(2021) 13:44
Yokokawa et al. Diabetol Metab Syndr
https://doi.org/10.1186/s13098-021-00646-3

Diabetology &Metabolic Syndrome
Open Access

RESEARCH

An association between visceralor subcutaneous fat accumulation and diabetes
mellitus among Japanese subjects
Hirohide Yokokawa1,2*, Hiroshi Fukuda1, Mizue Saita1, Kento Goto1, Tengen Kaku1, Taiju Miyagami1,
Yuichi Takahashi1, Chieko Hamada1, Teruhiko Hisaoka1 and Toshio Naito1

Abstract
Background: The impact of subcutaneous fat accumulation remains controversial. This study assessed the association between visceral or subcutaneous fat area (VFA and SFA, respectively) and diabetes mellitus (DM) among
Japanese subjects.
Methods: This was a cross-sectional study involving 1907 eligible participants (men, 1050; women, 857) who participated in a voluntary health check-up conducted at Juntendo University Hospital from January 2017 to December
2018, in Tokyo, Japan. Associations between VFA or SFA quartiles and DM were identified using adjusted odds ratios(AORs) and 95% confidence intervals (CIs) with multivariable logistic regression analysis adjusted for confounders.
Receiver operating characteristic (ROC) curve analysis was used to assess appropriate cut-off values of VFA or SFA.
Results: Multivariate analyses showed that Q4 (≥ 125 ­cm2) of VFA was significantly positively associated with DM
compared to Q1 (< 65 ­cm2) (AOR = 1.94, 95% CI 1.02–3.71), whereas there was no association between SFA and DM
in men. Among women, Q4 (≥ 85 ­cm2) of VFA was significantly positively associated with DM compared to Q1 (< 30­cm2) (Q4, AOR = 6.15, 95% CI 1.65–22.99). Also, Q3 and Q4 (≥ 135 ­cm2) of SFA were significantly positively associatedwith DM compared to Q1 (< 90 ­cm2) (Q3, AOR = 5.64, 95% CI 1.21–26.25; Q4, AOR = 7.81, 95% CI 1.71–35.65). The
appropriate cut-off value of VFA in men was 101.5 ­cm2. Those of VFA and SFA in women were 72.5 ­cm2 and 165.3 ­cm2,
respectively.
Conclusions: Our results suggest the importance of considering SFA as well as VFA, especially in women, for primaryand secondary prevention of DM.
Keywords: Lifestyle‐related disorder, Prevention, Epidemiology, Subcutaneous fat, Visceral fat, Diabetes mellitus,
Metabolic syndrome
Introduction
Type 2 diabetes mellitus (DM) has become a highly prevalent disease worldwide as changing lifestyles have led
to reduced physical activity and increased obesity, and
it is now recognized as major public health burden. The*Correspondence: yokokawa@pa3.so-net.ne.jp
2
Department of General Medicine, Juntendo University Schoolof Medicine, Hongo 2‑1‑1, Bunkyo‑ku, Tokyo 113‑8421, Japan
Full list of author information is available at the end of the article

prevalence of both type 2 DM and obesity has increased
worldwide over the last century, not only in developed
countries but also developing countries, sometimes coexisting with undernutrition [1]. It was estimated that in2017 there were 451 million (age 18–99 years) people
with diabetes worldwide. These figures are expected toincrease to 693 million by 2045, and it is estimated that
almost half of all people (49.7%) living with diabetes areundiagnosed. In 2017, approximately 5 million deaths© The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing,
adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) andthe source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material
in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material
is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds thepermitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​
mmons.​org/​licen​ses/​by/4.​0/. The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Yokokawa et al. Diabetol Metab Syndr(2021) 13:44

