Question 7PAGES, APA || Title: Psychology of Aging 7pages/n Bowling and Iliffe Health and Quality of Life Outcomes 2011, 9:13
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HEALTH AND QUALITY
OF LIFE OUTCOMES
RESEARCH
Open Access
Psychological approach to successful ageing
predicts future quality of life in older adults.
Ann Bowling*, Steve Iliffe²
Abstract
Background: Public policies aim to promote well-being, and ultimately the quality of later life. Positive perspectives
of ageing are underpinned by a range of appraoches to successful ageing. This study aimed to investigate whether
baseline biological, psychological and social aproaches to successful ageing predicted future QoL.
Methods: Postal follow-up in 2007/8 of a national random sample of 999 people aged 65 and over in 1999/2000.
Of 496 valid addresses of survivors at follow-up, the follow-up response rate was 58% (287). Measures of the
different concepts of successful ageing were constructed using baseline indicators. They were assessed for their
ability to independently predict quality of life at follow-up.
Results: Few respondents achieved all good scores within each of the approaches to successful ageing. Each
approach was associated with follow-up QoL when their scores were analysed continuously. The biomedical (health)
approach failed to achieve significance when the traditional dichotomous cut-off point for successfully aged (full
health), or not (less than full health), was used. In multiple regression analyses of the relative predictive ability of each
approach, only the psychological approach (perceived self-efficacy and optimism) retained significance.
Conclusion: Only the psychological approach to successful ageing independently predicted QoL at follow-up.
Successful ageing is not only about the maintenance of health, but about maximising one's psychological
resources, namely self-efficacy and resilience. Increasing use of preventive care, better medical management of
morbidity, and changing lifestyles in older people may have beneficial effects on health and longevity, but may
not improve their QoL. Adding years to life and life to years may require two distinct and different approaches,
one physical and the other psychological. Follow-up health status, number of supporters and social activities, and
self-rated active ageing also significantly predicted QoL at follow-up. The longitudinal sample bias towards healthy
survivors is likely to underestimate these results.
Background
The current generation of ageing adults expects to age
well, and to maintain their general well-being and, ulti-
mately, enhance the quality of later life. Most people
aged 50 and 65 and more rate themselves as ageing well,
or successfully, and few rate as high their chances of
becoming housebound, losing their memory or entering
a nursing home [1,2]. These positive perspectives reflect
a shift away from a predominantly pathological perspec-
tive of later life, which exaggerated the extent to which
chronic ill-health could be attributed to ageing, and
* Correspondence: a.bowling@sgul.kingston.ac.uk
Faculty of Health and Social Care, St George's, University of London and
Kingston University, St George's, University of London, Cranmer Terrace,
London SW17 ORE, UK
Full list of author information is available at the end of the article
BioMed Central
which largely ignored the heterogeneity of the older
population. A more positive view of old age sees it as a
period of opportunity and well-being, with retention, or
development, of the psychological resources to cope with
life's challenges [3]. This coincides with world-wide pol-
icy interest in the promotion of physical and mental well-
being in populations, and the compression of morbidity
into fewer years of later life, driven by concerns about
increasing expenditure on health and social care in an
ageing society. Although there is an awareness that well-
being has no clearly defined opposite, and that it is more
than the absence of ‘ill-being', there are no agreed defini-
tions, other than that it is a ‘good thing' [4,5]. Policy
guidance, including that in the UK, prefers to focus on
specific aspects of well-being that are potentially amen-
able to known interventions, including physical activity
© 2011 Bowling and Iliffe; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited. Bowling and Iliffe Health and Quality of Life Outcomes 2011, 9:13
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(e.g. exercise) to maintain mental and physical function-
ing, hence well-being [6], rather than as a dynamic,
multi-faceted state which includes more complex subjec-
tive, social, and psychological dimensions. There are
however exceptions to such reductionist views [7,8]. For
example, NHS Scotland (2006) [8] defined the state of
mental well-being broadly, encompassing subjective and
psychological feelings of life satisfaction, optimism, self-
esteem, mastery and feeling in control, having a purpose
in life, a sense of belonging and support. This is more
consistent with the long tradition of social research on
general well-being, dating back to the 1950s [1].
The current, international policy focus on promotion
of well-being has stimulated interest in quality of life
(QoL) as an outcome indicator. QoL has long been used
as an outcome measure in the evaluation of a diverse
range of health and social care interventions. It is a
multi-faceted, concept, encompassing macro societal
and socio-demographic influences and also micro con-
cerns, such as individuals' experiences, social circum-
stances, health, values and perceptions [1]. As it is
subjective, it needs grounding in people's own values
and perceptions.
