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International Psychogeriatrics (2012), 24:9, 1494–1504 C
International Psychogeriatric Association 2012
doi:10.1017/S1041610212000622
Functional impairment as a defining feature of: amnestic MCI
cognitive, emotional, and demographic correlates
.........................................................................................................................................................................................................................................................................................................................................................................
Igor Bombin,1,2 Sandra Santiago-Ramajo,3Maite Garolera,5Eva M. Vega-González,1
Noemí Cerulla,4,6 Alfonso Caracuel,3Alicia Cifuentes,1M. Teresa Bascarán7and
Julio Bobes7
1Reintegra Foundation, Oviedo, Spain
2Department of Psychology, Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, University of Oviedo, Oviedo, Spain
3Department of Personality Evaluation and Treatment Psychology, University of Granada, Granada, Spain
4Neuropsychology Unit Hospital de Terrassa-Consorci Sanitari de Terrassa, Barcelona, Spain
5Grup de Recerca Consolidat de Neuropsicologia (SRG0941), University of Barcelona, Spain
6Sant Jordi Day Hospital for Cognitive impairment-Consorci Sanitari de Terrassa, Barcelona, Spain
7Department of Medicine, Psychiatry Area, Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, University of Oviedo, Oviedo, Spain
ABSTRACT
Background: Early definitions of mild cognitive impairment (MCI) excluded the presence of functional
impairment, with preservation of a person’s ability to perform activities of daily living (ADL) as a diagnostic
criterion. However, recent studies have reported varying degrees of functional impairment associated
with MCI. Hence, we aimed to test the potential functional impairment associated with MCI and its
predictors.
Methods: Sixty-nine healthy elderly subjects, 115 amnestic single-domain MCI subjects (a-MCI), and 111
amnestic multi-domain MCI subjects (md-MCI) were assessed using a battery of neuropsychological tests
including measures of attention, memory, working memory, executive functions, language, and depression.
Additionally, functional ability was assessed by both qualitative (WHO-DAS II) and quantitative (CHART)
instruments. Cognitive and functional performance was compared between groups, and regression analyses
were performed to identify predictors of functional ability.
Results: The md-MCI group was more impaired than the a-MCI group, and both were more impaired than
healthy subjects in all cognitive measures, in total CHART score, CHART cognitive and mobility subscores,
and WHO-DAS II communication and participation subscales. For the rest of the functional measures,
the md-MCI group was more impaired than healthy controls. Prediction of functional ability by cognitive
measures was limited to md-MCI subjects and was higher for the CHART than for the WHO-DAS II. The
WHO-DAS II was largely influenced by depressive symptoms.
Conclusions: Functional impairment is a defining feature of MCI and is partially dependent on the degree
of cognitive impairment. Quantitative measures of functional ability seem more sensitive to functional
impairment in MCI than qualitative measures, which seem to be more related to depression.
Key words: mild cognitive impairment (MCI), disability, functional independence, cognition, healthy elderly, WHODAS-II, CHART, neuropsychology
Introduction
Since the early descriptions of mild cognitive
impairment (MCI) (Petersen et al., 1999), there has
been increasing interest in its clinical characteriza-
tion and prognosis (Nelson and O’Connor, 2008;
Correspondence should be addressed to: Dr. Igor Bombin, PhD, Reintegra
Foundation, Centro de Rehabilitación Neurológica, C/ Eduardo de Fraga
Torrejón, 4, bajo, Oviedo. 33011 Spain. Phone: +34 984 08 48 46; Fax: +34
984 08 48 41. Email: ibombin@reintegra-dca.es. Received 26 Jul 2011; revision
requested 16 Sep 2011; revised version received 2 Mar 2012; accepted 5 Mar
2012. First published online 19 April 2012.
Werner and Korczyn, 2008). In previous reports
(Petersen et al., 1999), subjects with MCI exhibit
poorer cognitive functioning than healthy subjects,
but not as impaired as patients with dementia.
Prognosis studies have stressed the use of this
nosological entity as a risk or prodromic state for
dementia, due to the high rate of conversion of
MCI subjects to dementia (10%–15% of patients
who meet the criteria of amnestic MCI develop
Alzheimer’s-type dementia per year, up to 80% at
5-year follow-up) (Amieva et al., 2004; Petersen,
2004; Gauthier et al., 2006). Approximately 16% of
Functional impairment as MCI defining feature 1495
the populations of older people who have not been
diagnosed with dementia meet the current criteria
for MCI (Petersen et al., 2010) and MCI prevalence
increases with age.
Dementia inevitably involves a loss of functional
independence, resulting in a progressive increase
in disability (Sauvaget et al., 2002). In parallel
with the progressive loss of personal autonomy,
increases in family/caregiver burden and in demand
for health and social resource use have been
reported (Potkin, 2002). However, disability, a
milder form than dementia, is not included as
an MCI diagnostic criterion. Furthermore, the
diagnosis of MCI requires preservation of the
person’s ability to perform activities of daily
living (ADL) (Petersen et al, 1999; Petersen
and Negash, 2008), “or at least that impairment
is minimal” in complex instrumental functions
(Winblad et al., 2004). Recently, the lack of
functional impairments of MCI in daily living
as a diagnostic criterion has been questioned as
the result of studies pointing to impairment in
instrumental ADL rather than basic ADL (Tam
et al., 2007; Pereira et al., 2008; Ahn et al., 2009;
Burton et al., 2009; Schmitter-Edgecombe et al.,
2009; Aretouli and Brandt, 2010; Bangen et al.,
2010; Reppermund et al., 2010; Teng et al., 2010a;
2010b). Although these studies were carried out in
different countries and used different instruments
to assess impairments in ADL, they all suggest that
people who meet the other criteria described for
MCI do show functional impairment of ADL.
