Exercise is considered as an unavoidable factor in maintaining health especially in individuals with lifestyle disorders such as diabetes. Studies till now considered only BMI and waist circumference as the surrogates for adiposity. However, the impact of body composition metrics for understanding the pathophysiology of comorbidities of diabetes such as CVD was less appreciated. A recent study published in the journal PLOS ONE revealed that high fat level contributes to reduced exercise capacity in adults with type 2 diabetes. The researchers used the data from the prospective randomized LOOK AHEAD study and machine learning algorithms to predict exercise capacity from the baseline data that included cardiovascular history, medications, blood pressure, demographic information, anthropometric and Dual-energy X-Ray Absorptiometry (DXA) measured body composition metrics.

      The recognition of body fat percentage as an important marker in determining CVD risk has prognostic implications with respect to cardiovascular morbidity and mortality. The LOOK AHEAD trial did a comparison between a group that underwent intensive lifestyle intervention focusing on weight loss achieved through dietary changes and increased physical activity and a control group that received only diabetes support and education. The inclusion criteria for the study were age between 45–74 years, BMI>25 kg/m2 (>27 kg/m2 if on insulin), and type 2 diabetes.

      According to the investigators, in both females as well as in males, the subtotal body fat percent and age are the most important features in predicting maximum exercise capacity, in persons with diabetes over the age of 40. Therefore, the study illustrates the significance of obtaining body composition metrics, as it may offer useful insights into the physical fitness and exercise capacity in persons with diabetes.