http://www.plosmedicine.org/article/info%3Adoi%2F10.1371%2Fjournal.pmed.1000
110
( or via http://www.plosmedicine.org/home.action).

Cost-Effectiveness of Interventions to Promote Physical Activity: A
Modelling Study

Linda J. Cobiac*, Theo Vos, Jan J. Barendregt

Centre for Burden of Disease and Cost-Effectiveness, School of Population
Health, The University of Queensland, Herston, Queensland, Australia

Background

Physical inactivity is a key risk factor for chronic disease, but a growing
number of people are not achieving the recommended levels of physical
activity necessary for good health. Australians are no exception; despite
Australia's image as a sporting nation, with success at the elite level, the
majority of Australians do not get enough physical activity. There are many
options for intervention, from individually tailored advice, such as
counselling from a general practitioner, to population-wide approaches, such
as mass media campaigns, but the most cost-effective mix of interventions is
unknown. In this study we evaluate the cost-effectiveness of interventions
to promote physical activity.
Methods and Findings

From evidence of intervention efficacy in the physical activity literature
and evaluation of the health sector costs of intervention and disease
treatment, we model the cost impacts and health outcomes of six physical
activity interventions, over the lifetime of the Australian population. We
then determine cost-effectiveness of each intervention against current
practice for physical activity intervention in Australia and derive the
optimal pathway for implementation. Based on current evidence of
intervention effectiveness, the intervention programs that encourage use of
pedometers (Dominant) and mass media-based community campaigns (Dominant)
are the most cost-effective strategies to implement and are very likely to
be cost-saving. The internet-based intervention program (AUS$3,000/DALY),
the GP physical activity prescription program (AUS$12,000/DALY), and the
program to encourage more active transport (AUS$20,000/DALY), although less
likely to be cost-saving, have a high probability of being under a
AUS$50,000 per DALY threshold. GP referral to an exercise physiologist
(AUS$79,000/DALY) is the least cost-effective option if high time and travel
costs for patients in screening and consulting an exercise physiologist are
considered.

==
Kaete Walker
Postal: 4/107 Denison Street, Hamilton. NSW. 2296. Australia.
Tel: +61 2 49 400 693 Mobile: +61 407 176 786
Email mytanwy@... URL: http://www.kaete.net/
~~~ ~ _@
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~~ (*)/ (*)

Kaete Walker.
Registered Nurse/Case Manager, Hunter Valley Mental Health Service.
Accredited Person, NSW Mental Health Act.
Postal:10/555 High Street, Maitland. NSW. 2320. Australia.
Tel: +61 2 49 39 2900. Mobile: +61 418 205 958.
E: Kaete.Walker@...


Conclusions

Intervention to promote physical activity is recommended as a public health
measure. Despite substantial variability in the quantity and quality of
evidence on intervention effectiveness, and uncertainty about the long-term
sustainability of behavioural changes, it is highly likely that as a
package, all six interventions could lead to substantial improvement in
population health at a cost saving to the health sector.

Please see later in the article for Editors' Summary

Citation: Cobiac LJ, Vos T, Barendregt JJ (2009) Cost-Effectiveness of
Interventions to Promote Physical Activity: A Modelling Study. PLoS Med
6(7): e1000110. doi:10.1371/journal.pmed.1000110

Academic Editor: Nikos Demiris, University of Cambridge, United Kingdom

Received: September 26, 2008; Accepted: June 4, 2009; Published: July 14,
2009

Copyright: © 2009 Cobiac et al. This is an open-access article distributed
under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the
original author and source are credited.

Funding: This research was funded by an Australian National Health and
Medical Research Council Health Services Research grant (no. 351558,
http://www.nhmrc.gov.au/grants/types/gra​nttype/strategic/healthserv.htm ).
The funders had no role in study design, data collection and analysis,
decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests
exist.

Abbreviations: ACE, assessing cost-effectiveness; CER, cost-effectiveness
ratio; DALY, disability-adjusted life year; GP, general practitioner; ICER,
incremental cost-effectiveness ratio; QALY, quality-adjusted life year; RCT,
randomised controlled trial; UI, uncertainty interval

* E-mail: l.cobiac@...