Disability in dementia and other neurological
and neuropsychiatric disorders has been largely
associated, and partially attributed, to cognitive
impairment (e.g. Millis et al., 1994 in brain injury;
Green, 1996 in schizophrenia). Those findings
seem to support the apriorihypothesis that MCI
would show some degree of functional impairment,
which could be at least partially predicted by
the cognitive impairment that characterizes MCI.
However, to date there are very few studies that
assess the potential associations between functional
performance and cognitive impairment in MCI
subjects or that attempt to determine which
cognitive areas are more likely to predict functional
abilities in MCI subjects.
In light of the above, we aimed to (1)
determine whether MCI is associated with
functional impairment; (2) identify the role
of sociodemographic, emotional, and cognitive
variables as independent predictors of functional
impairment in elderly healthy subjects, single-
domain amnestic MCI subjects and multi-domain
amnestic MCI subjects; and (3) discuss the extent
to which the two former issues are instrument-
dependent. We hypothesized that (1) MCI patients
will show impaired independent functioning; (2)
among subjects with MCI, such impairment will be
associated with the degree of cognitive impairment,
and to a lower degree with sociodemographic
and anxiety-depression symptoms, whereas in
healthy controls, impaired functioning will be only
associated with sociodemographic and anxiety-
depression symptoms; and (3) in MCI subjects the
degree of impairment and the nature and effect
size of associations will partially depend on the
type of independent functioning, in such a way that
quantitative measures based on performance (Craig
Handicap Assessment and Reporting Technique,
CHART) will be more reliable than qualitative
measures (World Health Organization Disability
Assessment Schedule, second version, WHO-DAS-
II) based on a subjective judgment of disability.
Methods
Participants
Recruitment of participants was conducted during
2010 and the beginning of 2011 in three
clinical or university settings in three regions
of Spain: the University of Oviedo (northern
Spain), Consorci Sanitari of Terrassa (Barcelona,
northeastern Spain), and the University of Granada
(southern Spain). Recruitment in the Consorci
Sanitari of Terrassa was done by review of clinical
history and application of inclusion and exclusion
criteria to outpatients attending its memory clinic.
The two universities recruited participants by
inviting subjects attending community services
for healthy elderly people to participate in
a free memory-training program. The memory
training program was conducted as part of a
randomized clinical trial, aimed to compare the
efficacy of two neuropsychological rehabilitation
strategies (restitution versus compensation and
substitution) in improving functional independence
and cognition in MCI subjects.
A total of 328 elderly people living in
the community were recruited. Inclusion criteria
included: age over 55 years, meeting the diagnostic
criteria for MCI as defined in Petersen et al.
(1999), living in the community, and signing
informed consent. Exclusion criteria were: living in
an assisted living residence, cognitive functioning
suggesting a possible diagnosis of dementia (see
below), previous diagnosis of dementia, previous
psychiatric disorder according to DSM-IV-TR at
the time of recruitment, presenting a moderate or
higher degree of disability due to other conditions
than MCI, and severe language impairments that
would compromise their active participation in the
neuropsychological rehabilitation clinical trial.
1496 I. Bombin et al.
Neuropsychological assessment
Cognitive assessment was performed by means
of a neuropsychological battery designed to com-
prehensively evaluate attention, working memory,
memory, executive functioning, and language (see
Table 1). In order to obtain a summary score
for each cognitive domain (mean of variables that
compounded a cognitive domain as presented in
Table 1) and a global score for cognition (average
of the four cognitive domains), raw test scores
were converted to T-scores (mean =50, SD =
10) based on normative data published in the
Spanish handbooks of the tests (WAIS-III digits,
Stroop) and normative data obtained in an ongoing
normative study with an independent healthy
sample (N=173). In this ongoing normative study,
normative data were obtained for the following
age groups: 56–65 years (n=56), 66–75 (n=
71), 76 or older (n=46). T-scores were truncated
at 10 (–4 standard deviations), to avoid outlying
values (as suggested in Rousseeuw and Leroy,
1987). Results are reported for cognitive areas
summary scores, in order to avoid an excess
of data (results of single test variables available
upon request). Language summary score was not
included in statistical analyses because none of the
recruited subjects showed language impairment and
distribution of this variable was very asymmetric due
to ceiling effect of the language measures employed.
Neuropsychological assessment was performed by
seven experienced neuropsychologists. Reliability in
administering and scoring the neuropsychological
tests were evaluated prior to baseline estimation in
an independent sample of ten subjects (inter-rater
reliability exceeded 0.80 for all instruments).
