SCREENING FOR SARCOPENIA IN A SMALL COHORT OF ELDERLY CARE HOME RESIDENTS USING HANDGRIP STRENGTH DYNAMOMETRY; AND BIOELECTRICAL IMPEDANCE ASSESSMENT OF SKELETAL MUSCLE MASS AND FAT FREE MASS
J Aging Res Clin Practice 2012;1(3):219-224
Objective: The loss of skeletal muscle strength and mass termed sarcopenia is linked to disability, frailty, nutritional risk and poor outcomes in the elderly. This study aimed to perform screening for sarcopenia in a group of elderly care home residents using handgrip strength (HGS) dynamometry and bioelectrical impedance assessment (BIA). Design: An observational study performed over a 2 month period with BIA screening performed at week 0 and HGS at 0, 4 and 8. Setting: A residential care home in Lincolnshire, United Kingdom. Participants: 14 elderly Caucasian participants were recruited (8 females and 6 males), mean age 85.6 ±6.2 (77-96). Measurements: Anthropometric measurements (height, weight, mid-upper arm (MUAC) and calf circumferences (CC)), calculation of body mass index (BMI), HGS, and BIA (Bodystat ®1500 MDD) were performed. Skeletal muscle mass index (SMI), kg/m2 was calculated using an equation by Janssen et al, 2000 and fat free mass index (FFMI), kg/m2 using both the Bodystat manufacturers equation and from Kyle et al, 2000. Cut-off points and criteria from the European Working Group on Sarcopenia in Older People (EWGSOP) for HGS and SMI were utilised to determine the presence of sarcopenia and values for FFMI compared and correlated with variables including SMI, BMI, MUAC, CC and age of participants. Results: HGS indicated that functional strength was low compared to reference values and cut-off points. SMI values indicated that all males (6/6) had some degree of sarcopenia and 3/8 females moderate sarcopenia (1 other borderline). FFMI analysis indicated good correlation with SMI and BMI (r = > 0.82; P < 0.0001) and moderately with MUAC and CC (r = 0.59-0.78; P < 0.05-0.0001), regardless of BIA equation used. Distinct regions of potential nutritional risk were identified on FFMI/SMI and /BMI graph-plots, whereby low FFMI and SMI coexisted in normal and even overweight BMI ranges. Conclusion: These results indicate that the utilisation of a combination of tools and methods may provide useful and practical information in the assessment of sarcopenia.