Lipid Accumulation Product: An Effective Obesity Index to Predict Metabolic Syndrome - Tabassum, Mariya; Mozaffor, Miliva; Rahman, Md Matiur; Huda, Reaz Mahmud (Journal of Bangladesh College of Physicians and Surgeons, 2022)
Background: Obesity is a significant risk factor in the development of metabolic syndrome (MetS). Lipid Accumulation Product (LAP) is an obesity index and has been proposed to be a predictor of metabolic syndrome. The present study aims to see the effectiveness of Lipid Accumulation Product as an obesity index to predict metabolic syndrome in a Bangladeshi population. Methods: This cross-sectional study was conducted in Department of Biochemistry and Molecular Biology, Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh, between March 2016 and February 2017. A total of 200 apparently healthy subjects (127 men and 73 women) were selected for the study, attending out-patient-departments of the same institution. Anthropometric measurements were recorded, which included their height, weight, waist circumference (WC) and body mass index (BMI). Overnight fasting blood samples were collected to estimate fasting serum glucose and lipid profile. Then LAP was calculated and evaluated as a tool in prediction of MetS in the study subjects. Receiver operating characteristic (ROC) curves were plotted to assess the performance of LAP in MetS prediction by gender. The power of MetS prediction was quantified by the area under the curve (AUC) with 95% confidence intervals. Results: Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NVP) of LAP in predicting MetS were 70.45%, 78.57%, 72.09% and 77.19% in male study subjects and 20.45%, 96.43%, 81.82% and 60.67% in female subjects respectively. ROC curve analysis showed that the optimal cutoff value of LAP in male study subjects was 40.72, while area under the curve was 0.92; in female study subjects, the values were 51.69 and 0.91 respectively (P<0.001). Conclusion: Lipid Accumulation Product was found simple, accessible and effective obesity index to predict metabolic syndrome in apparently healthy adults. J Bangladesh Coll Phys Surg 2022; 40: 5-9