worldwide in persons in the 20–99 years age range were
attributed to diabetes [1].
Obesity, especially abdominal obesity, is a well-known
underlying risk factor for the development of diabetes [2]. Visceral fat accumulation, which is a key featureof abdominal obesity, is in an upstream position in thepathogenesis and development of metabolic syndrome(Mets) with clustering of DM, dyslipidemia, and hypertension [2]. In particular, several epidemiologic studies
have shown that excess visceral fat area (VFA) is a wellknown risk factor for the development of DM and onsetof cardiovascular disorders [2, 3]. Therefore, measurement of visceral fat accumulation is important to assess
subjects with high risk of DM and other cardiovasculardisorders [2–4]. As for VFA cut-off values for Mets, there
are several differences associated with age distribution,
the number of study participants, degree of obesity, andethnicity [2–5]. In Japan, visceral fat accumulation is generally recognized as a waist circumference (WC) of over
85 cm in men and over 90 cm in women, which correspond to a VFA of 100 c­ m2 in an abdominal computed
tomography (CT) scan at the umbilical level [3].
However, the impact of subcutaneous fat accumulation
remains controversial. Several previous reports indicateda protective effect for glucose metabolism [6, 7]. In contrast, there is some evidence indicating a positive association between subcutaneous fat accumulation and adverse
cardiometabolic risk factors, including diabetes [8, 9].
There are differences between subcutaneous adipose tissue (SCAT) and visceral adipose tissue (VAT) present in
the abdominal cavity [10], including anatomic, cellular,
molecular, physiologic, clinical, and prognostic differences. Anatomically, VAT is present mainly in the mesentery and omentum and drains directly through the portal
circulation to the liver. Compared with SCAT, VAT ismore cellular, vascular, and innervated, contains a larger
number of inflammatory and immune cells, has less preadipocyte differentiating capacity, and has a greater percentage of large adipocytes [10].
The present study assessed the association between
DM and VFA and subcutaneous fat area (SFA) estimatedby CT scans in Japanese subjects.

Subjects and methods
This was a cross-sectional study that screened 2885
Japanese adults who participated in a voluntary healthcheckup conducted at Juntendo University Hospital fromJanuary 2017 to December 2018, in Tokyo, Japan. A totalof 978 subjects were excluded due to missing data, and 1
subject was excluded due to a duplicate case. Ultimately,1907 participants were included in the present study(men, 1050; women, 857).

Page 2 of 10

Variables

Height, weight, body mass index (BMI), and WC were
measured with participants in the standing position. BMI
was calculated by dividing body weight (kg) by heightsquared ­(m2). Mean systolic blood pressure (SBP) anddiastolic blood pressure (DBP) were calculated from themeans of two upper-arm blood pressure measurements
taken from participants who had been seated for at least
5 min. Serum levels of total cholesterol (mg/dl; TC),
high-density-lipoprotein cholesterol (mg/dl; HDL-C),
low-density-lipoprotein cholesterol (mg/dl; LDL-C), andtriglycerides (mg/dl; TGs) were also measured. LDL-C
was estimated using the Friedewald equation [(TC) –(HDL-C) – (TG/5)] [11]. Hemoglobin A1c (HbA1c) levels
were determined by high-performance liquid chromatography using an automated analyzer. Serum uric acid (mg/dl) and high-sensitivity C-reactive protein (mg/dl) werealso measured.
Participants were asked to complete a self-administeredquestionnaire that addressed healthy lifestyle characteristics based on Breslow’s seven health practices [12]. These
characteristics can be used to assess lifestyle health, andstrong associations have been found between healthy
lifestyle practices and successful blood pressure control
among patients with hypertension [13]. Healthy lifestyle
items in the questionnaire included non-daily alcohol
consumption, non-smoker status, exercise frequency of
two or more times per week, BMI of 18.5–24.9 kg/m2,
adequate sleep duration, daily breakfast consumption,and no snacking between meals [12, 13].
From the self-administered questionnaire, we alsocollected information on present medical history ofcomorbidities, such as hypertension, DM, dyslipidemia,
hyperuricemia, cardiovascular disease, and cerebrovascular disease. If participants answered as having thesecomorbidities, we registered the participants with a medical history of these comorbidities (present).
CT measurement of abdominal adipose tissue

Abdominal fat area, including VFA and SFA, was measured from CT scans taken at the level of the umbilicus
while in the supine position and during late expirationaccording to Japanese guidelines for obesity treatment[14]. An Aquilion ONE/GENESIS Edition CT scanner(Canon Medical Systems Corp., Tokyo, Japan) was used
to obtain CT scans. We manually traced the inner aspectof the whole trunk, muscular layer, and the abdominal
wall. In the computerized method using commercial
software designed for quantification of VFA and SFA(Canon Medical Systems Corp.), fat was defined as any
tissue with a threshold of − 150 to − 70 Hounsfield units.
Abdominal VFA was defined as the fat area enclosed

Yokokawa et al. Diabetol Metab Syndr(2021) 13:44

by the inner aspect of the abdominal wall, and SFA wasdefined as the fat area enclosed by the outer aspect of theabdominal wall [15, 16]. The method is widely used anda previous study indicated that CT and magnetic-resonance imaging (MRI) may yield different absolute valuesof fat areas (especially visceral fat) but that the ranking ofindividuals on the basis of their fat areas will be similar
by both methods [17, 18].
Definition of lifestyle‐related disorders