Editors' Summary Top
Background

The human body needs regular physical activity throughout life to stay
healthy. Physical activity—any bodily movement produced by skeletal muscles
that uses energy—helps to maintain a healthy body weight and to prevent or
delay heart disease, stroke, type 2 diabetes, colon cancer, and breast
cancer. In addition, physically active people feel better and live longer
than physically inactive people. For an adult, 30 minutes of moderate
physical activity—walking briskly, gardening, swimming, or cycling—at least
five times a week is sufficient to promote and maintain health. But at least
60% of the world's population does not do even this modest amount of
physical activity. The daily lives of people in both developed and
developing countries are becoming increasingly sedentary. People are sitting
at desks all day instead of doing manual labor; they are driving to work in
cars instead of walking or cycling; and they are participating less in
physical activities during their leisure time.
Why Was This Study Done?

In many countries, the chronic diseases that are associated with physical
inactivity are now a major public-health problem; globally, physical
inactivity causes 1.9 million deaths per year. Clearly, something has to be
done about this situation. Luckily, there is no shortage of interventions
designed to promote physical activity, ranging from individual counseling
from general practitioners to mass-media campaigns. But which intervention
or package of interventions will produce the optimal population health
benefits relative to cost? Although some studies have examined the
cost-effectiveness of individual interventions, different settings for
analysis and use of different methods and assumptions make it difficult to
compare results and identify which intervention approaches should be give
priority by policy makers. Furthermore, little is known about the
cost-effectiveness of packages of interventions. In this study, the
researchers investigate the cost-effectiveness in Australia (where physical
inactivity contributes to 10% of deaths) of a package of interventions
designed to promote physical activity in adults using a standardized
approach (ACE-Prevention) to the assessment of the cost-effectiveness of
health-care interventions.
What Did the Researchers Do and Find?

The researchers selected six interventions for their study: general
practitioner “prescription” of physical activity; general practitioner
referral to an exercise physiologist; a mass-media campaign to promote
physical activity; the TravelSmart car use reduction program; a campaign to
encourage the use of pedometers to increase physical activity; and an
internet-based program. Using published data on the effects of physical
activity on the amount of illness and death caused by breast and colon
cancer, heart disease, stroke, and type 2 diabetes and on the effectiveness
of each intervention, the researchers calculated the health outcomes of each
intervention in disability-adjusted life years (DALY; a year of healthy life
lost because of premature death or disability) averted over the lifetime of
the Australian population. They also calculated the costs associated with
each intervention offset by the costs associated with the five conditions
listed above. These analyses showed that the pedometer program and the
mass-media campaign were likely to be the most cost-effective interventions.
These interventions were also most likely to be cost-saving. Referral to an
exercise physiologist was the least cost-effective intervention. The other
three interventions, though unlikely to be cost-saving, were likely to be
cost-effective. Finally, a package of all six interventions would be
cost-effective and would avert 61,000 DALYs, a third of what could be
achieved if every Australian did 30 minutes of physical activity five times
a week.
What Do These Findings Mean?

As in all modeling studies, these findings depend on the quality of the data
and on the assumptions included by the researchers in their calculations.
Unfortunately, there was substantial variability in the quantity and quality
of evidence on the effectiveness of each intervention and uncertainty about
the long-term effects of each intervention. Nevertheless, the findings
presented in this study suggest that the assessment of the
cost-effectiveness of a combination of interventions designed to promote
physical activity might provide policy makers with some guidance about the
best way to reduce the burden of disease caused by physical inactivity. More
specifically, for Australia, these findings suggest that the package of the
six interventions considered here is likely to provide a cost-effective way
to substantially improve the health of the nation.
Additional Information

Please access these Web sites via the online version of this summary at
http://dx.doi.org/10.1371/journal.pmed.1​000110 .

