Obesity is a condition where fatty tissue increased to a point where it is a risk factor for certain health conditions or increased mortality. The most common clinical method used for identifying obesity is Body Mass Index (BMI) where BMI between 18-25 kg.m2 is considered normal, more than 25 Kg.m2 is considered overweight, or more than 30 kg-.m2 considered obese according to WHO guidelines. BMI is dependent on body weight. The body weight of a person depends on the amount of adipose tissue and muscle mass. The Same volume of muscle mass is heavier than the same volume of Fat. So those having more muscle mass will show more BMI than a person of similar height and weight with less muscle mass. More precisely, a person having more Fat-Free Mass (FFM) will show more BMI than a person having less FFM with more adiposity. Hence BMI is not an ideal parameter for a population with more muscularity genetically. For this reason, attempts were made to identify obesity ignoring BMI. Different methods like BMI Prime (Ratio of a person’s BMI to the upper-level weight limit of “healthy weight”), Body Adiposity Index (BAI), Body Fat % Range, Waist to Hip ratio, Waist to Height ratio, Waist circumference, Surface-based Body Shape Index (SBSI), Body Shape Index (BSI), Obesity Paradox, Corpulence Index (CI), Ponderal Index (PI), Pignet Index or Body Build Index, were developed as alternate obesity diagnosis method. But all these methods still have limitations. Alternately, the endomorph component which represents fattiness can be used as an indicator of obesity for all populations irrespective of athlete, non-athlete, or Fat-Free Mass (FFM). The diagnostic accuracy of BMI is limited and future studies are necessary to determine if the endomorph component can predict obesity better than other methods.
