed an increasing trend with increasing risk factors for Mets, but no significant difference was found between Type C and Type D; 3) The proportion of subjects with BMI <23 kg/m2 was significantly higher in Type A; 4) The proportion of subjects with FF index <15 kg/m2 was significantly higher in Type A. Although there were no significant differences among the other groups, the hazard ratio for FF index <15 kg/m2 decreased with increasing risk factors for Mets in the multivariate analysis as in the case of male. Therefore, it can be concluded that there is no difference in the results between male and female, but it should be noted that Type C and Type D are almost the same in terms of somatic composition among females. The F-FF ratio is a good indicator of somatic composition balance and is closely related to insulin resistance (26). It may be clinically important to note that somatic composition imbalance was associated with increased risk factors for Mets in our data. In other words, muscle mass increases with increasing risk factors for Mets, but fat mass increases more than muscle mass, and the F-FF index shows an increasing trend. A marked difference in F-FF ratio is observed in Type A and Type B for both male and female. It should be noted that when the WC exceeds the reference value for Mets, somatic composition balance deteriorates even in the absence of risk factors for Mets.

In this study, 1424 (18.3%) males were pre-metabolic and 1588 (20.4%) males had Mets, and 480 (4.7%) females were pre-metabolic and 368 (3.6%) females had Mets, which was a lower percentage than previously reported (30% of males and 10% of females had Mets) (1). One possible reason for these is that the area where our study was conducted was a relatively health-conscious area. It can also be said that people with high health awareness tend to take health examinations. It is also characteristic of the marked difference in somatic composition between sexes. However, recent studies have shown that some people without being obese have risks for health similar to Mets (27-30). Characteristics of the non-obese type of Mets include: 1) high total body fat mass, not just visceral fat, 2) lack of physical fitness, 3) low daily activity, 4) high triglyceride levels, and 5) low HDL cholesterol levels (31,32). In this study, the so-called non-obese Mets with BMI <23 kg/m2 was found in 98 (6.17%) males and 12 (3.26%) females. It should be noted that 86 (87.8%) of the males with non-obese Mets and five (41.7%) of the females with non-obese Mets had decreased muscle mass. These results are important when considering the relationship between the non-obese Mets and skeletal muscle mass. In subjects with non-obese Mets, body composition analysis may be mandatory. It has also been reported that Mets is more common in non-obese middle-aged and older adults with sarcopenia (27).

Limitations of the current research include the fact that it was a retrospective study at a single institution, and the lack of data on grip strength, making it difficult to determine sarcopenia (33). The subjects’ status on medications (e.g., antipsychotics) that may elicit Mets was unknown, potentially creating bias. In addition, our baseline features between sexes were not well balanced. However, the present study was based on health examination data from a large number of health checkup recipients, and the results of this study revealed that Mets and somatic composition are closely related, and that somatic composition balance worsens as risk factors for Mets increase. In conclusion, somatic composition and its balance as assessed by fat mass and fat-free mass well reflects the severity of Mets. Early intervention for Mets may ameliorate the somatic composition imbalance.

Conflicts of Interest

The Authors have no conflicts of interest to declare in relation to this study.

Authors’ Contributions

M.M, A.F. and H.N. wrote, reviewed, and revised the article. The other Authors collected clinical data. All Authors approved the final version of the article.

Acknowledgements

The Authors sincerely thank all medical staff in the department of OMPU hospital for their significant support.

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