Much of the focus on how to enhance the quality of
later life has been on the achievement of successful age-
ing, by promoting different approaches, ranging from
biomedical, as in the MacArthur Studies of Successful
Aging [9-11], to broader social,-psychological and lay-
based approaches [3,12]. These overlap with concepts of
‘active ageing' [13]. The criteria necessary for achieving
successful ageing, described in the literature, can be
grouped into five approaches: biological (i.e. ‘health'),
broader biological (i.e. health and social engagement),
social, psychological and lay. These have have been
reviewed in detail in a cross-disciplinary systematic
review of successful ageing [3], and their construction
for the research reported here is summarised next (the
measurement scales are described later under Methods):
•
Biomedical (i.e. health): Comprised summing of:
having diagnosed, chronic medical conditions (actual
number reported); ability to perform activities of
daily living (ADL) (originally no/little difficulty was
originally scored <10, with the remainder scoring a
range of levels of difficulty); psychiatric morbidity
measured using the General Health Questionnaire-
12 (GHQ-12) (original caseness was scored as 5 or
more, with no problems as 0-4).
• Broader biomedical (i.e health and social
engagement): Comprised summing of the above
plus number of different social activities engaged in
during past month (3+), as an index of social
engagement.
Social functioning: Comprised summing of num-
ber of different social activities engaged in during
past month, frequency of social contacts, number of
helpers/supporters.
.
› Psychological resources: Comprised summing of
self-efficacy score (best score was less than an origi-
nal score of 11), best optimism score (of less than an
original score of 6), plus GHQ-12 items on sense of
purpose: playing useful part; coping: facing up to
problems, overcoming difficulties; self-esteem: feels
has self-confidence and has self-worth.
.
Lay: Comprised summing of the above (note:
GHQ-12 items were counted once only given their
overlap across models, to avoid singularity being vio-
lated by double summing), plus gross annual income
and perceived social capital [rating of area facilities
(e.g. transport, closeness to shops, services), area
problems (e.g. crime, vandalism, graffiti, speed and
volume of traffic, air quality), somewhere nice to go
for a walk, feels safe walking alone during the day or
night].
Biological (or health) approaches to achieve successful
ageing have been defined as the avoidance of disease and
risk factors, maintenance of physical and cognitive func-
tioning and active engagement with life [9]. Some biolo-
gical appraoches are broader, also including numbers
of different social activities engaged in during past month
(i.e. health and social engagement). Current social
approaches include maintenance of high levels of social
activity, interaction and participation [14]; and psycholo-
gical approaches emphasise psychological resources for
coping with the challenges of ageing over time (e.g. per-
ceived self-efficacy, control over life, ability to compen-
sate for declining abilities [15,16]. While biological
approaches have been the most often investigated [3],
broader approaches, including psycho-social factors
accord more closely with lay views of successful ageing
[2] that include income and environmental quality and
safety. In cross-sectional analyses such broader biological
approaches are also associated with people's self-rated
quality of life [12]. These have been reviewed in depth by
Bowling [3].
In earlier work on alternate criteria of successful ageing,
we reported that broader approaches predicted self-rated
QoL more powerfully than unidimensional approaches,
and should be used to evaluate the outcomes of health
promotion interventions in the older population [12]. This
paper investigates the predictive ability of these different
biological, psychological and social approaches of success-
ful ageing on QoL over time, using a national random
sample of people aged 65 and over who were followed up
7-8 years later. Bowling and Iliffe Health and Quality of Life Outcomes 2011, 9:13
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Methods
A postal follow-up survey of community-dwelling people
aged 65 and over who had responded to four face-to-
face interview surveys about QoL during 1999/2000.
The sample was derived from four quarterly Office for
National Statistics Omnibus Surveys during 2000-1,
sampled quarterly from a small user postcode sampling
frame across Britain, with geographic and socio-eco-
nomic stratification.
Omnibus Survey respondents aged 65 and over were
asked whether they would be willing to be re-inter-
viewed by ONS interviewers for our module on QoL.
Those who consented were re-interviewed two months
later. Of the sample of 1,299 eligible respondents sifted
by Omnibus Survey staff, the overall response rate was
77% (999), 19% refused and 4% were not contactable.