Memory complaints were registered by means of
the Spanish version (García Martínez and Sánchez
Cánovas, 1994) of the Memory Failures Everyday
(MFE) test (Sunderland et al., 1984), a 28-item
questionnaire about experiences in daily living
associated with memory and other cognitive area
failures. It is scored according to a 3-point likert-
scale about the frequency of such failure (0 =never
or almost never; 1 =sometimes or rarely; 2 =many
times).
Sample subdivision
Based on the results of neuropsychological
assessment, the sample was divided in six groups:
healthy subjects (control group); subjects with
single domain amnestic MCI (a-MCI); subjects
with multi-domain amnestic MCI (md-MCI);
single non-amnestic MCI; multi-domain non-
amnestic MCI; and subjects with a dementia-like
cognitive functioning. Sample sociodemographic
and clinical characteristics of the groups are
described in Table 2. The classification of
Table 1. Neuropsychological tests and variables
grouped by cognitive domain
COGNITIVE DOMAIN
NEUROPSYCHOLOGICAL
VARIABLE
.....................................................................................................................................................
Attention WAIS-III digits forward
Time to complete TMT-A
Number of correct items
stroop 1 words
Number of correct items
stroop 2 colors
Working memory WAIS-III digits backward
Time to complete TMT-B
Learning and memory HVLT total learning
HVLT long term free recall
HVLT discrimination
Executive functions Number of words on
COWAT-FAS
Number of words on verbal
fluency (animals)
Stroop interference score
BADS key search test
Language Token test (comprehension)
Boston naming test (30 items)
(expression)
WAIS-III =Wechsler Adult Intelligence Scale, 3rd Edition;
TMT-A =Trail Making Test, part A; TMT-B =Trail
Making Test, part B; HVLT =Hopkins Verbal Learning Test;
COWAT =Control Oral Word Association Test. Total phonetic
cueing (F+A+S); BADS =Behavioral Assessment of the
Dysexecutive Syndrome.
subjects to different groups was made according to
performance in four cognitive domains (attention,
memory, working memory, and executive function):
•Healthy Group (HG; n=69):
subjects who, after neuropsychological
assessment, presented a performance
within normal limits. A cutoff point
of T-score equal or higher than 40
(z ≥−1 SD) in all the four cognitive
domains was established. All healthy
subjects were recruited at the above
cited community services for healthy
elderly.
•Subjects with MCI (n=238): subjects
with at least one cognitive domain
summary T-score equal to or below 35
(z≤−1.5), but whose possible dia-
gnosis of dementia was not supported.
This group was subdivided into four
subgroups, according to the four types
of MCI proposed by Petersen et al.
(2004):
- Amnestic Single-domain MCI Group
(a-MCI; n=115): subjects whose
T-score in the cognitive domain of
memory or in the long-term free-recall
of the Hopkins Verbal Learning Test
Functional impairment as MCI defining feature 1497
Table 2. Comparison of demographic, emotional, neuropsychological, and functional variables between healthy and MCI subjects
HEALTHY GROUP MCI GROUP T STUDENT a-MCI md-MCI ANOVA POST HOC BONFERRONI1
.....................................................................................................................................................................................................................................................................................................................................................................................................................................................
N=69 N =226 χ2N=115 N =111 χ2(p<0.05)
Demographic variables: Mean/SD Mean/SD pMean/SD Mean/SD p
- Age 70.10/8.5 73.50/8.4 0.004 71.79/8.3 75.27/8.2 <0.001 HG and a-MCI <md-MCI
- Education (years) 9.15/4.5 6.82/3.7 <0.001 8.01/3.7 5.61/3.2 <0.001 HG and a-MCI >md-MCI
- Gender: % Female 78.3% 68.6% 0.122 69.6% 67.6% 0.286
- Type of residence:
◦Rural 36.2% 38.2% 0.948 38.6% 37.8% 0.991
◦Urban 60.9% 58.7% 58.8% 58.6%
◦Semi-urban 2.9% 3.1% 2.6% 3.6%
Subjective memory complaints Mean/SD Mean/SD T Student Mean/SD Mean/SD ANOVA post hoc Bonferroni1(p<0.05)
MFE 13.85/8.5 20.68/11.6 <0.001 18.56/10.02 22.90/12.82 <0.001 HG <a-MCI <md-MCI
Emotional status Mean/SD Mean/SD T Student Mean/SD Mean/SD ANOVA
- GDS 9.57/5.9 10.72/6.3 NS 9.56/5.7 12.03/6.6 0.008 HG and a-MCI <md-MCI
