External validation of the relative fat mass (RFM) index in adults from north-west Mexico using different reference methods

Abstract

BackgroundAnalysis of body composition is becoming increasingly important for the assessment, understanding and monitoring of multiple health issues. The body mass index (BMI) has been questioned as a tool to estimate whole-body fat percentage (FM%). Recently, a simple equation described as relative fat mass (RFM) was proposed by Woolcott & Bergman. This equation estimates FM% using two anthropometric measurements: height and waist circumference (WC). The authors state that due to its simplicity and better performance than BMI, RFM could be used in daily clinical practice as a tool for the evaluation of body composition. The aim of this study was to externally validate the equation of Woolcott & Bergman to estimate FM% among adults from north-west Mexico compared with Dual-energy X-ray absorptiometry (DXA) as an alternative to BMI and secondly, to make the same comparison using air displacement plethysmography (ADP), Bioelectrical Impedance Analysis (BIA) and a 4-compartment model (4C model).MethodsWeight, height and WC were measured following standard procedures. The RFM index was calculated for each of the 61 participating subjects (29 females and 32 males, ages 20–37 years). The RFM was then regressed against each of the four body composition methods for estimating FM%.ResultsCompared with BMI, RFM was a better predictor of FM% determined by each of the body composition methods. In terms of precision the best equation was RFM regressed against DXA (y = 1.12 + 0.99 x; R2 = 0.84 p<0.001). Accuracy (represented by the closeness to the zero-intercept) was 1.12 (95% CI: -2.44, to 4.68) and thus, not significantly different from zero. For the rest of the methods, precision in the prediction of FM% was improved compared to BMI, with significant increases in the R2 and reduction of the root mean squared error (RMSE). However, the intercepts of each regression did not show accuracy since they were different from zero, for ADP: -9.95 (95%CI: -15.7 to -4.14), for BIA: -12.6 (95%CI: -17.5 to -7.74) and for the 4C model: -13.6 (95%CI: -18.6 to -8.60). Irrespectively, FM% measured by each of the body composition methods was higher for DXA than the other three methods (p<0.001).ConclusionsThis external validation proved that the performance of the RFM equation used in this study to estimate FM% was more consistent than BMI in this Mexican population, showing a stronger correlation with DXA than with the other body composition methods.

Nutrition Counseling in an Academic Medical Center According to Socioeconomic Status and Grocery Shopping Consumer Behavior Decreased Relative Fat Mass in Breast Cancer Survivors

“…These are two key reasons why breast cancer survivors with a healthy weight were not excluded from the study. This is the 1 st time that RFM is applied in oncology nutrition, with prior validation by four body composition methods in Northwest Mexican adults, as is our study population 5 . RFM has proven to be a better predictor than BMI for body fat percentage 5 , dyslipidemia, and metabolic syndrome 31 , probably due to the incorporation of WC in the equation and its relationship with abdominal and visceral fat 29 .…”

“…This is the 1 st time that RFM is applied in oncology nutrition, with prior validation by four body composition methods in Northwest Mexican adults, as is our study population 5 . RFM has proven to be a better predictor than BMI for body fat percentage 5 , dyslipidemia, and metabolic syndrome 31 , probably due to the incorporation of WC in the equation and its relationship with abdominal and visceral fat 29 . A decrease in RFM may aid for dyslipidemia and metabolic syndrome prevention and should be considered a beneficial health outcome for breast cancer survivors at risk for sarcopenic obesity.…”

“…The RFM equation used in this study as a fat mass % estimate 7 , was then validated in Northwest Mexican adults by DXA, air displacement plethysmography, bioelectrical impedance analysis, and a 4-compartment model 5 . Both H and WC must be added in meters to the equation (Equation S1) 7 .…”

“…Frequently, BMI is used to classify overweight and obesity in cancer 2 . However, BMI cannot distinguish lean and adipose tissue distribution and has been questioned as a ratio for FM estimation 1,5 . For these reasons, novel and reliable equations validated by dual-energy X-ray absorptiometry (DXA) could be used to assess body composition in adult cancer patients.…”

“…For these reasons, novel and reliable equations validated by dual-energy X-ray absorptiometry (DXA) could be used to assess body composition in adult cancer patients. Such equations have been recently proposed by Heymsfield et al for skeletal muscle mass (SM) 6 , and by Woolcott and Bergman for relative fat mass (RFM) 7 , additionally validated in Northwest Mexican adults by different reference methods along with DXA 5 . During and after cancer treatment, body composition assessment in breast cancer survivors is essential to design strategies and implement lifestyle interventions to prevent sarcopenic obesity 8 .…”