A critical appraisal of emerging obesity diagnostic frameworks to bridge gaps and refine clinical stratification

Novel obesity definitions that go beyond body mass index (BMI) have been recently suggested. They apply diverse clinical approaches and diagnostic criteria. The clinical utility of these new frameworks compared to the traditional BMI-based classification is currently unknown. We aimed to compare patient classification and their associated cardiometabolic risk profiles using three different systems: the traditional BMI-based classification, the Lancet Diabetes and Endocrinology Commission (LC) criteria, and the EASO New Framework (NF) criteria. A retrospective analysis was conducted on a cohort of 1002 individuals (mean age 51 years, 61% female). We assessed how each system classified participants and compared key cardiometabolic markers, including glycemic and lipid profiles, across these classifications. Significant discrepancies are found among the three systems. The traditional BMI and LC systems may underdiagnose people at high cardiometabolic risk. A crucial finding is that a significant proportion of participants labeled with ‘Preclinical Obesity’ by the LC criteria, but with ‘obesity’ by the EASO NF, consistently shows adverse metabolic profiles, including elevated glucose levels and unfavorable lipid profiles. The findings highlight the critical need for a unified diagnostic approach to obesity that more accurately captures the full spectrum of health risks. An improved classification system would ensure timely intervention and personalized management, particularly for those who, despite not being classified as having obesity by traditional or less stringent new criteria, already show significant metabolic risk. Obesity is usually diagnosed using body mass index (BMI), but BMI alone does not always reflect a person’s true health risks. New systems, including the Lancet Commission (LC) definition and the European Association for the Study of Obesity (EASO) New Framework (NF), have been proposed to improve diagnosis, yet it remains unclear how well they identify people at increased health risk. In this study, we analyzed clinical information and metabolic data (such as blood sugar, cholesterol, and insulin levels) from adults attending an endocrinology department and classified them using BMI, the LC and the NF criteria. We found that some definitions may misclassify individuals with increased cardiometabolic risk. Notably, many people labelled as having “preclinical obesity” under the LC criteria showed increased metabolic risk factors when assessed using the NF. These findings suggest that obesity classification systems may differ in how well they detect individuals at risk and that more consistent approaches are needed to guide decision making. Gomez-Ambrosi, Gonzalez-Alva, et al. compare BMI-based obesity classification existing definitions in a clinically characterized cohort. They find that disease-centric criteria exclude many individuals with substantial metabolic dysfunction, while broader frameworks better capture cardiometabolic risk.