ABSTRACT
BACKGROUND: Sarcopenia may explain, in a large proportion, physical disability, falls and fractures, especially in aged elderly. However, a diagnosis in an operationally systematic, simple and low cost way is extremely important, particularly for home-based, epidemiological studies. OBJECTIVE: The purpose of this study was to develop and validate predictive equations of appendicular lean soft tissue (ALST) in elderly older than 80 years. DESIGN AND SETTINGS: A validation study was performed in 106 elderly (men and women) aged 80 years and older. MEASUREMENTS: Body weight, height, circumference (arm, midcalf, hip and waist) and triceps skinfold were measured in the elderly. ALST were measured using as the reference method dual-energy X-ray absorptiometry (DXA). RESULTS: Two models were predicted. The first model (ALST, in kg = 0.074*height + 0.277*weight - 0.144*triceps skinfold - 0.103*waist circumference + 1.831*gender -0.966), which considered all possible variables in stepwise multiple regression, presented better statistical performance (r2 = 0.82; SEE = 1.67 kg), compared to the second model (ALST, in kg = 0.138*height + 0.103*weight + 3.061*gender - 12.489), a more practical equation, due to a lesser quantity of predictive variables (r2 = 0.75; SEE = 1.94 kg). Both models were validated, however, it was verified trend (p<0.05) for overestimation of predicted ALST. CONCLUSION: In summary, two models for predicting ALST in men and women with age ≥ 80 years were developed and cross-validated. Model 1, with a greater number of predictive variables, presented a better accuracy than did the model with only three variables (height, weight, and gender). Validation studies are needed to test the usefulness of both models in other populations.