Instead, the researchers said, clinical exercise testing — a diagnostic procedure to measure a person’s physiological response to exercise — may be a more useful tool to help individuals achieve intended fat loss goals. The study, which used a machine learning-based modeling approach, was published online today in Nutrition, Metabolism and Cardiovascular Disease.

“People with a goal of weight or fat loss may be interested in exercising at the intensity which allows for the maximal rate of fat burning. Most commercial exercise machines offer a ‘fat-burning zone’ option, depending upon age, sex, and heart rate,” says lead author Hannah Kittrell, MS, RD, CDN, a PhD candidate at Icahn Mount Sinai in the Augmented Intelligence in Medicine and Science laboratory. “However, the typically recommended fat-burning zone has not been validated, thus individuals may be exercising at intensities that are not aligned with their personalized weight loss goals.”

Ms. Kittrell is also Director of the Mount Sinai Physiolab, a clinical body composition and exercise physiology laboratory at Mount Sinai Morningside.

The term FATmax is sometimes used to represent the exercise intensity and associated heart rate at which the body reaches its highest fat-burning rate during aerobic exercise. At this point, fat is a significant fuel source and therefore this intensity may be of interest to those seeking to optimize fat loss during workouts.

As part of the study, the researchers compared heart rate at FATmax, as measured during a clinical exercise test, to predicted heart rate at percentages of maximal effort within the typically recommended “fat-burning zone.” In a sample of 26 individuals, the researchers found that there was poor agreement between measured and predicted heart rate, with a mean difference of 23 beats per minute between the two measures. This suggests that general recommendations for a “fat-burning zone” may not provide accurate guidance.

Next, the researchers plan to study whether individuals who receive a more personalized exercise prescription demonstrate more weight and fat loss, as well as improvement of metabolic health markers that identify health risks like type 2 diabetes, obesity, and heart disease.

“We hope that this work will inspire more individuals and trainers to utilize clinical exercise testing to prescribe personalized exercise routines tailored to fat loss. It also emphasizes the role that data-driven approaches can have toward precision exercise,” says senior author Girish Nadkarni, MD, MPH, Irene and Dr. Arthur M. Fishberg Professor of Medicine at Icahn Mount Sinai, Director of The Charles Bronfman Institute of Personalized Medicine, and System Chief, Division of Data-Driven and Digital Medicine, Department of Medicine.

The paper is titled “Discrepancy between predicted and measured exercise intensity for eliciting the maximal rate of lipid oxidation.”

The remaining authors are Fred J. DiMenna (The Mount Sinai Hospital), Avigdor D. Arad (Tel Aviv Medical Center), Wonsuk Oh (Icahn Mount Sinai), Ira Hofer (Icahn Mount Sinai), Ryan W. Walker (Icahn Mount Sinai), Ruth J.F. Loos (Icahn Mount Sinai & University of Copenhagen), and Jeanine B. Albu (Icahn Mount Sinai).