The characteristics of the baseline sample were broadly
representative of people aged 65 and over living at
home in Britain and have been reported in detail [1].
After removing the addresses of non-survivors identified
from flagging checks at NHS Central Registry), survivors
aged 65 and over at baseline were mailed a further postal
questionnaire in 2007-8 (n- 553), containing measures
of QoL, active ageing, health, psych-social and economic
circumstances. Of these 553 mailings, relatives replied and
informed us that a further five sample members had died,
and the Royal Mail returned a further 52 envelopes (9% of
the 553 mailings) as ‘person not at/unknown at that
address. Apart from sample flagging at ONS Central Reg-
istry, although there will be a time lag before revisions are
received, logged and released, all baseline respondents
were also given a Freepost card on which to notify us of
changes of address. As the follow-up study was postal,
there was no opportunity for interviewers to approach
neighbours for information about moves.
A total of 287 completed questionnaires were returned
by respondents. The raw response rate at final follow-up,
then, was 287 out of 553 mailed: 52%. The response was
52% if deaths were removed from the denominator (302/
553 minus 5 deaths = 287/548). The valid response rate
of 287 questionnaires returned out of 496 valid addresses
(removing both 5 deaths and 52 untraced respondents
from the denominator = base=496) was 58%.
Sample attrition is inevitable in longitudinal surveys of
older adults, where the most vulnerable and ill members
of the sample will have died, leaving the healthiest sam-
ple members. The follow-up sample was, by definition, a
sample of survivors. As the main source of non-response
was death, baseline characteristics of survivors and
deceased sample members by follow-up were compared.
These confirmed the expectation that the deceased
respondents were more likely than survivors to be older,
male, and less likely to rate their health optimally. For
=
example, of those who died by follow-up: 58% (133)
were in the oldest age group 75+, compared with 37%
(283) of survivors (Chi-square:55.260, 3df, p 0.001);
58% (132) were male, compared with 45% (343) of survi-
vors (Chi-square: 12.139, 1df, p = 0.001); and 59% (135)
had rated their health at baseline as 'Excellent/Very
good', compared with 77% (590) of survivors (Chi-
square: 29.338, 1df, p = 0.001). Hence, the results pre-
sented here need to be interpreted with caution, given
the healthier survivor bias.
The sample (287) was initially weighted by ONS to
correct for the unequal probability of small households
(in which people aged 65 and over usually live) being
included in the sample and this increased the effective
sample size to n = 302.
The baseline study was granted ethical committee
consent by London MREC and ONS Omnibus ethics
committee; the follow-up study was granted ethnical
committee consent to proceed by University College
London Research Ethics Committee, and registered with
UCL Clinical Governance.
Measures
QoL was the dependent variable, measured using the fol-
low-up QoL measure: the Older People's Quality of Life
Questionnaire (OPQOL). The OPQOL was designed to be
multi-dimensional, and was developed directly from older
people's views on the main components of QoL [1,17]. It
had 32 items with 5-point Likert scales ('Strongly Agree'
to 'Strongly Disagree'), representing: life overall (4 items),
health (4 items), social relationships and participation (7
items), independence, control over life, freedom (5 items),
area: home and neighbourhood (4 items), psychological
and emotional well-being (4 items), financial circum-
stances (4 items). Items are scored with higher scores
equalling higher QoL; the scale ranges from 32 to 160; cut
off points indicate levels of quality of life [17]. The
OPQOL had good psychometric properties when tested
on independent population and ethnically diverse sample
surveys in Britain; it had better reliability and validity over-
all than other QoL instruments [17]. Cronbach's alphas
for the OPQOL was a 0.901, and thus satisfied the a: 0.70
< 0.90 threshold for internal consistency: a: 0.901 [17].
The variables selected for the construction of the alter-
nate approaches to successful ageing (see Box 1) were
dichotomised into 'good' and 'not good' scores. The
number of good scores for each item included (see
below) was used to represent successful ageing for the
different approaches. Both numbers of good scores
within each approach, as well as traditional cut-off points
(achieving all or mostly good scores for the indicators
included within an approach [9]) were analysed. The bio-
medical approach was thus a sum of positive responses, Bowling and Iliffe Health and Quality of Life Outcomes 2011, 9:13
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indicating no problems to physical and psychological
health variables (diagnosed, chronic medical conditions,
activities of daily living, no psychological morbidity using
the General Health Questionnaire-12 [18]). The social
functioning approach comprised summing of: number of
different social activities engaged in during past month,
frequency of social contacts, and number of helpers and
supporters. The psychological resources approach
involved summing of positive self-efficacy score, best
optimism score, and positive responses to General Health
Questionnaire-12 (GHQ-12) [18] items measuring sense
of purpose, coping, self-confidence and self-worth (these
items were removed when the biological, social and psy-
chological approaches were entered together in a multi-
variate analyses to examine their independent predictive
ability). In addition to the GHQ-12 [18], the psycho-
social variables above were measured with validated
scales of social support [19], perceived neighbourhood
environment [20], self-efficacy [21], optimism-pessimism
[22], and items measuring social activities, loneliness, life
expectations, risk perceptions, and social comparisons.
