A new predictive equation for evaluating women body fat percentage and obesity-related cardiovascular disease risk

Obesity represents a global public health problem due to its association with cardiovascular diseases and reduced lifespan. The most widely used classification of obesity is expressed as Body Mass Index (BMI); however, this formula is an imprecise adiposity measurement that ignores several important factors involved. Body Adiposity Index (BAI) was more recently proposed as an indirect evaluation of percentage body fat (PBF). PBF is a direct measure of person's relative body fat and a better predictor of obesity-related risk diseases than BMI and BAI. Since obesity and consequent diseases are considered epidemic, new accurate formulas for epidemiological studies are of interest to the scientific community. Because direct measurement of body composition could be quite expensive, the aims of our work were to analyse the distributions of PBF by Dual X-ray absorptiometry, and the creation of new predictive equation using only anthropometric measures that could be helpful to clinicians to assess easily body fat of female patients. A sample of 1,031 Caucasian Italian women was recruited and BMI, BAI and PBF were evaluated. With the aim of developing a predictive model of PBF a multivariate regression model was fitted to observed data. The definition of universally recognized PBF by gender and age could have public health implications. In this study, we developed a new predictive PBF equation that does not require the use of medical instruments or skilled measurement techniques and that may be easily applicable to Italian women.