Page 220 - Petelin, Ana. 2021. Ed. Zdravje starostnikov / Health of the Elderly. Proceedings. Koper: University of Primorska Press.
P. 220
avje starostnikov | health of the elderly 218 The mini nutritional assessment (MNA) was used to assess the nutrition-
al status. Malnutrition indication scores ranged from 17 to 30 points. Partic-
ipants were classified according to achieved scores as follows: from 24 to 30
points (normal nutritional status), from 17 to 23.5 points (at risk of malnutri-
tion), and less than 17 points (malnourished) (Vellas et al., 1999).
Statistical analysis
Data were analysed using SPSS version 25 (SPSS Inc., Chicago, IL). For contin-
uous variables, we calculated mean values, standard deviations, and medians.
Categorical variables are expressed as numbers and percentages.
Normality in the distribution of variables was tested with the Shap-
iro-Wilk test. The homogeneity of variances was tested by Leven’s test for equal-
ity of variances. For continuous variables, differences in participant’s charac-
teristics between those with and without sarcopenia were examined using the
unpaired Student’s t-test or Mann-Whitney U test. For categorical variables,
comparisons between groups were made using the χ2-test. Risk factors were
determined using logistic regression with sarcopenic status as the outcome.
Initially, those dietary factors that were significantly different between groups
were included in a multivariate model to determine the best predictor of sarco-
penic status. Those factors that were significant at the p = .05 level were includ-
ed in the multivariate model, having taken into consideration possible covar-
iates, to determine whether the dietary intake differences between the groups
were related to sarcopenia. The following covariates were included for the eval-
uation of dietary intake: sex, age, body mass index, MNA malnutrition cate-
gory, energy intake, diabetes mellitus, hypertension, heart disease, depression,
chronic obstructive pulmonary disease (COPD) and physical activity level. All
statistical tests were 2-sided. A p value lower than .05 was considered statisti-
cally significant.
Results
Baseline characteristics of study participants in relation to the presence of sar-
copenia according to EWGSOP (Cruz-Jentoft et al., 2010) diagnostic criteria
are presented in Table 1 and Table 2. We found lower body mass index (t(113) =
2.839, p = .005), skeletal muscle index (U = 439, z = -4.801, p = < .001), gait speed
(U = 440, z = -4.794, p < .001), and grip strength (U = 319, z = -5.605, p < .001)
in the sarcopenic group. The sarcopenic participants also reported a lower lev-
el of physical activity than the nonsarcopenic older adults (U = 761, z = -2.792,
p = .005), and had significantly higher rates of diabetes mellitus (χ2(1) = 5.25, p
= .022), and hypertension (χ2(1) = 5.59, p = .018). The risk of malnutrition was
higher (χ2(1) = 10.45, p = .001) in the sarcopenic (42.3%) comparing to the non-
sarcopenic group (13.5%). None of the participants were malnourished.
al status. Malnutrition indication scores ranged from 17 to 30 points. Partic-
ipants were classified according to achieved scores as follows: from 24 to 30
points (normal nutritional status), from 17 to 23.5 points (at risk of malnutri-
tion), and less than 17 points (malnourished) (Vellas et al., 1999).
Statistical analysis
Data were analysed using SPSS version 25 (SPSS Inc., Chicago, IL). For contin-
uous variables, we calculated mean values, standard deviations, and medians.
Categorical variables are expressed as numbers and percentages.
Normality in the distribution of variables was tested with the Shap-
iro-Wilk test. The homogeneity of variances was tested by Leven’s test for equal-
ity of variances. For continuous variables, differences in participant’s charac-
teristics between those with and without sarcopenia were examined using the
unpaired Student’s t-test or Mann-Whitney U test. For categorical variables,
comparisons between groups were made using the χ2-test. Risk factors were
determined using logistic regression with sarcopenic status as the outcome.
Initially, those dietary factors that were significantly different between groups
were included in a multivariate model to determine the best predictor of sarco-
penic status. Those factors that were significant at the p = .05 level were includ-
ed in the multivariate model, having taken into consideration possible covar-
iates, to determine whether the dietary intake differences between the groups
were related to sarcopenia. The following covariates were included for the eval-
uation of dietary intake: sex, age, body mass index, MNA malnutrition cate-
gory, energy intake, diabetes mellitus, hypertension, heart disease, depression,
chronic obstructive pulmonary disease (COPD) and physical activity level. All
statistical tests were 2-sided. A p value lower than .05 was considered statisti-
cally significant.
Results
Baseline characteristics of study participants in relation to the presence of sar-
copenia according to EWGSOP (Cruz-Jentoft et al., 2010) diagnostic criteria
are presented in Table 1 and Table 2. We found lower body mass index (t(113) =
2.839, p = .005), skeletal muscle index (U = 439, z = -4.801, p = < .001), gait speed
(U = 440, z = -4.794, p < .001), and grip strength (U = 319, z = -5.605, p < .001)
in the sarcopenic group. The sarcopenic participants also reported a lower lev-
el of physical activity than the nonsarcopenic older adults (U = 761, z = -2.792,
p = .005), and had significantly higher rates of diabetes mellitus (χ2(1) = 5.25, p
= .022), and hypertension (χ2(1) = 5.59, p = .018). The risk of malnutrition was
higher (χ2(1) = 10.45, p = .001) in the sarcopenic (42.3%) comparing to the non-
sarcopenic group (13.5%). None of the participants were malnourished.
