It is calculated in a few seconds with a height and a weight.
BMI is so familiar today that it appears to have always been a medical tool designed to diagnose overweight and obesity. However, its story is much less linear. During the “Let’s Talk Obesity” event, Tuesday October 6, 2026 at Espace Pavée in Paris, Professor Karine Clément recalled the unexpected role played by American insurance companies in the way in which weight has long been associated with health risk.
In front of Dr. Gérald Kierzek and the other participants of the round table “Obesity, the evil of the century: anatomy of a silent epidemic“, the endocrinologist, diabetologist and nutritionist, director of the Inserm unit at Sorbonne University and president of AFERO, chose to return to the origins.
Why do we divide weight by height squared? And why does the number 30 mark the conventional boundary of adult obesity today? The story mixes statistics, mortality, insurance and, much later, medicine.
BMI and American insurance, the economic story behind weight
Professor Karine Clément begins her intervention by directly questioning the room on an indicator that almost everyone knows.
“Do you know why the body mass index was defined and why we say that it is an indicator? And why we say that beyond 30, we define obesity?”
His answer is immediately striking for its economic nature.
“In fact, it is on a purely economic basis. It was defined by American insurance companies in 1950 because it was necessary to make obese people pay more for health care.”
The mathematical formula itself is older. It dates back to the Belgian statistician, mathematician and astronomer Adolphe Quetelet who, from the 1830s, observed that the weight of an adult evolves approximately as the square of his height. Its “Quetelet index” is therefore not designed to individually diagnose obesity. It is used to study the physical characteristics of populations.
It was in the 20th century that the American insurance industry takes a major place in the history of weight as a measure of risk. Insurers have vast data on their policyholders and observe a relationship between corpulence and mortality. Metropolitan Life Insurance Company publishes weight and height tables intended to identify profiles associated with the lowest or highest mortalities. This data is then used for risk assessment.
A French medical publication devoted to the history of BMI recalls that the first research in the 20th century on the relationship between weight and health was encouraged by insurance companies wishing to identify indicators of excess mortality in order to to adapt their premiums.
Weight is therefore not only observed as medical data. It also has a financial value: the more a profile is statistically associated with a high risk of death, the more it is of interest to the insurer responsible for evaluating this risk.
From Quetelet to Ancel Keys, how BMI became a medical indicator
It was not until 1972 that the modern expression “Body Mass Index”, or BMI in English, was truly established. American physiologist Ancel Keys and his colleagues compare different indices from several male populations. They conclude that the weight/height² ratio imagined by Quetelet constitutes, among the tools studied, a practical indicator of corpulence at the population level.
Irony of history, Keys himself criticizes old Metropolitan Life Insurance Company tables
before bringing forward the Quetelet index and giving it the name by which we know it today.
BMI then eventually became established in public health. It has an obvious advantage: it is extremely simple to calculate. Weight in kilograms is divided by height in meters squared.
In adults, The World Health Organization currently considers that a BMI equal to or greater than 25 corresponds to overweight and that a BMI equal to or greater than 30 corresponds to obesity.
But this border is not a sort of biological switch causing a disease to suddenly appear when we go from 29.9 to 30. The WHO documents themselves specify that the relationship between BMI and risk is gradual and that other factors intervene. The international classification is largely based on the statistical associations observed between BMI, morbidity and mortality.
This is precisely what Karine Clément sought to remind us during the round table: a number that is very effective in classifying populations does not necessarily describe the entire medical situation of an individual.
Why BMI is not enough to define a person’s obesity
After telling this story, Karine Clément returns to what she considers to be the clinical definition of the disease.
“The clinical definition is an increase in fat mass with consequences for health.”
The distinction changes a lot of things. BMI knows weight and height, but not the precise composition of that weight. It does not directly say what amount corresponds to fat mass, how this fat is distributed or whether organs already present complications.
Health Insurance also recommends supplementing its calculation with other elements, such as waist size. She recalls that the definition based on BMI does not take into account the distribution of adipose tissue, while the accumulation of abdominal fat is linked to certain cardiovascular and metabolic risks.
Two people can therefore display exactly the same BMI without having the same body composition or presenting the same consequences on their health. This limit has been known for a long time in the scientific literature: BMI works better as a simple indicator at the population level than as an exhaustive snapshot of a person’s health.
This is also why the definition of obesity continues to evolve. During the round table, Karine Clément discussed the work of an international commission which brought together more than 60 specialists in order to go beyond a reading based solely on BMI and to further integrate fat mass, its distribution and the real impact of the disease.
She sums up this difficulty in a few words:
“One person’s obesity is not another’s.”
The IMC therefore remains useful for quickly identifying and comparing situations. But its historical journey tells something of its DNA: before becoming the individual figure that we consult today on our phone or at our doctor, the relationship between weight and height was first used to observe populations, while American insurers have largely contributed to transforming weight into a risk variable.