Lifestyle-related disorders were defined according to thefollowing criteria: (1) DM, high fasting plasma glucose(≥ 126 mg/dl) or HbA1c (≥ 6.5%) or taking antidiabetes
medications; (2) hypertension, increased blood pressure(SBP ≥ 140 mmHg or DBP ≥ 90 mmHg) or taking antihypertensive medications; (3) dyslipidemia, increased
TG level (≥ 150 mg/dl) or LDL-C level (≥ 140 mg/dl) or
reduced HDL-C level (< 40 mg/dl) or taking dyslipidemia
medications [3].
Statistical analysis

Results are presented as mean ± standard deviation (SD) for continuous variables or prevalence (%)
for categorical variables by sex. VFA and SFA quartiles were defined by sex [men; VFA ­(cm2): Q1 < 65,
65 ≤ Q2 < 95, 95 ≤ Q3 < 125, 125 ≤ Q4: SFA ­(cm2): Q1 < 85,85 ≤ Q2 < 115, 115 ≤ Q3 < 155, 155 ≤ Q4], [women; VFA­(cm2): Q1 < 30, 30 ≤ Q2 < 60, 60 ≤ Q3 < 85, 85 ≤ Q4: SFA­(cm2): Q1 < 90, 85 ≤ Q2 < 135, 135 ≤ Q3 < 190, 190 ≤ Q4].
Associations between VFA or SFA quartiles and DM
were identified using adjusted odds ratios (AORs) and
95% confidence intervals (CIs) with multivariable logistic regression analysis adjusted for age (years), dyslipidemia (yes), hypertension (yes), hyperuricemia (yes),
alcohol consumption (non-daily drinker), and smoking(non-smoker).
Receiver operating characteristic (ROC) curve analysis
was used to assess appropriate cut-off values of VFA and
SFA, and we estimated the area under the curve (AUC)
and measured the sensitivity and specificity for DM inboth sexes. All statistical analyses were performed using
the Statistical Package for Social Sciences, version 22(SPSS Inc., Chicago, IL, USA).
The research protocol was reviewed and approved by
the Ethics Committee of the Juntendo University Hospital (no. 18-297), and written informed consent was
obtained from all participants.

Results
The mean age (SD) of non-DM and DM was 59.9 (12.3)
and 65.7 (8.9) years in men and 60.2 (12.9) and 66.5 (9.4)
years in women, respectively (Table 1). Participants withDM had significantly higher mean BMI, WC, and VFA

Page 3 of 10

compared to non-DM participants. The mean SFA of DM
participants was significantly higher than that of nonDM participants among women, whereas no statisticallysignificant difference was observed among men.
The proportions of hypertension and SBP were significantly higher in DM compared to non-DM participantsin both sexes. Mean HDL-C was significantly lower and
TGs higher in DM compared to non-DM participants
among both sexes.
Table 2 shows the results of the multivariable logistic regression analysis among men. Q4 (≥ 125 ­cm2) of
VFA was significantly positively associated with DM
compared to Q1 (Q4, AOR = 1.94, 95% CI 1.02–3.71).
There was no association between SFA and DM. Among
women, Q4 (≥ 85 ­cm2) of VFA was significantly positively
associated with DM compared to Q1 (Q4, AOR = 6.15,
95% CI 1.65–22.99) (Table 3). In addition, Q3 and Q4of SFA were significantly positively associated with DM
compared to Q1 (Q3, AOR = 5.64, 95% CI 1.21–26.25;
Q4, AOR = 7.81, 95% CI 1.71–35.65).
The appropriate VFA cut-off value, sensitivity, specificity, and AUC in men were 101.5 ­cm2, 0.61, 0.59, and0.66, respectively (Fig. 1) and 72.5 ­cm2, 0.74, 0.78, and0.66, respectively, in women (Fig. 2a). The appropriate SFA cut-off value, sensitivity, specificity, and AUC inwomen were 165.3 c­ m2, 0.66, 0.60, and 0.66, respectively(Fig. 2b).