Physical health and functioning was measured with
Townsend's [23] physical functioning [activities of daily
living (ADL)] scale; self-rated health; and diagnosed med-
ical conditions. Standard socio-demographic and eco-
nomic items were also included in the questionnaire.
These included age, sex, socio-economic status (NS-
SEC), housing tenure, gross annual income, age left full-
time education, highest education qualification, house-
hold size, and marital status. Indicators of successful age-
ing were selected after examination of the literature
[3,12].
Statistical analysis
The OPQOL was selected on the basis of its multi-
dimensionality as the outcome indicator against which to
test the independent predictive ability of the approaches
to successful ageing. The OPQOL was developed from
open-ended responses to questions about quality of life
at baseline, and tested in the follow-up survey. Thus
there was thus no baseline multidimensional measure of
OPQOL.
Item non-response was minimal at baseline. The range
of baseline item-non-response was16-21 out of the 999
respondents. This was due to the baseline study being a
face-to-face interview survey, conducted by trained
interviewers from the office of National Statistics (and
whose training emphasised the importance of item
response). The follow-up item response was less good as
the mode was self-completion (postal). The range of fol-
low-up item non-response was 55-58 out of the 302
weighted sample (287 raw sample size)
Univariate analyses included frequency distributions,
Spearman's rho correlations, means, and chi-square tests.
The Spearman rank correlation coefficient is calculated
on occasions when it is not possible to give actual values
to variables, but only to assign a rank order to instances
of each variable. Sex was coded in rank order (0,1) it was
therefore legitimate to use this method.
Linear multiple regression analysis was used for model
comparison in relation to quality of life outcomes (after
checks for multicollinearity). The ability of theoretically
relevant variables to independently predict successful
ageing classifications was tested. There are inconsistent
associations in the literature between socio-demographic
variables and indicators of well-being, including quality
of life, and these were included last (to control for their
effects) [1]. A hierarchical approach was used, with
entry of independent variables in theoretical order of
importance. The level for statistical significance was set
at 0.05. Item non-response was small, although
cumulative.
The scales and items included in the baseline measures
of successful ageing, were conceptually distinct from the
lay-based 'OPQOL' at follow-up. They did not over-cor-
relate by more than 0.60, and satisfied criteria for multi-
collinearity. For example, the baseline measures were
more objective indicators (e.g. number of chronic condi-
tions to number of social contacts). In contrast, the fol-
low-up OPQOL was subjective and contained evaluative
items (e.g. feelings of needing (more) companionship).
The multiple regression analysis was limited to testing
the biomedical (i.e. health), social and psychological
approaches, as independent predictors of quality of life,
as they overlapped in content with the broader biomedi-
cal (i.e. health and social engagement) and the multidis-
ciplinary lay approaches.
Results
Characteristics of sample
The baseline sample was evenly divided between men and
women, just under two thirds, were aged 65 < 74, and the
remainder were aged 75 and over; most were married
although over a quarter were widowed; and a third lived
alone; Less than half had an income of £7,280 or more.
The vast majority of respondents were white, as would be
expected in a national sample of people aged 65 and over
[1]. At follow-up, 17% (47) of the sample were aged 65 <
75; the remainder were all aged 75 and over. Over half of
the sample comprised women (54%, 152). In addition, 49%
(138) were married or cohabiting compared with being
single or widowed; 49% (137) lived alone, rather than with
others, and 85% (239) were owner-occupiers.
