P116 ANTHROPOMETRIC INDICES AND DYSLIPIDAEMIA IN A SEMI-URBAN NIGERIAN POPULATION

Background/Objective: Obesity and dyslipidaemia are cardiovascular/metabolic risk factors. Dyslipidaemia's intricacy with obesity is dependent on several individual factors and hyperinsulinaemia is a major drive for obesity induced dyslipidaemia. Cost remains a challenge for lipid assay in our locality as majority pay out of pocket for healthcare. Hence, aim of the study- to correlate anthropometric indices with dyslipidaemia and determine which amongst six anthropometric indices best predicts dyslipidaemia. Methods: Consents were obtained from two hundred and sixteen subjects recruited consecutively, from three primary health care centres in a semi-urban Nigerian population. Biodata and cardiovascular risk factors’ history were obtained using interviewer administered questionnaire. Bodyweight, height, waist and hip circumferences were obtained using standard methods. Oscilliometric method was used for blood pressure check while body mass index (BMI), ratios of waist to hip (WHR) circumference and waist to height(WHtR), a body shape index (ABSI) and body roundness index (BRI) were calculated using online calculators. Fasting blood glucose (FBG) was performed using hexokinase method while enzymatic method was used for serum total cholesterol (TC), high density lipoprotein (HDL-C), low density lipoprotein (LDL-C) and triglyceride (TGD) assays after a 12hr overnight fast. Correlation, ROC curve and multivariate analysis using binary logistic regression analysis were used in the analysis. Results: Mean age of participants was 54.8±15.0years. Majority, (71.8%) were females. The prevalence of dyslipidaemia was 94.9%. A weak positive correlation exists between BRI and TC (r =0.134, p=0.049) and with LDL (r =0.182, p=0.007). The AUC was 0.686 (0.516-0.856) for ABSI, cut-off of -1.479, (sensitivity 81.0%; specificity 54.5%). Predictors of dyslipidaemia included age <60years (AOR=15.94, 95%CI: 1.8-143.2) and male gender(AOR=0.08, 95%CI: 0.02-0.50). Conclusions: There is a high prevalence of dyslipidaemia. Lipid levels increases as anthropometric readings rise. ABSI best predicted dyslipidaemia though moderately specific therefore, can be used to screen individuals and identify those in whom lipid assay must be done at all cost during management of cardiovascular/metabolic risk factors. Table: Area under ROC curve (AUC), optimal cut-off points, sensitivities and specificities of anthropometric indices in predicting dyslipidaemia.