<![CDATA[Introduction. Sarcopenia is defined as a declined in skeletal muscle mass and strength along with its function may causes an increase in hospitalization, mortality, and health burden. Multi-factorial conditions of the aging process may cause sarcopenia. To assess those multi-factorial conditions in the elderly, a comprehensive geriatric assessment (CGA) method should be used, in which comprises of socio-demographic, medical, psychological, and functional domains. This research aims to analyze the components of CGA, including age, gender, nutritional status, mental status, and functional status as factors associated to sarcopenia in the elderly community in Surabaya. Methods. This community research was a cross sectional designed analytic observational study. The subjects were all elderly people visiting five chosen Posyandu, an integrated health service post, that meet the inclusion and exclusion criteria. A total of 308 data were collected and then bivariate and multivariate analyzes were performed to determine the components related to sarcopenia. Bivariate analysis was performed on components of age, sex, nutritional status, comorbidities, cognitive status, mental status, and functional status. Variables included in multivariate analysis were age, sex, nutritional status, comorbidities, cognitive status, and functional status. Results. The subjects were dominated by elderly females (74.7%). The median of age were 63 years (range 60-100 years). After performing multivariate analysis, three variables had the association to sarcopenia which were nutritional status assessed by MNA score ≤23.5 (OR 3.61, 95% CI 2.11–6.19), age ≥70 years old (OR 2.82, 95% CI 1.58–5.04), and male (OR 1,83, 95% CI 1,04–3,24). An area under curve (AUC) of 66.2% was obtained from the prediction model. Conclusion. The method of CGA has the power to predict sarcopenia of the elderly in the community as much as 66.2%]]>
