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| Journal of the New Zealand Medical Association,
05-November-2010, Vol 123 No 1325
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Predictors of physical activity and quality of life
in New Zealand prostate cancer survivors undergoing androgen-deprivation
therapy
Justin W L Keogh, Daniel Shepherd, Christian U
Krägeloh, Clare Ryan, Jonathan Masters, Greg Shepherd, Rod
MacLeod
Prostate cancer (PCa) is the most common cancer affecting
men in New Zealand, with the incidence rates rivalling that of breast cancer for
women.1
Many PCa survivors undergo androgen-deprivation therapy
(ADT) as it slows down the progression of the disease and increases survival
rates by reducing testosterone production.2
This reduction in testosterone causes many side-effects. It directly results in
a significant loss of muscle and bone mass and a gain in fat
mass,2,3 which appears to be a major
determinant of the significant losses in muscular strength and endurance as well
as functional capacity in tasks like sit to stand, stair climbing and fast
walking.4–6
As a result of these (and possibly other) physiological and
psychological changes, PCa survivors on ADT also report significant increases in
fatigue and decreases in quality of life
(QOL).2,7,8
Several cross-sectional studies have shown a link between
physical activity and QOL in PCa survivors.9,10
For example, PCa survivors who were more physically active had greater
health-related QOL9 and lower levels of
fatigue10 than their less-active PCa peers.
Recent reviews suggest that physical activity comprising
strength, aerobic or combined strength and aerobic training can reduce fatigue
as well as improve health and QOL (e.g. psychological, social and sexual),
muscular strength and aerobic fitness in PCa survivors, with the magnitude of
most of these changes of clinical
significance.11,12
It has also been reported that physical activity can reduce
PSA levels, meaning that the PCa survivors could avoid or delay conventional
treatments such as ADT for a period of two
years.13,14
The American Cancer Society recommends that cancer survivors
would improve their overall health if they were to perform ≥150 minutes of
moderate-strenuous intensity physical activity per week, of which ≥60
minutes should be strenuous.15
A recent review of the literature, however, suggests that
many PCa survivors are insufficiently active, with some of the reviewed studies
reporting physical activity rates of only
29–30%.16 In order to increase the
physical activity levels to generate health benefits, the determinants of
physical activity in PCa survivors on ADT need to be understood. Currently
little information is available on the physical activity patterns of PCa
survivors on ADT, particularly within New Zealand.
This exploratory cross-sectional study will collect this
information and will also utilise the Theory of Planned Behaviour (TPB)
model17, 18 to assess PCa survivors’
attitudes about physical activity, subjective norm and self-efficacy. Finally,
measures of health quality of life will be taken using the New Zealand version
of the World Health Organization WHOQOL-BREF35
questionnaire; with this QOL data compared to those of an age-matched sample
from the general population.
Research design and methodsThis cross-sectional survey-based study involved a
convenience sample recruited using the PCa survivor register held by the
Auckland District Health Board’s (ADHB) Urology Department. Initially, a
cover letter was sent out explaining the study and how they could participate.
One week later, a series of questionnaires, an information sheet, and a stamped
return-addressed envelope were mailed to 205 potential participants currently
diagnosed with PCa and undergoing ADT.
Two weeks following the initial distribution of
surveys, another letter was dispatched thanking those who had responded and
encouraging those who had not returned the questionnaires to do so.
Concurrently, normative data were collected from age- and gender-matched
individuals to afford comparison with a healthy sample.
Participants—From the initial
205 questionnaires posted to potential participants, 84 replies were received,
yielding a 41% response rate. The mean age of participants was 78.4 years
(SD=8.21), and 70 (84%) identified themselves as New Zealand European. Fifty-two
participants reported recent PSA levels (M=9.94 ng/mL, SD=22.76, Min=0.05,
Max=130), and the mean time elapsed since undertaking ADT was 3.9 years
(SD=3.6).
A second convenience sample from 26 organisations,
including senior citizens clubs and retirement villages, was undertaken to
provide comparative QOL data. From these organisations, 362 valid surveys were
completed and returned, 82 of which provided a balanced sample of age, gender
and ethnically matched but healthy individuals.
Measures—A self-report
questionnaire asking about QOL, physical activity, and factors related to
physical activity was utilised. QOL was assessed using the brief version of the
World Health Organization’s Quality of Life (WHOQOL-BREF)
scale.19 This scale consists of physical (7
items), psychological (6 items), social (3 items), and environmental (8 items)
domains, and two general items probing global quality of life and self-assessed
health.
