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Obesity (Silver Spring). 2010 Sep;18(9):1836-44. doi: 10.1038/oby.2009.453. Epub 2009 Dec 24.

The lipid accumulation product and all-cause mortality in patients at high cardiovascular risk: a PreCIS database study.

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  • 1Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA.


The BMI is the most frequently used marker to evaluate obesity-associated risks. An alternative continuous index of lipid over accumulation, the lipid accumulation product (LAP), has been proposed, which is computed from waist circumference (WC, cm) and fasting triglycerides (TGs) (mmol/l): (WC - 65) x TG (men) and (WC - 58) x TG (women). We evaluated LAP and BMI as predictors of mortality in a high-risk cohort. Study population included 5,924 new consecutive patients seen between 1995 and 2006 at a preventive cardiology clinic. Fifty-eight percent of patients were discordant for their LAP and BMI quartiles. Patients whose LAP quartile was greater than BMI quartile had higher mortality compared with those with LAP quartile was lower than BMI quartile (8.2 vs. 5.4% at 6 years, P = 0.007). After adjustment for age, gender, smoking, diabetes mellitus, blood pressure, low-density lipoprotein-cholesterol (LDL-C) and high-density lipoprotein-cholesterol (HDL-C), (ln)LAP was independently associated with mortality (hazard ratio (HR) = 1.46, P < 0.001). BMI was not associated with increased mortality (HR = 1.06, P = 0.39). Adding LAP to a model including traditional risk factors for atherosclerosis increased its predictive value (C statistic 0.762 vs. 0.750, P = 0.048). Adding BMI to the same model did not change its predictive value (0.749 vs. 0.750, P = 0.29). Subgroup analyses showed that LAP predicted mortality in the nondiabetic patients (adjusted HR for (ln)LAP 1.64, P < 0.001), but did not reach significance in the diabetic patients (HR = 1.21, P = 0.11). In conclusion, LAP and not BMI predicted mortality in nondiabetic patients at high risk for cardiovascular diseases. LAP may become a useful tool in clinical practice to stratify the risk of unfavorable outcome associated with obesity.

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