Discussion
The present cross-sectional study results showed that
VFA ≥ 125 ­cm2 was significantly positively associated with DM compared to VFA < 65 ­cm2 in men, and
VFA ≥ 85 ­cm2 was significantly positively associated with
DM compared to < 30 ­cm2 in women after adjusting forconfounders. SFA ≥ 135 ­cm2was significantly positively
associated with DM compared to SFA < 90 ­cm2 in women,
whereas no association was observed in men. VFA wasclosely and positively associated with DM in both sexes,
and appropriate estimated cut-off points might be 101.5­cm2 in men and 72.5 ­cm2 in women for DM, respectively.
SFA was also associated with DM only in women, suggesting a cut-off value of 165.3 ­cm2. To the best of ourknowledge, analyses of the association between DM and
VFA and SFA are limited.
Visceral fat accumulation is widely regarded as a risk
factor for cardiovascular diseases, including DM. Mets
is a metabolic condition that predicts individuals who
are likely to be affected by cardiovascular disorders via
insulin resistance [3]. One major feature of Mets is visceral fat accumulation, which is closely related to insulin
resistance. Visceral fat accumulation is generally recognized as a WC ≥ 85 ­cm2 in men and ≥ 90 ­cm2 in women,
which correspond to a VFA of 100 ­cm2 in an abdominal

59.9 (12.3)

669 (77.1)

410 (82.8)

148 (30.6)

524 (60.4)

382 (76.9)403 (80.1)

341 (77.7)

Alcohol consumption(non-daily
drinker)

Smokingbehavior(nonsmoker)

Exercisefrequency(≥ 2 times per
week)

Body massindex 18.5–
24.9 kg/m2

Adequate
sleep duration (yes)Breakfast(everymorning)

Snackbetweenmeals (no)Healthy lifestylecharacteristics< 0.01

0.37

0.34

0.14

< 0.01

0.58

0.54

0.50

0.40

< 0.01< 0.01< 0.01331 (75.6)

404 (77.8)

386 (77.8)

560 (69.9)

133 (28.1)

468 (90.7)

722 (90.0)

143.9 (78.1)

60.6 (37.7)

81.0 (9.7)

21.8 (3.4)

60.2 (12.9)

24 (68.6)

33 (86.8)

27 (77.1)

30 (54.5)

11 (31.4)

36 (97.3)

54 (98.2)

185.9 (81.3)

97.8 (47.6)

88.0 (10.0)

24.5 (3.8)

66.5 (9.4)

DM(n = 55 )

0.36

0.19

0.93

0.02

0.67

0.17

0.04

< 0.01< 0.01< 0.01< 0.01< 0.01(2021) 13:44

81 (73.6)

104 (83.9)

118 (83.1)

88 (48.4)

33 (28.0)

99 (80.5)136 (74.7)

126.0 (59.0)

Subcutaneous 122.1 (56.5)
fat are ­(cm2)

Visceral fat
area ­(cm2)112.1 (50.1)

89.5 (9.6)

Waist circum- 86.7 (8.4)
ference (cm)

94.5 (46.5)

25.2 (3.6)

24.3 (3.1)

Body massindex (kg/m2)

65.7 (8.9)

Non-DM(n = 802)

Non-DM(n = 868)

Anthropometric measurements

Age (years)

Mean (SD) or n (%)

Mean (SD) or n (%)
DM(n = 182)

Women (n = 857)

Men (n = 1050)

Table 1 Sex-specific characteristics (n = 1907)

Yokokawa et al. Diabetol Metab Syndr
Page 4 of 10

74.8 (10.5)

68.1 (10.1)

Diastolicbloodpressure(mmHg)

Heart rate
(beats permin)

1.9 (0.9)

2.1 (1.5)

C-peptide

Homeostasis
modelassessmentof insulin
resistance369 (42.5)

2.1 (0.6)

Immuno-reac- 8.4 (5.5)
tive insulin

Dyslipidemia(yes)10.0 (5.7)

5.7 (0.3)

Hemoglobin
A1c (%)

90 (49.5)

3.4 (2.1)

7.0 (0.8)

98.9 (8.8)

135.3 (23.3)

69.8 (11.0)

74.1 (11.4)

126.5 (15.1)

77 (42.3)

29 (28.7)

Fasting blood
glucose(mg/dl)Diabetesrelated items

122.3 (14.0)

234 (27.0)

116 (28.3)

0.93

0.09

< 0.010.21< 0.01< 0.01< 0.010.04

0.38< 0.01< 0.01279 (348)

1.7 (1.3)

1.5 (0.6)

7.2 (5.3)

5.7 (0.3)

93.9 (8.9)

72.2 (10.8)

70.5 (10.6)

117.0 (15.6)

147 (18.3)

149 (39.7)

Non-DM(n = 802)

Non-DM(n = 868)

Systolic bloodpressure(mmHg)

Hypertension(yes)

