Exploring obesity phenotypes: a longitudinal perspective

Abstract

Traditional reliance on Body Mass Index (BMI) as a diagnostic tool for obesity is increasingly challenged due to its inability to differentiate between fat and lean mass and to capture fat distribution. Emerging evidence-including findings from our longitudinal study in Latino patients with obesity and insights from the 2025 Lancet Commission on Obesity-suggests that a comprehensive evaluation of body composition is essential for accurate risk stratification. This review synthesizes historical perspectives and recent developments in obesity phenotyping, detailing how the field has evolved from simple BMI-based assessments to multifaceted approaches incorporating bioelectrical impedance analysis (BIA) and supplementary anthropometric measures such as waist circumference and waist-to-hip ratio. We also examine the metabolic, genetic, and hormonal mechanisms underlying phenotypic variability, which help explain why individuals with similar BMIs may exhibit markedly different health risks. By integrating our original data with an extensive review of current literature, we demonstrate that refined obesity phenotyping can serve as an early indicator of progression from preclinical to clinical obesity. Such nuanced classifications offer the potential for more personalized therapeutic interventions aimed at optimizing weight loss outcomes and reducing cardiometabolic risk. Overall, our findings advocate for a multidimensional approach to obesity assessment that promises to improve clinical outcomes through tailored, phenotype-based strategies.

Fig. 1

Classification of individuals based on body mass index (BMI) and metabolic health status. MUNO (metabolically unhealthy non-obesity), MUNW (metabolically unhealthy normal weight), MUO (metabolically unhealthy obesity), MHNO (metabolically healthy non-obesity), and MHO (metabolically healthy obesity) [14]

Fig. 2

Body Composition Assessment in Obesity Diagnosis: A Dual Approach. Left (Bicompartmental Approach): Focuses on quantifying body composition by assessing the proportions of fat mass and muscle mass. This approach provides insight into the overall balance of tissue types within the body, helping to better understand the patient’s metabolic health. Right (Fat Distribution): Evaluates where the fat is distributed within the body, emphasizing the importance of differentiating between visceral, subcutaneous, and ectopic fat. This is critical for understanding the metabolic risks associated with obesity, as fat distribution plays a key role in determining health outcomes

Fig. 3

Body Composition Phenotypes. (a) Body-composition phenotype classification criteria by groups of SMI (Skeletal Muscle Index) and FMI (Fat Mass Index) [17, 18]. The quadrants represent four possible phenotypes: Low Adiposity - High Muscle Mass (LA-HM), High Adiposity - High Muscle Mass (HA-HM), Low Adiposity - Low Muscle Mass (LA-LM), and High Adiposity - Low Muscle Mass (HA-LM). (b) Proposed dynamic phenotypic trajectories during weight loss observed longitudinally: Lean Preservers (lose fat, gain muscle), Mass Retainers (gain both fat and muscle), Mass Reducers (lose both fat and muscle), and Adipose Overload (gain fat, lose muscle)