Lipid Accumulation Product Index as Visceral Obesity Indicator in Psoriasis: A Case-control Study

Background: Psoriasis has well-known associations with individual components of metabolic syndrome such as hypertension, dyslipidemia, insulin resistance, and obesity. Traditional anthropometric measurements of obesity such as waist circumference (WC) and body mass index (BMI) do not differentiate between subcutaneous fat and visceral fat, the latter being associated with cardiovascular risk factors. Lipid accumulation product (LAP) index is a measure of visceral fat and has been found to be a better predictor of cardiovascular risk. However, LAP index has not been well-studied in psoriasis patients. Aims and Objectives: Our objective was to find out if LAP index differs significantly between psoriasis patients and controls and whether LAP index shows a correlation with duration and severity of psoriasis. Materials and Methods: A case-control study was undertaken with 40 chronic plaque psoriasis patients and 42 controls. BMI and LAP index were calculated for all the patients and controls. Psoriasis area severity index (PASI) was calculated for all the psoriasis patients. Mann-Whitney U-test was done for comparing the age, BMI, WC, serum triglyceride, and LAP index between the cases and controls and to compare the LAP index between mild psoriasis and moderate-to-severe psoriasis groups. Spearman's correlation coefficient was used to assess the correlation of LAP index with duration of psoriasis and with PASI. Logistic regression models were done to assess the risk factors in psoriasis. Results: A statistically significant difference was observed between the LAP index of controls (23.79 +/- 13.02) and that of psoriasis patients (46.42 +/- 27.2). LAP index was significantly higher in the moderate-to-severe psoriasis group as compared to the mild psoriasis group. LAP index was a significant risk factor associated with psoriasis (OR = 1.07; 95% CI: 1.03 - 1.11). Conclusion: Calculation of LAP index in psoriasis patients helps in identification of more individuals at high risk of cardiovascular morbidity than traditional anthropometric measurements of obesity.