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Although the total “Timed-Up-and Go” test (TUG) performance time can characterize an age-related decline of general mobility, this result alone doesn’t give any detailed information about the test subtasks. The primary objective of the study was to identify in nursing home women a variable extracted from instrumented TUG (iTUG) that is the best predictor of age. The secondary objective was to assess whether this variable is associated with the results of the isometric knee extension peak torque (IKEPT); lower limb strength measured by the 30-s chair stand test (30sCST), and walking capacity measured by the 6-min walk test (6MWT). Twenty-six women (mean ± SD: age—85.8 ± 3.6 years; body weight—59.4 ± 12.3 kg; body height—151.0 ± 7.3 cm; BMI—26.0 ± 4.9 kg/m2) performed iTUG (while wearing a body-fixed inertial sensor) and functional tests. Total iTUG performance time significantly correlated with age (r = 0.484; p 0.05). Additionally, the subjects’ age correlated with 30sCST (r = −0.422; p 0.05). The obtained results suggest that in the oldest old group of nursing home women an age-related decline in TUG performance is mainly associated with a reduction of “explosive” strength of lower limb muscles.

The aims of the study were to assess whether commonly used anthropometric indices are associated with body fat measures obtained by Bioelectrical Impedance Analysis (BIA) method, and to determine the best anthropometric predictor of BIA-based body fat percentage (%Fat) and visceral fat rating (VFR) in elderly women. The sample consisted of 24 women aged 80 years and older, the residents of long-term care facilities in Upper Silesia (Poland). All women were subjected to standard anthropometric measurements including the following variables: body weight, body height, waist circumference, hip circumference and neck circumference. On the basis of these measures Body Mass Index (BMI) as well as waist-to-hip ratio (WHR) were calculated. The subjects’ %Fat and VFR were determined by body composition analyzer TANITA BC 420MA (Japan). Pearson’s correlation coefficients were used to quantify the relationships between variables. Stepwise multiple regression analysis with backward elimination was performed to identify possible predictors. The basic characteristics of the investigated subjects were as follows (mean±SD): age -85.5±3.7 years;body weight -60.4±11.6 kg;body height -150.6±7.6cm; BMI -26.6±4.6 kg/m2; %Fat -31.3±9.6%; VFR -10.7±2.5. Both of BIA-based measures significantly, positively correlated with body weight, BMI and circumferences of waist, hip and neck (r values from 0.477 to 0.835). The multiple regression analysis for %Fat revealed that the body weight was the only variable statistically significant (r2=0.414; p