Diabetes Research and Clinical Practice
Volume 95, Issue 1 , Pages 19-24, January 2012

Which metabolic syndrome criteria best predict the presence of non-alcoholic fatty liver disease?

  • Hyun Il Seo

      Affiliations

    • Division of Gastroenterology, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
    • ,
  • Yong Kyun Cho

      Affiliations

    • Division of Gastroenterology, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
    • Corresponding Author InformationCorresponding author at: Kangbuk Samsung Hospital, 108 Pyungdong, Jongnogu, 110-746 Seoul, Republic of Korea. Tel.: +82 2 2001 2080; fax: +82 2 2001 2610.
    • ,
  • Won Young Lee

      Affiliations

    • Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
    • ,
  • Eun Jung Rhee

      Affiliations

    • Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
    • ,
  • Ki Chul Sung

      Affiliations

    • Cardiology, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
    • ,
  • Bum Soo Kim

      Affiliations

    • Cardiology, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
    • ,
  • Byung Ho Son

      Affiliations

    • Department of Surgery, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
    • ,
  • Jun Ho Shin

      Affiliations

    • Department of Surgery, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
    • ,
  • Kwan Joong Joo

      Affiliations

    • Urology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
    • ,
  • Hyun Pyo Hong

      Affiliations

    • Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
    • ,
  • Seoung Wan Chae

      Affiliations

    • Pathology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
    • ,
  • Wook Jin

      Affiliations

    • Laboratory of Molecular Disease and Cell Regulation, Lee Gil Ya Cancer and Diabetes Institute, Gacheon University of Medicine and Science, Incheon, Republic of Korea

Received 2 June 2011; received in revised form 5 August 2011; accepted 15 August 2011. published online 12 September 2011.

Article Outline

Abstract 

Aims

To know which MS criteria best predict the presence of NAFLD and the prevalences of metabolic syndrome (MS) and non-alcoholic fatty liver disease (NAFLD) diagnosed ultrasonographically among pre-diabetic and diabetic subjects based on three different MS criteria (IDF, ATP III, WHO).

Methods

Subjects were screened and those with a fasting serum glucose level ≥100mg/dL were further tested with a 75g oral glucose tolerance test. And those who were newly diagnosed as having pre-diabetes or diabetes were evaluated for MS and NAFLD. We compared the risk ratios of NAFLD among three MS criteria using multivariate and multiple logistic regression analyses.

Results

A total of 1365 subjects (977 males, mean age 48.4±9.5 years) were analyzed. The WHO criteria produced the highest prevalence of MS in both the pre-diabetic (49.8%) and diabetic (58.9%) groups. The IDF criteria produced the highest odds ratio for NAFLD in both pre-diabetic (3.89 [95% CI 2.75–5.51]) and diabetic (5.53 [95% CI 3.21–9.52]) groups.

Conclusions

The prevalence of MS depends on the set of diagnostic criteria used. IDF criteria best predicts the presence of NAFLD. The presence of NAFLD should be considered as a component of the diagnostic criteria for MS.

Keywords: NAFLD, Metabolic syndrome, Metabolic syndrome criteria

 

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1. Introduction 

It is known that NAFLD (non-alcoholic fatty liver disease) can progress into chronic liver disease, such as liver cirrhosis [1], [2]. It is also known that NAFLD itself can cause insulin resistance, which leads to increased risk of cardiovascular disease and metabolic syndrome [2], [3], [4], [5]. Currently, NAFLD is not a component of the diagnostic criteria for metabolic syndrome; however, the development of NAFLD has some common mechanisms with the development of metabolic syndrome, as they share the pathophysiologic basis of insulin resistance. It is also recognized that NAFLD is the hepatic manifestation of metabolic syndrome [6], [7], [8]. This phenomenon is indirectly supported by the fact that the prevalence of NAFLD has increased in conjunction with the increased prevalence of other insulin resistance related conditions which were also a component of metabolic syndrome [9], [10], [11]. The increased prevalences of NAFLD and metabolic syndrome are emerging as a major public health issue [12].

