Frailty and nutritional status in older people: the Mini Nutritional Assessment as a screening tool for the identification of frail subjects
Clinical Interventions in Aging
Frailty and nutritional status in older people: the Mini nutritional Assessment as a screening tool for the identification of frail subjects
Alessia Valentini 1
Massimo Federici 1
Maria Assunta Cianfarani 1
Umberto Tarantino 0
Aldo Bertoli 1
0 Department of Orthopaedics and Traumatology, University of rome “Tor Vergata” , rome , Italy
1 Department of systems Medicine, University of rome “Tor Vergata” , rome , Italy
PowerdbyTCPDF(ww.tcpdf.org) Introduction: Frailty is a condition characterized by reduced resistance to low-level stress events, resulting from the progressive decline of multiple physiological systems observed with aging. Many factors can contribute to the pathogenesis of frailty, and nutritional status appears to play a key role. The objective of the study was to investigate the relationship between nutritional status, evaluated using Mini Nutritional Assessment (MNA), and frailty among older people. Patients and methods: An observational study was carried out at the University Hospital “Tor Vergata” in Rome among patients aged 65 years or older, with or without hip fracture. The study sample included 62 patients hospitalized for a hip fracture and 50 outpatients without fracture. All subjects underwent blood sampling for laboratory assays and received a multidimensional geriatric evaluation comprising Activity of Daily Living (ADL), Instrumental Activity of Daily Living (IADL), Mini-Mental State Examination (MMSE), Geriatric Depression Scale (GDS), and MNA. Comorbidity was assessed using the Cumulative Illness Rating Scale for Geriatrics (CIRS-G). Muscle strength was measured by handgrip dynamometry, and frailty score was calculated using the Survey of Health, Ageing and Retirement in Europe-Frailty Index (SHARE-FI). Results: Approximately 38% of the study population was frail, with the prevalence of frailty being greater among hospitalized older patients. Among frail subjects, 65% were at risk of malnutrition (RMN) and 10% were malnourished. The prevalence and RMN progressively diminished in the pre-frail group and not frail group. Nutritional status was closely associated with the degree of frailty, and in a logistic regression, MNA was the best variable predicting both pre-frailty and frailty. Discussion and conclusion: Malnutrition contributes to the development of frailty. MNA can generate vital information to help identify a substantial part of both frail and pre-frail patients at low cost and care.
Frailty is a condition characterized by reduced resistance to low-level stress events1
resulting from the progressive decline of multiple physiological systems observed
According to the phenotypic model, frailty is a condition of increased vulnerability,
distinguished by the presence of at least three of the following elements in the same
individual: muscle strength reduction, unintentional weight loss, exhaustion, reduced
walking speed and decreased physical activity.1
A number of tools have been developed to help identify frail subjects,4–6 but there is
still a lack of consensus on both the definition of frailty and frailty assessment tools.7
Clinical Interventions in Aging 2018:13 1237–1244 1237
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Patients and methods
Our data are derived from an observational study conducted
at the “Tor Vergata” Polyclinic in Rome in patients aged 65
or older the main objectives of which were to evaluate the
major indicators of frailty and to establish their relationship
with changes in the endocrine system that occur with aging.
The secondary objective of the study was to identify which
indicators of frailty were most frequently present in a
subgroup of patients with an acute stress such as hip fracture
following low-energy trauma.
The study population comprised 112 elderly subjects,
aged between 68 and 98 years, referred to “Tor Vergata”
Polyclinic from March 2014 to March 2015. Of these
subjects, 62 subjects were enrolled as patients hospitalized in the
Orthopedic Department following hip fracture, representing
a population with higher frailty prevalence, and 50 subjects
were enrolled as outpatients evaluated at the Department of
Internal Medicine (Clinical Program on Atherosclerosis).
All investigations were carried out according to the
Declaration of Helsinki, as modified in 2000, and included a
written consent from all participants. For patients with mild
cognitive impairment, informed consent was obtained with
the help of the caregiver. The ethics committee of the “Tor
Vergata” Polyclinic approved the study protocol.
