REAL BODY

Overview

Obesity is characterized by excessive or abnormal accumulation of fat and is a significant contributor to chronic diseases, including type 2 diabetes, fatty liver disease, cardiovascular disease and some cancers. Obesity costs the US healthcare system nearly $173 billion annually with global impact expected to exceed $4.32 trillion annually by 2035.

Current medical research and practice rely heavily on total body weight and Body Mass Index (BMI) to evaluate obesity. While convenient and accessible, both measures are unable to differentiate between total fat, visceral fat, and fat-free mass; therefore, not an accurate representation of adiposity nor body composition, and unable to inform on the quality of weight loss. Additionally, there is a high degree of variability in fat and lean mass distribution across the US population.

The Lancet Diabetes & Endocrinology Global Commission has highlighted the need for solutions that go beyond BMI to address the heterogeneity of obesity. Similarly, the FDA’s Draft Guidance on Developing Drugs and Biological Products for Weight Reduction underscores the importance of monitoring body composition in clinical trials recognizing that BMI and weight loss alone are insufficient metrics for evaluating the success of obesity treatments. Currently, advanced imaging methods like DXA and MRI are considered the gold standards for accurately measuring body composition of total fat mass, fat-free mass, and visceral fat. However, these methods have significant drawbacks including cost, time, and accessibility, which make them impractical for use in clinical practice and drive-up costs in clinical trials. Although BIA and 3DO systems are readily accessible and affordable methods for measuring body composition, their performance has not been thoroughly evaluated across the wide array of available devices.

This prospective study addresses the need for accessible, accurate body composition measurement by validating the BUILDING BRIDGES TO BREAKTHROUGHS™ performance of modern BIA and 3DO systems against DXA and MRI. The study will assess the cross-sectional accuracy and between-day reliability of these methods to better inform their clinical and research applications. By generating robust data on their performance, this project hopes to establish scalable and affordable tools for accurately measuring total fat mass, fat-free mass, and visceral fat. These tools will enable healthcare providers to identify patients for treatment and to monitor patients’ treatment. It will also afford drug developers the opportunity to recruit people to clinical trials based on their total fat mass and/or body composition instead of BMI. Ultimately, this work will advance clinical practice, improve patient care, and lay the foundation for future obesity treatment research. By aligning with both scientific and regulatory priorities, this project aims to transform the landscape of obesity care and research, making body composition a practical, reliable metric for improving patient outcomes and advancing the development of next-generation obesity treatments.