There are three current sets of diagnostic criteria for metabolic syndrome that have been set forth by the International Diabetes Federation (IDF) [13], the National Cholesterol Education Program Adult Treatment Panel III (ATP III) [14], and the World Health Organization (WHO) [15]. Each set of diagnostic criteria produces a different prevalence of metabolic syndrome within the same population. We thus aimed to calculate the prevalences of metabolic syndrome and NAFLD among pre-diabetic and diabetic subjects based on each of those three diagnostic sets of criteria for metabolic syndrome and also aimed to determine which set best predicted the presence of NAFLD.

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2. Subjects and methods 

2.1. Subjects 

Our study population were recruited from those presenting for their routine health status check up at the Heath Promotion Center in Kangbuk Samsung Hospital, Seoul, Korea between January 1st and December 31st, 2007. Those who had a 100mg/dL or higher fasting blood glucose level without a past medical history of diabetes were requested for oral glucose tolerance test (OGTT). Total 1365 subjects diagnosed predabetes or diabetes and agreed to participate in the study were analyzed. We excluded subjects with a history of alcohol consumption of 140g (70g in women) or more per week by semi-quantitative questionnaire, viral hepatitis with positive serologic markers for hepatitis B or C, liver transplantation, medications known to cause fatty liver, cardiovascular disease, or malignant tumor. Informed consent was obtained from the participating subjects. The study protocol was approved by the Institutional Review Board at Kangbuk Samsung Hospital, and this study was performed in compliance with the Helsinki declaration of 1964.

2.2. Study methods 

2.2.1. Anthropometric measurements 

The measurements collected in this study included body weight, height, body mass index (BMI), waist circumference (WC), hip circumference (HC), and systolic and diastolic blood pressures. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared (kg/m2). The WC and HC were measured at the levels of the umbilicus and greater trochanter of the femur, respectively. The subject's blood pressure was measured twice by a skilled nurse following at least ten minutes of rest, and the mean value was calculated and recorded.

2.2.2. Biochemical laboratory tests 

Blood samples were collected from the antecubital vein following a minimum 12-h overnight fast. We analyzed the samples for aspartate aminotransferase, alanine aminotransferase, blood lipid profile, fasting blood glucose level, serum insulin level and HbA1c. Biochemical markers were measured using Bayer Reagent Packs on an automated chemistry analyzer (ADVIA 1650 Autoanalyzer; Bayer HealthCare, Tarrytown, NY). Fasting blood sugar levels were measured using the hexokinase method. Lipid profiles, including values for total cholesterol (TC), triglycerides (TG), low density lipoprotein (LDL) cholesterol, and high density lipoprotein (HDL) cholesterol, were measured via enzymatic colorimetric assay. To measure the secretion amount of urinary albumin, we collected early morning mid-stream urine samples and calculated the urinary albumin-to-creatinine ratio using an immunonephelometric method. Serum insulin concentrations were measured via immunoradiometric assay using a BioSource INS-IRMA kit (BioSource, Belgium). As a marker of insulin resistance, the homeostatic model assessment (HOMA-IR) was calculated using the following formula [16]:

HOMA-IR=[fasting insulin (μIU/ml)×fasting glucose (mmol/l)]/22.5.

2.2.3. Diagnosis of NAFLD 

Abdominal ultrasonography (ASPEN; Acuson, Pennsylvania, USA) was performed by one of three radiologists using a 3.5MHz probe to evaluate the presence of hepatic steatosis in all subjects. The diagnosis of fatty liver was made based on the following criteria [17], [18]: a diffuse hyperechoic echotexture, hepatorenal echo contrast in reference to the cortex of the right kidney, and vascular blurring and deep-echo attenuation. When making the diagnosis of NAFLD, the results of the liver function test were not taken into consideration.