Inclusion criteria were age $65 years in both groups and
current hip fracture in hospitalized patients. Exclusion criteria
were the presence of a malignancy or a history of cancer and
the presence of severe dementia. For each patient, medical
history was collected, comorbidities were evaluated, sex
and age were recorded, anthropometric parameters (weight,
height) were measured and body mass index (BMI) was
computed. All subjects participating in the study underwent
clinical examination and blood sampling for laboratory
Blood cell count was evaluated using routine laboratory
tests (Sysmex XE-2100; Dasit, Milano, Italy), and
concentrations of glucose, creatinine, albumin, total cholesterol,
high-density lipoprotein (HDL) cholesterol, low-density
lipoprotein (LDL) cholesterol, and triglycerides were measured
using homogeneous chemiluminescence assay (Dimension
VISTA 1500; Siemens, Milano, Italy).
Participating patients received a multidimensional geriatric
evaluation comprising Activity of Daily Living (ADL)14 and
Instrumental Activity of Daily Living (IADL),15 Mini–Mental
State Examination (MMSE),16 Geriatric Depression Scale
(GDS),17 and MNA.18 Reference values were 0–6 for ADL and
0–8 for IADL: all patients whose ADL score was greater than
or equal to 5 and whose IADL score was greater than or equal
to 6 were considered as independent. MMSE (reference values
0–30) was used to assess the presence of cognitive impairment:
patients whose MMSE score was greater than or equal to 24
were classified as normal, while patients whose MMSE score
was between 20 and 24 were identified as having mild
cognitive impairment. GDS reference values were between 0 and
30: patients whose GDS score was higher than 11 were
categorized as suffering from depression. According to Guigoz
et al,18 an MNA score greater than or equal to 24 identified
subjects with normal nutritional status, while patients whose
MNA score was less than or equal to 17 were classified as
malnourished; subjects with MNA scores between 17 and
23.5 were at risk of malnutrition (RMN).
Comorbidity was assessed using the Cumulative Illness
Rating Scale for Geriatrics (CIRS-G).19
In patients able to collaborate, muscle strength was
measured using type Jamar® digital hand-held dynamometer
(Kern & Sohn, Balingen, Germany). Measurements were
performed with the dominant hand. Men and women with a
handgrip strength of ,30 and, ,20 kg, respectively, were
identified as having sarcopenia.20
Frailty score and the degree of frailty were
subsequently calculated using the SHARE-FI.8 According to the
SHARE-FI results, patients were classified as frail if their
score was .3 for men and .2.13 for women; pre-frail, if the
score was between 1.21 and 3 for men and between 0.32 and
2.13 for women; not frail, if the score was ,1.21 for men
and ,0.32 for women.
Ambulant patients enrolled in the study underwent
dualenergy X-ray absorptiometry (DEXA) for evaluation of
bone mineral density (BMD) of lumbar spine and femoral
neck, T-score and Z-score of lumbar spine and femoral neck,
and body composition. DEXA scans were performed and
analyzed according to the manufacturer’s guidelines, using
either DEXA Lunar (Lunar Corp., Madison, WI, USA) for
subjects enrolled at the Orthopedic Department or DEXA
Hologic (Hologic Inc., Waltham, MA, USA) for subjects
enrolled at the Department of Medicine. BMD and T-score of
femoral neck were obtained from the databases. For patients
with body composition data available, Fat Free Mass Index
(FFMI) was calculated as the ratio between lean mass (kg)
and height squared (m2).
The Kolmogorov–Smirnov test was used to assess normal
distribution variables. Student’s t-test and analysis of
variance (ANOVA) test served to compare continuous
variables, while the χ2 test and the Fisher’s exact test were
deployed to compare proportions. Pearson’s linear regression
was used to correlate continuous variables. Nonparametric
correlations were evaluated using Spearman’s rank
correlation, as indicated. One-way ANOVA and simple linear
correlation assessed the relationship between continuous
variables. The analysis of covariance (ANCOVA) was used
to evaluate the influence of fracture on the relationship
between nutritional status (through the MNA) and frailty
(frailty score). Multinomial logistic regression was used to
assess which independent variables affect frailty.
All data are presented as mean±standard deviation (SD).
Values of p,0.05 were considered as significant. Statistical
analysis was performed using StatView 5 (SAS Institute Inc.,
Cary, NC, USA) and SPSS version 21 (IBM Corporation,
Armonk, NY, USA). Graphs were designed using GraphPad
Prism 5 (GraphPad Software, Inc., La Jolla, CA, USA).
Older outpatients did not differ from hospitalized older
patients for age, BMI, and fat mass, but they had significantly
greater values of FFMI, muscle mass, handgrip, T-score
(Table 1), and albumin (Table 2) and they exhibited greater
autonomy in basic and daily life activities (anamnestic based)
and a significantly higher MNA score (Table 3).
