OBJECTIVEType 2 diabetes is an established risk factor for development of hepatic steatosis and nonalcoholic fatty liver disease (NAFLD). We aimed to determine the prevalence and clinical correlates of these conditions in a large cohort of people with type 2 diabetes.RESEARCH DESIGN AND METHODSA total of 939 participants, aged 61–76 years, from the Edinburgh Type 2 Diabetes Study (ET2DS)—a large, randomly selected population of people with type 2 diabetes—underwent liver ultrasonography. Ultrasound gradings of steatosis were compared with magnetic resonance spectroscopy in a subgroup. NAFLD was defined as hepatic steatosis in the absence of a secondary cause (screened by questionnaire assessing alcohol and hepatotoxic medication use, plasma hepatitis serology, autoantibodies and ferritin, and record linkage to determine prior diagnoses of liver disease). Binary logistic regression was used to analyze independent associations of characteristics with NAFLD.RESULTSHepatic steatosis was present in 56.9% of participants. After excluding those with a secondary cause for steatosis, the prevalence of NAFLD in the study population was 42.6%. Independent predictors of NAFLD were BMI, lesser duration of diabetes, HbA1c, triglycerides, and metformin use. These remained unchanged after exclusion of participants with evidence of hepatic fibrosis from the group with no hepatic steatosis.CONCLUSIONSPrevalences of hepatic steatosis and NAFLD were high in this unselected population of older people with type 2 diabetes, but lower than in studies in which ultrasound gradings were not compared with a gold standard. Associations with features of the metabolic syndrome could be used to target screening for this condition.

We found poor correlation between the five biomarkers of liver fibrosis studied. Using the top 5% of each biomarker resulted in good agreement on the absence of advanced liver disease but poor agreement on the presence of advanced disease. Further work is required to validate these markers against liver biopsy and to determine their predictive value for clinical liver-related endpoints, in a range of different low and high risk population groups.

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