Heuristic evaluation of body mass index with bioimpedance data in the Mexican population

Abstract Introduction: given the problematic battle against cardio-metabolic diseases and the increase in computational power, different applications are being developed to help estimate overweight and obesity in the population. Objectives: to evaluate the body mass index (BMI) formula (kg/m2), taking body fat measured by bioimpedance as a reference and comparing it with variations of the same form obtained by applying algebraic transformation rules using an artificial intelligence heuristic search method. Material and methods: an artificial intelligence heuristic method was applied to search for the formula that most accurately calculates people’s body fat percentage. The formula was generated from body mass and stature, variables used to estimate BMI. Thousands of formulas involving body mass and stature were generated from BMI using transformation rules with algebraic variations and increased and decreased constants. Results: body mass, stature, and body fat percentage data set from 142 female and 150 male participants were used. Body mass and stature were used to classify participants into two classes based on body fat percentage (excessive or adequate, with cutoff points of 30 % for women and 15 % for men). The Youden index guided the search algorithm by evaluating candidate formulas to generate new ones. Among the formulas with the maximum value of the Youden index, Body mass1.1 / Stature2.9, is proposed as the best candidate as an alternative formula to apply instead of the BMI conventional formula. Conclusions: although BMI showed a high Youden index, the AI algorithm found that the W1.1 / H2.9 formula is even more efficient in assessing body fat in men and women.