Proportion ofparticipants
with 6 or
7 totalnumber ofhealthy lifestyle items

Mean (SD) or n (%)

Mean (SD) or n (%)
DM(n = 182)

Women (n = 857)

Men (n = 1050)

Table 1 (continued)

25 (5.5)

3.5 (2.1)

2.3 (0.7)

11.3 (6.9)

6.8 (0.8)130.1 (27.1)

74.0 (13.0)

74.4 (9.5)

126.2 (13.0)

20 (36.4)

12 (1.4)

DM(n = 55 )0.11< 0.01< 0.01< 0.01< 0.01< 0.010.25< 0.01< 0.01< 0.01

0.86

Yokokawa et al. Diabetol Metab Syndr(2021) 13:44
Page 5 of 10

114.4 (28.5)

124.1 (82.8)

224 (25.8)

Low-densitylipoproteincholesterol(mg/dl)Triglycerides(mg/dl)Hyperuricemia(yes)

0.12 (0.28)

29 (3.3)

17 (2.0)

Heart

Brain

Organ damage/cardiovascular disease

High-sensitivity
C-reactive
protein (mg/dl)

Uric acid (mg/ 6.1 (1.2)
dl)

52.2 (12.0)

56.2 (14.6)

High-densitylipoproteincholesterol(mg/dl)1 (0.5)

14 (7.7)

0.14 (0.26)

5.9 (1.2)

42 (23.2)

140.8 (91.3)

106.4 (29.4)

190.4 (36.1)< 0.010.34< 0.01

0.21

0.01

0.46

0.02

< 0.01< 0.01

16 (2.0)

17 (2.1)

0.10 (0.39)

4.7 (1.1)

17 (2.1)

90.0 (49.3)

118.8 (28.8)

68.5 (15.4)

215.3 (33.4)

Non-DM(n = 802)

Non-DM(n = 868)

Total choles201.2 (32.4)
terol (mg/dl)

Mean (SD) or n (%)

Mean (SD) or n (%)
DM(n = 182)

Women (n = 857)

Men (n = 1050)

Table 1 (continued)

0 (0.0)3 (5.5)0.21 (0.50)

5.4 (1.3)

7 (12.7)

121.4 (87.0)

112.3 (27.3)

59.2 (14.6)

202.5 (37.8)

DM(n = 55 )

0.62

0.11

0.06

< 0.01< 0.01< 0.010.11< 0.01< 0.01

Yokokawa et al. Diabetol Metab Syndr(2021) 13:44
Page 6 of 10

Yokokawa et al. Diabetol Metab Syndr(2021) 13:44

Page 7 of 10

Table 2 Odds ratios and 95% confidence intervals for diabetes mellitus among men (logistic regression analysis) (n = 1050)
NumberUnivariate
OR

Multivariable
95% CI

AOR

P

95% CIP

0.71

Visceral fat area ­(cm2)
Q1 < 65

252

Ref

65 ≤ Q2 < 95

285

1.26

0.75–2.09

0.38

1.13

0.60–2.13

236

1.86

1.13–3.08

0.02

1.67

0.88–3.16

0.11

125 ≤ Q4

274

2.44

1.52–3.93< 0.01

1.94

1.02–3.71

0.04

Q1 < 85282

Ref

85 ≤ Q2 < 115

236

0.87

0.55–1.38

0.55

0.69

0.37–1.29

0.24

270

0.83

0.53–1.31

0.43

0.97

0.54–1.73

0.91

155 ≤ Q4

262

1.10

0.71–1.68

0.68

1.16

0.83–2.58

0.19

95 ≤ Q3 < 125Ref

Subcutaneous fat area ­(cm2)115 ≤ Q3 < 155Ref

OR: odds ratio; AOR: adjusted odds ratio; CI: confidence interval
Multivariable analysis was adjusted for visceral/subcutaneous fat area quartiles, age (years), dyslipidemia (yes), hypertension (yes), hyperuricemia (yes), alcohol
consumption (non-daily drinker), and smoking (non-smoker)

Table 3 Odds ratios and 95% confidence intervals for diabetes mellitus among women (logistic regression analysis) (n = 857)
NumberUnivariate
OR

