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Review
. 2025 Jun 18.
doi: 10.1007/s11154-025-09976-3. Online ahead of print.

Exploring obesity phenotypes: a longitudinal perspective

Affiliations
Review

Exploring obesity phenotypes: a longitudinal perspective

Ricardo Rosero-Revelo et al. Rev Endocr Metab Disord. .

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.

Panel (A) illustrates the evolution of obesity diagnosis, contrasting traditional anthropometric measurements with modern technologies like bioelectrical impedance analysis (BIA) for accurate body composition assessment. Panel (B) represents the conventional assumption that weight loss follows a predictable trajectory with proportional reductions in fat and muscle mass. Panel (C) showcases our longitudinal study findings in 709 Latino patients with obesity who underwent nutritional and exercise interventions, revealing four distinct phenotypic trajectories: Lean Preservers (49%), Mass Reducers (32%), Mass Retainers (10%), and Adipose Overload (9%), demonstrating the importance of dynamic body composition assessment beyond static BMI-based classification.

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Conflict of interest statement

Declarations. Statement of Ethics: All authors have made significant contributions to the research and manuscript preparation. This study utilized anonymized bioimpedance data, and in accordance with Colombian regulations (Resolution 1480 of 2011), written informed consent was not required, as the study involved minimal risk and did not include identifiable personal information. The research adhered to ethical standards, including the Declaration of Helsinki. The study protocol was reviewed and approved by the Institutional Ethics Committee of CES University in Colombia, under approval number 880-143-2 (dated December 10, 2019). Competing interests: The authors declare no competing interests.

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References

    1. Rubino F, Cummings DE, Eckel RH, Cohen RV, Wilding JPH, Brown WA et al. Definition and diagnostic criteria of clinical obesity. Lancet Diabetes Endocrinol [Internet]. 2025; Available from: http://www.ncbi.nlm.nih.gov/pubmed/39824205
    1. Bosy-Westphal A, Müller MJ. Diagnosis of obesity based on body composition-associated health risks—Time for a change in paradigm. Obes Rev. 2021;22:S2. - DOI
    1. Costa-Urrutia P, Vizuet-Gámez A, Ramirez-Alcántara M, Guillen-González MÁ, Medina-Contreras O, Valdes-Moreno M, et al. Obesity measured as percent body fat, relationship with body mass index, and percentile curves for Mexican pediatric population. PLoS ONE. 2019;14(2):1–13. - DOI
    1. Deurenberg P, Yap M, van Staveren W. Body mass index and percent body fat: a meta analysis among different ethnic groups. Int J Obes. 1998;22(12):1164–71. - DOI
    1. The Association of Life Insurance Medical Directors and the Actuarial Society of America. Medico-actuarial mortality investigation. The Association of Life Insurance Medical Directors and the Actuarial Society of America. 1913. Obes Res. 1995;3(1):100–6.

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