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Author Spotlight: Assessing the Cardiovascular Profile of Patients with Metabolic Syndrome
Published on: September 27, 2024
Cardiometabolic risk stratification using a novel obesity phenotyping system based on body adiposity and waist
Javier Gómez-Ambrosi1, Victoria Catalán1, Beatriz Ramírez1
1Metabolic Research Laboratory, Clínica Universidad de Navarra, Pamplona, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Pamplona, Spain; Obesity and Adipobiology Group, Instituto de Investigación Sanitaria de Navarra (IdiSNA) Pamplona, Spain.
Background:
The estimation of obesity-associated cardiometabolic risk does not usually take into account body composition or the distribution of adiposity. The aim of the present study was to assess the clinical usefulness of a novel obesity phenotyping system based on the combination of actual body fat percentage (BF%) and waist circumference (WC) according to the cardiometabolic risk estimation.
Methods:
A classification matrix combining BF% and WC as measures of both amount and distribution of adiposity establishing nine body phenotypes (3 BF% x 3 WC) was developed. Individuals were grouped in five different cardiometabolic risk phenotypes. We conducted a validation study in a large cohort of White subjects from both genders representing a wide range of ages and adiposity (n = 12,754; 65 % females, aged 18-88 years).
Results:
The five risk groups using the matrix combination of BF% and WC exhibited a robust linear distribution regarding cardiometabolic risk, estimated by the Metabolic Syndrome Severity Score, showing a continuous increase between groups with significant differences (P < 0.001) among them, as well as in other cardiometabolic risk factors. An additional 24 % of patients at very high risk was detected with the new classification system proposed (P < 0.001) as compared to an equivalent matrix using BMI and WC instead of BF% and WC.
Conclusions:
A more detailed phenotyping should be a priority in the diagnosis and management of patients with obesity. Our classification system allows to gradually estimate the cardiometabolic risk according to BF% and WC, thus representing a novel and useful tool for both research and clinical practice.
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