Neuropsychological functioning: Mean/SD Mean/SD Mean/SD Mean/SD MANCOVA post hoc Bonferroni2(p<0.05)
- Attention 51.64/6.4 41.52/8.9 <0.001 47.26/5.8 35.57/7.6 <0.001 HG >a-MCI >md-MCI
- Memory 50.77/6.9 31.69/7.2 <0.001 34.54/6.5 28.74/6.8 <0.001 HG >a-MCI >md-MCI
- Working memory 52.91/7.7 39.44/11.2 <0.001 48.30/6.0 30.25/7.2 <0.001 HG >a-MCI >md-MCI
- Executive function 49.98/6.0 43.61/7.0 <0.001 46.47/6.7 40.56/5.8 <0.001 HG >a-MCI >md-MCI
- Global cognition 51.33/4.9 39.01/6.6 <0.001 44.14/4.2 33.69/4.0 <0.001 HG >a-MCI >md-MCI
Functional independence: Mean/SD Mean/SD Mean/SD Mean/SD MANCOVA post hoc Bonferroni2(p<0.05)
WHODAS II total : 41.82/13.0 51.65/19.0 <0.001 46.42/14.3 57.16/21.7 <0.001 HG and a-MCI <md-MCI
- Communication 8.34/3.7 10.92/4.8 0.001 9.79/3.5 12.11/5.7 <0.001 HG <a-MCI <md-MCI
- Mobility 6.89/3.3 8.60/4.3 <0.001 7.89/3.8 9.34/4.6 <0.001 HG <md-MCI
- Self- care 4.17/0.8 5.29/2.7 <0.001 4.71/1.7 5.89/3.4 <0.001 HG and a-MCI <md-MCI
- Interpersonal 4.56/1.7 5.58/2.6 <0.001 5.25/2.0 5.94/3.1 0.006 HG <md-MCI
- Life activities 6.68/3.5 8.13/4.7 0.007 6.80/3.6 9.53/5.3 <0.001 HG and a-MCI <md-MCI
- Participation 11.15/4.2 13.11/5.1 0.002 11.96/4.6 14.32/5.4 <0.001 HG and a-MCI <md-MCI
CHART total: 350.42/37.6 303.78/68.0 <0.001 320.46/57.8 286.79/73.4 <0.001 HG >a-MCI >md-MCI
−Cognitive 93.82/13.5 75.42/24.3 <0.001 82.15/19.4 68.57/26.9 <0.001 HG >a-MCI >md-MCI
−Mobility 97.85/5.5 91.64/12.9 <0.001 93.22/11.8 90.03/13.8 <0.001 HG and a-MCI >md-MCI
−Occupation 73.58/24.7 60.70/31.5 0.001 66.76/29.74 54.53/32.3 0.002 HG >md-MCI
−Social integration 85.16/20.1 76.00/28.4 0.004 78.32/26.9 73.64/29.9 0.009 HG >md-MCI
Note: GDS =Geriatric Depression Scale; MFE =memory failures everyday; WHODAS II =the World Health Organization Disability Assessment Schedule; SD =Standard Deviation;
CHART =Craig Handicap Assessment and Reporting Technique. HG =Healthy Group; a-MCI =amnestic-MCI group; md-MCI =multidomain-MCI group.
1Bonferroni post hoc test for the ANOVA. 2Bonferroni post hoc test for the MANCOVA after controlling for age, years of education, and GDS score.
1498 I. Bombin et al.
(HVLT) was equal to or below 35 (z ≤
−1.5), and the other cognitive domain
summary T-scores above 35 (z >−1.5).
- Amnestic multi-domain MCI Group
(md-MCI; n=111): subjects with
T-scores below 35 (z ≤−1.5) in at
least two cognitive domain summary
T-scores, including memory summary
score or long-term free recall of HVLT.
- Non-amnestic single-domain MCI
Group (n=10): subjects with a unique
cognitive domain other than memory
or HVLT long-term free-recall T-score
equaltoorbelow35(z≤−1.5), and
the other cognitive domain summary
T-scores above 35 (z >−1.5).
- Non-amnestic multi-domain MCI
Group (n=2): subjects with T-scores
below 35 (z ≤−1.5) in at least two
cognitive domains, other than memory
summary score or long-term free recall
of HVLT.
Given the low sample size of the non-amnestic
single-domain (n=10) and the non-amnestic multi-
domain (n=2) MCI groups, these two groups were
not included in further analyses.
•Subjects with a dementia-like cognitive
functioning (n=21): subjects with at
least two cognitive domain summary
T-score below 25 (z<−2.5). The
diagnosis of dementia was not proven
due to the lack of neuroimaging
data, but this conservative strategy was
adopted in order to minimize a potential
magnifying effect of differences on func-
tional ability between groups exclusively
due to outliers.
Functional independence assessment
Assessment of functional independence was
performed by means of two different scales, one
based on subjective judgment of disability – the
World Health Organization Disability Assessment
Schedule, second version (WHO-DAS-II) – and
another based on frequency rates of time spent
performing ADL – Craig Handicap Assessment and
Reporting Technique (CHART). The WHO-DAS
II (Federici et al., 2009) is a 36-item inventory
based on the World Health Organization’s
(WHO) International Classification of Functioning,
Disability and Health Framework (WHO-ICF) that
evaluates six domains of functioning in daily life:
understanding and communicating, mobility, self-
care, interpersonal, life activities, and participation
in society. The participants interviewed were
asked to rate the experienced level of “difficulty”
(none, mild, moderate, severe, extreme), by taking
into account the way in which they normally
perform a given activity, and including the use of
whatever support or/and help by a person (aids).
