Predictive Capacity for Mortality and Severe Liver Disease of the Relative Fat Mass Algorithm

In the latest decades, obesity has become a major global health problem. Obesity has traditionally been defined as a body mass index (BMI) of equal to or more than 30 kg/m². It is now well known that persons with obesity to a high degree develop nonalcoholic fatty liver disease and are at risk for developing cirrhosis.¹ However, BMI has been criticized for being an imperfect measurement of body fat composition.² Recently, a new algorithm was developed to better estimate the percentage of body fat.³ The relative fat mass (RFM) was based on height, waist circumference (WC), and sex. The RFM was found to be superior to BMI and other estimators in estimating body fat percentage, using dual-energy X-ray absorptiometry as the gold standard. RFM had also a stronger association with diabetes status than BMI. However, because the analyzed data came from a cross-sectional source, it is unclear if the RFM is superior to BMI or other measures of body composition in predicting incident clinically significant outcomes, including mortality. In addition, RFM was not compared with WC or waist-hip-ratio (WHR), which are commonly used clinically and in epidemiologic studies.