Unpacking adiposity: a narrative critical appraisal of diverse obesity definitions.

Abstract

Background: Obesity is a complex, multifaceted chronic disease that poses a major global health challenge. Traditionally, population-level screening and follow-up have relied heavily on body mass index (BMI). Although BMI provides a simple, standardized measure for epidemiological studies, it does not account for individual variations in muscle mass, fat distribution, or metabolic health. Consequently, relying solely on weight-to-height ratios-even when supplemented with waist circumference, waist-to-hip ratio, or waist-to-height ratio-limits precise individual diagnosis and comprehensive health risk assessment. Comprehensive risk stratification incorporating clinical factors beyond body weight is therefore needed to capture the heterogeneity of obesity and enable a more individualized, patient-centered approach to management.

Main body: This critical narrative review evaluates the main definitions and classification systems used for obesity, including the traditional World Health Organization classification, the Edmonton Obesity Staging System (EOSS), the Lancet Commission framework, the European Association for the Study of Obesity framework, and classifications based on weight history. BMI remains valuable for population-level assessment and may also be useful at the individual level when combined with additional anthropometric measurements and sex-, age-, and ethnicity-specific cutoff values. The EOSS complements anthropometric assessment by incorporating metabolic, physical, psychological, and functional consequences, thereby supporting treatment intensity according to disease severity. The Lancet Commission definitions of preclinical and clinical obesity broaden diagnosis beyond BMI but have raised concerns regarding the absence of standardized screening tools, potential diagnostic inconsistency, and possible delays in treatment for people classified as having preclinical obesity. Such limitations may be particularly relevant for children and adolescents, in whom delayed intervention may increase long-term health risks. Weight-history classifications provide an additional perspective by incorporating maximum weight attained in life, supporting realistic treatment goals, reinforcing the chronic nature of obesity, reducing stigma, and encouraging long-term treatment adherence.

Conclusion: No single classification adequately captures the biological and clinical heterogeneity of obesity. BMI should not be abandoned, but interpreted alongside anthropometric, metabolic, functional, psychological, and weight-history information. Integrating complementary classification systems may improve diagnostic accuracy, risk stratification, treatment prioritization, and patient-centered obesity care.