Multivariable
95% CI

AOR

P

95% CIP

2

Visceral fat area ­(cm )Q1 < 30205

Ref

30 ≤ Q2 < 60

237

1.31

0.36–4.69

0.68

1.05

0.23–4.87

0.95

192

3.35

1.06–10.57

0.04

2.35

0.56–9.84

0.24

219

8.92

3.01–25.65< 0.01

6.15

1.65–22.99< 0.0160 ≤ Q3 < 8585 ≤ Q4

Ref

Subcutaneous fat area ­(cm2)
Q1 < 90219

Ref

90 ≤ Q2 < 135

195

1.52

0.52–4.46

0.45

2.23

0.40-12.54

0.36

222

2.76

1.06–7.18

0.04

5.64

1.21–26.25

0.03

221

4.53

1.82–11.27< 0.01

7.81

1.71–35.65< 0.01135 ≤ Q3 < 190

190 ≤ Q4

Ref

OR: odds ratio; AOR: adjusted odds ratio; CI: confidence interval
Multivariable analysis was adjusted for visceral/subcutaneous fat area quartiles, age (years), dyslipidemia (yes), hypertension (yes), hyperuricemia (yes), alcohol
consumption (non-daily drinker), and smoking (non-smoker)

CT scan at the umbilical level [3]. Visceral fat accumulation is also known to be an independent risk factor for
type 2 diabetes. A longitudinal study that determined
the optimal cut-off value of VFA for predicting type 2
diabetes among 13,004 Koreans reported values of 118.8­cm2 in men and 82.6 c­ m2 in women [4]. Another longitudinal survey that followed Japanese Americans for 10
years reported a baseline intra-abdominal fat area (IFA)of 102.7 ­cm2 in the incident diabetes group and 74.3 ­cm2in those without incident diabetes, respectively. Also, an
increase of 1 SD in IFA was associated with a 1.65-foldincrease in the odds of diabetes over 10 years (OR = 1.65,
95% CI 1.21–2.25) after adjusting for the above covariates [19]. These previous study results are closely similar to our results. Thus, sex-specific reference values

for visceral fat accumulation such as that men with a
VFA ≥ 100 ­cm2 and women with a VFA ≥ 80 ­cm2 should
be considered to prevent and manage type 2 diabetes.
Our results showed that SFA was significantly positively associated with DM in women, whereas no association was observed in men. The role of subcutaneous
fat in cardiovascular risk remains controversial. The
Shanghai Nicheng Cohort Study, which was conductedamong 12,137 Chinese adults aged 45–70 years, reported
multivariable-adjusted ORs and 95% CIs of newly diagnosed diabetes per 1-standard deviation increase in SFA
and VFA of 1.29 (1.19–1.39) and 1.61 (1.49–1.74) in men
and 1.10 (1.03–1.18) and 1.56 (1.45–1.67) in women,
respectively [6]. However, the association between SFA
and newly diagnosed diabetes disappeared in men andYokokawa et al. Diabetol Metab Syndr(2021) 13:44

Fig. 1 Analysis of visceral fat area receiver operating characteristic
curve for diabetes mellitus in men. AUC: area under the curve

was reversed in women (OR 0.86 [95% CI 0.78–0.94])
after additional adjustment for BMI and VFA [6]. A study
that surveyed 3001 participants from the Framingham
Heart Study reported that multivariable-adjusted general linear regression analyses of SAT and VAT showedsignificant associations with blood glucose in both sexes

Page 8 of 10[age-adjusted Pearson correlation coefficients; 0.23 for
SAT and 0.34 for VAT in women (P < 0.001), 0.12 for SAT
and 0.19 for VAT in men (P < 0.001)]. In addition, themagnitude of association between VAT and all risk factors was greater for women than men, and weaker sex
differences were observed for SAT [8]. The Jackson Heart
Study, which surveyed 2477 African Americans, reported
that abdominal VAT and SAT were both associated withadverse cardiometabolic risk factors, including diabetes,
and the effect size of VAT in women was larger than thatof SAT [fasting plasma glucose, 5.51 ± 1.0 vs. 3.36 ± 0.9;
diabetes, 1.82 (1.6–2.1) vs. 1.58 (1.4–1.8); and Mets,
3.34 (2.8–4.0) vs. 2.06 (1.8–2.4), respectively; P < 0.0001
for difference between VAT and SAT] [9]. The possible
mechanism of the association between diabetes and SAT
as well as VAT is insulin resistance. To date, numerous
studies have assessed the association between excess visceral fat accumulation and insulin resistance. Regarding
SAT, several previous surveys indicated a positive association between excess subcutaneous fat accumulation andinsulin resistance. A Japanese study that surveyed 912
non-diabetic participants reported that subjects in higher
tertiles of SAT and VAT had significantly higher HOMAIR and lower Matsuda ISI levels (P < 0.001) [20]. Excess
SAT accumulation may cause insulin resistance and contribute to glucose intolerance as well as VAT. Therefore,
it is necessary to consider adiposity, including SAT and
VAT, to better maintain body composition.