*

The World Health Organization provides information about physical
activity and health (in several languages); it also provides an explanation
of DALYs
*

The US Centers for Disease Control and Prevention provides information
on physical activity for different age groups and for health professionals
*

The UK National Health Service information source Choices also
explains the benefits of regular physical activity
*

MedlinePlus has links to other resources about exercise and physical
fitness (in English and Spanish)
*

The University of Queensland Web site has more information on
ACE-Prevention (Assessing Cost-Effectiveness Prevention)

Introduction Top

Physical activity occurs during work, transport, domestic, and leisure-time
activities. Too little physical activity increases the risks of ischaemic
heart disease, stroke, colon cancer, breast cancer, and type 2 diabetes [1],
as well as obesity [2] and falls in later life [3]. The World Health
Organization recommends at least 30 minutes of regular, moderate-intensity
physical activity on most days to reduce the risk of disease and injury [4].

Lack of physical activity is a problem in many developed countries, and a
growing concern for developing countries adopting a progressively
“Westernised” lifestyle [5]. Australia is no exception, with only 44% of men
and 36% of women achieving sufficient physical activity for health [6]. This
inactivity contributes 7% of Australia's disease burden and 10% of all
deaths, mostly due to cardiovascular disease and diabetes [7]. It also
places a substantial burden on the Australian economy through the costs of
treatment for physical activity–related disease and injury, lost
productivity, and diminished quality of life [8].

Interventions to promote physical activity (referred to herein as “physical
activity interventions”) typically involve teaching individuals the skills
to change physical activity behaviour, providing the population with
knowledge about physical activity goals or opportunities to be active, or
creating a more physically active environment [9]. Currently, in Australia,
general practitioners (GPs) are relied upon to deliver physical activity
interventions (when time permits). In addition, governments provide some
encouragement to change physical activity behaviour through local mass media
and transport campaigns, but investment is minimal. It is likely that a
combination of intervention approaches will be needed to achieve a
meaningful change in population participation in physical activity
[10]–[12].

Efficient allocation of health resources to different intervention programs
hinges on identifying those interventions (or combinations of interventions)
that achieve maximum population health benefits relative to cost. However,
there is a need for more cost-effectiveness analyses using standardised
methods to enable comparison of different types of physical activity
interventions [13]. Although there have been a number of cost-effectiveness
analyses of individual interventions [14]–[20], including two studies
reporting cost-effectiveness of GP prescription in the Australian context
[17],[19], there has been only one cost-effectiveness analysis, by the
National Institute of Clinical Excellence (NICE) in the United Kingdom [21],
that used a standardised approach to compare multiple interventions. All ten
interventions, which involved brief advice by a health professional or
referral to an exercise physiologist, were found to be dominant (i.e.,
cost-saving) when compared with usual care. However, the NICE study focused
only on intervention alternatives rather than evaluating a range of
complementary interventions (including broader public health approaches
incorporating media, active transport, etc.) and the potential benefits of
combining interventions as a package.

In Australia, a standardised approach to assessing cost-effectiveness (ACE)
has been developed for evaluating interventions in the Australian health
care context [22]. These methods are being used to evaluate 150
interventions, focusing on prevention of noncommunicable disease, including
six interventions to promote physical activity. In this paper, we present
the ACE results for the physical activity interventions, which range from
individualised counselling interventions to broad population health
approaches. The cost-effectiveness of each intervention is compared with
current practice for physical activity intervention in the Australian
population, and from this we derive an optimal intervention pathway for
improving population health.
Methods Top
Interventions

We reviewed the physical activity and transport intervention literature to
identify a range of interventions targeting the adult population, which
would be suitable for implementation in Australia, and had evidence of
efficacy/effectiveness to support the analyses. Where there were multiple
studies of the same type of intervention, studies were combined in a
meta-analysis, using a random effects approach where there was heterogeneity
between trial results. However, where multiple studies were too
heterogeneous to enable a precise definition of the intervention and
comparator (i.e., who did what, to whom, when, and where) and accurate
measurement of resources used, a single study was chosen for economic
evaluation. This selection was based on the strength of evidence of
effectiveness and generalisability of the setting and population to the
Australian context (i.e., giving consideration to both the internal and
external validity of the intervention evidence). A full description of the
review and criteria for selection of interventions is provided in Text S1.
