Reviews in Endocrine & Metabolic Disorders · 4 authors, 4 centres
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This narrative review examines classical and emerging obesity classification systems and argues that BMI alone is insufficient for accurate phenotyping. It concludes that incorporating body composition techniques and cardiometabolic risk factors into clinical practice can improve diagnosis and treatment of obesity.
BMI is described as not accurately reflecting body adiposity, while advances in body composition techniques have enabled identification of entities such as sarcopenic obesity. The authors highlight emerging developments such as machine learning-based classification systems incorporating genetic and metabolic traits. The authors advocate for implementing these advances in routine clinical practice to optimize obesity management.
