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Print version ISSN 1807-5932

Clinics vol.67 no.3 São Paulo  2012 



Metabolic syndrome in patients with chronic hepatitis C virus genotype 1 infection who do not have obesity or type 2 diabetes



Lucivalda Pereira Magalhães OliveiraI,II; Rosangela P. de JesusII; Ramona SSB BoulhosaI; Carlos Mauricio C. MendesI; Andre Castro LyraI,III,IV; Luiz Guilherme C. LyraI,IV

IFederal University of Bahia, Medicine and Health, Postgraduate Program, Salvador/BA, Brazil
IIFederal University of Bahia, Nutrition Science Department, Salvador/BA, Brazil
IIIFederal University of Bahia, Department of Medicine, Division of Gastroenterology and Hepatology, Salvador/BA, Brazil
IVHospital São Rafael, Gastro-Hepatology Unit, Salvador/BA, Brazil




OBJECTIVE: The individual components of metabolic syndrome may be independent predictors of mortality in patients with liver disease. We aimed to evaluate the prevalence of metabolic syndrome and its related components in hepatitis C virus–infected patients who are not obese and do not have type 2 diabetes.
METHODS: This cross-sectional study included 125 patients infected with hepatitis C virus genotype 1. Metabolic syndrome was defined according to the International Diabetes Federation. Anthropometric data were measured according to standardized procedures. Bioimpedance analysis was performed on all patients.
RESULTS: Metabolic syndrome was diagnosed in 21.6% of patients. Of the subjects with metabolic syndrome, 59.3% had hypertension, 77.8% had insulin resistance, 85.2% were overweight, 48.1% had a high waist circumference, 85.2% had an increased body fat percentage, and 92.3% had an elevated waist:hip ratio. In the bivariate analysis, female sex (OR 2.58; 95% CI: 1.09–6.25), elevated gamma-glutamyl transferase (γGT) (OR 2.63; 95% CI: 1.04–7.29), elevated fasting glucose (OR 8.05; 95% CI: 3.17-21.32), low HDL cholesterol (OR 2.80; 95% CI: 1.07–7.16), hypertriglyceridemia (OR 7.91; 95% CI: 2.88–22.71), elevated waist circumference (OR 10.33; 95% CI: 3.72–30.67), overweight (OR 11.33; 95% CI: 3.97–41.07), and increased body fat percentage (OR 8.34; 95% CI: 2.94–30.08) were independent determinants of metabolic syndrome. Using the final multivariate regression model, similar results were observed for abdominal fat (OR 9.98; 95% CI: 2.63–44.41) and total body fat percentage (OR 8.73; 95% CI: 2.33–42.34). However, metabolic syndrome risk was also high for those with blood glucose >5.55 mmol/L or HDL cholesterol <0.9 mmol/L (OR 16.69; 95% CI: 4.64–76.35; OR 7.23; 95% CI: 1.86–32.63, respectively).
CONCLUSION: Metabolic syndrome is highly prevalent among hepatitis C virus–infected patients without type 2 diabetes or obesity. Metabolic syndrome was significantly associated with hypertension, insulin resistance, increased abdominal fat, and overweight.

Keywords: Metabolic Syndrome; Chronic Hepatitis C; Genotype 1; Overweight; Insulin Resistance.




Over 170 million people worldwide, constituting 3% of the global population, are infected with the hepatitis C virus (HCV) (1). In Brazil, it is estimated that 1–2% of the national population is infected with HCV (2,3).

HCV infection increases oxidative stress, tissue damage, and pro-inflammatory cytokine secretion, all of which contribute to progressive fibrosis, cirrhosis, cancer, a nd liver failure (4,5). Chronic hepatitis C is associated with significant morbidity and mortality and is the main reason for liver transplants in the developed world (6).

Recent data suggest a close relationship between HCV infection and metabolic syndrome (7). It is possible that HCV infection causes fatty liver disease, a precursor of hepatic steatosis, which is a recognized component of metabolic syndrome (8). Individual components of metabolic syndrome are independent predictors of mortality in patients with chronic liver disease, including those infected with HCV (9).

Metabolic syndrome is more prevalent among patients with type 2 diabetes and obesity. However, there are no data regarding metabolic syndrome in non-obese, non-diabetic patients with chronic hepatitis C. In this study, we evaluated the prevalence of metabolic syndrome and its risk predictors in HCV genotype 1–infected patients who do not have obesity or type 2 diabetes.



