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Obesity is associated with a number of risk factors for cardiovascular disease. Body mass index (BMI) is the most commonly recommended and used anthropometric measure to classify general obesity in clinical and epidemiological studies. It is widely accepted that obesity increases the risk of heart disease and is thought to be a risk factor for adverse outcomes after cardiac surgery. However, recent studies show paradoxical results, wherein obese patients can experience fewer adverse events and lower mortality than patients with normal-low body mass index(BMI) . The discriminative capacity of BMI has been criticized because it cannot distinguish muscle mass from fat mass, or reflect fat distribution . Alternatively, abdominal obesity indices, such as waist circumference (WC) and waist-to-height ratio (WHtR), have been suggested to be better predictor of cardiometabolic abnormalities because they modulate the limitation of BMI. However, they were insufficient in studies.For this reason, scientists turned to find a new anthropometric formula that could better detect obesity-related mortality and morbidity and they developed 2 new methods. Body Shape İndex (ABSI) is calculated using waist circumference, BMI and height parameters. Body Roundness İndex (BRI) is calculated using waist circumference and height parameters. These new indices may reflect visceral adiposity and strongly predict cardiovascular risk, postsurgical outcomes and resource utilisation.
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