2.2.4. Assessment of pre-diabetes and diabetes 

The 75-g oral glucose tolerance test (OGTT) was performed on those who had a 100mg/dL or higher fasting blood glucose level without a past medical history of diabetes. Impaired fasting glucose (IFG) was defined as having a fasting serum glucose level of 100–125mg/dL. Impaired glucose tolerance (IGT) was defined as having a fasting glucose level of 140–199mg/dL 2h after administration of the oral glucose tolerance test. All study subjects were classified into normal, pre-diabetes (IFG or IGT), and diabetes groups based on the American Diabetes Association guidelines (2003) [19].

2.2.5. Diagnostic criteria for metabolic syndrome 

The three sets of diagnostic criteria for metabolic syndrome adopted in this study are described below and summarized in Supplementary Table 1.

i)International Diabetes Federation Task Force on Epidemiology and Prevention (IDF) [13]. Ethnic-specific values for waist circumference were used. Waist circumference greater than 90cm in men or 80cm in women and having two or more of the following criteria: (1) triglyceride level ≥150mg/dL or under specific treatment for this lipid abnormality; (2) HDL cholesterol level <40mg/dL in men, <50mg/dL in women, or under specific treatment for this lipid abnormality; (3) blood pressure ≥130/85mmHg or on antihypertensive medication; and (4) fasting plasma glucose level ≥100mg/dL.

ii)Modified National Cholesterol Education Program (NCEP), Adult Treatment Panel III (ATP III) [14]. Having three or more of the following components: (1) Waist circumference (using ethnic-specific values for waist circumference from IDF [13]) >90cm in men or >80cm in women; (2) triglyceride level ≥150mg/dL; (3) HDL cholesterol level <40mg/dL in men or <50mg/dL in women; (4) blood pressure ≥130/85mmHg; and (5) fasting plasma glucose level ≥100mg/dL. Note that the 2002 definition identified a fasting plasma glucose level of ≥6.1mmol/l (110mg/dl) as elevated; this was modified in 2004 to ≥5.6mmol/l (100mg/dl) in accordance with the American Diabetes Associations updated definition of impaired fasting glucose [20].

iii)World Health Organization (WHO) [15]. The presence of insulin resistance (Type 2 Diabetes Mellitus or IFG or IGT) and two or more of the following components: (1) plasma triglycerides ≥150mg/dL; (2) low HDL-cholesterol <35mg/dL in men or <39mg/dL in women; (3) blood pressure ≥140/90mmHg or on antihypertensive medication; (4) central obesity, measured by the waist-to-hip ratio, >0.90 in men, >0.85 in women, and/or BMI >30kg/m2; and (5) microalbuminuria (urinary albumin excretion rate ≥20μg/min or albumin:creatinine ratio ≥20mg/g). The criteria for insulin resistance (Type 2 Diabetes Mellitus or IFG or IGT) is available at Table 1 in same reference [15].
Table 1. General characteristics and prevalences of metabolic syndrome in the study subjects.
Total (n=1365)
pre DM (n=951, 69.7%)p valueDM (n=414, 30.3%)p value
non-NAFLD (n=484)NAFLD (n=467, 49.1%) non-NAFLD (n=139)NAFLD (n=275, 66.4%)
Age (years)47 (42–54)46 (40–52)0.00950 (44–57)49 (43–56)0.349
WC (cm)79.9±7.6286.7±6.587<0.00181.1±7.15587.9±6.889<0.001
BMI (kg/m2)23.6±2.45325.9±2.518<0.00124±2.41126.2±2.555<0.001
Body fat (%)a24 (19.5–30.9)25 (22.3–30)<0.00122.6 (19.7–31.2)25.3 (23.1-30.9)<0.001
Systolic BP (mmHg)116 (104–130)120 (110–132)<0.001120.5±15.417123.6±14.8340.045
Diastolic BP (mmHg)76 (70–82)80 (72–86)<0.00178 (70–84)80 (72–86)0.028
AST (U/L)22 (19–25.8)25 (21–30)<0.00123 (19–27)26 (21–34)<0.001
ALT (U/L)19 (15–25)30 (21–42)<0.00121 (17–27)32 (22–47)<0.001
LDL-C116.9±31.273123.3±31.6980.002114.4±33.747129.2±33.828<0.001
Triglyceride (mg/dL)113 (86–156)162 (119–235)<0.001115 (77–164)168 (126–240)<0.001
HDL-C(M/F <40/50)48.5 (42–56)44 (38–51)<0.00147 (40–55)43 (38–49)<0.001
HbA1c(%)5.6 (5.4–5.8)5.6 (5.4–5.8)0.0576 (5.6–6.4)6.2 (5.8–6.6)0.001
Insulin8.9 (7.6–10.8)11 (9.1–13.4)<0.0018.8 (7.5–10.3)10.7 (8.8–14.1)<0.001
HOMA-IR2.3 (1.9–2.9)2.9 (2.4–3.6)<0.0012.6 (2.1-3)3.3 (2.6–4.4)<0.001
IDF14.0% (=68)33.2% (n=155)<0.00115.8% (n=22)46.2% (n=127)<0.001
ATP-III26.1% (n=125)55.4% (n=258)<0.00133.1% (n=46)63.3% (n=174)<0.001
WHO38.0% (n=184)62.1% (n=290)<0.00143.2% (n=60)66.9% (n=184)<0.001

