A few extra pounds can extend your life. Or so chirped the press, reporting on a recent study from the journal Obesity. The new research, which supports earlier findings that being slightly overweight is associated with living longer, has added to an ongoing controversy over how we measure obesity. At the center of this debate is the body mass index, a simple equation (your weight in kilograms divided by the square of your height in meters) that has in the last decade claimed a near-monopoly on obesity statistics. Some researchers now argue that this flawed and overly reductive measure is skewing the results of research in public health.
For years, critics of the body mass index have griped that it fails to distinguish between lean and fatty mass. (Muscular people are often misclassifed as overweight or obese.) The measure is mum, too, about the distribution of body fat, which makes a big difference when it comes to health risks. And the BMI cutoffs for "underweight," "normal," "overweight," and "obese" have an undeserved air of mathematical authority. So how did we end up with such a lousy statistic?
Belgian polymath Adolphe Quetelet devised the equation in 1832 in his quest to define the "normal man" in terms of everything from his average arm strength to the age at which he marries. This project had nothing to do with obesity-related diseases, nor even with obesity itself. Rather, Quetelet used the equation to describe the standard proportions of the human build—the ratio of weight to height in the average adult. Using data collected from several hundred countrymen, he found that weight varied not in direct proportion to height (such that, say, people 10 percent taller than average were 10 percent heavier, too) but in proportion to the square of height. (People 10 percent taller than average tended to be about 21 percent heavier.)
The new equation had little impact among the medical community until long after Quetelet's death. While doctors had suspected the ill effects of obesity since at least as far back as the 18th century, their evidence was anecdotal. The first large-scale studies of obesity and health were conducted in the early 20th century, when insurance companies began using comparisons of height and weight among their policyholders to show that "overweight" people died earlier than those of "ideal" weight. Subsequent actuarial and medical studies found that obese people were also were more likely to get diabetes, hypertension, and heart disease.
By the early 1900s, it was well-established that these ailments were the result of having too much adipose tissue—so the studies used functions of height and weight as little more than a proxy for determining how much excess body fat people had. It would have been more accurate for the actuaries to compare longevity data with more direct assessments of body fat—such as caliper-measured skinfold thickness or hydrostatic weighing. But these data were much harder for them to obtain than standard information on height, weight, and sex.
The insurance tables gave us correlations between these physical characteristics and expected lifespan. But medical researchers needed a standard measure of fatness, so they could look at the health outcomes of varying degrees of obesity across an entire population. For decades doctors couldn't agree on the best formula for combining height and weight into a single number—some used weight divided by height; others used weight divided by height cubed. Then, in 1972, physiology professor and obesity researcher Ancel Keys published his "Indices of Relative Weight and Obesity," a landmark study of more than 7,400 men in five countries. Keys examined which of the height-weight formulas matched up best with each subject's body-fat percentage, as measured more directly. It turned out that the best predictor came from Quetelet: weight divided by height squared. Keys renamed this number the body mass index.
The new measure caught on among researchers who had previously relied on slower and more expensive measures of body fat or on the broad categories (underweight, ideal weight, and overweight) identified by the insurance companies. The cheap and easy BMI test allowed them to plan and execute ambitious new studies involving hundreds of thousands of participants and to go back through troves of historical height and weight data and estimate levels of obesity in previous decades.