Comparison of predictive equations of lean mass in young and postmenopausal women.

BACKGROUND AND AIM: The lean mass (LM) is a predictor of functional capacity, quality of life, and mortality. In this way, the LM should be measured by reliable methods. However, it presents high cost and generally predictive equations are used in clinical practice, but little is known which is the best predictive equation of LM in women. The purpose of the present study was to verify which predictive equation of LM correctly estimates the LM in young and postmenopausal women. METHODS: Eighty-one women aged 19-81 years were evaluated. Body weight, height, waist circumference, and skin folds (bicipital, tricipital, subscapular and suprailiac) were measured. The LM was evaluated by DXA and also estimated using the predictive equations of Hume I, Hume II, Salamat, Kulkarni I, and Kulkarni II. Bland-Altman analysis was performed to evaluate the over/underestimation of the LM by predictive equations. RESULTS: The equations of Salamat, Kulkarni II, Hume I and Kulkarni I overestimated the LM by 0.0 (7.0; -6.9) kg; 2.3 (7.5; -3.0) kg; 5.1 (9.0; 0.4) kg; and 9.7 (16.3, 3.1) kg, respectively; whereas Hume II equation underestimated the LM by -16.9 (-11.5; -22.2) kg. CONCLUSIONS: The equation that presented a better prediction of LM was Salamat. However, it should be used with caution in clinical practice since this equation showed elevated confidence intervals and limits of agreements, and can lead to significant errors for some individuals.

Adductor pollicis muscle thickness has a low association with lean mass in women.

BACKGROUND & AIM: Lean mass (LM) is a functional component of body composition and is an important parameter of nutritional status assessment. The adductor pollicis muscle thickness (APMT) has been used as a predictor of LM, but it is not well known if this method presents a higher prediction of LM than simple anthropometric measurements, such as weight. Thus, we aimed to associate APMT (alone and plus weight) with LM in women. METHODS: This cross-sectional study was conducted with 82 young and postmenopausal women. Body weight (Filizola®) and height (Welmy®) was quantified and APMT was measured by Lange® caliper. Body composition (LM and fat percentage) was estimated by dual-energy X-ray absorptiometry. RESULTS: APMT was positively correlated with LM (r = 0.35; p = 0.001), however, weight was strongly correlated with LM (r = 0.81; p < 0.001). APMT showed a prediction of 12% of LM (ß = 0.346, R2 = 0.120, p < 0.001), and weight explained the variations of LM by 65% (ß = 0.808, R2 = 0.654, p < 0.001). When weight and APMT were evaluated together, there was an increase of only 0.06% in LM prediction (ß = 0.820, R2 = 0.655, p < 0.001), compared to weight alone. CONCLUSION: When compared to weight, APMT showed a low association with LM. These results suggest that a simpler anthropometric measurement, such as weight, can be a better predictor of LM than APMT.