Abstract
The detection and classification of sarcopenia involves the analysis of many variables (50 to 60), which increases the time and costs required to diagnose and manage this condition. The objective of the study was to develop a synthetic statistical index to diagnose and classify sarcopenia in physically active older women. With this in mind, we conducted a cross-sectional study in 100 physically active women (64.88 ±4.4 years) in whom body composition measurements, muscle strength, and gait tests were performed. One thousand random selections of both training and test sets (80% and 20%, respectively) were made, logistic regression was fitted, and the regularization procedure (Elastic net regression) was performed. Results showed that the skeletal appendicular mass index (kg/m2) and slow gait speed (m/sec) were the variables that contributed the most to the diagnosis of sarcopenia. In conclusion, appendicular lean mass, gait speed, and explosive strength sufficiently describe the state of muscle and functional deterioration (sarcopenia) in physically active older women.