Forget BMI.
Think FML.

We need new terms for a new era. The concept of Body Mass Index — BMI — was created by a Belgian astronomer and statistician in 1835 as a way to describe the "average man." It is a number derived from a single, blunt calculation: a person's weight in kilograms divided by height in meters squared. That is the entire formula. No blood work. No scan. No clinical nuance.

BMI provided a ready and convenient way to place individuals into weight status categories such as underweight, normal weight, overweight, and obese. With time its usage spread, and in 1972 the now-ubiquitous term "BMI" was coined and advocated for use in population studies. The World Health Organization (WHO), the Centers for Disease Control and Prevention (CDC), and countless other health organizations now use BMI as a basic metric to categorize weight health and to estimate general health risk.

A metric in almost all electronic health records, BMI is frequently if not universally found in patient health assessments, and is a commonly used gauge to calculate whether a patient has a healthy body weight for their height. In everyday medical practice, it's often one of the first numbers used to guide conversations about weight and overall health.

And yet, BMI has become the de facto standard by which health organizations, insurers, electronic health records, and now major telehealth platforms screen patients, set policy, and determine who qualifies for life-changing GLP-1 medications. The WHO, the CDC, the FDA — they all lean on BMI. Ro, WW, Medvi, and other large-scale telehealth obesity programs rely on it as both an eligibility screen and a measure of treatment success. Some rely on self-reported BMI.

Why BMI Falls Short

It cannot distinguish fat from muscle

Because BMI uses only height and weight, it assumes all weight is the same. However, muscle, fat, bone, and water all have varying densities and weigh differently — and have different health effects. A highly muscular athlete may carry a BMI above 30 and be flagged as "obese," despite having low body fat and excellent metabolic health. Conversely, someone who is "skinny fat" — low muscle, high fat percentage — may show a perfectly normal BMI while harboring elevated metabolic risk. BMI both over-diagnoses and under-diagnoses in the same patient population.

It ignores where fat lives in the body

BMI tells you how much total weight someone has, but nothing about location — and where on the body fat is stored is of crucial importance in evaluating someone's overall health risk. Visceral fat — the fat packed around organs in the abdomen — is strongly linked to cardiovascular disease, type 2 diabetes, and insulin resistance. Subcutaneous fat, stored under the skin around the hips and thighs, carries far less risk. Two patients can share an identical BMI yet have completely different fat-distribution profiles and therefore completely different health trajectories.

It doesn't account for age, sex, or ethnicity

Because BMI uses the same cutoffs for everyone, it discounts the fact that body composition and health risk vary significantly across different age, sex, and ethnic groups. The three main dimensions:

• Gender: Women naturally carry higher body fat percentages than men at the same BMI, and men tend to accumulate more visceral (riskier) fat.
• Age: Older adults lose muscle mass (sarcopenia) and gain fat, meaning a "normal" BMI can still mask high body fat and frailty risk.
• Ethnicity: Some populations — notably from Asia — develop metabolic diseases at lower BMI thresholds, while others may have higher muscle mass or different fat distribution patterns.

The clinical consequence of adhering to standard BMI thresholds in the face of these variabilities is that it may underestimate risk in some groups, misclassify obesity status across populations, and lead to less personalized, less accurate, and less effective care.

It tells you nothing about metabolic health

Because BMI does not measure what is happening inside the body metabolically, it is unable to provide clinically relevant or actionable information about a person's health condition. It's like using dollar-store reading glasses when what you actually need is a microscope. Some individuals with a high BMI can in fact be metabolically healthy — normal blood sugar, cholesterol, and blood pressure — while some individuals with a normal BMI may have poor metabolic health: insulin resistance, high triglycerides, fatty liver. Major takeaway: BMI does not equate to health status.

It oversimplifies obesity as a single number

Obesity is complicated. It is a complex, multifactorial disease — not just a matter of excess weight that can be defined and categorized according to simplistic numerical thresholds. Obesity involves many interacting factors:

• Hormones (e.g. leptin, insulin, ghrelin)
• Genetics (predisposition to fat storage and metabolism)
• Environment and lifestyle (diet, physical activity, sleep, stress)
• Psychological factors (behavior, mental health)

BMI captures none of these underlying causes or mechanisms. Two patients with the same BMI could have completely different causes of obesity, different health risks, and different responses to treatment. Relying on BMI runs the risk of applying a one-size-fits-all approach instead of evidence-based, individualized treatment.