Approximately 38% of the study population was frail and
28.3% was pre-frail. The prevalence of frailty was greater
among hospitalized patients than among outpatients (59%
vs 18.75%, respectively), while pre-frailty prevalence was
greater among outpatient subjects than among
hospitalized patients (37.5% vs 21.4%, respectively), as shown in
Figure 1A (χ2=17.53, p,0.0001).
Moreover, 9.3% of hospitalized patients were
malnourished, 46.3% were at risk for MN, and 44.4% had a nutritional
status within the normal range. Among outpatient subjects,
77.8% had a normal nutritional status, 22.2% were at RMN,
and none were malnourished (χ2=12.77, p=0.0017), as shown
in Figure 1B. Among frail subjects, 65% were at RMN and
10% were malnourished. The prevalence of RMN
progressively diminished in the pre-frail group (29.6%, of which
3.7% had poor nutritional status) and in the not frail group
(6.2%, none of which had poor nutritional status). The
difference between groups was statistically significant (χ2=36.77,
p,0.0001; Figure 1C).
femoral neck’s T-score (F=9.21, p=0.0036) but not with
comorbidity, cognitive status, and fracture.
Our multinomial logistic regression model that included
the degree of frailty as a dependent variable and CIRS-G,
MMSE, ADL, GDS, MNA, and fracture presence as
independent variables showed that the MNA was the best variable
predicting both pre-frailty (χ2=6.22, p=0.0126) and frailty
Discussion and conclusion
Frailty is a condition of increased vulnerability, characterized by
weakness, unintentional weight loss, slowness, exhaustion, and/
or low activity, the prevalence of which increases with aging.1
In our study, 38% of participants were frail and 28.3%
pre-frail, with a prevalence of frail subjects among
hospitalized patients (59% vs 18.75%) and pre-frail subjects among
outpatient older people (37.5% vs 21.4%).
Like frailty, MN is frequent in older patients across social
strata,21 with an extremely variable but significantly greater
prevalence among the hospitalized older subjects.13
In our study population, nutritional impairment,
evaluated through both MNA and laboratory parameters, was
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more frequent in frail subjects than in pre-frail and not frail
subjects. In the frail group, the prevalence of MN and RMN
was significantly higher while plasma albumin
concentrations were significantly lower than that observed in
prefrail and not frail subjects. Moreover, subjects who were
malnourished or at RMN also presented with osteopenia and
osteoporosis more frequently than well-nourished subjects
(data not shown). Both conditions, frailty and MN, were more
frequent among the hospitalized older patients than among
the outpatient older subjects.
MN contributes to the development of frailty by
accelerating the onset of sarcopenia and osteoporosis,22–24 conditions
that increase the risk of fracture.25 In frail older subjects, hip
fracture is a dramatic event that can lead to a rapid and sudden
decline in residual functional autonomy, already limited by
physiology and the inevitable aging process.
In our study, subjects hospitalized for hip fracture did not
differ in terms of age, BMI, and comorbidity (CIRS-G) from
community-dwelling older people. However, they differed in
terms of degree of disability (ADL and IADL), evaluated on
the basis of anamnestic data preceding hip fracture, and
cognitive status (MMSE). They also had a more compromised
pre-fracture nutritional status, as evidenced when evaluated
through a questionnaire (MNA).
Plasma albumin concentration and total cholesterol,
measured during in-hospital stays, were significantly lower
in fracture patients, thereby confirming a compromised
nutritional status. Furthermore, lipid profile can be modified
by the use of cholesterol-lowering drugs (statins) and low
hemoglobin levels are not only MN related.
Plasma albumin concentration is known to be a sensitive
parameter for assessing nutritional status in clinically stable
patients and, as per the study population, was found to be
directly related to nutritional status determined by MNA.26
In addition, plasma albumin concentration was found to be
closely related with muscular strength and degree of
disability evaluated through ADL, in both community-based
and hospitalized patients.26 In fact, in patients treated for
hip fracture, plasma albumin concentration represents an
important predictor of functional recovery.26
However, low serum albumin concentrations are not
necessarily indicative of MN as hypoalbuminemia could
reflect inflammation or disease state.21,26
As suggested by Dorner et al,10 there is a strong overlap
between frailty and nutritional status.
