SCREENING MARKERS; Comparison of BMI, WHpR and lap for identifying hypercholesterolemia, hyperglycemia, hypertension and enhanced atherosclerosis

The screening measures to identify various cardiovascular risks relatedto hyperglycemia, hypertension and hypercholesterolemia are involves both anatomicassessments like anthropometric measures or body’s physiological evaluation by performingbiochemical parameters. In this regard “lipid accumulation product” (LAP) has surfaced as amarker to incorporate both these anatomic and physiological considerations. Objectives: 1. Tomeasure the LAP differences between subjects having normal and higher levels of glucose, totalcholesterol, age, carotid intima media thickness and subjects with and without hypertension. 2.To compare BMI and LAP in terms of effectiveness as a screening marker for diagnosis of diabetesmellitus and hypertension through ROC curve calculation. Design: Cross-sectional analysis.Place and duration of study: This study was carried out at the departments of pathology, PNSRAHAT hospital from Jan-2011 to Oct-2011. Subjects and methods: After several exclusionsincluding know diabetics a total of 202 subjects were enrolled to undergo sampling for Fastingblood glucose, and lipids in exact medical fasting status. These subjects were later evaluatedfor their various anthropometric measurements including BMI and WHpR (Wait to hip ratio) asper the WHO protocol. Then the individuals went to radiology department where carotid intimamedia thickness measurements were made by experienced radiologist. LAP (Lipid accumulationproducts) score was calculated as: LAP score (Male) = [WC (cm) - 65] x triglycerides (mmol/L)LAP score (Female) = [WC (cm) – 58] x triglycerides (mmol/L). LAP scores, BMI. WHpR andmean CIMT readings were grouped as per their high or low results. Results: Out of BMI, WHpRand LAP score, only groups based upon LAP score were observed to be significantly differentfor fasting blood glucose, total cholesterol and mean CIMT levels. Hypertensive subjects hadhigher LAP scores and WHpR than non-hypertensive subjects; however, BMI differences werenot considered significant. One way ANOVA shows the LAP scores progressively rising formnormoglycemic subjects {58.38 (95% CI: 51.08-65.67)} to subjects having IFG {70.94(95%CI:60.88-81.00)} to newly diagnosed diabetes mellitus {101.59(95%CI: 78.35-124.83)}.[P=0.001]The AUCs for diagnosing hypertension was higher for LAP scores than for BMI and WHpR[{(LAP score: 0.648 (95% CI: 0.536-0.760), p= 0.027} vs {(WHpR: 0.588 (95% CI: 0.466-0.709),p= 0.191} vs {(BMI: 0.541 (95% CI: 0.412-0.670), p=0.545}]. Similarly, the AUCs for BMI andWHpR were lower than that of LAP score for predicting a diagnosis of diabetes mellitus [{(LAPscore: 0.584 (95% CI: 0.502-0.665), p= 0.047} vs {(BMI: 0.531 (95% CI: 0.448-0.613), p=0.468}vs {WHpR: 0.518 (95% CI: 0.435-0.601), p=0.668}]. Conclusion: LAP scores were higherin subjects with established cardiovascular risks like hyperglycemia, hypercholesterolemia,accelerated atherosclerosis and hypertension that simple anthropometric indices like BMI andWHpR.