Клінічна та профілактична медицина (Jun 2024)

A NEW ALGORITHM FOR DIAGNOSING OBESITY BASED ON INDICATORS OF BODY COMPOSITION

  • Olga S. Palamarchuk,
  • Myroslav M. Leshko,
  • Vladyslav O. Klushyn,
  • Svitlana V. Lukashchuk,
  • Halyna I. Moroz,
  • Volodymyr P. Feketa

DOI
https://doi.org/10.31612/2616-4868.4.2024.02
Journal volume & issue
no. 4
pp. 13 – 18

Abstract

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Introduction. Body mass index (BMI), which is measured as the ratio of body weight to height squared, is one of the widely used criteria for classifying overweight and obesity. Despite its popularity, BMI is often criticized for not taking into account individual differences in body composition and fat distribution, which can lead to inaccuracies in the classification of the degree of obesity. Aim. To develop and test a somatotype diagnostic algorithm based on the integration and comprehensive analysis of fat content, skeletal muscle mass, and fat distribution. Materials and methods. The study was conducted on a group of 82 men with different indicators of BMI. A developed algorithm was used to diagnose somatotype, which included body fat index (IBF), limb muscle mass index (IASM), and waist circumference to height ratio (WHtR). The results were analyzed and classified according to the defined criteria. Results. The proposed algorithm was tested on a sample of 82 examined men, who were divided into 2 groups depending on BMI. Thanks to our algorithm, it was possible to identify prognostically unfavorable somatotypes characterized by sarcopenia with a central type of fat distribution. These are F1S1C1 and F2S1C1 somatotypes, the total number of which was 9 examined (10.96% of the sample). Approbation of the algorithm was carried out on a group of examined men, confirmed its effectiveness and ability to detect different somatotypes, taking into account complex parameters of the body. Conclusions. Our research algorithm turned out to be a useful tool for somatotype diagnosis, especially in cases where BMI may not accurately reflect the real state of health. Taking into account individual differences in body components such as fat content, skeletal muscle mass and fat distribution, we provide a more accurate classification of somatotype and the possibility of a more individualized approach to treatment and prevention.

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