In our study, regardless of the presence of an acute
stress such as hip fracture, frailty and nutritional status
were closely related to both hospitalized fracture subjects
and community-dwelling older people. Furthermore, with
frailty, the degree of bone mineralization was also closely
related to nutrition: osteoporosis, in fact, is more frequent
among malnourished subjects and, in a linear regression
model, was strongly associated with nutritional status (data
While osteoporosis is the primary condition for fractures,
it is not the only factor that reduces bone strength, nor does
the reduction in bone strength alone increase the risk of
fracture. Fracture in older people is often the result of
lowenergy trauma. A number of conditions, both medical and
nonmedical, can play a predisposing role. Muscle mass and
muscle strength, for example, are crucial to maintaining
balance and avoiding falls and their consequences.27
The reduction in muscle mass and strength are the most
important features of sarcopenia and, in more severe forms,
is also associated with a reduction in physical performance.28
In our study, frail subjects showed lower values of both
muscle mass and muscle strength than pre-frail and not frail
subjects. Similarly, malnourished subjects had lower median
values of both muscle mass and muscle strength than subjects
at RMN and those with normal nutritional status. Such
observations could indicate a greater prevalence of sarcopenia in
frail and malnourished subjects, potentially placing them at
greater risk of falls, fractures, and disabilities.
As with nutritional status, there is a strong overlap
between sarcopenia and frailty.28 In our study, the frailty score
was closely associated with muscle gain, while correlation
with muscle mass was not statistically significant, probably
due to the small size of the sample.
Osteoporosis and sarcopenia are closely linked because
they are related to and/or are dependent on nutritional status
and physical activity.22,29,30 Reduced protein intake and
consequent MN contribute to both bone mass loss31,32 and weight
loss and therefore to lean mass loss22 and are thus predictive
factors for osteoporosis, sarcopenia, and frailty.31
Like He et al,29 we also found a significant correlation
between the femoral neck’s T-score and muscle strength,
between femoral neck’s T-score and lean mass, and between
the femoral neck’s T-score and the frailty score among
our limited number of patients with DEXA data available.
Additionally, we found that the femoral neck’s T-score is
strongly correlated with nutritional status as evaluated with
MNA, which also depends on muscle mass. As expected,
MNA and handgrip values are strongly correlated with
MN can exacerbate the loss of muscle mass and bone
mass observed with aging32 and therefore contributes to
the development of frailty. In our study, MNA was the best
predictor of both pre-frailty and frailty, and frailty score was
the only predictor of the RMN and poor nutritional status.
Nutritional status and frailty alike are independent of
cognitive status and comorbidity. Cognitive decline, disability, and
comorbidity may coexist in elderly subjects, but they are not
synonymous with frailty, as per Fried et al.33
According to many published data, MNA is a useful tool
for the assessment of nutritional status in both
communitydwelling older people and hospitalized older patients. MNA
seems to be a good method to assess nutritional status because
unlike plasma albumin levels, it is independent from
inflammation and acute diseases.34
Our study, notwithstanding the limitations of small
sample size, found that the MNA can generate vital
information to help identify a substantial part of both frail and
pre-frail patients at low cost and care. Furthermore, it can
inform a care path for preventing the progression of
prefrailty to frailty, thereby reducing potential adverse events
associated with frailty.
Several tools have been proposed to help identify frail
subjects,4–6 including SHARE-FI.8
Even though the introduction of SHARE-FI was intended
to facilitate the rapid assessment of frailty in primary care,
as described by Romero-Ortuno et al,8 this instrument
requires greater collaboration on the part of the patient than
the MNA tool.
SHARE-FI takes into account exhaustion (referred to by
the patient as little energy to do the things he/she wanted to do),
loss of appetite (described as a reduction in the desire for food
and/or eating), walking difficulties, low physical activity, and
weakness.8 The evaluation of weakness is based on the
measurement of handgrip strength, which requires the use of a
dynamometer and patient collaboration; this can be very difficult
to obtain in subjects with cognitive impairment or dementia.
Unlike SHARE-FI, the MNA tool is simpler and does
not require patient collaboration because it is predominantly
anamnestic based and several of its components can be
resolved by the caregiver in subjects with cognitive
impairment or dementia.
In conclusion, given that nutritional status is strongly
associated with frailty, the use of MNA as a screening tool
can help identify at low cost and care a substantial part of
frail and especially pre-frail patients alike. In both cases, early
intervention can be instrumental in preventing the
progression of frailty and reducing its adverse effects.
A limitation of this study is the small sample size that may
not be representative of frail older people.
This study was financially supported by Fondazione Roma
NCD CALL and PRIN 2015MPESJS-004.
The authors have no conflicts of interest in this work.
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