This cross-sectional study included 125 HCV genotype 1–infected patients who attended the Nutrition and Hepatology Clinic at the Hospital of the Federal University of Bahia. We recruited treatment-naive patients, as well as nonresponders and relapsers to antiviral therapy. All patients were over 18 years of age, consumed less than 20 g/day of alcohol and were not taking antiviral therapy or had discontinued antiviral therapy for at least three months. HCV infection was diagnosed by the presence of serum antibodies to HCV (anti-HCV), which was confirmed by qualitative determination of HCV RNA. Reverse transcription–polymerase chain reaction (RT-PCR) was performed on all samples to quantify the HCV RNA.

Patients with diabetes mellitus or obesity (BMI>30 kg/m2) were excluded. Additionally, pregnant women and patients with HIV, HBV, renal failure, heart disease, decompensated cirrhosis, or malignancy were also excluded from the study.

All subjects signed a written informed consent. The study was approved by the ethics commitee of Federal University of Bahia according to the Declaration of Helsinki.

Complete demographic and social history data were obtained from all patients. Clinical data, such as diagnosis, viral genotype, necroinflammatory index, and presence of fibrosis, were collected from the patients' medical records. Anthropometric data, including body weight, height, and waist circumference, were measured according to standardized procedures. Waist circumference (WC) was measured according to World Health Organization (WHO) recommendations (10).

Waist circumference was measured at the midpoint between the superior aspect of the iliac crests and the lower lateral margins of the ribs using an inelastic tape (TBW Import Ltd) that was 0.5 cm in width and 200 cm in length. Additionally, multicompartmental bioimpedance analysis (model Inbody 520®) was performed according to the manufacturer's instructions. For men and women, body fat percentages >25% and >32%, respectively, were considered to increase the risk for obesity-related comorbidities (11).

After a 12-hour fast, blood samples were collected to determine serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transferase (γGT), alkaline phosphatase (ALP), plasma glucose, insulin, triglyceride, total cholesterol, and lipoprotein fraction levels. Analyses were performed using Beckman Coulter LX20 PRO equipment and a CX-9 Chemistry Analyzer with Labtest kits. Serum insulin was measured by the electrochemiluminescence method using Elecsys 2010 equipment (Roche Kit).

The insulin resistance index was calculated according to the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR): HOMA-IR = fasting insulinemia (microU/mL) x fasting glycemia (mmol/L)/22.5) (12).

Patients underwent abdominal ultrasonograp hy with one of three radiologists using a single machine. Hepatic steatosis was graded as mild, moderate or severe according to the classification of Saverumuttu et al. (13).

Metabolic syndrome was defined based on the International Diabetes Federation (IDF) criteria, including the presence of a waist circumference >90 cm for men and >80 cm for women plus at least two of the following: arterial blood pressure >130/85 mmHg or taking medications for blood pressure, triglycerides >150 mg/dl or taking fibrates, HDL cholesterol <40 mg/dl for men and <50 mg/dl for women or taking pharmacological therapy, and fasting glucose >100 mg/dl or a diagnosis of diabetes (14).

The cut-off points adopted for classifying central obesity as a predictor of increased risk for metabolic syndrome were a waist circumference >88 cm for women and >102 cm for men; these cut-offs are associated with a substantially increased risk of metabolic complications according to the WHO (10). Abdominal obesity was further defined as a waist:hip ratio (WHR) >0.90 for men and >0.85 for women. An increased WHR is associated with greater cardiovascular risk (10,15).

We used the medical record to determine whether patients had arterial hypertension. This determination included subjects who had been previously diagnosed with hypertension by their clinicians and all patients who were under pharmacological treatment.

All data were analyzed using statistical package R version 2.12 (16). Statistical analysis was performed using the Mann–Whitney test for comparisons of continuous variables between groups and the corrected Fisher's exact test for comparisons of frequencies. Logistic regression analysis was used to evaluate risk predictors for metabolic syndrome. A two-tailed p-value <0.05 was considered to be statistically significant.



Patient Characteristics and Prevalence of Metabolic Syndrome

Metabolic syndrome was diagnosed in 21.6% of the patients with HCV. The mean age was 53.3 years (±10.5 years), and 78 (62.4%) of the patients were male. Additionally, 74 patients (59.2%) had previously undergone antiviral treatment, and 51 (40.8%) were treatment-naive. Table 1 shows the prevalence of metabolic syndrome (MS) and the demographic, clinical, and anthropometric characteristics of the patients. Women had a higher prevalence of MS (55.6%). Among patients with metabolic syndrome, hypertension was present in 59.3%, HOMA-IR >3 was present in 77.8%, 85.2% were overweight, 48.1% had an increase d waist circumference, 85.2% had an increased body fat percentage, and 92.3% had an elevated waist:hip ratio. There was no significant association between metabolic syndrome and hepatic steatosis, degree of liver fibrosis, age or previous treatment (nonresponders/relapsers vs. treatment-naive; p = 0.508). The distribution of treatment-naive patients vs. nonresponders/relapsers was similar for those with and without MS (Table 1). Of note, after logistic regression analysis, previous antiviral treatment did not appear to be a risk factor for metabolic syndrome.

