Page 130 - Petelin, Ana, and Šarabon, Nejc. 2018. Eds. Zdravje starostnikov / Health of the Elderly. Znanstvena monografija / Proceedings. Koper: University of Primorska Press
P. 130
avje starostnikov | health of the elderly 130 tinction based on BMI, although adapted to the elderly, shows poor sensitiv-
ity. Therefore, the use of BMI would be more appropriate for monitoring the
changes of nutritional status during the hospitalization. Although WHO clas-
sifies the risk of malnutrition based on low BMI for all age groups in the same
way, Beck and Ovesen (1998) argued in the previous researches that the cut-
off point for determination of malnourished older adults should be 24 kg/m2
and healthy BMI should be raised on 24–29 kg/m2. Similarly, Rojer et al., 2016
in study came to the conclusion, that overweight patients with unintentional
weight loss had still high BMI which is typical also for geriatric patients. In our
sample, as well as in the group with INR, there was no statistical correlation be-
tween age and BMI (Table 1) which means that in our sample age did not im-
pact on lower BMI.
BIA and dynamometer were used for the measurements of body compo-
sition while cut-off points for a clinical diagnosis of malnutrition and sarcope-
nia (Cruz-Jentoft et al., 2010; Cederholm et al., 2015; Guerra et al., 2015) were
used for determining nutritional status. Patients that screened positive with
NRS-2002 (39) were classified as malnourished according to cut-off points of
measured parameters FFMI, HGS and PA (Table 2). The majority of malnour-
ished patients were determined by PA (29). In the recent study, Ringaitiene et
al., 2016 showed that a preoperative PA value derived from BIA distinguish-
es malnourished from well-nourished patients. It is possible to conclude that
the use of PA is a good indicator of malnutrition. However, further research is
needed to evaluate the clinical application of PA.
The measured parameters FFMI, HGS and PA inside the groups with LNR
and INR showed significant statistical difference (P < 0.05). In the whole sam-
ple, age showed statistical correlation with FFMI, HGS, PA (P < 0.05), which
means that age impacts nutritional status (Elia in Stratton, 2012). It is interest�-
ing that in the group with INR there was no statistically significant correlation
between age and FFMI, HGS, PA (P > 0.05) (Table 1). Besides age, the disease,
infection, physical inactivity, etc., which affect the change in body composi-
tion, reduction of muscle mass and muscle strength (Cruz-Jentoft et al., 2010)
may have greater influence on patients’ nutritional status in the group with
INR.
Limitations
-he information on unintentional weight loss at the admission in older adults
is unreliable and can affect the misinterpretation of the results in determining
the nutritional status because most of the patients do not remember or moni-�
tor their weight. Therefore, we have used the information about unintention-
al weight loss only in the NRS-2002. Information on unintentional weight loss
is reliable only when the body weight during hospitalization or at the readmis-
sion is compared to the body weight from patient’ medical record at the last ad-
mission.
ity. Therefore, the use of BMI would be more appropriate for monitoring the
changes of nutritional status during the hospitalization. Although WHO clas-
sifies the risk of malnutrition based on low BMI for all age groups in the same
way, Beck and Ovesen (1998) argued in the previous researches that the cut-
off point for determination of malnourished older adults should be 24 kg/m2
and healthy BMI should be raised on 24–29 kg/m2. Similarly, Rojer et al., 2016
in study came to the conclusion, that overweight patients with unintentional
weight loss had still high BMI which is typical also for geriatric patients. In our
sample, as well as in the group with INR, there was no statistical correlation be-
tween age and BMI (Table 1) which means that in our sample age did not im-
pact on lower BMI.
BIA and dynamometer were used for the measurements of body compo-
sition while cut-off points for a clinical diagnosis of malnutrition and sarcope-
nia (Cruz-Jentoft et al., 2010; Cederholm et al., 2015; Guerra et al., 2015) were
used for determining nutritional status. Patients that screened positive with
NRS-2002 (39) were classified as malnourished according to cut-off points of
measured parameters FFMI, HGS and PA (Table 2). The majority of malnour-
ished patients were determined by PA (29). In the recent study, Ringaitiene et
al., 2016 showed that a preoperative PA value derived from BIA distinguish-
es malnourished from well-nourished patients. It is possible to conclude that
the use of PA is a good indicator of malnutrition. However, further research is
needed to evaluate the clinical application of PA.
The measured parameters FFMI, HGS and PA inside the groups with LNR
and INR showed significant statistical difference (P < 0.05). In the whole sam-
ple, age showed statistical correlation with FFMI, HGS, PA (P < 0.05), which
means that age impacts nutritional status (Elia in Stratton, 2012). It is interest�-
ing that in the group with INR there was no statistically significant correlation
between age and FFMI, HGS, PA (P > 0.05) (Table 1). Besides age, the disease,
infection, physical inactivity, etc., which affect the change in body composi-
tion, reduction of muscle mass and muscle strength (Cruz-Jentoft et al., 2010)
may have greater influence on patients’ nutritional status in the group with
INR.
Limitations
-he information on unintentional weight loss at the admission in older adults
is unreliable and can affect the misinterpretation of the results in determining
the nutritional status because most of the patients do not remember or moni-�
tor their weight. Therefore, we have used the information about unintention-
al weight loss only in the NRS-2002. Information on unintentional weight loss
is reliable only when the body weight during hospitalization or at the readmis-
sion is compared to the body weight from patient’ medical record at the last ad-
mission.