aBody fat percent measured by Inbody 720 (Biospace Co., Ltd, South Korea), NAFLD: non-alcoholic fatty liver disease, WC: waist circumference, BMI: body mass index, BP: blood pressure, AST: aspartate aminotransferase, ALT: alanine aminotransferase, LDL-C: low density lipoprotein cholesterol, HDL-C: high density lipoprotein cholesterol, M: male, F: female, HOMA-IR: insulin resistance as estimated by the homeostasis model assessment, IDF: prevalence of metabolic syndrome according to the International Diabetes Federation, ATP III: prevalence of metabolic syndrome according to the National Cholesterol Education Program Adult Treatment Panel, WHO: prevalence of Metabolic Syndrome according to the World Health Organization.


2.3. Statistical analysis 

All data were analyzed using PASW Statistics 17.0 (SPSS Inc., Chicago, IL, USA). In univariate analysis, we compared normal continuous variables with the t-test. For those variables without normality, the Mann-Whitney test was used. Categorical variables were compared using the Chi-square test. For normality test results, mean and standard deviations are given for continuous variables; frequency and percentage are shown for categorical variables. A p value less than 0.05 was considered statistically significant. Multiple logistic regression analysis was performed to determine the association between NAFLD and pre-diabetes or diabetes status in subjects with metabolic syndrome. Odds ratios and 95% confidence intervals were obtained.

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3. Results 

A total of 1365 subjects (977 males, 388 females, mean age 48.4±9.5 years) were analyzed, including 951 (69.7%) with pre-diabetes and 414 (30.3%) with diabetes. The prevalences of NAFLD among the pre-diabetes group and diabetes group were 49.1% (467/951) and 66.4% (275/414), respectively, with a significantly higher prevalence of NAFLD in the diabetes group (p<0.001). When we compared subjects with and without NAFLD in both the pre-diabetes and diabetes groups, those with NAFLD had significantly higher mean values for factors related to metabolic syndrome, such as body mass index, waist circumference, hip circumference, serum insulin, triglyceride, LDL cholesterol, and insulin resistance (HOMA-IR) values. The prevalences of metabolic syndrome in the pre-diabetes and diabetes groups were also significantly higher for those with NAFLD compared to those without NAFLD (Table 1).