Quality of life
OPQOL scores at follow-up were slightly positively
skewed: 7% (17) scored as QoL as bad as can be (<11)
and 12% (29) scored at the most optimum QoL end of Bowling and Iliffe Health and Quality of Life Outcomes 2011, 9:13
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the scale (140+). The mean OPQOL score was 121.385;
standard deviation 14.048 (scale range 32-160, with
higher scores equating with better QoL). The QoL sub-
scales on which respondents scored most positively
were home and neighbourhood, followed by psychologi-
cal well-being and outlook (36% (106) and 30% (87)
respectively scored ‘QoL as good as can be'). The areas
that they scored worst on were health and functioning
and financial circumstances (21% (58) and 15% (45)
respectively scored ‘QoL as bad as can be'). This may be
expected with the decline in health and financial
reserves that often
These areas
accompany older age.
also had the lowest mean sub-scale scores. There were
no significant differences in mean score or subscale
scores and age or sex of respondents.
Successful ageing
Approaches to conceptualising successful ageing are tra-
ditionally constructed with dichotomous cut-off points
(successfully aged, or not), with the requirement that, to
be categorised as successfully aged, individuals should
have met the criteria for successful ageing on each
Table 1 Baseline successful ageing+ by follow-up OPQOL++
Successful ageing+++:
indicator included [9]. For this study, as stated earlier,
both numbers of good scores within each approach, as
well as traditional, dichotomous cut-off points indicating
success were analysed. At both baseline and follow-up,
the sample distributions were skewed positively towards
people achieving higher numbers of good scores within
all except the lay approach to successful ageing (which
had a normal distribution). However, few achieved all
good scores within each approach, indicating that tradi-
tional approaches are unrealistic as they exclude most
people.
Table 1 shows the associations between baseline
approaches to successful ageing, using traditional cut-
offs for success (all or mostly good scores on each indi-
cator in the approach), and follow-up OPQOL. The
smaller numbers in the successfully aged groups are
shown. Only the narrow biomedical (health) approach
failed to achieve statistical significance at the 0.05 level
with OPQOL categories.
Continuous scores for the measures of successful age-
ing were also analysed in relation to OPQOL scores. All
approaches were then significantly associated with
OPQOL: Quality of life is:
So bad could not be worse
scores <99
Middle scores
100-119
So good could not be better
scores 120+
% (n)
% (n)
% (n)
Successful ageing biomedical (health)
Not successfully aged
81 (13)
70 (64)
60 (75)ns
Successfully aged on all 3/3 indicators
19 (3)
30 (27)
40 (50)
Successful ageing broader biomedical (health and
social engagement)
Not successfully aged
88 (14)
73 (66)
62 (77)*
Successfully aged on all 4/4 indicators
13 (2)
28 (25)
38 (48)
Successful ageing psychological
Not successfully aged
100 (16)
85 (78)
72 (90)**
Successfully aged on all 7/7 indicators
15 (14)
28 (35)
Successful ageing social
Not successfully aged
81 (13)
57 (53)
38 (47)***
Successfully aged on all 3/3 indicators
19 (3)
43 (40)
62 (78)
Successful ageing lay
Not successfully aged (<10)
100 (13)
81 (70)
50 (61)***
Successfully aged on 10-13 indicators
No. of responders
13-14
19 (16)
91-93
50 (60)
125
NS not statistically significant using Chi-square tests at least at 0.050; * p < 0.05; ** p < 0.01; *** p < 0.001; Caution in interpretation is required where there are less
then 5 counts per cell.
+Recoded baseline scores; ++OPQOL scores grouped at follow-up.
+++ Biomedical (health): sum of (1 problem, 0 no problem) no diagnosed, chronic medical conditions, no problems with activities of daily living, no psychiatric
morbidity (GHQ-12 with 5+ cut-off); broader biomedical model (health and social engagement): sum of: the above plus number of different social activities engaged in
during past month (3+), as an index of social engagement; social functioning model: sum number of different social activities engaged in during past month (as above
3+), frequency of social contacts score (1-8), helped/supported in all 5 areas of life asked about.; psychological resources model: sum of self-efficacy score (best <11),
best optimism score (<6), plus best ratings on single GHQ items (3, 6, 8, 10, 11) on: sense of purpose: playing useful part; coping: facing up to problems, overcoming
difficulties; self-esteem: feels has self-confidence, has self-worth. Lay model: sum of all the above (note: duplicated items between above models counted once) plus
gross annual income (>£7280), and optimal perceived social capital scores (ratings of area facilities, e.g. transport, closeness to shops, services, area problems, e.g.
crime, vandalism, graffiti, speed and volume of traffic, air quality, somewhere nice to go for a walk, feels safe walking alone during the day or night).
