Post on 16-May-2023
Impact of physical and psychological resourceson functional autonomy in old age
PASQUALINA PERRIG-CHIELLO1, WALTER J. PERRIG1,
ANDREAS UEBELBACHER1, & HANNES B. STAHELIN2
1Institute of Psychology, University of Berne, and 2Geriatric Clinic, University Hospital, University of
Basel, Switzerland
AbstractFunctional autonomy is a core condition of successful ageing. To maximize autonomous functioning isnot only a claim of social policy but also primarily an individual need. Part of the challenge ofpreventing unnecessary dependence in old age is to recognize the diversity among the elderly and thedifferent availability of their physical, psychological and social resources. The aim of this study is toexamine the age- and time-related changes in functional autonomy (activities of daily living, ADL, andinstrumental activities of daily living, IADL) and the psychophysical resources correlated with thesechanges in a sample of 441 healthy elderly persons aged 65 – 95. Furthermore, we are interested in thelong-term predictive power of physical resources (objective and subjective health, physical strength)and psychological resources (memory) on functional autonomy. Results show significant age- andtime-related deteriorations in functional autonomy and in most psychophysical resources. Structuralequation model analyses were performed to test the long-term predictive power of these resources.Results suggest that ADL is better predicted by physical resources than by psychological ones, but forIADL the reverse is the case; here memory variables play a dominant role. Physical and psychologicalvariables are thus specifically related to different components of functional autonomy. This has to betaken into account in the development of preventive and intervention programmes.
Keywords: Functional autonomy, health, memory, well-being, muscle strength, old age
Introduction
The demographic changes of the last decades have led to a substantial increase in the years
of later life (Grundy & Bowling, 1999). Considering the fact that old age is a period of life,
which contains an increased risk of becoming dependent, the maintenance of independence
and the fostering of autonomy has become a high priority public health issue.
The interest in promoting autonomy until very old age is not only related to the
demographical changes, it has also psychosocial reasons. In western society, a possible loss
of autonomy is considered as more distressing than ever before. The reason why is twofold:
(a) establishing and maintaining autonomy is a highly valued goal in western society and
therefore a central developmental task throughout an individual’s life-span—thus a loss of
autonomy is perceived as a painful and sorrowful experience. (b) In our modern
individualistic society, social networks and family ties are not as solid as they used to be
Correspondence: Pasqualina Perrig-Chiello, Universitat Bern, Institut fur Psychologie, Muesmattstr. 45, CH-3000 Bern
9/Switzerland. Tel/Fax: þ41-(0) 61-331 75 19. E-mail: Pasqualina.perrigchiello@psy.unibe.ch
Psychology, Health & Medicine,
November 2006; 11(4): 470 – 482
ISSN 1354-8506 print/ISSN 1465-3966 online ª 2006 Taylor & Francis
DOI: 10.1080/13548500600726633
in the past—loss of autonomy therefore mainly means institutionalization (Hopflinger &
Hugentobler, 2003). We can thus infer that functional autonomy is closely related to
psychological well-being and considered a core condition of successful ageing. It has been
postulated that independent living is the essence of human functioning because it promotes
physical and psychological health (Coleman & Iso-Ahola, 1993; Deci & Ryan, 1987).
Research results indicate that the ability to be self-determined and to exercise control over
one’s life is critical to both psychological and physical well-being and health (Perrig-Chiello,
Perrig, & Stahelin, 1999; Searle, Mahon, & Iso-Ahola, 1995; Searle, Mahon, Iso-Ahola,
Sdrolias, & van Dyck, 1998).