Fig. 2 Analysis of visceral fat area (a) and subcutaneous fat area (b) receiver operating characteristic curves for diabetes mellitus in women. AUC:
area under the curve

Yokokawa et al. Diabetol Metab Syndr(2021) 13:44

In regard to the impact of SAT, a sex difference wasobserved. There is little evidence available to explain
the difference. The Jackson Heart Study, which involved
2,799 African Americans, reported a direct association
between SAT and adiponectin (β = 0.18; P = 0.002) thatpersisted when controlling for BMI and WC amongmen, whereas the significance was borderline among
women (β = 0.05; P = 0.05) [21]. Although the evidence
is limited to explain the sex difference, it is possiblethat adiponectin may contribute. Further analyses are
required to assess the sex difference.
Our study has several limitations. First, it was susceptible to selection bias, as the participants consistedof those who received voluntary medical check-ups ata single medical institution. As such, these participants
may be inherently more aware of their health behaviors relative to the general population. In addition, 978among 2885 screened participants were excluded due
to missing data (33.9%). It is necessity to minimize theexclusion rate. Second, this was a cross-sectional observational study, thus limiting consideration of the causal
relationship between SFA/VFA and DM. Further analyses that include data from a more diverse cohort arethus needed. Third, some key data regarding items suchas details of diabetes medications, eating behaviors,and nutritional status were not collected. Future prospective studies including these data are also needed.
In conclusion, the results of the present crosssectional study indicate that VFA ≥ 125 ­cm2 in men
is significantly positively associated with DM compared to VFA < 65 ­cm2, and VFA ≥ 85 ­cm2 in womenis significantly positively associated with DM compared to VFA < 30 ­cm2 after adjusting for confounders. SFA ≥ 135 ­cm2 in women is significantly positively
associated with DM compared to SFA < 90 ­cm2, butno association was observed in men. Appropriate estimated VFA cut-off points for DM are 101.5 c­ m2 in men
and 72.5 c­ m2 in women, respectively. As SFA was associated with DM only in women, the appropriate estimated cut-off is 165.3 ­cm2. Our results suggest that it isimportant to consider both SFA and VFA, especially inwomen, for primary and secondary prevention of DM.
Acknowledgements
The authors thank all participants who underwent the voluntary medical
check-ups and the data collection staff at Juntendo University Hospital.
Authors’ contributions
HY, HF, and TN participated in the design of the study. HY, HF, MS, KG, TK, TM,
YT, CH, and YH participated in data collection and revised the manuscript.
HY, HF, and TN conceived the study, participated in its design, and revised themanuscript. HY participated in analysis of the data and revised the manuscript.
All authors read and approved the final manuscript.
Funding
Not applicable.

Page 9 of 10

Availability of data and materials
The ethics committee imposed restrictions to data access and sharing. Individuals who wish to access our data must obtain further permission from thecommittee, which can be achieved by contacting the corresponding author.

Declarations
Ethics approval and consent to participate
The research protocol was reviewed and approved by the Ethics Committee of
the Juntendo University Hospital (no. 18–297), and written informed consent
was obtained from all participants.
Consent for publication
Not applicable.
Competing interests
The authors have no conflicts of interest to declare.
Author details
1
Department of General Medicine, Juntendo University Faculty of Medicine,
Hongo 2‑1‑1, Bunkyo‑ku, Tokyo 113‑8421, Japan. 2 Department of General
Medicine, Juntendo University School of Medicine, Hongo 2‑1‑1, Bunkyo‑ku,
Tokyo 113‑8421, Japan.
Received: 17 November 2020 Accepted: 27 February 2021

