Body mass index, or BMI, is a widely-used value to determine if a person is underweight, normal, overweight, or obese for their height. Calculated by dividing one's weight in kilograms by one's height in meters squared, BMI is often criticized because it doesn't take into account gender differences and doesn't distinguish between bone mass, muscle mass and excess fat. Researchers at Cedars-Sinai Medical Center have now come up with a formula they claim paints a more accurate picture of one's body fat.
Unlike BMI, which requires a set of scales and a tape measure to calculate, the new formula developed at Cedars-Sinai requires just a tape measure. Called the relative fat mass index, or RFM, it involves calculating a ratio from the height and waist measurements in meters, which is multiplied by 20 before being subtracted from a figure to take into account differences for gender.
With excess fat often stored around the waist, many medical professionals believe waist circumference measurements are a valuable indicator of the risk of developing weight-related health problems. And in arriving at their new RFM formula, the team's findings appear to back this belief up.
Drawing on a database of 12,000 adults that had participated in a health and nutrition survey conducted by the Centers for Disease Control and Prevention, the researchers tested over 300 potential formulas for estimating body fat. After calculating the RFM of 3,500 patients, they compared these to the patients' DXA, or DEXA, (dual-energy x-ray absorptiometry) scans. DXA scans are used to measure bone density and are considered an accurate way to measure body tissue, bone, muscle and fat. The RFM reached using the above formulae was found to correspond most closely with the DXA body scan.
"The relative fat mass formula has now been validated in a large data base," says Richard Bergman, PhD, the senior author of the study and director of the Cedars-Sinai Sports Spectacular Diabetes and Obesity Wellness and Research Center. "It is a new index for measuring body fatness that can be easily accessible to health practitioners trying to treat overweight patients who often face serious health consequences like diabetes, high blood pressure and heart disease."
That means that RFM will classify more people as obese.
Our selected regression models included those based on the simplest indices with the highest correlation with body fat percentage among women and among men.
We found a progressive decline in body weight, height and fat-free mass after 50 years of age, and a steeper decline in fat mass and waist circumference after 70 years of age among women and men, which coincided with the lower predicting ability of all models in older individuals.
Height/waist equation, named as the relative fat mass, was the final model selected because of its simplicity, it was superior to BMI in predicting body fat percentage among men, had similar predicting ability relative to BMI among women and had overall better performance than BMI among women and men, independently.
“Our results confirmed the value of our new formula in a large number of subjects: Relative fat mass is a better measure of body fatness than many indices currently used in medicine and science, including the BMI” said Orison Woolcott.
More than 93 million people—nearly 40 percent of the U.S. population—are considered overweight, according to the CDC. Obesity is associated with a poor quality of life and premature death from chronic disease.
“We still need to test the RFM in longitudinal studies with large populations to identify what ranges of body fat percentage are considered normal or abnormal in relation to serious obesity-related health problems,” Woolcott said.