Bioimpedance analysis: Potential for measuring lower limb skeletal muscle mass

Background: Ambulation, balance, and lower extremity bone mass and strength are all partially dependent on lower limb skeletal muscle mass. At present , both research and clinical methods of evaluating lower limb skeletal musc le mass as a component of nutrition assessment are limited. One potential s imple and inexpensive method is lower extremity bioimpedance analysis (BIA) . The present study had two objectives: to examine the determinants of lowe r limb resistance, with the underlying hypothesis that fluid-containing mus cle is the main electrical conductor of the lower limbs; and to establish i f a correlation of equivalent magnitude and similar covariates is observed when height squared (H-2) is used instead of lower limb length squared (L-2 ) in multiple regression models relating resistance to independent variable s. Methods: Lower limb resistance was measured using a contact-electrode BI A system, and lower limb fat and skeletal muscle were estimated by dual-ene rgy x-ray absorptiometry in healthy adults. A physical BIA model was develo ped in the form of a regression equation with pathlength (as L-2 and H-2)-a djusted resistance as dependent variables and lower limb skeletal muscle, f at, age, and gender as potential independent variables. Results: There were 94 subjects, 34 men and 60 women, with a mean (+/-SD) age of 41.5 +/- 17.8 years. Strong associations were observed between L-2/resistance and lower limb skeletal muscle, although for both men and women, age entered into the model as a significant covariate (total R-2, men = .79 and women = .72; bo th p < .001). Similar models were observed with H-2/resistance as dependent variable. Additional analyses showed a significantly lower resistance in l ower limb skeletal muscle and height-matched old vs young subjects. Conclus ions: Strong associations exist; between measured fewer limb resistance and lower limb muscle mass, adjusting for electrical path length either by L-2 or H-2. These observations suggest the potential of predicting skeletal mu scle using BLA-measured lower limb resistance adjusted for stature. Age is also an independent variable in lower limb resistance-skeletal muscle assoc iations, suggesting the need to establish underlying mechanisms of age-rela ted resistance effects and to consider subject age when developing BIA pred iction models.