Goodbye BMI? Why Body Composition Is Gaining Ground in Clinics
The rise of incretin-based therapies for obesity care, like Wegovy (semaglutide) and Zepbound (tirzepatide), has brought renewed attention to the risk of muscle atrophy that can accompany rapid weight loss. To better assess changes in skeletal muscle mass, clinicians are turning to body composition assessment tools to track progress over time.
However, the ability to measure, interpret, and communicate changes in body composition is a skill most clinicians haven’t been formally trained in, leaving many feeling like it’s not a tool they can confidently use.
I want to push back against that assumption and offer some basic principles to help you better understand body composition and consider how it could be a valuable addition to your practice.
Redefining Health Through Body Composition
Body Mass Index (BMI), which compares an individual’s height to weight, has long been the standard for assessing how body size impacts health. However, due to its many limitations—including its inability to account for gender, age, activity level, hormonal status, and muscle mass—clinicians are shifting toward a more nuanced approach to evaluating the relationship between body shape, size, and overall health.
New consensus reports suggest that obesity exists on a biological continuum and can be categorized based on body adiposity, clinical presentation, and impairment in daily functioning.
We are also gaining a better understanding of how visceral and ectopic fat, stored deep within and around the organs, impacts an individual’s risk for chronic diseases.
A recent study suggests that simply living in a larger body is not a root cause of type 2 diabetes. Rather, when an individual exceeds their personal threshold for body adiposity, particularly around the liver and other vital organs, their risk increases significantly. This may help explain why relatively lean individuals can still develop type 2 diabetes.
The Risks Associated with Body Adiposity
Rather than focusing solely on the risks associated with higher body weight, researchers are shifting their attention to the risks linked to elevated levels of body fat (adiposity), especially when it exists in disproportion to lean body mass.
The term sarcopenic obesity is becoming more widely recognized. With the adoption of new consensus statements on diagnosing obesity, beyond relying on BMI alone, this imbalance of low skeletal muscle and high body fat is now understood to occur across a much wider range of body weights.
High levels of body adiposity are believed to be inflammatory, which can disrupt normal metabolic processes such as insulin sensitivity. Adipose tissue has also been linked to certain cancers, including breast, colon, and stomach cancer.
Understanding Body Composition
To accurately understand and interpret body composition, it’s important to have a general understanding of what the body is made of and how these components relate to one another in comparison to standard recommendations. Most body composition assessment tools categorize the body into three main components: adipose (fat) tissue, fat-free mass (including muscle, bone, and organs), and water.
Adipose or Fat Tissue
According to the World Health Organization, a healthy body fat percentage for adult males ranges from 15–20%, and 20–25% for adult females. In general, men with more than 25% body fat and women with more than 32% are considered at increased risk for adiposity-related comorbidities.
Athletes tend to fall on the lower end of the range due to higher lean muscle mass, whereas older adults and postmenopausal women may have higher body fat percentages due to natural muscle loss with aging and decreased reproductive hormone levels.
Fat-Free Mass
Fat-free mass generally includes skeletal muscle, bone, organs, connective tissue, and sometimes extracellular fluids, although these fluids are often categorized under total body water.
Skeletal muscle typically accounts for about 35–40% of total body weight. Younger men generally have the highest percentage of lean skeletal muscle, while older women tend to have the lowest. When skeletal muscle mass falls below 30% in men and 20% in women, it can be problematic and is associated with sarcopenia.
Body Water
Body water typically accounts for 50–65% of total body weight in men and 45–60% in women. Variations occur based on fluid intake, age, body composition, and overall health status.
Fat-to-Lean Mass Ratio
While there isn’t a specific ideal or target fat-to-lean mass ratio, a higher proportion of fat mass relative to lean mass is associated with increased risk for various diseases and overall poorer health. A middle-aged woman with a body fat percentage of 25% and lean mass percentage of 75% would have a fat-to-lean ratio of 1:3, or 0.33—with a lower ratio generally being more favorable for overall health.
Measuring Body Composition
In order to review and interpret body composition, it must first be measured using an appropriate tool. There are a variety of tools available for measuring body composition, including:
Anthropometry – Includes skinfold measurements, waist circumference, and related calculations.
Bioelectrical Impedance Analysis (BIA) – Found in smart scales and devices like the InBody scale; estimates body composition by measuring resistance to electrical currents.
Hydrostatic Weighing – Also known as underwater weighing; estimates body fat by comparing weight in and out of water.
Air Displacement Plethysmography (ADP) – Uses air displacement to estimate body volume and composition; commonly performed using the Bod Pod.