Individuals with metabolic syndrome had significantly higher fasting glucose (p = 0.0005), fasting insulin (p<0.0001), HOMA-IR (p<0.0001), and triglycerides (p = 0.0003) and lower HDL (p = 0.006) (Table 2).



Predictors of Metabolic Syndrome

Bivariate analyses of risk factors for metabolic syndrome in this population are shown in Table 3. Women were 2.5 times more likely to have MS (OR 2.58; 95% CI: 1.09–6.25), and patients with γGT>85 U/L were 2.6 times more likely to have MS (OR 2.63; 95% CI: 1.04–7.29). Fasting hyperglycemia (OR 8.05; 95% CI: 3.17–21.32), hypertriglyceridemia (OR 7.91; 95% CI: 2.88–22.71), and abnormal waist circumference (OR 10.33; 95% CI: 3.72–30.67) were major contributors to MS. Overweight (OR 11.33; 95% CI: 3.97–41.07) and increased body fat percentage (OR 8.34; 95% CI: 2.94–30.08) also contributed to metabolic syndrome. Using the final multi variate regression model, similar results were observed for abdominal fat (OR 9.98; 95% CI: 2.63–44.41) and total body-fat percentage (OR 8.73; 95% CI: 2.33–42.34). However, MS risk was higher for those with blood glucose >5.55 mmol/L and those with HDL cholesterol <0.9 mmol/L (OR 16.69; 95% CI: 4.64–76.35; OR 7.23; 95% CI: 1.86–32.63, respectively) (Table 4).






The prevalence of metabolic syndrome in our study was 21.6%, which is similar to the prevalence of 24.7% found by Huang et al. using the same IDF criteria. Indeed their study did not exclude diabetic and obese patients (17).

When the NCEP/ATPIII criteria were used, only 12.1% of the patients were diagnosed with metabolic syndrome (data not shown). Sersté et al. (2010) found similar results (12.4%) in a large cohort of patients with chronic hepatitis C (18). The NCEP/ATPIII criteria would not have diagnosed almost 9.5% of the individuals with MS who were diagnosed using the IDF definition (12.1% vs. 21.6%; p<0.006). Therefore, we chose to use the IDF definition of metabolic syndrome, which adopts lower waist circumference and fasting glucose cut-offs to define obesity and hyperglycemia.

It should be noted that even after excluding patients with diabetes and obesity, there was a high prevalence of metabolic syndrome among patients with chronic hepatitis C. These patients also presented a significantly higher percentage of total body fat, waist circumference, waist:hip ratio and BMI compared to those without MS. In the present study, MS patients had significantly higher BMI than others. These results are in agreement with a study conducted in Taiwan that demonstrated that patients with hepatitis B and C and MS, as defined by NCEP/ATP III criteria, had higher BMI compared to those without MS (19).

Antiviral treatment in patients with chronic HCV infection may induce changes in body weight, insulin resistance and serum lipid levels. However, all previously treated patients in our study had stopped receiving treatment for at least 3 months and therefore were not under the effects of interferon.

In the absence of MS, patients usually had an appropriate BMI and body-fat percentage and normal insulin sensitivity. We found a mean HOMA-IR >3.0 in patients with MS. This finding is in agreement with a study by Grigoresceu et al. (20) of treatment-naive patients with HCV, which found significantly higher HOMA-IR values in patients with MS (7.88 vs. 4.29). However, those authors observed a metabolic syndrome prevalence of 61.48% using the IDF criteria. We speculate that this higher MS prevalence may be explained by the inclusion of obese patients and a greater proportion of women (65.4%); our study excluded obese subjects, and only 37.4% of our patients were women. Furthermore, those authors used a HOMA-IR value >2.0 to define insulin resistance and a value of >4 to diagnose a pre-diabetic state. If we had used those cut-off values, we would have found that most patients with hepatitis C and HOMA-IR values between 2 and 3 had insulin resistance, rather than metabolic syndrome. In addition, half of our patients with MS had a HOMA-IR value >4 and would have been considered pre-diabetic.

