RFM Calculator - Relative Fat Mass
Relative Fat Mass (RFM) estimates your body fat percentage using only two measurements: height and waist circumference. Developed in 2018 by researchers at Cedars-Sinai Medical Center, RFM consistently outperforms BMI at predicting actual body fat levels. Enter your sex, height, and waist size and your RFM percentage and category update instantly. Metric and imperial units are both supported.
Formula
Worked example
A male with height 175 cm and waist 85 cm: ratio = 175 / 85 = 2.0588; RFM = 64 - 20 x 2.0588 = 64 - 41.18 = 22.8%. This falls in the Average category for men (18-24%).
What is Relative Fat Mass (RFM)?
Relative Fat Mass is a body fat percentage estimator published in 2018 by Dr. Orison Woolcott and Dr. Richard Bergman at Cedars-Sinai Medical Center. The formula uses only two measurements, height and waist circumference, to produce an estimate that correlates strongly with DXA (dual-energy X-ray absorptiometry) scans, the gold-standard clinical method for measuring body composition. Unlike BMI, which simply divides weight by height squared and cannot distinguish fat from muscle, RFM captures the size of the waist relative to overall height, giving it a direct relationship to abdominal adiposity. The 2018 study, published in Scientific Reports, found that RFM estimated DXA-measured body fat percentage more accurately than BMI in both men and women.
How to measure waist circumference correctly
Waist measurement technique matters because an error of even a centimetre can shift your RFM by about 0.3 percentage points. Stand upright with feet together and arms relaxed at your sides. Locate the midpoint between the top of your hip bone (iliac crest) and the bottom of your lowest rib, usually just above the navel. Wrap a flexible tape measure horizontally around this point, keeping it snug but not tight. Take the reading at the end of a normal, relaxed exhale - do not suck in your stomach. Record to the nearest millimetre (0.1 cm). Repeat twice and average the readings if they differ by more than 5 mm.
RFM vs BMI: what the research shows
Body Mass Index (BMI) has been used as a population screening tool since the 1970s, but it has well-documented limitations: it cannot distinguish muscle from fat, it tends to misclassify muscular individuals as overweight and metabolically unhealthy people with little muscle as normal weight. The original Woolcott-Bergman study generated 365 candidate anthropometric indices, developed the model on 12,581 adults from NHANES 1999-2004 and validated it on a separate 3,456 adults from NHANES 2005-2006, all with DXA body-composition scans. In that validation set, RFM diagnosed body-fat-defined obesity better than BMI in men (area under the ROC curve 0.94 vs 0.91, P < 0.001) and about as well as BMI in women (0.929 vs 0.933, P = 0.52), while also estimating body fat percentage itself more accurately and producing fewer false negatives in both sexes. For a practical example: a bodybuilder with substantial muscle mass might have a BMI of 28 (overweight) but an RFM of 10% (athlete range), while a sedentary adult with little muscle could have a BMI of 24 (healthy) but an RFM of 28% (obese). RFM captures that distinction; BMI does not.
Body fat categories and health implications
The categories in this calculator follow American Council on Exercise standards. Essential fat (roughly 2-5% for men, 10-13% for women) is the minimum needed for basic physiological function including hormone production and organ protection. The athlete range (6-13% men, 14-20% women) is typical of competitive athletes but can be difficult to sustain long-term. The fitness range reflects a physically active lifestyle without competitive training. The average range is associated with moderate cardiometabolic risk, and obesity (25% or above for men, 32% or above for women) is associated with substantially elevated risk of type 2 diabetes, cardiovascular disease, and all-cause mortality. A separate analysis by Woolcott and Bergman (International Journal of Obesity, 2020), which linked 31,008 NHANES adults to national death records, derived RFM obesity cutoffs of roughly 30% in men and 40% in women as the points where all-cause mortality risk begins to rise.
Body fat percentage categories (American Council on Exercise)
| Category | Males (%) | Females (%) | Health implication |
|---|---|---|---|
| Extremely low | Below 2 | Below 10 | Risk of organ dysfunction |
| Essential fat | 2-5 | 10-13 | Minimum for basic function |
| Athletes | 6-13 | 14-20 | Typical for trained athletes |
| Fitness | 14-17 | 21-24 | Above-average fitness level |
| Average | 18-24 | 25-31 | Moderate health risk |
| Obese | 25 and above | 32 and above | Elevated cardiometabolic risk |
These ranges apply to adults. RFM estimates may differ from DXA or underwater weighing by a few percentage points.
Frequently asked questions
Is RFM more accurate than BMI?
Yes for estimating body fat percentage, and yes for diagnosing obesity in men. The Woolcott-Bergman 2018 study screened 365 anthropometric indices against DXA scans in 12,581 adults and validated the winner in a further 3,456 adults: RFM estimated whole-body fat percentage more accurately than BMI in both sexes, and detected DXA-defined obesity better than BMI in men (AUC 0.94 vs 0.91) and about equally well in women (0.929 vs 0.933). BMI cannot distinguish fat from muscle, so it mislabels muscular people as overweight and low-muscle individuals as healthy. RFM uses waist circumference, which directly reflects abdominal fat, giving it a stronger link to actual body composition and cardiometabolic risk.
What do I need to measure to calculate RFM?
You need only two measurements: your standing height and your waist circumference. No scale required. Measure waist at the midpoint between your top hip bone and lowest rib, after a normal exhale, keeping the tape horizontal and snug but not compressed.
Why is the formula different for men and women?
Men and women store fat differently. Women naturally carry more body fat at the same waist-to-height ratio due to reproductive and hormonal factors, so the female formula uses a higher constant (76 vs 64) to account for this. The 2018 research derived separate equations for each sex by fitting regression models to DXA measurements across thousands of adults.
Does RFM work for athletes with high muscle mass?
RFM handles athletes better than BMI because it relies on waist circumference rather than total body weight. A muscular athlete with a lean waist will have a low RFM even if they are heavy for their height. That said, RFM is still an estimate: DXA scanning, hydrostatic weighing, or air displacement plethysmography provide more precise measurements for athletes who need exact figures for performance tracking.
Can RFM be used for children or teenagers?
The Woolcott-Bergman formula was validated on adults aged 20 and over using NHANES data. Body proportions change substantially during growth, so the formula constants are not appropriate for children or adolescents. For people under 20, age- and sex-specific body fat percentile charts are more appropriate.
What is the healthy RFM range for women?
For women, the commonly used ranges are: essential fat 10-13%, athletes 14-20%, fitness 21-24%, average 25-31%, and obese 32% and above. These are based on American Council on Exercise standards. A value in the fitness or athlete range is considered healthy and associated with low cardiometabolic risk.
What is the healthy RFM range for men?
For men, the commonly used ranges are: essential fat 2-5%, athletes 6-13%, fitness 14-17%, average 18-24%, and obese 25% and above. These are based on American Council on Exercise standards. The fitness range (14-17%) is associated with a healthy active lifestyle and low cardiometabolic risk.
Sources
- Woolcott OO, Bergman RN. Relative fat mass (RFM) as a new estimator of whole-body fat percentage - a cross-sectional study in American adult individuals. Scientific Reports. 2018;8:10980.
- Woolcott OO, Bergman RN. Relative Fat Mass as an estimator of whole-body fat percentage among children and adolescents: a cross-sectional study using NHANES. Scientific Reports. 2019;9:15279.
- Woolcott OO, Bergman RN. Defining cutoffs to diagnose obesity using the relative fat mass (RFM): association with mortality in NHANES 1999-2014. International Journal of Obesity. 2020;44(6):1301-1310.