From the review process, we selected six intervention programs for
cost-effectiveness analysis:
GP prescription.

Patients are screened opportunistically when visiting their general
practice; inactive patients receive a physical activity prescription from
the GP and follow-up phone call(s) from an exercise physiologist.
GP referral to exercise physiologist.

Screening questionnaires are mailed to all patients on the GP patient list;
inactive patients are invited to attend a series of counselling sessions
with an exercise physiologist at their local general practice.
Mass media-based campaign.

A six-week campaign combines physical activity promotion via mass media
(television, radio, newspaper, etc.), distribution of promotional materials,
and community events and activities.
TravelSmart.

An active transport program targets households with tailored information
(e.g., maps of local walking paths, bus timetables) and merchandise (e.g.,
water bottles, key rings) as an incentive and/or reward for reducing use of
cars for transport.
Pedometers.

A community program encourages use of pedometers as a motivational tool to
increase physical activity (e.g., to 10,000 steps per day).
Internet.

Participants are recruited via mass media to access physical activity
information and advice across the internet via a Web site and/or email.

Table 1 gives a summary of the intervention effects, costs, and target
groups. The effect of each intervention on physical activity in the
Australian population is derived from the characteristics of the
intervention target group (e.g., age, sex, and baseline physical activity
participation) and intervention changes in intensity, duration, and/or
frequency of physical activity. The cost of implementing each intervention
is derived from an Australian health sector perspective. This includes costs
to both government and patients, including time and travel costs, but
excluding patient time costs associated with changes in physical activity.
Intervention start-up costs (e.g., costs of research and development of
intervention materials for GP prescription) are excluded so that all
interventions are evaluated and compared as if operating under steady-state
conditions (i.e., fully implemented and operating in accordance with
effectiveness potential). Further details of each intervention are provided
in Text S1.
thumbnail

Table 1. The target groups, physical activity effects, and costs associated
with implementing the physical activity interventions in Australia for one
year (2003 baseline year).
doi:10.1371/journal.pmed.1000110.t001
Modelling Health Outcomes and Costs

Cost-effectiveness analysis is based on intervention in the first year, with
all health outcomes and costs measured over the lifetime of the Australian
population in a baseline year of 2003. All future health outcomes and costs
are discounted at 3% per annum.

The health outcomes of each intervention are evaluated in
disability-adjusted life years (DALYs), the measure favoured by the World
Health Organization [23], and the alternative to the quality-adjusted life
year (QALY) measure used in some cost-effectiveness analyses of physical
activity interventions [21],[24]. The critical difference between the DALY
and QALY measures is in the measurement of utility weights for the QALY and
disability weights for the DALY. Utility weights are typically elicited from
general population samples or groups of patients, and do not always match
the specific disease and physical activity states used in modelling
cost-effectiveness of interventions, a limitation acknowledged by Roux et
al. [25] in their recent evaluation of physical activity interventions using
QALY measures. Utility weights also lack consistency across many different
diseases. Although techniques for eliciting disability weights for each
disease are controversial [26], the use of a standard set of weights across
all diseases has advantages in large projects, where cost-effectiveness
decision-making encompasses many disease and risk factor interventions
(e.g., Australia's ACE–Prevention project) and sometimes many regions of the
world (e.g., World Health Organization's WHO-CHOICE [27]).

DALYs are calculated using a multi-state, multiple cohort life-table
approach to determine changes in mortality and morbidity for five physical
activity-related diseases: ischaemic heart disease, ischaemic stroke, type 2
diabetes, breast cancer, and colon cancer. The effects of physical activity
on other risk factors (e.g., obesity and falls), which require more complex
modelling, and the effects of physical activity on prevention of depression,
which is still a subject of debate [28], are being evaluated in separate ACE
modelling analyses and results are not presented here.

The cost of each intervention is offset by the cost per incident case of
breast cancer and colon cancer averted and the cost per prevalent case of
ischaemic heart disease, ischaemic stroke, and type 2 diabetes averted.
Health care costs for all other diseases in added years of life are excluded
from basic results, but their influence on cost-effectiveness is explored in
additional analyses, as recommended by the Panel on Cost-Effectiveness in
Health and Medicine in the United States [29].

