The predictability of the metabolic syndrome by adipokines

Abstract

Purpose Obesity can cause impairment in adipose tissue-derived hormones levels, which, in turn, might lead to metabolic syndrome occurrence. This study aims to assess the relationship between the levels of adiponectin, resistin, retinol-binding protein 4 (RBP4) and insulin with metabolic syndrome (MetS) indices. Also, optimal cutoff points of the adipokines and insulin for MetS prediction were determined. Design/methodology/approach In this study, 180 women (90 women with MetS and 90 women without MetS) were studied. The National Cholesterol Education Program Adult Treatment Panel III criteria were used for MetS diagnosis. Anthropometric and biochemical indices were measured. Data were analyzed using SPSS software version 21. Findings Serum adiponectin correlated negatively with age, BMI, waist circumference (WC), triglyceride (TG), total cholesterol, SBP, DBP, FBS and positively correlated with high-density lipoprotein-cholesterol. Both resistin and RBP4 levels correlated positively with BMI, WC, TG, SBP, DBP and FBS. Also, serum insulin correlated positively with BMI, WC, SBP and DBP. All the studied adipokines and insulin showed significant areas under the receiver operating characteristics curve. The largest area under the curve was observed for adiponectin (0.93, 95 per cent CI = 0.89-0.97, p < 0.001) with the optimal cut-off point of 11.94 µg/L. Also, the upper level of adiponectin was associated with 70 per cent lower prevalence odds of metabolic syndrome after adjusting for confounders. Originality/value The authors determined the optimal cutoff points of the adipokines and insulin for MetS prediction and calculated the diagnostic odds ratio for various cutoff values. Adiponectin could be used as a biomarker in MetS regarding its largest AUC.