For every item receiving a positive answer, the
subsequent question asks the number of days (“in
thelast30days”) in which the interviewee has
found such a difficulty; however, for the present
study only the 36-item answers were analyzed.
A total WHODAS-II functional impairment score
was obtained by adding up all functional areas
subscores, except for the work subscale (possible
total score range: 36–180), higher values indicating
higher degree of functional impairment. The
WHO-DAS II is available at http://www.who.
int/icidh/whodas/whodasversions/36sa.pdf, and ex-
amples of items are “How much difficulty did you
have in: Moving around inside your home? Washing
your whole body? Getting along with people who
are close to you? Taking care of your household
responsibilities?”
The CHART was designed to provide a simple,
objective measure of the degree of impairments
and disabilities (Whiteneck et al., 1992). Each
CHART dimension is characterized by directly
observable qualities which lend themselves to
easy quantification. CHART consists of six
subscales assessing (1) physical independence; (2)
cognitive independence; (3) mobility / accessibility
to activities and resources inside and outside
the home; (4) occupation, including household
activities, caring activities, volunteer activities,
entertainment, etc.; (5) quantity and quality
of interpersonal relationships, and (6) financial
independence (this subscale was not administered).
For each subscale a percentage score (0%–
100%) is calculated by raw scores conversions
and mathematical operations, indicating a 100%
absolute independence for that domain. A total
CHART functional impairment score was obtained
by adding up all functional areas subscores, except
for the Physical Independence and Economic Self-
Sufficiency subscales (possible total score range: 0–
400), with higher values indicating lower degree of
functional impairment. The Physical Independence
subscore was not included in the summary score
because presence of a moderate or higher degree
of disability due to other conditions than MCI
was an exclusion criterion, so all subjects scored
100. The economic self-sufficiency was excluded
in order to preserve participants’ privacy given
the fact that the fulfillment of this subscale
requires providing data of annual income. The
CHART is available at http://www.craighospital.
org/Research/CHART%20Manual.pdf, and ex-
amples of items are “How many hours per week
do you spend in active homemaking including
parenting, housekeeping, and food preparation?”;
“In a typical week, how many days do you get out
Functional impairment as MCI defining feature 1499
of your house and go somewhere?”; How many
friends... do you visit, phone, or write to at least
once a month?”
Both functional independence scales, which
gather information about both basic and in-
strumental ADL, were administered by trained
neuropsychologists within the context of an
interview in such a way that information was
provided by subjects and a caregiver together when
available, or by subjects alone (some of these
subjects lived alone, or with a spouse with higher
degrees of disability).
Depression symptoms
The presence and severity of depression symptoms
were assessed by the Geriatric Depression Scale
(GDS) (Yesavage, 1988). The GDS is a
screening depression scale for geriatric populations
comprising 30 items to which the subject provides
a “yes” or “no” answer. Each item is scored
as 1 (presence of a depression/anxiety symptom)
or 0 (absence of a depression/anxiety symptom).
According to previous reports, scores ranging 0–10
indicate the absence of depression; 11–20 would
suggest a mild possible depression; and scores
higher than 20 would be suggestive of severe
depression. The GDS was administered by the
neuropsychologists who performed the cognitive
and functional evaluation.
Statistical analyses
Mean and standard deviation are provided
for continuous variables. Discrete variables are
expressed as frequencies and/or percentages.
Distribution of variables was tested by the
Kolmogorov–Smirnov test, and when dividing the
sample into the three subgroups (Healthy, a-MCI,
md-MCI), only the variables of years of education
and WHO-DAS II total score showed non-
normal distributions. On the basis of the normal
distribution of most variables, the sample sizes, the
robustness of the parametric tests based on analysis
of variance, and the need to use post hoc analyses,
these techniques were chosen for statistical analyses.
For sociodemographic data Student’s t-test for
two independent samples (Healthy Group versus
MCI subjects) were used to compare means for
continuous variables. When more than two groups
were considered (for sociodemographic and clinical
data), one-way analysis of variance (ANOVA)
was conducted. When significant differences were
detected the Bonferroni post hoc test was used to
identify which specific groups differed. The χ2
statistics were used for comparison of categorical
measures. As healthy control and MCI groups
differed for age and years of education, the
healthy group differed from the md-MCI group
in age and years of education, analyses on
neuropsychological and functioning variables were
performed controlling for these variables when
required. For doing so, full factorial multivariate
analysis of covariance (MANCOVA) models were
performed, using group (MCI/control and a-
MCI/md-MCI/controls) as fixed factors, cognitive
summary T-scores and WHO-DAS-II and CHART
scores as dependent variables, and age, years of
education, and GDS as covariates. Again, the
Bonferroni post hoc test was performed to identify
specific differences/effects when the MANCOVA
was significant.
Receiver operating characteristic (ROC) curve
analyses were conducted to test diagnostic accuracy
(Healthy vs. all MCI as a group) of the WHO-DAS
II, CHART, MFE, and total cognition variables.
The estimate of the area under the ROC curve was
computed using a binegative exponential model.
Multiple regression analyses were performed
separately with the total sample together and for the
three groups independently (a-MCI, md-MCI, and
controls), with total WHO-DAS II and CHART
scores as dependent variables, and age, years of
education, GDS, and cognitive domain summary
scores as independent variables or predictors.