A review of literature reveals that the majority of elderly people maintain their functional
autonomy,1 although considerable individual differences can be observed. Functional
autonomy can be defined on different levels. The basic components of an autonomous life
are the activities of daily living (ADL: eating, dressing, personal hygiene and body care,
moving around; Baltes, Maas, Wilms, & Borchelt, 1996; Baltes, Mayr, Borchelt, Maas, &
Wilms, 1993). These basic competencies are highly automatized and necessary for survival,
they are universal, free from cultural influences and only partly dependent on socio-
demographic, psychological and economical factors—but they are, however, strongly
determined by objective health. If they are restricted, physical dependency and need of care
result. The other crucial components of autonomous living, the instrumental activities of daily
living (IADL), are more complex than ADL and correspond to the expanded competencies
of daily activities (mobility, i.e., moving around on foot, by car, shopping, house-keeping)
(Baltes et al., 1993, 1996). Since this component does not depend primarily on physical
resources (e.g., health status), but essentially on psychosocial factors such as socio-economic
status (Andrieu et al., 2002), cultural and ethnical belonging (Carrasquillo, Lantigua, &
Shea, 2000), cognitive capacity (Sousa & Figueiredo, 2002; Steeman, Abraham, &
Godderis, 1997) and personality variables (Curyto, Chleski, & Lichtenberg, 1999; Sousa
& Figueiredo, 2002), large interindividual differences can be observed. If these IADL are
limited, behavioural dependency is the result.
Several scientific approaches explain the various pathways of aetiology of dependency
(impairment approach) or maintenance of autonomy (resource approach). Traditionally, the
impairment approach has tried to explain the aetiology of dependency in terms of decreasing
levels of ADL and IADL by using pathogenic models (Verbrugge & Jette, 1994). These
studies have indicated a very complex relationship between physical and psychological risk
factors for dependence such as physical and sensory impairments, pain, dementia or
depression (Johnson, Kramer, Lin, Kowalsky, & Steiner, 2000; Mossey, Gallagher, &
Tirumalasetti, 2000). In a study by Steeman and collaborators (1997), risk profiles for the
institutionalization of elderly people were identified. High-risk profile persons were not only
highly dependent in ADL, but in addition had severe cognitive impairments, poor
communication skills and behavioural problems (Steeman, Abraham, & Godderis, 1997).
More recently, resource-oriented approaches have focussed more on the processes that
predict the maintenance of autonomy (Baltes et al., 1993, 1996; Grundy & Bowling, 1999).
Here the identification of protective factors, such as physical activity, social contacts, life-
skills, psychological well-being, but also good cognitive functioning, are at the centre of
interest (Heathcote, 2000; Miller, Rejeski, Reboussin, Ten-Have, & Ettinger, 2000;
Topinkowa, 1999). Resource-oriented approaches have the advantage of emphasizing the
multidimensional nature of the maintenance of functional autonomy and of exploring the
related intervention possibilities (Peter-Wuest, Stuck, Dapp, Nikolaus, Goetz, Gillmann,
et al., 2000). However, the state of the art of research is far from being consistent. A review
of the large amount of studies on predictors of functional autonomy reveals that the majority
Functional autonomy in old age 471
of these studies include either ADL or IADL, or the sum index of both, without
differentiating between elements. With respect to the resource constellation, either physical
or psychological resources are considered. Results are therefore quite contradictory. On the
one hand, cognitive functioning seems to be primarily associated with IADL (Cahn,
Sullivan, Shear, et al., 1998; Steen, Sonn, Borjesson, & Steen, 2001). On the other hand,
positive correlations between cognitive parameters and ADL have only partially been
confirmed. This might be explained by the fact that a considerable amount of studies on
functional autonomy are mostly correlational and cross-sectional, but seldom interdisci-
plinary (mostly either medical or psychological), and mainly based on subjective ratings
rather than on objective ones.
The present study was designed to reduce some of these shortcomings by:
. Describing age- and time-correlated changes of functional autonomy in old age;
. Describing the relation between functional autonomy and health respectively of
functional autonomy and psychological variables;
. Taking into account objective measures as far as possible; and
. Finally, testing the differential and long-term impact of physical and cognitive
resources on ADL and IADL by using structural equation model (SEM) analysis.
