The body mass index misses half of the obesity diagnoses © ANSA/Ansa
The Body Mass Index (Bmi), the most used mathematical formula in the world to evaluate the body weight of men and women, invented in the 1800s by the Belgian mathematician Adolphe Quetelet, after 50 years of honorable service could soon retire or at least be accompanied by other parameters, such as the measurement of the waist and the estimate of the body composition measured by the skinfold caliper. According to an American study just presented at the Endo 2023 annual meeting of the Endocrine Society, concluded a few days ago in Chicago, the Bmi – which is obtained by dividing weight by the square of height – is wrong in the estimate of too much fat in 53 % of cases, giving indications inferior to reality. The research, conducted by Rutgers University, verified that half of those classified as obese on the basis of BMI alone were classified as such on the basis of Dexa, an ionizing radiation test capable of providing the most precise and accurate information on body composition.
However, adding waist circumference to the traditional BMI measure made 69% of obesity diagnoses congruent with Dexa, reducing the margin of error by 23%. “The main limitation of the BMI – underlines Anna Maria Colao, president of the Italian Society of Endocrinology (SIE) – is that it does not distinguish between water, bone mass, muscle mass and fat tissue nor between the accumulation of visceral fat, the so-called ‘pancetta’, and subcutaneous fat, thus not taking into account the influence of gender.Women, in fact – specifies the expert -, have more subcutaneous fat than men, located on the hips and thighs, which is less harmful to health than abdominal fat , which males accumulate more easily in the central sections of the body.It is therefore evident that using a single parameter that does not take into account these substantial differences leads both to erroneously overestimating obesity in women and to underestimating it in men, with a dangerous distortion physicians’ understanding of the risk of obesity-related disease and mortality”.
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