Contribution of body adiposity index and conicity index in prediction of metabolic syndrome risk and components

Abstract

Background and aimsBody adiposity index (BAI) and conicity index have been known as useful measures in predicting cardio-metabolic diseases. This study aimed to evaluate the predictive potential of BAI and conicity index for the risk of metabolic syndrome (MetS) in comparison with body mass index (BMI), waist circumference (WC), hip circumference (HC), and waist-hip ratio (WHR). MethodsIn this cross-sectional study, 174 adults (87 with MetS and 87 healthy individuals) were recruited from a medical weight loss center. Anthropometric parameters, systolic and diastolic blood pressures (SDP and DBP), lipid profile, and fasting blood sugar (FBS) were measured. ResultsAll anthropometric parameters were significantly higher in subjects with MetS than in healthy subjects. Both in MetS and healthy subjects, females had significantly higher BAI and BMI than males. In the fully adjusted model, the odds of MetS increased for each unit increase in BAI by 27 % (p = 0.001), in BMI by 33 % (p = 0.001), in WC by 13 % (p < 0.001), and in HC by 9 % (p = 0.005). ROC curve analysis showed that all the anthropometric parameters displayed clinical importance in predicting MetS, but WHR had the largest area under the curve (AUC) in total, male, and female patients. In participants with MetS, the conicity index was negatively correlated with FBS; BAI was positively associated with HDL level. ConclusionAll studied anthropometric parameters had acceptable accuracy for predicting MetS. Traditional parameters, particularly the WHR, exhibited a higher predictive power concerning MetS. The results underscore the reliability of conventional anthropometric measures in clinical and epidemiological settings.