In fact, the study of the impact of cognitive and physical resources on various aspects of
functional autonomy requires a differential approach to the resource side as well as to the
competence or outcome side. The rationale of our SEM is based to the two-component
model of everyday competence of Baltes and collaborators (1993, 1996), which
differentiates between a basic level of competence (ADL), and an expanded level of
competence (IADL). In our model, we distinguish between indirect predictors (age) and
proximal predictors (directly related with autonomy such as physical resources such as
mobility or psychological resources such as memory) having an impact on both
components of functional autonomy, that is, ADL and IADL. Our study allows
optimizing the two-component model of Baltes and collaborators by introducing
objectively assessed cognitive and physical resources (memory tests performed on a
computer or muscle strength measured in Watt). We expect that age has little direct
impact on ADL and IADL, but a significant negative impact on both proximal resources,
mobility and especially on memory. Furthermore, and based on existing correlational
data, we expect that mobility and memory have a strong differential impact on functional
autonomy—mobility being the stronger long-term predictor for ADL than memory, and
for IADL the inverse. Indeed, because the IADL are more complex than ADL tasks,
they are also more affected by cognitive functions (Steen et al., 2001; Willis, 1996). On
the other hand, ADL are primarily determined by objective health, especially by a good
physical functioning (Baltes et al., 1993, 1996).
Methods
Participants
This study is part of the Basle Inter-Disciplinary Study on Aging (IDA-Study) with status
measurements in a 2-year interval (Perrig-Chiello, 1997; Perrig-Chiello, Perrig, Stahelin,
Krebs & Ehrsam, 1996).2 The project is a follow-up of a longitudinal study that started in
1960 and collected mostly biomedical data from a large sample of 6,400 healthy persons
472 P. Perrig-Chiello et al.
recruited from an industrial base (the sample is considered representative of the healthy
elderly urban population in Switzerland; Widmer et al., 1981). In the current project, the
Interdisciplinary Study on Aging (IDA), subjects from the original sample have been
recruited if they conformed to two criteria. Firstly, they had to be at least 65 years old and
secondly, they had to live independently (i.e., not in an institution) in the area of Basle.
From 3,768 persons that corresponded to this restriction, 848 persons were randomly
selected and invited to participate in the study. They were informed that they would be
required to travel to the test site, the Geriatric University Clinic of Basle, independently. A
total of 442 persons aged 65 – 94 years (312 males, 132 females, mean age¼ 75) agreed to
participate in the initial wave of the IDA-Study, which took place in 1993 at the Geriatric
University Clinic of Basle. Participants arrived in the morning with an empty stomach.
After blood samples had been drawn, they had a breakfast. Next, a team of physicians
collected the anthropometric and clinical data, and psychometric data were collected by a
team of psychologists; 337 persons (227 men and 107 women) were re-tested in the second
wave 2 years later. A telephone inquiry revealed that the main reasons for attrition were illness
(42%), death (22%) and absence from home/travel in the scheduled test period (16%).
Variables3
Functional autonomy*. To assess functional autonomy we used an adapted version of the
I/ADL scales (Katz, Ford, Moskowitz, Jackson & Jaffe, 1963; Lawton & Brody, 1969;
Perrig-Chiello, 1995), consisting of 11 items with a 3-point scale (1¼ yes, I’m able, 2¼ I’m
partly able, 3¼ I’m not able at all; minimal total score: 11 points¼ absolutely independent;
maximal score: 33 points¼ absolutely dependent). This test was administered in 1993 (T1)
and 1995 (T2). T1 mean (M)¼ 12.1, SD¼ 1.6, Cronbach’s alpha¼ .81; T2 M¼ 19,
SD¼ 2.1; Cronbach’s alpha¼ .76. Factor analysis revealed two factors:
. ADL grouping together the rather basic components of independent living, and
. IADL including more expanded competencies of daily activities:
� Subtest 1: ADL—consisted of six items: climb stairs, washing/bathing, dressing,
pedicure, moving around in own house and the surroundings (T1 M¼ 6.3,
SD¼ 0.7, range¼ 7, Cronbach’s alpha¼ .65; T2 M¼ 6.5, SD¼ 0.8, range¼ 8,
Cronbach’s alpha¼ .61).