The step-wise method was used in the regression
analyses due to the fact that it provides a final
model including only significant predictors, which
are presented decreasingly according to the amount
of variance explained.
All statistical analyses were performed with SPSS
v13 (Statistical Package for the Social Sciences,
Chicago, Illinois), and a 2-tailed p-value lower than
0.05 was considered statistically significant.
Results
Differences in demographic and clinical
variables
Comparisons of demographic, cognitive, depression
symptoms, and functional independence variables
are presented in Table 2. Both healthy subjects
and a-MCI were younger and had more years of
education and less depression symptoms than md-
MCI, with no differences in these variables between
the two former groups. Similarly, the md-MCI
group showed higher rates of depression symptoms
than both healthy and a-MCI subjects. Given these
results, for the following comparisons between
the three groups (MANCOVA) age, years of
education, and GDS were introduced as covariates.
MANCOVA analyses results suggested that healthy
subjects had a better cognitive functioning than
both a-MCI and md-MCI in all cognitive areas
1500 I. Bombin et al.
1,0 0,8 0,6 0,4 0,2 0,0
Specificity
1,0
0,8
0,6
0,4
0,2
0,0
MMSE
MFE Total
Global Cognition
CHART Total
WHODAS Total
Sensitivity
Figure 1. ROC curve to distinguish normal from the MCI using total CHART, total WHO-DAS II, total MFE, and global cognitive score.
assessed, and that cognitive performance of the a-
MCI group was superior to that of md-MCI in all
cognitive areas. Frequency and severity of subjective
memory complaints followed an identical pattern:
more prominent in md-MCI than in a-MCI, and in
both MCI groups than in healthy subjects.
As to functional independence, the healthy
group showed better functional adjustment than
the MCI group according to both WHO-DAS II
and CHART total scores. When the MCI group
was subdivided into a-MCI and md-MCI, CHART
total score and cognitive domain, and WHO-DAS
II communication subscale showed a similar profile
as cognitive functioning, after controlling for age,
education, and GDS score: md-MCI was more
functionally impaired than a-MCI, showing that
both MCI groups had higher rates of disability than
the healthy group. The md-MCI group showed
a higher degree of functional impairment than
both healthy subjects and a-MCI in the WHO-
DAS II total score and self-care, life activities, and
participation subscales, and in the CHART mobility
domain. The remaining functional ability measures
showed a consistent functional impairment only of
md-MCI in comparison with healthy subjects (for
more details, see Table 2).
In comparing the ROC curves, the CHART
appears with a larger area under the curve (AUC =
0.707) than the WHO-DAS II (AUC =0.347) and
the MFE (AUC =0.331), but less than the global
cognition score (AUC =0.923), and very close to
MMSE (AUC =0.714) (Figure 1).
Predictors of functional status (regression
analyses)
The results of the regression analyses are shown
in Table 3. When the whole sample was analyzed
together, attention and memory summary scores
explained a total variance of 8.2% and 0.8% of the
WHO-DAS II, respectively, and 9.8% and 1.8%
of the CHART, respectively. When depression
and age were entered in both former models, the
WHO-DAS II score was predicted by depression
symptoms as measured by the GDS (19.2%) and
by executive functions (8.1%) only in the healthy
group. By contrast, CHART total score was only
predicted by age among healthy subjects. For both
MCI groups, WHO-DAS II was predicted by
depression symptoms only, with a total variance
explained of 17.3% for a-MCI and 13.9% for md-
MCI. CHART score was predicted only by age on
a-MCI subjects, and by age, attention, and GDS
score on md-MCI subjects. Attention explained
9.1% variance of CHART total score.
Discussion
Our results show that functional impairment is a
defining feature of MCI, and that the impairment
Functional impairment as MCI defining feature 1501
Table 3. Regression analyses with total WHO-DAS II and CHART as dependent variables
GROUPS DEPENDENT VARIABLES PREDICTORS Adj. R2FP
...................................................................................................................................................................................................................................................................................................................
All subjects together (N=295) WHODAS-II GDS 0.184 58.318 <0.001
Attention 0.266 47.313 <0.001
Age 0.281 34.154 <0.001
Memory 0.289 26.910 <0.001
CHART Age 0.203 65.552 <0.001
Attention 0.301 55.633 <0.001
GDS 0.320 40.931 <0.001
Memory 0.338 33.470 <0.001
Healthy group (n=69) WHODAS-II GDS 0.192 15.301 <0.001
Executive functions 0.273 12.248 <0.001
CHART Age 0.117 8.805 0.004
Amnestic-MCI group (n=115) WHODAS-II GDS 0.173 22.576 <0.001
CHART Age 0.178 22.837 <0.001
Multidomain-MCI group (n=111) WHODAS-II GDS 0.139 15.571 <0.001
CHART Age 0.138 15.722 <0.001
Attention 0.229 14.644 <0.001
GDS 0.271 12.372 <0.001
Method: Step-wise. Independent variables: age, years of education, GDS, attention, memory, working memory and executive functions.