Physical activity was gauged using the Rapid Assessment
of Physical Activity Scale (RAPA), a nine-item scale (each question requiring a
Yes/No response) designed to assess levels of physical activity among adults
older than 50 years.20
The nine questions of the RAPA cover a range of
physical activity levels, from sedentary to active, as well as strength training
and flexibility. The responses to the nine items allows the RAPA to classify
participants into one of five activity groups:
Factors
influencing physical activity were assessed using a pre-existing 47-item
inventory probing intention to be physically active, perceived control of
factors that prevent or encourage physical activity, attitudes towards physical
activity, and pressures from significant others to be physically active or
not.17, 18 Additionally, demographic items
elicited information about the participant’s age and ethnicity, their time
on ADT, length of PCa diagnosis, and if known, the most recently assessed PSA
levels.
Statistical analyses—Data
analyses were conducted in SPSS v17 software. Because of the modest sample size
(n=84), a thorough screen was undertaken to ensure that the data adhered to the
assumptions stipulated by the respective tests, and nonparametric alternatives
were employed when assumptions were violated. Prior to constructing composite
measures, item mean and standard deviations were calculated to identify any
floor or ceiling effects, corrected item-total correlations were scrutinised to
ensure the unidimensionality of item sets, and then Cronbach’s alpha
computed to assess internal consistency.
Group differences in QOL domains were assessed using
independent samples t-tests or Mann Whitney U-Tests. The Theory of Planned
Behaviour (TPB) was applied to investigate the relationship between behavioural
intention and a linear combination of the following composite variables:
attitudes to physical activity, pressure from others to partake (or not) in
physical activity (subjective norm), and perceived behavioural control (PBC) in
relation to undertaking physical activity. In its standard form, the TPB is
represented by the following equality:
Behavioural Intention =
(W1)ATTITUDE+(W2)SUBJECTIVE
NORM + (W3)PBC
where Wi are
empirically derived weights. The TPB was assessed using a multiple linear
regression analysis, with standardised beta coefficients (β) examined to
gauge the predictive utility of each component. The association between the
three components of the TPB and actual physical activity as defined by the RAPA
(i.e. active vs. insufficiently active) was determined using a binary logistic
regression.
In both regression analyses covariates were not
included due to sample size limitations. However, the lack of correlation
between potential covariates (e.g. age, time on ADT, PSA level) and the
components of the TPB meant any exclusion was likely only to reduce the overall
predictive accuracy of the models rather than introduce specification errors.
ResultsLevels of physical activity—Physical
activity levels, shown in Figure 1, indicate that 45% of participants
(n=38) lead an active lifestyle, while the remainder (n=46) were
insufficiently active. Correlation coefficients (r) indicated a lack of
association between physical activity level and either age (r=0.106, p=0.343),
time since diagnosis (r=0.141, p=0.252), time on ADT (r=-0.081, p=0.470), or PSA
level (r=0.118, p=0.382).
Twelve participants (14%) responded yes to the question
“I do activities to increase muscle strength, such as lifting weights or
callisthenics, once a week or more.”, and 19 participants (23%) responded
yes to “I do activities to improve flexibility, such as stretching or
yoga, once a week or more.”
Figure 1. The left portion of the figure shows
the number of individuals falling into the five physical activity categories
specified by the RAPA scale. The right portion shows those undertaking
activities improving strength or flexibility
 Differences in QOL—PCa survivors had
significantly lower mean physical (p<0.001) and environmental (p=0.025) QOL
scores than the matched sample. Furthermore, mean ratings of global QOL
(p<.001) and self-assessed health status (p<.001) were also lower than the
matched sample.
When PCa survivors were sorted into active and
insufficiently active groups, the active group had higher mean physical QOL
(p=0.034), global QOL (p=0.023), and self-assessed health
(p=0.037). An additional series of Mann-Whitney U-tests were undertaken
to assess group differences between those who reported engaging in strength
training (n=12) and those who did not (n=72), and those engaging in flexibility
activities (n=19) and those who were not (n=65).
Those undertaking some form of strength training had
significantly higher global (p=0.039) and environmental (p=0.023) QOL than those
not reporting such activities. Those partaking in activities designed to improve
flexibility had significantly higher global (p=0.006), physical (p=0.018) and
environmental (p=0.008) QOL. Note that, for any of the difference tests
performed between groups, there were no significant differences recorded between
mean QOL scores on the psychological or social domains (p>0.05).