The prevalence of metabolic syndrome was higher in the diabetes group than in the pre-diabetes group. Among the three sets of diagnostic criteria for metabolic syndrome, the WHO criteria produced the highest prevalence of metabolic syndrome (49.8% in the pre-diabetes group, 58.9% in the diabetes group) (Fig. 1).

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  • Fig. 1. 

    The prevalences of metabolic syndrome according to three sets of criteria in pre-diabetes and diabetes mellitus groups.

  • preDM: pre-diabetes mellitus, DM: diabetes mellitus, IDF: International Diabetes Federation, ATP III: National Cholesterol Education Program Adult Treatment Panel, WHO: World Health Organization.

We calculated the prevalence of NAFLD among subjects with metabolic syndrome in the pre-diabetes and diabetes groups using the three different diagnostic criteria for metabolic syndrome (Fig. 2). The IDF criteria produced the highest prevalence for NAFLD among the three (69.5% in the pre-diabetes group, 85.2% in the diabetes group).

  • View full-size image.
  • Fig. 2. 

    The prevalences of NAFLD using three sets of metabolic syndrome criteria in pre-diabetes and diabetes groups.

  • preDM: pre-diabetes mellitus, DM: diabetes mellitus, IDF: International Diabetes Federation, ATP III: National Cholesterol Education Program Adult Treatment Panel, WHO: World Health Organization.

We also calculated the risk ratio for NAFLD (odds ratio) in the pre-diabetes and diabetes groups using the three different sets of diagnostic criteria for metabolic syndrome. The IDF criteria results were 3.89 (95% CI 2.75–5.51) and 5.53 (95% CI 3.21–9.52), respectively; the modified ATP-III criteria produced results of 3.74 (95% CI 2.81–4.96) and 3.62 (95% CI 2.34–5.61), respectively; and the WHO criteria results were 2.48 (95% CI 1.90–3.25) and 2.57 (95% CI 1.68–3.93), respectively. The IDF criteria therefore produced the highest odds ratio (Table 2).

Table 2. Odds ratios from multivariate logistic regression analyses of each set of metabolic syndrome criteria as a predictor for NAFLD in pre-diabetes mellitus and diabetes mellitus.
MetS criteriaPre DMDM
NAFLD prevalence (%)OR (95% CI)NAFLD prevalence (%)OR (95% CI)
IDF 200569.53.89 (2.757–5.512)85.25.53 (3.211–9.523)
ATPIII67.43.74 (2.818–4.964)79.13.62 (2.346–5.611)
WHO61.22.48 (1.902–3.25)75.42.57 (1.686–3.938)

preDM: pre-diabetes mellitus, DM: diabetes mellitus, MetS: metabolic syndrome, IDF: International Diabetes Federation, ATP III: National Cholesterol Education Program Adult Treatment Panel, WHO: World Health Organization.

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4. Discussion 

This study shows that the prevalences of metabolic syndrome among the pre-diabetes and diabetes groups were high. The prevalence varied depending on the type of diagnostic criteria for metabolic syndrome because of the different components included in each set. The observed higher prevalence of metabolic syndrome in subjects with NAFLD compared to that of those without NAFLD suggests that the presence of NAFLD probably contributed to the development of systemic insulin resistance, or that NAFLD might be an early manifestation of systemic insulin resistance. This is in line with the conclusions of previous clinical and experimental studies [6], [7]. It is reported that NAFLD results from an abnormality in insulin transduction signaling, which is independent of fat and muscle tissue. Various factors of NAFLD affect the insulin sensitivities of fat and muscle tissues, which may result in the development of systemic insulin resistance [21], [22], [23], [24].

It has been reported that the presence of NAFLD activates the intrahepatic NF-κB pathway and facilitates the secretion of inflammatory cytokines, such as interleukin-6, tumor necrosis factor alpha, and interleukin-1β, which may result in increased systemic insulin resistance [25], [26]. These findings imply that NAFLD may be an early warning and facilitating factor for the development of metabolic syndrome.