References
1. Cho NH, Shaw JE, Karuranga S, Huang Y, da Rocha Fernandes JD,
Ohlrogge AW, et al. IDF diabetes atlas: global estimates of diabetes
prevalence for 2017 and projections for 2045. Diabetes Res Clin Pract.
2018;138:271–81.
2. Després JP, Lemieux I. Abdominal obesity and metabolic syndrome.
Nature. 2006;444:881–7.
3. Matsuzawa Y. Therapy insight: adipocytokines in metabolic syndrome
and related cardiovascular disease. Nat Clin Pract Cardiovasc Med.
2006;3:35–42.
4. Kim EH, Kim HK, Bae SJ, Lee MJ, Hwang JY, Choe J, et al. Gender differences of visceral fat area for predicting incident type 2 diabetes in
Koreans. Diabetes Res Clin Pract. 2018;146:93–100.
5. Bays HE. Adiposopathy is “sick fat” a cardiovascular disease? J Am Coll
Cardiol. 2011;57:2461–73.
6. Chen P, Hou X, Hu G, Wei L, Jiao L, Wang H, et al. Abdominal subcutaneous adipose tissue: a favorable adipose depot for diabetes? Cardiovasc
Diabetol. 2018;17:93.
7. Hou X, Chen P, Hu G, Wei L, Jiao L, Wang H, et al. Abdominal subcutaneous fat: a favorable or nonfunctional fat depot for glucose metabolism inChinese adults? Obesity. 2018;26:1078–87.
8. Fox CS, Massaro JM, Hoffmann U, Pou KM, Maurovich-Horvat P, Liu CY,
et al. Abdominal visceral and subcutaneous adipose tissue compartments: association with metabolic risk factors in the Framingham Heart
Study. Circulation. 2007;116:39–48.
9. Liu J, Fox CS, Hickson DA, May WD, Hairston KG, Carr JJ, Taylor HA. Impactof abdominal visceral and subcutaneous adipose tissue on cardiometabolic risk factors: the Jackson Heart Study. J Clin Endocrinol Metab.
2010;95:5419–26.
10. Ibrahim MM. Subcutaneous and visceral adipose tissue: structural andfunctional differences. Obes Rev. 2010;11:11–8.
11. Warnick GR, Knopp RH, Fitzpatrick V, Branson L. Estimating low-density
lipoprotein cholesterol by the Friedewald equation is adequate for classifying patients on the basis of nationally recommended cut points. Clin
Chem. 1990;36:15–9.
12. Belloc NB, Breslow L. Relationship of physical health status and healthpractices. Prev Med. 1972;1:409–21.
13. Yokokawa H, Goto A, Sanada H, Watanabe T, Felder RA, Jose PA, et al.
Achievement status toward goal blood pressure levels and healthy
lifestyles among Japanese hypertensive patients; Cross sectional survey

Yokokawa et al. Diabetol Metab Syndr

14.
15.
16.
17.
18.

(2021) 13:44

results from Fukushima Research of Hypertension (FRESH). Intern Med.
2011;50:1149–56.
Committee to Evaluate Diagnostic Standards for Metabolic Syndrome.
Definition and the diagnostic standard for metabolic syndrome. Nihon
Naika Gakkai Zasshi. 2005;94:794–809. (Japanese).
Oike M, Yokokawa H, Fukuda H, Haniu T, Oka F, Hisaoka T, Isonuma H.
Association between abdominal fat distribution and atheroscleroticchanges in the carotid artery. Obes Res Clin Pract. 2014;8:e448-58.
Sato F, Maeda N, Yamada T, Namazui H, Fukuda S, Natsukawa T, et al. Association of epicardial, visceral, and subcutaneous fat with cardiometabolic
diseases. Circ J. 2018;82:502–8.
Yoshizumi T, Nakamura T, Yamane M, Islam AH, Menju M, Yamasaki K,
Arai T, Kotani K, Funahashi T, Yamashita S. Abdominal fat: standardized
technique for measurement at CT. Radiology. 1999;211:283–6.
Seidell JC, Bakker CJ, van der Kooy K. Imaging techniques for measuring
adipose-tissue distribution–a comparison between computed tomography and 1.5-T magnetic resonance. Am J Clin Nutr. 1990;51:953–7.

Page 10 of 10

19. Wander PL, Boyko EJ, Leonetti DL, McNeely MJ, Kahn SE, Fujimoto WY.
Change in visceral adiposity independently predicts a greater risk ofdeveloping type 2 diabetes over 10 years in Japanese Americans. Diabetes Care. 2013;36:289–93.
20. Oka R, Yagi K, Sakurai M, Nakamura K, Nagasawa SY, Miyamoto S, et al.
Impact of visceral adipose tissue and subcutaneous adipose tissue
on insulin resistance in middle-aged Japanese. J Atheroscler Thromb.
2012;19:814–22.
21. Bidulescu A, Liu J, Hickson DA, Hairston KG, Fox ER, Arnett DK, et al. Gender differences in the association of visceral and subcutaneous adipositywith adiponectin in African Americans: the Jackson Heart Study. BMC
Cardiovasc Disord. 2013;22(13):9.

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

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