Hugh E Senior1, Tim R Henwood2, Elaine M Beller3, Geoffrey K Mitchell4, Justin W L Keogh5. 1. Discipline of General Practice, School of Medicine, The University of Queensland, 11 Salisbury Road, Queensland 4305, Australia. Electronic address: h.senior@uq.edu.au. 2. The University of Queensland and Blue Care Research and Practice Development Centre, School of Nursing and Midwifery, University of Queensland, 56 Sylvan Road, Toowong, Queensland 4066, Australia. Electronic address: t.henwood@uq.edu.au. 3. Faculty of Health Sciences and Medicine, Bond University, 14 University Dr, Robina, Queensland 4226, Australia. Electronic address: ebeller@bond.edu.au. 4. The University of Queensland and Blue Care Research and Practice Development Centre, School of Nursing and Midwifery, University of Queensland, 56 Sylvan Road, Toowong, Queensland 4066, Australia. Electronic address: g.mitchell@uq.edu.au. 5. Faculty of Health Sciences and Medicine, Bond University, 14 University Dr, Robina, Queensland 4226, Australia. Electronic address: jkeogh@bond.edu.au.
Abstract
OBJECTIVES: Sarcopenia is a progressive loss of skeletal muscle and muscle function, with significant health and disability consequences for older adults. We aimed to evaluate the prevalence and risk factors of sarcopenia among older residential aged care adults using the European Working Group on Sarcopenia in Older People (EWGSOP) criteria. STUDY DESIGN: A cross-sectional study design that assessed older people (n=102, mean age 84.5±8.2 years) residing in 11 long-term nursing homes in Australia. MAIN OUTCOME MEASUREMENTS: Sarcopenia was diagnosed from assessments of skeletal mass index by bioelectrical impedance analysis, muscle strength by handheld dynamometer, and physical performance by the 2.4m habitual walking speed test. Secondary variables where collected to inform a risk factor analysis. RESULTS: Forty one (40.2%) participants were diagnosed as sarcopenic, 38 (95%) of whom were categorized as having severe sarcopenia. Univariate logistic regression found that body mass index (BMI) (Odds ratio (OR)=0.86; 95% confidence interval (CI) 0.78-0.94), low physical performance (OR=0.83; 95% CI 0.69-1.00), nutritional status (OR=0.19; 95% CI 0.05-0.68) and sitting time (OR=1.18; 95% CI 1.00-1.39) were predictive of sarcopenia. With multivariate logistic regression, only low BMI (OR=0.80; 95% CI 0.65-0.97) remained predictive. CONCLUSIONS: The prevalence of sarcopenia among older residential aged care adults is very high. In addition, low BMI is a predictive of sarcopenia.
OBJECTIVES:Sarcopenia is a progressive loss of skeletal muscle and muscle function, with significant health and disability consequences for older adults. We aimed to evaluate the prevalence and risk factors of sarcopenia among older residential aged care adults using the European Working Group on Sarcopenia in Older People (EWGSOP) criteria. STUDY DESIGN: A cross-sectional study design that assessed older people (n=102, mean age 84.5±8.2 years) residing in 11 long-term nursing homes in Australia. MAIN OUTCOME MEASUREMENTS: Sarcopenia was diagnosed from assessments of skeletal mass index by bioelectrical impedance analysis, muscle strength by handheld dynamometer, and physical performance by the 2.4m habitual walking speed test. Secondary variables where collected to inform a risk factor analysis. RESULTS: Forty one (40.2%) participants were diagnosed as sarcopenic, 38 (95%) of whom were categorized as having severe sarcopenia. Univariate logistic regression found that body mass index (BMI) (Odds ratio (OR)=0.86; 95% confidence interval (CI) 0.78-0.94), low physical performance (OR=0.83; 95% CI 0.69-1.00), nutritional status (OR=0.19; 95% CI 0.05-0.68) and sitting time (OR=1.18; 95% CI 1.00-1.39) were predictive of sarcopenia. With multivariate logistic regression, only low BMI (OR=0.80; 95% CI 0.65-0.97) remained predictive. CONCLUSIONS: The prevalence of sarcopenia among older residential aged care adults is very high. In addition, low BMI is a predictive of sarcopenia.
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