We found that the prevalences of NAFLD among subjects with pre-diabetes and diabetes were as high as 49.1% and 66.4%, respectively. These figures are similar to the prevalence of NAFLD among diabetes patients (34–74%) reported in a previous study [27].

The limitations of our study were absence of hepatic biopsy and potential inter-observer variation among the three radiologists. In clinical practice, obtaining liver biopsy specimens from asymptomatic healthy subjects is difficult and the specimens dose not represent the whole liver. There are intra- and inter-observer variations among pathologist as high as 5–10% [28], [29]. With based on these reasons, the large sample size of our study led the authors to consider the results of this study meaningful.

The prevalence of NAFLD was higher among subjects with metabolic syndrome, and the IDF criteria produced the highest figure. This appears to be due to the IDF criteria's use of waist circumference, which is a measure of abdominal obesity, as an essential component. A number of studies have reported that NAFLD is more closely related to waist circumference and central obesity than is any other component of metabolic syndrome, although the pathophysiology of the disease is not yet clearly known [30], [31], [32].

Some researchers have proposed a hypothesis to explain this phenomenon. One such explanation is the portal/fatty acid flux theory, which states that the level of resistance against insulin inhibition in lipolysis is higher in visceral fat than subcutaneous fat, and anatomical structures allow the free fatty acids and glycerol released by the visceral fat to directly flow to the portal vein in high concentrations, resulting in insulin resistance and fat accumulation in the liver [33], [34].

It has been found that inflammatory cytokines, such as interleukin-6 and tumor necrosis factor alpha, are expressed to a greater degree in visceral fat than they are in subcutaneous fat [33], [35], and surgical removal of abdominal fat improves hepatic insulin resistance [36], providing supporting evidence for the presence of a relationship between visceral fat and NAFLD. For this reason, the authors expect that waist circumference, which reflects the degree of abdominal obesity, is a better predictor of the presence of NAFLD than is body mass index.

The presence of NAFLD was associated with higher values both for metabolic components and cardiovascular risk factors, which include body mass index, waist circumference, body fat mass, serum insulin, serum triglyceride, LDL cholesterol and HOMA-IR values. We infer that NAFLD should not be regarded as simply a kind of liver disease but should be recognized as a hepatic manifestation of systemic disease such as metabolic syndrome.

The best treatment for any disease is prevention and early detection. The prevention of critical chronic disease, such as cardiovascular disease, should be a top priority in the public health field. In this regard, the authors propose that NAFLD, which is known to increase the risk of cardiovascular disease and is also an early manifestation of metabolic syndrome, be considered as a component of the criteria for metabolic syndrome. In the future, the usefulness of adding NAFLD to the diagnostic criteria for metabolic syndrome should be assessed by studying the relationship between NAFLD and the long term prognoses of patients with metabolic syndrome. And comparable study in other ethnic groups should be performed to clarify the generalizability of this study.

Our study findings are summarized below:

1.The prevalence of metabolic syndrome among pre-diabetic and diabetic subjects varied depending on the diagnostic criteria used.

2.If pre-diabetic and diabetic subjects also have metabolic syndrome, the prevalence of NAFLD is higher than in those without metabolic syndrome.

3.Among the three sets of criteria for metabolic syndrome, the IDF criteria best predictes the presence of NAFLD. The greater accuracy of the IDF criteria appears to be related to the emphasis on abdominal obesity.

4.In the future, the presence of NAFLD should be considered as a component of the diagnostic criteria for metabolic syndrome. We recommend further study to determine whether NAFLD is related to the long term prognoses of those with metabolic syndrome.

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Conflict of interest 

The authors declare that they have no conflict of interest.

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Appendix A. Supplementary data 

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PII: S0168-8227(11)00458-X

doi:10.1016/j.diabres.2011.08.013

Diabetes Research and Clinical Practice
Volume 95, Issue 1 , Pages 19-24, January 2012

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