GDS =Geriatric Depression Scale; WHODAS-II =the World Health Organization Disability Assessment Schedule, second edition;
CHART =Craig Handicap Assessment and Reporting Technique; Adj. R2=adjusted R2.
showed by MCI subjects is partially dependent
on the degree of their cognitive impairment.
Furthermore, measures of functional ability show
adequate psychometric properties (i.e. discriminant
power) to contribute to the MCI diagnosis.
Functional measures based on quantitative rates of
number and quality of ADL performed seem to be
more sensitive to identifying functional impairment
in MCI than those based on a subjective judgment
of disability.
The idea of a functional compromise associated
with MCI is not new, and previous studies have
reported a higher degree of functional impairment in
MCI subjects when compared with matched healthy
subjects (Tam et al., 2007; Pereira et al., 2008;
Ahn et al., 2009; Burton et al., 2009; Schmitter-
Edgecombe et al., 2009; Aretouli and Brandt,
2010; Bangen et al., 2010; Reppermund et al.,
2010; Teng et al., 2010a; 2010b). Independent
of the instrument used to evaluate functional
ability, most of these studies agree that higher
order ADL are more likely to be impaired than
those ADL with a lower degree of cognitive
involvement/demand (Burton et al., 2009; Aretouli
and Brandt, 2010; Reppermund et al., 2010). In
our results, the highest effect sizes between healthy
controls and MCI subjects were functioning areas
related to cognitive difficulties (CHART cognitive
subscale; WHO-DAS II communication subscale),
and participation in productive and social activities
(CHART occupation and mobility subscales;
WHO-DAS II life activities and participation
subscales). All these data support the apriori
intuitive notion that highly cognitive-dependent
living skills are more likely to be affected as a
consequence of cognitive impairment, and that
MCI subjects show significant impairment in these
functional domains. On the other hand, it is
noteworthy that differences between healthy and
MCI subjects were not restricted to higher order
ADL, but also to functional areas such as moving
around and self-care, usually referred to as basic
ADL.
The early descriptions of MCI excluded the
presence of disability or functional impairment
as a characteristic, perhaps to differentiate from
dementia. However, as a consequence of the
enrichment and improvement of the conceptual
definitions of functional independence and parti-
cipation, and the increasing importance of these
concepts in the sphere of health and well-being (see
WHO International Classification of Functioning,
Disability and Health: WHO-ICF), instruments to
assess independent living abilities have improved
their ability to identify impairments included in
WHO-ICF activity and participation levels. In
WHO-ICF, the concept of disability is no longer
restricted to the notion of “inability to perform
basic ADL,” but includes quantitative (inability,
reduction in the number of times the ADL
is performed) or qualitative (increased time or
difficulty in performing ADL) difficulties with both
basic and instrumental ADL (see Wade, 2005 for an
interesting approach to the application of the WHO-
ICF model to patients with cognitive deficits). As
a result of this paradigm shift, and in the light of
1502 I. Bombin et al.
previous and the present results, it would be very
helpful for clinicians, caregivers, and health-system
managers if MCI definitions included the presence
of impairment of functional abilities as a clinical
feature inherent to MCI.
Moreover, given the moderately good psy-
chometric properties demonstrated in our study
of the CHART in discriminating healthy from
MCI subjects, assessing functional ability would
improve the identification of MCI subjects, and the
use of qualitative and/or quantitative impairment
of functional abilities as an MCI diagnostic
criterion should be further explored. Goldberg
et al. (2010) found that a sensitive performance-
based measure they developed (the University of
California, San Diego Performance-Based Skills
Assessment; UPSA) had a remarkably good
discriminant power to distinguish healthy from
MCI (area under the curve 0.84), and to
distinguish MCI subjects from Alzheimer’s disease
patients (area under the curve 0.88). Hence, the
inclusion of functional competence measures seems
convenient for the screening and early identification
of neurodegenerative processes characterized by
cognitive impairment.
As to the type of functional assessment
instrument, our results suggest that performance-
rate measures of functioning are superior to those
based on a subjective judgment of disability.
The latter was consistently more biased by
depressive symptoms, and the CHART showed
better discriminant power between healthy and
MCI groups than the WHO-DAS II, suggesting
that the more objective the approach to measuring
independent functioning, the more sensitive it
was to to functioning loss secondary to cognitive
impairment. In this regard, the study by Pereira
et al. (2008) also reported high effect sizes
between healthy subjects, MCI subjects, and
Alzheimer’s disease patients with an objective
measure of functioning; the Direct Assessment
of Functional Status Scale (DAFS-R) (Loewen-
stein et al., 1989), which evaluates functional
competence by simulating ADL (time orientation,
communication skills, ability to deal with finances,
shopping, grooming, eating, and transportation).
Additionally, the associations found between the
DAFS-R and cognitive measures of executive
functions were quite robust (r=−0.872, p<
0.001). The previously noted study of Goldberg
et al. (2010) showed that their performance-based
measure of functional ability was more discriminant
of healthy-MCI- Alzheimer’s disease groups than a
questionnaire based on a caregiver response. Hence,
independent functioning assessment instruments
should be designed in a way that places emphasis
on the subject’s ability to perform complex ADL
and the frequency with which such activities are
performed, rather than on subjective judgments of
difficulties.
