Relative fat mass (RFM) is an emerging alternative to body mass index (BMI). The application of RFM may prove useful as a predictor of cardiovascular disease including atrial fibrillation (AF), heart failure (HF), and coronary artery disease (CAD). The establishment of RFM cut-offs, however, needs refinement. To that end, Victor W. Zwartkruis, MD, PhD-candidate, and colleagues developed a study drawing from data captured during the Lifeline Cohort Study.
The authors sought to determine the association of RFM with individual outcomes and composite outcomes regarding the incidence of AF, HF, and CAD. The study also explored RFM for cardiovascular disease (CVD) risk. Dr. Zwartkruis spoke with Physician’s Weekly regarding the findings of the study, which was published in the International Journal of Obesity.
Why did you feel this topic needed exploration?
Obesity is a major risk factor for cardiovascular disease. Traditionally, physicians used BMI to classify obesity. However, BMI has its shortcomings as a measure of body fat because it does not differentiate between fat and muscle mass. RFM was specifically developed as a more accurate marker of total body fat. RFM calculations calculated use a sex-specific formula containing height and waist circumference. Previous studies demonstrated an association between RFM with type 2 diabetes and allcause mortality. However, the association between RFM and cardiovascular disease has not been studied in detail. Therefore, we aimed to study the association of RFM with incident AF, HF, and CAD in the general population. Furthermore, we wanted to explore potential RFM cutoffs that clinical practices may use for assessing cardiovascular risk.
What are the most important findings from your study?
We found that RFM is significantly associated with AF, HF, and CAD. In our study, optimal RFM cutoffs for the prediction of cardiovascular disease (≥26 for men, ≥38 for women) were lower when compared with previously proposed RFM cutoffs for obesity (≥30 for men, ≥40 for women). The overall predictive ability of RFM and its cutoffs was at least similar, and in some cases better, when compared with BMI and waist circumference.
How can physicians incorporate these findings?
RFM provides an accurate and more intuitive estimate of fat mass compared with BMI and waist circumference. In addition, RFM is easy to measure, requiring only height and waist circumference. Therefore, we believe that physicians may easily apply the use of RFM in clinical practice for the classification of obesity and the prediction of cardiovascular risk. Our study provides potential RFM cutoffs for CVD prediction that future studies may use for creating preventive strategies that target obesity and cardiovascular risk.
What would you like future research to focus on?
Future research should validate our findings in other populations. Furthermore, it would be interesting to perform prospective studies to investigate whether using RFM can lead to improved treatment of individuals at risk of developing cardiovascular disease and whether this can help prevent adverse cardiovascular events.
