Diabetes prediction, Lipid accumulation product, and adiposity measures; 6 – year follow – up
Diabetes prediction, Lipid accumulation product, and adiposity measures; 6-year follow-up: Tehran Lipid and Glucose Study
The body mass index (BMI) is the most commonly used marker for evaluating obesity related risks, however, central obesity measures have been proposed to be more informative. Lipid accumulation product (LAP) is an alternative continuous index of lipid accumulation, which is computed from waist circumference (WC, cm) and triglycerides (TGs, mmol/l): (WC-65) xTG (men) and (WC-58) xTG (women).
We sought in this study to assess if LAP can outperform BMI, waist-to-height-ratio (WHtR), or waist-to-hip-ratio (WHpR) in identifying prevalent and predicting incident diabetes.
Results: The cross-sectional analyses were performed on a sample included 4156 men and 5485 women who were not pregnant, aged [greater than or equal to]20 years. According to the age ([greater than or equal to]50 and <50 years) - and sex-specific analyses, odds ratios (ORs) of LAP for prevalent diabetes were higher than those of BMI, WHpR, or WHtR among women, after adjustment for mean arterial pressure and family history of diabetes.
The OR of LAP in old men was lower than those of other adiposity measures; in young men, however, LAP was superior to BMI but identical to WHpR and WHtR in identifying prevalent diabetes. Except in young men, LAP showed highest area under the receiver operating characteristic curves (AROC) for prevalent diabetes (P for trend[less than or equal to]0.005).For longitudinal analyses, a total of 5,018 non-diabetic subjects were followed for ~6 years.
The ORs of BMI, WHpR, and WHtR were the same as those of LAP in both sexes and across age groups; except in young men where LAP was superior to the BMI. AROCs of LAP were relatively the same as anthropometric adiposity measures.
Conclusions: LAP was a strong predictor of diabetes and in young individuals had better predictability than did BMI; it was, however, similar to WHpR and WHtR in prediction of incident diabetes.
Author: Mohammadreza BozorgmaneshFarzad HadaeghFereidoun Azizi
Credits/Source: Lipids in Health and Disease 2010, 9:45