11/25/2025
Cleveland Clinic endocrinologist Ricardo Rosero partnered with the Center for Quantitative Metabolic Research to uncover which body composition metrics matter most. In this Q&A, he outlines what patients and clinicians need to know.
Cleveland Clinic endocrinologist Ricardo Rosero-Revelo, MD, has developed a predictive model that flags patients with obesity who are most likely to lose muscle mass during standard weight loss programs. His research-based insights, published in Clinical Nutrition ESPEN, could help clinicians design strategies to help patients lose fat while preserving muscle.
“Over the years, I’ve seen many of my patients lose weight but feel worse. I’ve also heard of colleagues who have had patients lose weight but keep the same body fat percentage,” he explains. “These symptoms are all known consequences of too much muscle loss, which told me something was missing in our approach to weight management as physicians.”
Dr. Rosero-Revelo discusses what his research means for patients and providers, and how to lose weight without losing muscle.
I wanted to understand which body composition metrics predict muscle loss during weight loss, so I could tailor treatment plans to maximize muscle retention for my at-risk patients.
I focused on body composition because body weight or BMI alone doesn’t tell us enough about what’s happening inside the body. Body composition gives us a clear picture of fat volume, muscle quantity and cellular integrity. If you don’t see a patient with obesity through body composition, you have a narrow vision.
Almost everybody who goes through any kind of weight management program will lose around 10 to 20 percent of their muscle mass. Any time you have a big calorie deficit, whether from medication or diet, your body will break down muscle because muscle is calorically expensive to maintain. However, some people don’t lose any, and some even gain muscle.
Losing muscle during weight loss sets off a cascade of problems. Muscle burns more calories than fat, so losing it slows metabolism. With a lower metabolic rate, the body needs fewer calories to maintain weight, making regain more likely.
Muscle also helps fight inflammation, while fat tissue acts as an inflammatory organ. When muscle disappears, inflammation takes over, leaving patients feeling sick, fatigued, and less likely to exercise.
Then comes fat infiltration. Because fat and muscle share the same stem cell origin, weakened muscle tissue can be invaded by fat. The result is a muscle that looks big but is filled with fat, offering no strength.
Together, these consequences make a perfect storm of less muscle, less energy, less activity, slower metabolism and more weight regain. It can become a cycle.
We partnered with Cleveland Clinic’s Center for Quantitative Metabolic Research and analyzed body scans from over a thousand patients who had received weight loss care (without the use of anti-obesity medications) in the past decade. This gave us a large dataset to look for patterns.
Two metrics stood out: phase angle and fat-free mass. Phase angle reflects cell integrity, and fat-free mass reflects muscle cell quantity. Both were strong predictors of muscle loss during weight reduction.
Fat-free mass includes muscle, water, and other tissues. It’s a way to understand how much lean tissue you have compared to fat. In our study, people with higher fat-free mass were more likely to lose muscle during weight loss. So, it’s an important metric for predicting risk.
Yes, it’s ironic. If you start with a lot of muscle, you have more to lose. When you go through aggressive weight loss interventions, your body tries to protect fat because fat is an energy reserve. Muscle becomes a sacrifice. People with very little muscle don’t have much to lose, so their loss percentage is smaller. That’s why these patients need extra attention with protein and resistance training.
Better sleep hygiene, more protein (up to 1.6 grams per kilogram per day) and resistance training. Walking or biking is good, but for patients at elevated risk of losing muscle mass, strength training matters more than cardio.
This retrospective study on past patients gave us the foundation we needed. Now we’re doing a prospective study on patients in real time to validate our model and refine recommendations. Ultimately, we want to personalize treatment so our patients lose fat, not muscle.
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