� Subtest 2: IADL—consisted of five items: cooking/preparing meals, shopping,
house-keeping, taking care of financial matters, carrying out minor repair work at
home (T1 M¼ 5.2, SD¼ 0.6, range¼ 6, Cronbach’s alpha¼ .69; T2 M¼ 5.6,
SD¼ 0.7 range¼ 7, Cronbach’s alpha¼ .62).
For our analyses, we were primarily interested in the combined measure of functional
autonomy (IADL/ADL). For the SEM analyses, however, we used the two separate
measures in order to get a better appreciation of the differential effects of physical and
cognitive resources.
Physical and psychological resources
. Objective health was assessed only at T1 and was operationalized through 20
parameters. Each parameter was assigned either 0 (¼parameter is in the normal
Functional autonomy in old age 473
range) or 1 (¼parameter is beyond the normal range); the sum was defined as the
‘‘objective health index’’ (M¼ 2.7, SD¼ 1.71, range¼ 9). The indicators were:
� Anthropometric parameters: Systolic and diastolic blood pressure, pulse;
� Serum parameters: cholesterol, iron, blood sugar, ferritin, haemoglobin, MCV
(mean cell volume), HDL (high density lipoprotein), triglycerides, leukocytes,
thrombocytes;
� Electro-cardiogram parameters: rhythm, blocks, ischaemia, necroses, hypertrophy
and digitalis.
. Subjective health* (3-point scale: 3¼ very good, 1¼ very bad health) (T1 M¼ 2.83,
SD¼ 0.43; T2 M¼ 2.7, SD¼ .44; range¼ 2 at both measurements).
. Health complaints*: a list of 11 frequent health complaints (e.g., headaches, stomach/
intestinal complaints, rheumatic pains, heart troubles, respiratory difficulties, etc.) as
well as three open categories was presented to participants (yes/no responses) (T1
M¼ 2, SD¼ 1.29, range¼ 7; T2 M¼ 2.8, SD¼ 1.5, range¼ 8).
. Physical strength legs (mobility)* was measured by a leg extensor power rig (measured in
Watt) (T1 M¼ 15 (7), range¼ 18; T2 M¼ 13 (8) range¼ 19).
. Memory*: A computerized test was used to investigate memory performance. The test,
which allows assessing different memory dimensions and has been used before in
different studies, meets all psychometric requirements (Perrig-Chiello & Perrig, 1995;
Perrig, Perrig-Chiello & Stahelin, 1997). The memory parameters are assessed as
follows:
� Free recall (explicit memory): 20 min after having scanned two almost identical
scenes for missing elements, participants are asked to recall all the missing items
they had detected before (T1 M¼ 9.6, SD¼ 4.03, range¼ 20; T2 M¼ 8.6,
SD¼ 4.52, range¼ 18).
� Perceptual speed (reaction time): As quickly as possible, participants had to identify
and to name pictures on the computer screen, which became progressively clearer
(T1 M¼ 5.62, SD¼ 1.11, range¼ 6.9; T2 M¼ 5.54, SD¼ 1.21, range¼ 7.5).
� Working memory: A picture-naming task, as described above, was repeated with
old pictures and a set of new pictures. At the same time, subjects had to respond
with their left or right index finger to little suns flashing on either the left side or
the right side of the computer screen. The percentage of correct responses was
used for this variable (T1 M¼ 75, SD¼ 22, range¼ 100; T2 M¼ 72, SD¼ 23,
range¼ 100).
. Psychological well-being was assessed by means of a nine-item test, which includes the
following dimensions: satisfaction with own past, purpose of life and mastery (3-point
scale: 1¼ I do not agree to 3¼ I absolutely agree) (range¼ 16). This instrument meets
all psychometric standards (T1 M¼ 23.53, SD¼ 2.74; T2 M¼ 23.32, SD¼ 2.8;
Cronbach’s alpha at both measurements¼ .66 and .68; 3-year-stability: r¼ .60,
p5 .001) (Perrig-Chiello, 1996, 1997).