Dual-Energy X-ray Absorptiometry (DXA or DEXA) – A clinical tool that provides detailed information on fat, lean mass, and bone density.
Advanced Imaging (MRI and CT scans) – Used primarily in research or specialized medical settings to assess fat distribution and muscle quality.
Choosing the Right Measurement Tool
When selecting a body composition measurement tool, experts recommend evaluating cost, accuracy and precision, and feasibility of use in clinical practice. Below are two informative and insightful slides prepared by Dr. John M. Jakicic, PhD, for the Academy of Nutrition and Dietetics’ Obesity Care webinar, presented in May 2025.
Many clinics are choosing to use in-office bioimpedance tools, such as InBody, or are periodically referring patients for DEXA scans.
Adjusting Treatment Based on Body Composition
On average, weight loss from diet and exercise results in approximately 80% fat loss and 15–20% loss of lean body mass. Current research suggests that with GLP-1 use, the breakdown shifts to around 60–75% fat loss and as much as 25–40% loss of lean body mass. This highlights the importance of monitoring lean mass during treatment.
Changes in lean body mass that exceed 20 percent should raise concern. In some cases, it may be appropriate to down titrate the medication, prioritize nutrition with a focus on protein intake, and increase strength training to help preserve muscle mass
Getting Personal: A Review of My Data
I recently had the opportunity to complete both an InBody assessment, which uses Bioelectrical Impedance Analysis, and a commercial-grade DXA scan to evaluate my own body composition. The experience was eye-opening, to say the least.
While the reports use slightly different formats and terminology, making direct comparison a bit tricky, the results were fairly similar—suggesting that both tools can be viable options for tracking body composition changes over time.
- Lean Mass – InBody 97 lbs. DXA 90 lbs.
- Lean Precent – InBody 82%. DXA 76%.
- Body Fat Mass – InBody 20 lbs. DXA 22 lbs.
- Body Fat Precent – Inbody 17%. DXA 20%.
- Muscle Mass – InBody 52 lbs. DXA n/a
- Calories – InBody (BMR) 1321. DXA (RMR) 1281
Note that while the InBody provides an estimate of Basal Metabolic Rate (BMR), the DXA scan calculates Resting Metabolic Rate (RMR), which is typically slightly higher. Between the two, DXA is generally considered more accurate than InBody.
Integrating Body Comp in Your Practice
As our understanding of obesity and metabolic health evolves, so too should the tools we use in clinical practice. Body composition assessment offers a more accurate and personalized picture of health than BMI alone, particularly in the context of GLP-1 therapy and other obesity treatments.
By measuring changes in fat, lean mass, and water, clinicians can help minimize risks like muscle loss, and tailor nutrition and exercise plans more effectively.
If you’re considering incorporating body composition into your practice but aren’t sure where to start—you’re not alone. Contact me to set up a discovery call and explore how to bring body composition assessment into your clinic confidently and effectively.
- Academy of Nutrition and Dietetics. Considerations for Body Composition, Physical Activity, and Nutrition with Use of Obesity Medications [webinar]. EatRight Store. Published 2024. Accessed May 13, 2025. https://www.eatrightstore.org/product-type/online-learning/considerations-for-body-composition-physical-activity-and-nutrition-with-use-of-obesity-medications.
- Wadden TA, Chao AM, Moore M, Tronieri JS, Gilden A, Amaro A, Leonard S, Jakicic JM. The Role of Lifestyle Modification with Second-Generation Anti-obesity Medications: Comparisons, Questions, and Clinical Opportunities. Curr Obes Rep. 2023 Dec;12(4):453-473. PMID: 38041774; PMCID: PMC10748770.
- Taylor, Roy, et al. “Aetiology of Type 2 Diabetes in People with a ‘Normal’ Body Mass Index: Testing the Personal Fat Threshold Hypothesis.” Clinical Science, vol. 137, no. 16, Aug. 2023, pp. 1333–46. DOI.org (Crossref), https://doi.org/10.1042/CS20230586.
- Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organ Tech Rep Ser. 1995;854:1-452.
- Yoo, J.H., Kim, G., Park, S.W. et al. Effects of low skeletal muscle mass and sarcopenic obesity on albuminuria: a 7-year longitudinal study. Sci Rep 10, 5774 (2020). https://doi.org/10.1038/s41598-020-62841-y.
- Nishikori, S., Fujita, S. Association of fat-to-muscle mass ratio with physical activity and dietary protein, carbohydrate, sodium, and fiber intake in a cross-sectional study. Sci Rep 14, 10631 (2024). https://doi.org/10.1038/s41598-024-61289-8.
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