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.