Analyses
First we analysed the age and time changes of functional autonomy and psychophysical
resources (analyses of variance; ANOVAs). Then, a correlational approach was used to
474 P. Perrig-Chiello et al.
determine the relationship between these variables. Finally, SEM analyses were used to
determine the differential longitudinal predictive power of physical strength and memory on
ADL and IADL (always controlling for age). The analyses were performed with SPSS
(version 9.0) and AMOS (version 4.0).
Results
Age and time-correlated changes in functional autonomy
Results of ANOVAs showed significant main effects for age (F(3,337)¼ 12.19,
p5 .0001) and for time F(1,337)¼ 14.15, p5 .0001) with regard to limitations in
functional autonomy in general (IADL and ADL; Figure 1). No significant interactions
were found. An increase of the limitations in functional autonomy is not only observed
with advancing age (i.e., cross-sectional change for all age groups) but also already within
a 2-year period, especially in the oldest cohort (longitudinal change). At the first
measuring point, 65% of our sample did not show any impairment of autonomy; 2 years
later this was only the case for 51%.
ANOVAs controlling for age, time and gender revealed that women scored significantly
higher in limitations of functional autonomy than men (F(1,337)¼ 4.45, p5 .05) (no
significant interactions). Separate analyses for ADL and IADL showed, however, that this is
only the case for ADL (F(1,337)¼ 37.24, p5 .001) and not for IADL (F(1,337)¼ 0.07,
n.s.). Further ANOVAs controlling for education and marital status did not show any
significant main effects.
Correlates of functional autonomy and their age- and time-related change
Our data show that functional autonomy is positively correlated with subjective
and objective health, muscle strength, memory functions and psychological well-being
(Table I).
Results of ANOVAs show significant main effects for age group and time for most of these
variables, especially for memory variables and muscle strength (Table IIa and b). The only
correlated variable, which did not show any decline, is psychological well-being.
Figure 1. Age- and time-associated increase of dependency in four age groups.
Functional autonomy in old age 475
Longitudinal predictors of ADL and IADL
On the basis of these insights, we were interested in the long-term predictive power of the
age-and time-deteriorating resources of functional autonomy, such as memory (free recall,
working memory, perceptual speed) and physical strength (mobility). In order to test this
SEM analyses were used. Because we expected differential long-term predictive effects of
the two proximal resources physical strength (mobility) and memory on ADL and IADL, we
calculated separate models for both autonomy components. In every model, age was
introduced as a control variable. Memory variables were expected to predict better IADL
and mobility was expected to predict better ADL. To test these hypotheses, we used the chi-
square difference test to compare two models, in which one of the path coefficients is fixed at
zero. In line with the recommended use of the SEM approach (Anderson & Gerbing, 1984),
this test allows inferences on the significance of a specific path based on test results of an
overall model.
In the first step, we tested the long-term impact of memory and mobility measured at the
first wave (T1) on ADL competence 2 years later (ADL-T2). The longitudinal analysis
results with the corresponding fit-indices and results of Dw2 tests for the whole model are
presented in Figure 2. In this test, mobility clearly appears as a significant predictor for
ADL, whereas memory does not. Both proximal resources, mobility and memory, are
significantly related to age—however, in this model, age per se is not a significant predictor
of ADL.
In the second step, we tested the same model, however, with IADL as dependent variable.
Results show that the strongest predictor is now memory, and not mobility. Again, age is not
a significant predictor of IADL (Figure 3).
Discussion
The present study aimed to provide a description of age- and time-related changes of
functional autonomy and the psychophysical resources correlated with these changes. A
central question was to find out how several physical and psychological resources have a
differential long-term predictive power on ADL and IADL. Although our sample was
composed of average healthy elderly, an increase of limitations in functional autonomy was
not only observed with advancing age but already within a 2-year period, this independently
from educational or marital status. This shows that significant losses are to be expected
within and between age groups and that the time factor becomes a crucial variable for
Table I. Correlation between dependency and health and psychological variables (T1).