HCV proteins can activate TNF-α expression and inhibit the function of insulin receptor substrate (IRS) proteins, which contribute to insulin resistance by decreasing glucose transporter (GLUT-4) expression and lipoprotein lipase in peripheral tissues (21). Insulin resistance has frequently been asso ciated with steatosis, fibrosis progression and lower response to HCV antiviral therapy with PEGylated interferon and ribavirin (22-25). The data from this study suggest that the evaluation of HOMA-IR in certain patients with HCV, especially those who are overweight, might be beneficial in the early detection of abnormal glucose metabolism in this population.

In our evaluation of independent risk factors for metabolic syndrome, overweight individuals were 11 times more likely to develop MS than were non-overweight patients. When the body fat percentage criteria were considered, the risk for developing metabolic syndrome was 8.3 times higher. These data highlight the importance of body composition analysis in screening for metabolic syndrome and the importance of using a sensitive cut-off for diagnosing abdominal obesity, such as the one suggested by the IDF.

Our study also found that γGT >85 U/L was an independent predictor of MS; these data are consistent with the results observed by Lee et al. in the participants of the Framingham study. The authors found that an increase in serum γGT predicts the onset of metabolic syndrome, cardiovascular disease, and death, suggesting that γGT is a marker of metabolic and cardiovascular risk (26).

Although γGT is commonly used in clinical practice as an indicator of hepatobiliary disease and active ethanol consumption, this enzyme might also be used as a biomarker for metabolic syndrome and cardiovascular risk and is strongly associated with insulin resistance (27). Insulin resistance, type 2 diabetes, hypertension, obesity, and metabolic syndrome are independent predictors of mortality in individuals with hepatitis C (9,28). Our study was a cross-sectional study of adults with chronic HCV infection who were divided into two groups based on whether they had metabolic syndrome. Therefore, this study did not have a sex-and age-matched control group.

In conclusion, our study showed that 21.6% of patients infected with HCV genotype 1 had MS. MS was significantly associated with hypertension, insulin resistance, increased abdominal fat, and overweight. Therefore, frequent monitoring for insulin resistance and weight gain among patients with HCV is beneficial because these clinical conditions can negatively affect disease prognosis. Maintaining a healthy body weight is important because it reduces the incidence of comorbidities and possibly delays the progression of chronic liver disease. Further studies are needed to evaluate whether an intervention involving lifestyle modifications and/or drug treatments for MS components can improve the response to antiviral treatments in these patients.



Oliveira LM designed the study, evaluated and assisted the patients, conducted the research, analyzed the data and performed the statiscal analysis and was also responsible for the manuscript writing. Jesus RP designed the study, evaluated and assisted the patients, conducted the research and was also responsible for the manuscript writing. Lyra AC designed the study, evaluated and assisted the patients and was also responsible for the manuscript writing. Lyra LG designed the study and was also responsible for the manuscript writing. Boulhosa RB evaluated and assisted the patients, conducted the research and was also responsible for the manuscript writing. Mendes CM analyzed the data and performed the statistical analysis.



1. Sabahi A. Hepatitis C Virus entry: the early steps in the viral replication cycle. Virol J. 2009;6:117.         [ Links ]

2. Ferreira C, Silveira T. Hepatites virais: aspectos da epidemiologia e da prevenção. Rev Bras Epidemiol. 2004;7(4):473-87.         [ Links ]

3. Ministério da Saúde. Casos confirmados de Hepatite C. Brasil, Grandes Regiões e Unidades Federadas. 2007. Available at: http://portal.saude (accessed December 2010).         [ Links ]

4. Loguercio C, Federico A. Oxidative stress in viral and alcoholic hepatitis. Free Radic Biol Med. 2003;34(1):1-10.         [ Links ]

5. Parola M, Robino G. Oxidative stress-related molecules and liver fibrosis. J Hepatol. 2001;35(2):297-306.         [ Links ]

6. World Health Organization. Initiative for Vaccine Research (IVR): Hepatitis C, 2008. 2010. Available at: (accessed December 2010).         [ Links ]

7. Negro F, Alaei M. Hepatitis C virus and type 2 diabetes. World J Gastroenterol. 2009;15(13):1537-47.         [ Links ]

8. Kotronen A, Yki-Jarvinen H. Fatty liver: a novel component of the metabolic syndrome. Arterioscler Thromb Vasc Biol. 2008;28(1):27-38.         [ Links ]

9. Stepanova M, Rafiq N, Younossi ZM. Components of metabolic syndrome are independent predictors of mortality in patients with chronic liver disease: a population-based study. Gut. 2010;59(10):1410-5.         [ Links ]

10. World Health Organization. Waist Circumference and Waist–Hip Ratio: Report of a WHO Expert Consultation. Geneva: World Health Organization (WHO); 2008.         [ Links ]