Predictors of physical activity—Table
1 shows the results from a multiple linear regression, which indicates the
association between the intention to exercise and the three components of the
Theory of Planned Behaviour. Of remark in Table 1 is the strong link between
attitudes towards physical activity and the intention to be physically active
(p<0.001). Societal and peer pressures (i.e. subjective norm), and
perceptions of efficacy to undertake activity (i.e. PBC), do not appear to be
significantly associated with the intention to partake in physical activity.
Table 1. Estimates of unstandardised and
standardised coefficients for a multiple linear regression of intention to
partake in physical activity
Note: R=0.775;
R2=0.601,
adj-R2=0.585;
SEest=4.893
Predictors of actual physical
activity—Table 2 displays the results of a binary logistic
regression, where positive values of the regression coefficient B
indicate that the predicted odds increase as the predictor value increases
(i.e. more likely to be in the physically active group). Scrutiny of the Wald
chi-square statistics in Table 2 indicates that attitude and subjective norm are
not significant predictors of physical activity category.
The PBC component of the TPB emerges as a significant
predictor of physical activity (p=0.015), indicating that the odds of being in
the active group is positively related to PBC. Goodness-of-fit tests
(Hosmer-Lemeshow) suggested an adequate fit to the data. The improvement of the
model displayed in Table 2 over a baseline model (i.e. one containing none of
the predictors) is evident in the classification table displayed in Table 3,
which indicates the agreement between predicted and actual outcomes.
Table 2. Logistic regression analysis of
prostate cancer survivor’s activity levels. The table displays maximum
likelihood parameter estimates, both in raw form as logits (i.e. B) and
as odds ratios (eb), accompanied by
95% confidence intervals
Note: Cox & Snell
R2=0.242. Nagelkerke
R2=0.323. Hosmer and Lemeshow test:
χ2(8)=9.41, p=0.309.
Table 3. Observed and predicted frequencies for
physical activity/inactivity by logistic regression with a cut-off of 0.50.
Parentheses contain the predictions from the baseline (i.e. intercept-only)
model
 Barriers to physical
activity—Responses to open-ended questions provided insight into
additional preventative and supportive factors influencing participants’
physical activity. Of the preventative factors, lack of energy and health
problems additional to PCa were the most common factors that prevented
participants from being physically active, as well as weather and interference
by paid employment. The most common factors that supported participants in being
physically active were the health and mental health benefits, and the enjoyment
of participating in activities that had physical components to them (e.g.
gardening and household tasks).
DiscussionThe majority of PCa survivors in our sample were classified
as insufficiently active, with just 45% meeting the recommended guidelines set
out by the American Cancer Society of at least 30 minutes of moderate intensity
physical activity on five or more days per
week.15
These results appears to lie within the extremes reported in
a recent review of the physical activity levels of PCa
survivors.16 Additionally, we found no
relationship between physical activity level and time since diagnosis, PSA
levels, or time on ADT. This finding has consequences in relation to timing of
interventions based on physical activity, and suggests no critical time window
exists immediately after diagnosis or ADT onset.
Beyond the direct physical changes, ADT has also been shown
to cause very substantial reductions in QOL for PCa
survivors.8 In our sample we found PCa
survivors had significantly lower physical and environmental QOL when compared
to age-matched healthy individuals. Whether this constitutes evidence that the
cancer or the cancer treatment may be affecting the physical domain is unclear,
as 64% of respondents also reported other conditions. However, it can be argued
that either a single disease or a combination of diseases would have the
potential to degrade physical QOL.
Additionally, PCa survivors also had significantly lower
global QOL and self-assessed health than the matched sample, echoing previous
research.7,8 Physical activity has positive
benefits on QOL,9,10 and a comparison between
PCa survivors classified as active and those classified as insufficiently active
supports this relationship.
On average those PCa survivors classified as active had
significantly higher global and physical QOL, and higher self-rated health than
insufficiently active survivors, suggesting that efforts to maintain or increase
physical activity levels in this group are a worthwhile objective. Furthermore,
12 (14%) participants reported regularly partaking in strength training. This
finding concurs with a recent review that suggests prevalence rates of
10–15% for strength training in older
adults.21
While there are likely many factors contributing to the low
rates of strength training in older adults (including PCa survivors), Winnett et
al.21 argue that the primary factors may be
public health policy not emphasising strength training, misinformation, and the
lack of theoretically driven approaches to maintain adherence in the long-term.
