Repository Article

·2011

An algorithm to predict risk of type 2 diabetes in Turkish adults: contribution of C-reactive protein.

Altan Onat , G. Can , H. Gülru Yüksel YTU , Erkan Ayhan , Yüksel Doğan , Gülay Hergenç YTU

PubMed

Abstract

BACKGROUND AND AIM: An algorithm for predicting Type 2 diabetes (DM) risk in a population with prevalent metabolic syndrome (MetS) is needed since ethnicity influences the pathogenesis of DM. MATERIAL AND METHODS: The 8- yr risk of DM was estimated in 2261 middle-aged Turkish adults free of DM at baseline who were followed for over 7.6 yr. DM newly developed in 212 subjects. Cox proportional hazard regression and 15 variables were used to predict DM. Discrimination was assessed with area under receiver operating characteristics curve (AROC). RESULTS: In multivariable analysis, height, family income brackets, systolic blood pressure, smoking status, alcohol usage, and HDL-cholesterol levels were not predictive in either sex. In addition to sex, family history of DM, fasting glucose, and waist circumference were predictors, in men, age and non-HDL-cholesterol, while in women physical inactivity and serum C-reactive protein were so. AROC of the final model was 0.783 in men, 0.772 in women (p

Keywords

Medicine Waist Metabolic syndrome Internal medicine Population Hazard ratio Type 2 diabetes Receiver operating characteristic Family history C-reactive protein Diabetes mellitus Demography Proportional hazards model Algorithm Endocrinology Body mass index Confidence interval Mathematics Inflammation Environmental health

Subject Areas

Adipokines, Inflammation, and Metabolic Diseases ·Epidemiology ·Health Sciences
Diabetes, Cardiovascular Risks, and Lipoproteins ·Endocrinology, Diabetes and Metabolism ·Health Sciences
Dermatoglyphics and Human Traits ·Genetics ·Life Sciences

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