11. Lohman TG. Advances in body composition assessment. Current issues in exercise science series. Champaing: Human Kinetics; 1992.         [ Links ]

12. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28(7):412-9.         [ Links ]

13. Saverymuttu SH, Joseph AE, Maxwell JD. Ultrasound scanning in the detection of hepatic fibrosis and steatosis. Br Med J (Clin Res Ed). 1986;292(6512):13-5.         [ Links ]

14. Alberti KG, Zimmet P, Shaw J. The metabolic syndrome—a new worldwide definition. Lancet. 2005;366(9491):1059-62.         [ Links ]

15. Han TS, van Leer EM, Seidell JC, Lean ME. Waist circumference action levels in the identification of cardiovascular risk factors: prevalence study in a random sample. BMJ. 1995;311(7017):1401-5.         [ Links ]

16. R DEVELOPMENT CORE TEAM. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. 2010. Internet: (accessed October 2010).         [ Links ]

17. Huang JF, Chuang WL, Yu ML, Yu SH, Huang CF, Huang CI, et al. Hepatitis C virus infection and metabolic syndrome—-a communitybased study in an endemic area of Taiwan. Kaohsiung J Med Sci. 2009;25(6):299-305.         [ Links ]

18. Serste T, Nkuize M, Moucari R, Van GM, Reynders M, Scheen R, et al. Metabolic disorders associated with chronic hepatitis C: impact of genotype and ethnicity. Liver Int. 2010;30(8):1131-6.         [ Links ]

19. Hsieh MH, Ho CK, Hou NJ, Hsieh MY, Lin WY, Yang JF, et al. Abnormal liver function test results are related to metabolic syndrome and BMI in Taiwanese adults without chronic hepatitis B or C. Int J Obes (Lond). 2009;33(11):1309-17.         [ Links ]

20. Grigorescu M, Radu C, Crisan D, Grigorescu MD, Serban A, Neculoiu D, et al. Metabolic syndrome, insulin resistance and adiponectin level in patients with chronic hepatitis C. J Gastrointestin Liver Dis. 2008;17(2):147-54.         [ Links ]

21. Zekry A, McHutchison JG, Diehl AM. Insulin resistance and steatosis in hepatitis C virus infection. Gut. 2005;54(7):903-6.         [ Links ]

22. Abdel-Azziz MY, Zalata KR, El-Bendary MM. Insulin resistance and liver fibrosis progression in patients with chronic hepatitis C virus infection. Arab Journal of Gastroenterology. 2010;11(1):30-4.         [ Links ]

23. Fartoux L, Poujol-Robert A, Guechot J, Wendum D, Poupon R, Serfaty L. Insulin resistance is a cause of steatosis and fibrosis progression in chronic hepatitis C. Gut. 2005;54(7):1003-8.         [ Links ]

24. Mizuta T, Kawaguchi Y, Eguchi Y, Takahashi H, Ario K, Akiyama T, et al. Whole-body insulin sensitivity index is a highly specific predictive marker for virological response to peginterferon plus ribavirin therapy in chronic hepatitis C patients with genotype 1b and high viral load. Dig Dis Sci. 2010;55(1):183-9.         [ Links ]

25. Romero-Gomez M, Del M, V, Andrade RJ, Salmeron J, Diago M, Fernandez-Rodriguez CM, et al. Insulin resistance impairs sustained response rate to peginterferon plus ribavirin in chronic hepatitis C patients. Gastroenterology. 2005;128(3):636-41.         [ Links ]

26. Lee DS, Evans JC, Robins SJ, Wilson PW, Albano I, Fox CS, et al. Gamma glutamyl transferase and metabolic syndrome, cardiovascular disease, and mortality risk: the Framingham Heart Study. Arterioscler Thromb Vasc Biol. 2007;27(1):127-33.         [ Links ]

27. Thamer C, Tschritter O, Haap M, Shirkavand F, Machann J, Fritsche A, et al. Elevated serum GGT concentrations predict reduced insulin sensitivity and increased intrahepatic lipids. Horm Metab Res. 2005;37(4):246-51.         [ Links ]

28. Hanouneh IA, Feldstein AE, Lopez R, Yerian L, Pillai A, Zein CO, et al. Clinical significance of metabolic syndrome in the setting of chronic hepatitis C virus infection. Clin Gastroenterol Hepatol. 2008;6(5):584-9.         [ Links ]



Received for publication on September 22, 2011; First review completed on October 19, 2011; Accepted for publication on October 26, 2011
No potential conflict of interest was reported.



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