Such views appear somewhat consistent with the predictors of physical activity
found in this study along with studies on the factors associated with the use of
complementary therapies by cancer
survivors.22–24
These studies indicate that the misinformation regarding
exercise often comes from potentially unreliable sources such as family, friends
and the media,22 even though exercise
counselling23 and the support of clinicians may
play an important role in cancer survivors adopting and maintaining healthy
behaviours such as exercise.24
In light of the way that cancer survivors obtain information
about the benefits of physical activity and other complementary therapies and
our findings indicating that most PCa survivors are insufficiently active,
considerably more effort needs to be focused on ensuring that a greater
proportion of PCa survivors especially those on ADT are physically active. Such
results would suggest that clinicians working with PCa survivor are in a unique
place to offer such advice.
Intention to engage in physical activity is driven by a
number of factors, including attitude, subjective norms and PBC. Two studies of
PCa survivors using the TPB25,26 report that
these three factors explain a high percentage of the variance in physical
activity intention.
Consistent with these previous
studies,25,26 the best predictor of physical
activity in the present dataset was the PBC. The PBC component combines the
notions of perceived control and self-efficacy in relation to a behaviour, where
perceived control is an assessment of external constraints and self-efficacy the
belief that one has the ability to perform certain behaviours.
Our participants identified a range of factors that both
prevented and supported them in being physically active, with health problems
and disability being the highest preventative factor. Additionally, lack of
energy was the most highly reported factor that prevented participants from
engaging in physical activity. This was expected, as fatigue is a debilitating
side-effect of both cancer and cancer treatment, including
ADT.2,10
Such a result is a sort of vicious cycle, whereby if a PCa
survivor is tired, they won’t exercise, and if they don’t exercise,
they will be more tired. However, as increasing physical activity can actually
reduce fatigue in PCa survivors,27 this further
demonstrates the importance of exercise counselling for these individuals.
Limitations and future research—Small
convenience samples increase the probability of type I errors by preventing the
use of more sophisticated multivariate techniques, and also invite type II
errors by providing less than satisfactory power. However, while the findings we
report here may be considered somewhat speculative and need to be confirmed with
a larger New Zealand sample, they are congruent with findings reported
overseas.7,16,26
A second limitation is the use of self-report inventories,
with participants potentially overstating their levels of physical activity and
under-reporting sedentary behaviours due to social desirability
bias.28 Furthermore, while the PCa group
differed to the matched group on the basis of the cancer diagnosis and use of
ADT, no attempt was made to match the groups on the basis of self-reported
health or comorbidities.
It is therefore not entirely clear how the cancer, use of
ADT, health status or comorbidities contributed to the findings of this study.
Future research may address this question by comparing various sub-groups of PCa
survivors to determine the effect of treatment type, health status or
comorbidities on physical activity, QOL and their inter-relationships.
Randomised controlled trials should also be conducted to examine the effect that
exercise counselling has on the adoption and maintenance of physical activity
levels in PCa survivors, and how these potential changes in physical activity
may be associated with improved QOL and reduced fatigue.
Competing interests: None.
Author information: Justin W L Keogh,
Associate Professor, Centre for Physical Activity and Nutrition Research Centre,
Person Centred Research Centre, AUT University; Daniel Shepherd, Senior
Lecturer, Department of Psychology, AUT University; Christian U Krägeloh,
Senior Lecturer, Department of Psychology, AUT University; Clare Ryan,
Department of Psychology, AUT University; Jonathan Masters, Honorary Senior
Lecturer, Department of Surgery, Medical School, University of Auckland; Greg
Shepherd, Department of Psychology, AUT University; Rod MacLeod, Associate
Professor, School of Population Health, University of Auckland
Acknowledgements: We thank the Cancer
Society of New Zealand and the Faculty of Health and Environmental Sciences, AUT
University for funding this project; Professor Robert Newton for providing
expertise and assistance in the initial design of this study; and all of the
prostate cancer survivors who gave up their time to participate in this
research.
Correspondence: Associate Professor Justin
Keogh, School of Sport and Recreation, AUT University, Private Bag 92006,
Auckland, New Zealand. Fax: +64 (0)9 9219960; email: justin.keogh@aut.ac.nz
References:
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