1 2 3 4 5 6 7 8 9
1. Subjective health 1 .33*** .09 7.13* .13* 7.11 7.19** 7.26*** .12*
2. Health complaints 1 .05 7.19** 7.09 .10 7.11 7.13* .13*
3. Objective health 1 .08 7.03 .02 .01 .04 .14*
4. Psych. well-being 1 .04 7.08 .02 7.02 7.19**
5. Muscle strength legs 1 7.24*** .29*** .33*** 7.25***
6. Reaction time/speed 1 7.37*** 7.32*** .23**
7. Free recall 1 .36*** 7.19**
8. Working memory 1 7.32**
9. Dependency 1
*p5 .01; **p5 .001; ***p5 .0001.
476 P. Perrig-Chiello et al.
Tab
leII
a.A
ge
and
tim
ech
anges
inh
ealt
han
dp
sych
olo
gic
alva
riab
les:
mea
ns
and
SD
of
the
fou
rag
egro
up
s.
65
–6
9ye
ars
70
–7
4ye
ars
75
–79
year
s8
04
year
s
T1
T2
T1
T2
T1
T2
T1
T2
Ob
ject
ive
hea
lth
2.3
(1.4
1)
2.5
(1.7
5)
2.7
(1.7
8)
3.3
(1.9
)
Su
bje
ctiv
eh
ealt
h2
.88
(0.3
3)
2.9
5(0
.22)
2.8
8(0
.36
)2
.77
(0.5
2)
2.7
7(0
.47
)2
.75
(0.4
8)
2.8
0(0
.44
)2
.67
(0.5
7)
Hea
lth
com
pla
ints
1.0
9(1
.26
)2
.5(1
.7)
1.2
5(1
.25
)2
.52
(1.3
7)
2.6
(1.4
5)
3.1
5(1
.5)
3.1
1(1
.2)
3.1
4(1
.45
)
Mu
scle
stre
ngth
legs
17
.90
(4.7
6)
17
.7(4
.99)
16
.80
(6.2
4)
14
.83
(6.9
4)
13
.9(7
.72
)1
1.7
1(7
.97
)9
.75
(7.6
5)
7.7
1(7
.23
)
Psy
cho
log.
wel
l-b
ein
g2
3.7
3(2
.54
)2
3.5
7(2
.62)
22
.99
(2.6
3)
23
.33
(2.7
2)
23
.48
(2.8
2)
23
.09
(3.1
4)
23
.92
(2.9
8)
23
.31
(2.7
4)
Rea
ctio
nti
me
5.1
0(.
87
)5
.24
(1.1
0)
5.1
1(.
84
)5
.26
(.9
3)
5.5
(.9
1)
5.5
6(1
.08
)6
.39
(1.6
1)
6.5
1(1
.96
)
Fre
ere
call
11
.0(4
.46
)1
2.0
1(4
.98)
9.5
1(3
.85
)11
.13
(4.8
7)
8.1
1(4
.24
)8
.84
(4.0
5)
6.0
0(3
.58
)6
.58
(4.1
9)
Wo
rkin
gm
emory
85
.6(1
2.6
3)
84
.82
(16
.91
)7
9.7
5(1
8.5
4)
76
.96
(21.0
5)
73
.84
(19
.17
)7
4.8
4(1
7.6
6)
62
.6(2
3.3
)5
8.0
(26.0
6)
Functional autonomy in old age 477
preventive measures. Furthermore, our data revealed significant gender differences: even
though women show significantly higher dependency in ADL than men, they do not differ in
IADL. Women’s higher dependency in ADL may be a consequence of the gender
differences in objective and subjective health during the life-span observed in various other
studies on the one hand, and significantly lower muscle strength on the other hand.
