We here at the Kansas Business Group on Health are big on the BMI (no pun intended). The “body mass index,” which compares a person’s weight in kilograms to the square of his height in meters (BMI = kg/m2), is a very crude predictor of metabolic health. I’m willing to bet that if you’ve used a commercial health risk assessment for your employees, the vendor calculated everyone’s BMI. But when we use a standard like the BMI, we’re obligated to discuss its limitations.

The BMI is not a recent, cutting-edge invention. Belgian polymath Adolphe Quetelet first described it in the 19th century. After a couple of relatively fallow centuries in the scientific literature, it reemerged in 1972 thanks to legendary University of Minnesota nutrition researcher Ancel Keys. But the cutoffs for what constituted normal or excessive body weight for a given height were hard to settle on. At first in the United States, data from the second National Health and Nutrition Examination Survey (NHANES II) were used to define obesity in adults as a BMI of 27.3 kg/m2 or more for women and a BMI of 27.8 kg/m2 or more for men. Investigators based these seemingly arbitrary numbers on the gender-specific 85th percentile values of BMI for persons 20 to 29 years of age in NHANES II, the years 1976-1980, a big problem considering the year-over-year growth of excess body weight in America. Then, in 1998, an NIH expert panel elected to adopt the World Health Organization (WHO) classifications for overweight and obesity. Since then, we’ve considered a BMI of ≥25.0 kg/m2 to be “overweight” and a BMI of ≥30.0 kg/m2 to be “obese.” The American Medical Association declared obesity a disease in 2013, using the same definitions. Nowadays, the US Preventive Services Task Force, the independent panel whose recommendations underlie which preventive services are paid for by insurance, recommends screening all adults and children over age six with a BMI. However, experts still define childhood obesity as a BMI ≥95th percentile rather than a hard cutoff as in adults.

Defining an abnormal body weight in hard numbers like this has its advantages. In theory, it removes subjective judgment from the clinician or the patient on the shape of the patient’s body and simply places everyone in a category of risk. We use these cutoffs in our work here at KBGH in CDC-funded work. A person with an “overweight” BMI of 25.0 kg/m2 or above, for example, qualifies for the Diabetes Prevention Program, a one-year behavioral change program meant to reduce the risk of developing diabetes over time. Since the Diabetes Prevention Program has been shown to increase quality of life, decrease absenteeism, and lower the cost of care, we encourage folks to see if they qualify.

But given its long pedigree and the crudeness of the measure, it comes as no surprise that the BMI and similar measures have some shortcomings. As early as 1942, investigators showed that professional football players initially rejected for military service due to elevated weights relative to their heights actually had smaller proportions of body fat than nonathletic young naval men. A later NFL Study revealed that some players, even at positions not typically associated with body mass, such as wide receivers, had elevated BMIs due to their massive muscles. The BMI does not take into account body composition, after all.

And we’ve long known that different racial groups (speaking of measures with some shortcomings) have different BMI “cutoffs” for risk of disease. The recognition that different BMI cutoffs should trigger actions to prevent complications has caused investigators to try to identify ethnicity-specific BMI cutoffs. A new study in the Lancet attempts to do just that.

Investigators looked at millions of visits of non-diabetic patients to primary care offices over about thirty years. They collapsed the self-reported ethnicities of the patients into five categories: White, South Asian, Black, Chinese, and Arabic. Since the study was in England, the population was overwhelmingly white (90.6%), so take that into account as you interpret the results.

They used the White BMI cutoff of ≥30 kg/m2 as their reference group and compared everyone else to the risk in that population. The numbers showed that to equal the diabetes risk of a population of White patients with a BMI of ≥30 kg/m2, other ethnic populations would need to exceed the following cutoffs:

• South Asian: ≥23.9 kg/m2

• Black: ≥28.1 kg/m2

• Chinese: ≥26.9 kg/m2

• Arabic: ≥26.6 kg/m2

They concluded that “Revisions of ethnicity-specific BMI cutoffs are needed to ensure that minority ethnic populations are provided with appropriate clinical surveillance to optimise the prevention, early diagnosis, and timely management of type 2 diabetes.” That is, in the opinion of the researchers, we need to take into account the self-reported ethnicity of the person when we decide how risky their BMI is. I guess I’m on board with this recommendation as long as we don’t use the data to stigmatize but instead to non-judgementally and proactively address health risks.

If your company is interested in getting more employees at risk of diabetes into the Diabetes Prevention Program, please contact us!

As the Medical Director of the Kansas Business Group on Health, I’m sometimes asked to weigh in on hot topics that might affect employers or employees. This is a reprint of a blog post from KBGH.