A case-control study on insulin resistance, metabolic co-variates & prediction score in non-alcoholic fatty liver disease
- PMID: 19491421
A case-control study on insulin resistance, metabolic co-variates & prediction score in non-alcoholic fatty liver disease
Abstract
Background & objective: Asian Indians have a high prevalence of insulin resistance and the metabolic syndrome. Currently, non-alcoholic fatty liver disease (NAFLD) is considered to be an integral part of the metabolic syndrome with insulin resistance as a central pathogenic factor. We studied anthropometric parameters, insulin resistance and metabolic co-variates in subjects with NAFLD as compared to those without NAFLD, and also developed a prediction score for NAFLD.
Methods: Thirty nine subjects with NAFLD and 82 controls were selected for the study after ultrasonography of 121 consecutive apparently healthy subjects. Anthropometric profile [body mass index (BMI), waist circumference (WC) etc,], lipid profile, hepatic aminotransferases, fasting blood glucose (FBG), insulin were recorded and value of homeostasis model assessment of insulin resistance (HOMA-IR) was analysed. Step-wise logistic regression analysis and area under the receiver operator curve (aROC) were analysed to arrive at a prediction score.
Results: Overall, prevalence of NAFLD was 32.2 per cent and prevalence of metabolic syndrome was seen in 41 per cent among cases and 19.5 per cent in controls (P<0.01). Subjects with NAFLD had significantly higher values of BMI, WC, hip circumference, FBG, fasting insulin, total cholesterol and serum triglycerides. Step-wise logistic regression analysis showed odds ratio (OR) and 95 per cent confidence interval (CI) for BMI [ 4.3 (1.6, 11.3)], FBG [5.5 (1.5, 19.8)] and fasting insulin [ 2.4 (1.0, 5.8)] as independent predictors of NAFLD. The prediction score for NAFLD was; 1 (fasting insulin) +1.6 (BMI) + 1.9 (FBG) (sensitivity of 84.6%, specificity of 51.2% and aROC 76%).
Interpretation & conclusion: In this study, presence of NAFLD indicated close relationship with multiple features of metabolic syndrome. The prediction score developed could be used as a screening tool to predict NAFLD among Asian Indians in north India.
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