Explanators of Sarcopenia in Individuals With Diabesity: A Cross-Sectional Analysis

Abstract

Background and purpose: Excess lower extremity intermuscular adipose tissue (IMAT), reduced strength, and functional limitations are common in obese individuals with and without diabetes (the former termed diabesity). Individuals with diabesity are particularly susceptible to accelerated sarcopenia, which may be underdiagnosed. The purpose of this study was to determine critical values for leg IMAT volume, plantar flexor (PF) muscle strength, and physical performance that help identify individuals with diabesity who have sarcopenia.

Methods: Forty-three age- and sex-matched obese adults were studied: 12 with type 2 diabetes, 21 with diabetes and peripheral neuropathy, and 10 nondiabetic controls. Dual-energy x-ray absorptiometry-derived skeletal muscle index determined classification of sarcopenia. Leg fat (% IMAT), ankle (PF) peak torque, and power while ascending 10 steps, were used as explanators of sarcopenia. Receiver operating curves identified critical values for each explanator individually. Logistic regression models using all 3 explanators, and only PF torque and stair power, were also created. Receiver operating curve analyses identified the predicted probability that maximized each model's sensitivity and specificity. A leave-one-out cross validation was used to simulate the models' performance in an independent sample.

Results and discussion: Thirty-two participants were sarcopenic, and 11 were not. Critical values for individual explanators were 21% IMAT, 68 Nm PF torque, and 441 watts of stair power. Predicted probabilities of .76 and .67 were chosen as the optimal cutoff probabilities for the model combining all 3 explanators, and the model combining PF torque and stair power, respectively. The cross-validation analysis produced an accuracy of 82.4%, using the cutoff probability of .5, and an accuracy of 76.5% using the cutoff of 0.76. The area under the curve for the cross validation receiver operating curve analysis was 0.82. Critical values of leg % IMAT, PF torque, and stair power can classify individuals with diabesity as sarcopenic. The results of the cross validation give us confidence that the sample used in this study was representative of the target population, and suggests models created from this sample may perform well in externally derived data sets.

Conclusion: Clinicians may be able to use these critical values to select interventions that specifically target sarcopenia. Measures of % IMAT, PF torque, and stair power may offer a customized alternative to traditional sarcopenic classification systems, which may not be optimally suited to the common impairments among individuals with diabesity.

Fig. 1

Results from the individual and combined ROC analyses. a. Scatterplot of leg intermuscular adipose tissue volume (% IMAT; y-axis) and skeletal muscle index (% SMI; x-axis) for all participants. Triangles represent males. Circles represent females. Filled shapes denote participants who were sarcopenic. Open circles denote participants who were not sarcopenic. The dotted line shows the 21% IMAT cutoff determined through ROC analysis. b. Scatterplot of stair power (y-axis) and skeletal muscle index (%SMI; x-axis) for all participants. Symbols are the same as A. The dotted line shows the 441 watts of stair power cutoff determined through ROC analysis. c. Scatterplot of PF peak torque (y-axis) and skeletal muscle index (%SMI; x-axis) for all participants. The dotted line shows the 68 Nm cutoff determined through ROC analysis. d. ROC curves for each logistic regression model. The (- • -) line represents the ROC curve for the linear combination of %IMAT, PF peak torque, and stair power. The black dot on the curve denotes the cutoff probability of .76, and its sensitivity and 1-specificity. The (- - -) line represents the ROC curve for the linear combination of PF peak torque and stair power. The black dot on the curve denotes the cutoff probability of .67, and its sensitivity and 1-specificity. The (___) line represents chance. The area under the curve (AUC), and its significance, for each model is reported (p<.05 indicates classification by the model is significantly better than chance). *Note: 4 participants missing data for all 3 variables, 2 missing %IMAT, 2 missing PF torque, and 1 missing stair power.