Our results also noted that subjective judgments
of disability (i.e. WHO-DAS II) are more influenced
by depressive symptoms, suggesting depression
may play a confounding role in this measure.
That the most robust predictor of the WHO-
DAS II score was the severity of depressive
symptoms, and that the amount of variance
explained was close to 20% support this
hypothesis. By contrast, the more objective measure
of functional ability was less influenced by
depression, although it is noteworthy that in md-
MCI subjects, depression symptoms influenced
functional impairment as measured by both WHO-
DAS II and CHART, and that this group showed
higher rates of depressive symptoms than the other
two (healthy and a-MCI groups). Hence, it may
be the case that when depressive symptoms reach
syndromic levels, they play a more important
role in independent functioning. The alternative
hypothesis would be that depressive symptoms
are partially secondary to functional impairment.
The relationship between depression and functional
impairment in MCI subjects requires further
examination, because our study design does not
allow us to disentangle the relationship between
depression and functional impairment. On the other
hand, the influence of depression on functioning
measures may have been partially increased in
those cases in which these scales were administered
to subjects without an independent informant to
contrast information.
We found several results supporting the associ-
ation of the degrees of functional impairment with
cognitive impairment. The evidence supporting this
association is the finding that the higher the number
of impaired cognitive domains the higher the degree
of functional impairment, so that healthy controls
showed more functional independence than a-
MCI, and these more than md-MCI. A similar
gradual profile of global cognitive functioning can
be found between the three groups. The ability of
cognitive functioning to predict performance rates
of functional activities (CHART) was restricted to
MCI subjects also supports this notion, suggesting
that the impact of cognition on functional ability
gets higher as cognitive impairment increases. In
other words, variability on cognitive functioning
is irrelevant when cognitive functioning is within
normal limits, but when cognitive resources are
impaired they show a higher weight on functional
independence. The higher contribution of cognitive
measures on the regression model of all subjects
together (around 11.6%) is putatively due to
the heterogeneity of the entire sample, whereas
Functional impairment as MCI defining feature 1503
no cognitive measure seems to predict functional
ability in a-MCI subjects because these subjects
have a very similar cognitive profile (i.e. all subjects
present memory impairment alone). In other words,
the stratification based on their degree of cognitive
impairment is likely to be the best predictor of
functional impairment.
Limitations of the study include the potential
measure error derived from the fact that in
many cases the MCI subjects were the informants
of their own functional independence levels.
Although functional assessment was conducted in
an interview context with the collaboration of a
caregiver when available, for approximately half
the sample the subject was the key informant
and the accuracy of the subjects’ reports might
have been mediated by their cognitive impairment
and/or depression symptoms. However, given that
recruitment was mostly conducted in community
locations, a close informant was not always
available with enough knowledge of the subject’s
daily routine. Unfortunately, the exact number of
measures gathered from subjects only versus those
gathered from subjects and caregivers together was
not recorded. A second methodological issue is that
the sample recruitment may have been biased as
invitation to participate in the study was addressed
to people willing to participate in a memory training
program, and hence it could be argued that people
with subjective memory complaints were more
likely to enroll in the study. As a consequence,
our healthy subjects might have presented more
subjective memory complaints than the general
population. However, given the large sample size,
the effect size differences between healthy and
MCI groups on the subjective memory complaints
scale (MFE), and that most participants (including
all healthy subjects) were recruited in community
settings, we consider the sample to be representative
of the elderly living in the community. Finally,
cognitive and functional assessments were in most
cases performed by the same person, and although
group assignment (healthy vs. a-MCI vs. md-MCI)
was not undertaken until the conclusion of all data
gathering, this may have led to possible bias in
functional ability assessment.
In summary, these and previous results
emphasize the presence of qualitative and
quantitative functional impairments of both basic
and instrumental ADL in MCI as a logical
consequence of cognitive impairment. Although
dementia is characterized by a more severe
degree of disability than MCI, the WHO-ICF
conceptualization of disability would include MCI
as a disabling condition, although to a lower degree.
The need for a better definition of disability as
a diagnostic criterion (putatively, by shifting from
a categorical notion of able/disable to a more
spectrum/gradual approach) to discriminate MCI
from dementia must not conceal the fact that
MCI subjects have their own health/functional
assistance needs. Researchers and clinicians have
the responsibility and opportunity of designing,
testing, and implementing effective therapeutic
strategies targeted to improve, or at least preserve,
both functional and cognitive functioning in MCI.
Conflict of interest
None.
Description of authors’ roles
I. Bombin designed the study, supervised the data
collection, and wrote the paper. S. Santiago-Ramajo
collected the data and assisted with writing the
paper. M. Garolera, E. M. Vega-González, N.
Cerulla, A. Caracuel, A. Cifuentes, and M. T.
Bascarán collected the data and assisted with
preparation of data for analyses. J. Bobes assisted
with design of the study. All authors reviewed the
paper and contributed to its final version.
Acknowledgments
This study was financially supported by the Spanish
Ministry of Science and Innovation, Instituto
de Salud Carlos III, and European Regional
Development Fund (ERDF).
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