It cannot measure body composition directly

Understanding a patient's whole body composition is important in obesity medicine. Crucial factors include percent body fat, lean muscle mass, bone density, and water weight. Two individuals with the exact same BMI can have completely different body compositions — illustrating one of BMI's many limitations for accurately diagnosing obesity. Relying too heavily on BMI can mean neglecting more valuable indicators, such as fat loss vs. muscle loss, and may increase the risk of incorrect or incomplete clinical decision-making.

BMI: From Official Threshold to Standard Measure of Weight Loss Success

The FDA-approved indications for all anti-obesity medications — including semaglutide (Wegovy) and tirzepatide (Zepbound) — are defined entirely by BMI thresholds: BMI 30+, or BMI 27+ with at least one comorbidity such as hypertension or type 2 diabetes. Telehealth obesity programs like Ro must prescribe within FDA-labeled indications to maintain regulatory compliance as well as to conform to insurance and pharmacy procedures. So BMI serves as the determinative criterion for both screening eligibility and tracking treatment progress. Compounding the reliability problem is that telehealth platforms rely not just on BMI, but on self-reported BMI.

There Are Better Tools

Waist circumference measures abdominal (visceral) fat directly, making it a strong predictor of heart disease and type 2 diabetes. The classic Waist-to-Hip Ratio (WHR) compares waist size to hip size, identifies fat distribution patterns — the so-called "apple or pear shape" — and is a better indicator of metabolic risk than BMI alone. That said, measuring yourself can lead to inaccurate results; the WHO recommends measuring at the midpoint between the lowest rib and the iliac crest, while the NIH/NHLBI recommends just above the iliac crest.

When it comes to full body composition scanning, DEXA — Dual-Energy X-ray Absorptiometry — remains the gold standard. It uses low doses of X-rays to accurately measure body fat, lean muscle, and bone density. However, DEXA is expensive and not widely available in private clinical settings.

Bioelectrical Impedance Analysis (BIA), via systems like InBody, Seca, and ImpediMed, passes small electrical currents through the body to generate measurements of body fat percentage, muscle mass, and water distribution — specific to various parts of the body. It is quick, non-invasive, and commonly used in clinics. While BIA does not directly measure body composition the way DEXA does, it is most useful for longitudinal tracking within an individual patient over the course of treatment.

Enter FML: Percent Fat Mass Loss

The metric that matters is FML — percent fat mass loss. It is calculated simply:

FML = (Fat Mass Lost ÷ Total Weight Lost) × 100

FML measures what the body is actually losing — not just how much. Rather than relying on the scale alone, this metric measures the proportion of weight lost that comes specifically from fat, helping distinguish high-quality fat loss from undesirable muscle or water loss — which, as previously discussed, is a factor BMI lacks entirely.

Data from the STEP 1 trial show that of the average 13.6 kg lost with semaglutide, approximately 62% was fat mass and 38% was lean body mass. A subsequent meta-analysis found lean mass loss accounted for roughly 25% of total GLP-1 weight loss. This is not a rounding error — it is a clinically significant finding that BMI-based assessment misses entirely.

FML focuses the entire clinical conversation on what genuinely matters: the preservation of lean muscle while driving down fat. It correlates more meaningfully with improvements in metabolic health, physical function, and long-term treatment sustainability than any number a scale produces on its own.

The Bottom Line

We have much improved our methodologies and our technology since the invention of BMI nearly two centuries ago. It's time we update our measures of success as well. BMI was created to describe statistical populations, not to diagnose and treat individual patients. In the GLP-1 era — where millions of people are losing weight rapidly, where muscle preservation is a genuine clinical concern, and where the stakes of accurate metabolic assessment have never been higher — we owe patients better than a 19th-century astronomer's approximation. By prioritizing fat reduction while monitoring the preservation of lean mass, FML more accurately reflects improvements in metabolic health, physical function, and long-term sustainability. We have the technology and the metrics to do this right. The question is whether we choose to use them.