STATISTICAL ANALYSIS
Statistical analysis was performed using the IBM SPSS version 23.0 software (IBM Corp., Armonk, NY, USA). Descriptive data were expressed in mean ± standard deviation (SD) for normally distributed variables, median and ’minimum-maximum’ values for non-normally distributed variables. After looking at the statistical difference with the Mann-Whitney U test in two group comparisons and the Kruskal Wallis test in more than two group comparisons, Dunn-Bonferroni double comparison test was performed. The relationship between the numerical variables was examined using the Spearman correlation coefficient. The strength of the relationship was determined according to the correlation coefficient (r). A r value of 0 to 0.2 was considered very weak, 0.2 to 0.4 weak, 0.4 to 0.6 moderate-to-severe, 0.6 to 0.8 strong, and 0.8 to 1 very strong relationship. A p-value of <0.05 was considered statistically significant. A multiple lineer regression model was used to identify predictors sarcopenia. The model fit was assessed using appropriate residual and goodness-of-fit statistics. A 5 % type –Ӏ error level was used to infer statistical significance. The criteria value to consider the variables for the multivariate analyses was p < 0.10. Standardized coefficients (β, ranging from -1 to 1) for all independent variables included in the regression equations ,coefficient of determination(r2) and correlation coefficient (r ) were analyzed for all…independent variables.Statistical significance was set at p < 0.05.