Although women live longer and invest more in their health, they show a significantly higher
morbidity and dependency rate than men (Verbrugge, 1989; Rahman, Strauss, Gertler,
Ashley, & Fox, 1994; Drever, Doran, & Whitehead, 2004). The fact that the women in our
study do not differ in IADL might indicate that they have to continue functioning in every
day life despite possible health impairments (in contrast to old men, old women are more
likely to live alone, which is also the case in our study).
Furthermore, our data show that functional autonomy is positively correlated with a series
of health variables (subjective and objective health, muscle strength) and memory functions
as well as with psychological well-being. With the exception of psychological well-being, all
these measures show an age- and time-correlated decrease. These results clearly
demonstrate imperatives and limitations of possible preventive interventions. On the one
hand, improving the age- and time-deteriorating resources such as muscle strength and
memory might be a meaningful goal of prevention attempts. On the other hand, age- and
time-resistant measures such as psychological well-being need to be considered differently,
in the sense that they may be more resistant to modification. As has been shown,
psychological well-being can be considered indeed as a rather stable personality trait
(Kozma et al., 1991), but also as a powerful prerequisite of functional autonomy in old age.
Table IIb. Age and time changes in health and psychological variables.
df F p
Objective health
Age 3,392 2.38 5.05
Time – – –
Subjective health
Age 3,434 2.29 5.05
Time 1,341 2.74 .10
Health complaints
Age 3,341 3.30 .02
Time 1,341 146.22 .001
Muscle strength legs
Age 3,320 23.91 5.0001
Time 1,320 18.64 5.0001
Psychological well-being
Age 3,341 0.96 n.s.
Time 1,341 1.87 n.s.
Reaction Time
Age 3,338 11.13 5.0001
Time 1,338 8.91 5.0001
Free recall
Age 3,337 28.77 5.0001
Time 1,337 29.35 5.0001
Working memory
Age 3,332 27.54 5.0001
Time 1,332 6.21 .01
478 P. Perrig-Chiello et al.
Finally, the SEM analyses allowed testing of differential long-term effects of resources,
memory and physical strength for ADL and IADL. Age per se is not significant, but has a
strong indirect impact on ADL and IADL. The strongest direct predictors are physical
strength for ADL and memory, and physical strength for IADL. Both predictors are strongly
related to age—indicating the age-correlated decrease of these resources.
With regard to the practical implementation of our results, this means that even though
individual differences exist in respect to the age-correlated decrease of physical strength and
memory, training programmes to prevent losses as well as to maintain and foster the existing
resources can and should be promoted. As shown in experimental intervention studies, both
physical strength as well as memory can be modified successfully (Oswald et al., 1996;
Perrig-Chiello, Perrig, Ehrsam, & Stahelin, 1998). A promising step in this direction is an
Figure 2. Long-term predictors of activities of daily living (ADL).
Functional autonomy in old age 479
intervention programme for resistance training that has been carried out in our study
programme (IDA-Study), it showed positive direct effects on muscle strength, but also
positive indirect effects on memory and well-being (Perrig-Chiello et al., 1998).
Our study adds some strong evidence that psychological factors have an important impact
on functional autonomy, especially on IADL, in old age. Part of the challenge of preventing
unnecessary dependency in old age should therefore be (a) to take into account the large
differences in availability, utilization and interaction of old people’s physical and
psychological resources and (b) to recognize the large diversity among the elderly—age
per se is not the best predictor for autonomy.
Acknowledgements
This study was supported by the Swiss National Science Foundation (Study-Nr. 4032-
035642).
Figure 3. Long-term predictors of instrumental activities of daily living (IADL).
480 P. Perrig-Chiello et al.
Notes
1. In the year 2000, this was the case for 80% of the people aged 80 – 85 in Switzerland , and
for 65 – 70% of people 85 and over (Hopflinger & Hugentobler, 2003).
2. This study has been approved by the ethic committee of the University Hospital of Basel.
3. All variables with a * were measured in both waves.
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