The intervention effects on disease risk have previously been modelled from
observed changes in prevalence of physical activity across two or more
categories, with relative risks derived for each intervention from health
outcome studies using comparable physical activity categories (e.g., [21]).
The two key drawbacks to this approach are that it limits evaluation to
intervention studies that measure categorical outcomes (e.g.,
active/inactive) and precludes analysis of intervention combinations to
calculate an optimal intervention pathway, because categories are rarely
defined the same way in different intervention studies. We instead estimate
the change in relative risk of each physical activity–related disease from a
change in energy expenditure, which we derive from estimates of activity
intensity, duration, and/or frequency for each intervention (Text S1).

The relationships between relative risk and energy expenditure are derived
for each physical activity–related disease from meta-analyses carried out
for the World Health Organization's Comparative Quantification of Health
Risks [1]. Relative risks are assumed to decrease linearly with increasing
energy expenditure, up to the level of physical activity at which there is
no excess risk (≈30 min of activity on 5 d of the week at a moderate
intensity of 5 METs, i.e., 5× the resting metabolic rate). Full details of
these modelling methods and assumptions, and all data sources, are included
in Text S2.
Intervention Cost-Effectiveness

A cost-effectiveness ratio (CER) is evaluated for each intervention in
comparison with current practice, which approximates a “do nothing”
scenario. Our review of intervention implementation in Australia found that
while some interventions were in place in 2003, all were operating at less
than 5% of the estimated full capacity (Table 2).
thumbnail

Table 2. Current practice for the six physical activity interventions in
2003.
doi:10.1371/journal.pmed.1000110.t002

Ninety-five percent uncertainty intervals are determined for all outcome
measures by Monte Carlo simulation (2,000 iterations), using the Excel
add-in tool @RISK (Palisade, Version 4.5). Uncertainty distributions around
input parameters are described in Text S3.

The results of the Monte Carlo analysis are used to determine probability of
intervention cost-effectiveness against a range of threshold values. In this
paper, results are reported against a cost-effectiveness threshold of
AUS$50,000 per DALY [30],[31].
Intervention Pathway Analysis

The optimal pathway for implementation of interventions is developed using a
generalised cost-effectiveness approach [32]. We first derive the disease
incidence rates that would have occurred in 2003 if none of the
interventions under evaluation (Table 2) were in place. This scenario is
referred to as the “partial null.” The cost-effectiveness of each
intervention is then evaluated in comparison with the partial null to
determine the order of interventions in the pathway, from most
cost-effective to least cost-effective. Finally, the cost-effectiveness of
each intervention combination in the pathway is evaluated in comparison with
the partial null. From this we derive an incremental cost-effectiveness
ratio (ICER) for each intervention, which reflects the cost-effectiveness of
adding the intervention to the pathway.
Sensitivity Analysis

The sustainability of intervention health effects over time is an important
parameter in the cost-effectiveness analysis, but there are currently too
few studies with long-term participant follow-up (e.g., greater than two
years) to quantify the sustainability of the physical activity effect
associated with each of the interventions. In our base case analysis we
assume that the intervention effects on physical activity are sustained for
the first year, but decay exponentially at a rate of 50% per annum
thereafter; therefore, there will be virtually no intervention effect after
five years. Sensitivity of the intervention pathway to this assumption is
evaluated by varying decay rates between 0% (lifelong behaviour change) and
100% (behaviour change reversed after the first year).
Results Top
Intervention Cost-Effectiveness

There is large variability in the health gain that can be achieved with
different methods of intervention. The number of DALYs averted ranges from
740 (95% uncertainty interval [UI] 110–1,900) for internet-based
intervention to 23,000 (95%UI 7,600–40,000) for a mass media campaign (Table
3). Intervention costs also vary substantially, ranging from AUS$13 million
(95%UI AUS$11 million to 16 million) for the mass media campaign to AUS$410
million (95%UI AUS$210 million to 570 million) for the TravelSmart
individualised marketing program.
thumbnail

Table 3. Cost-effectiveness of physical activity interventions when compared
with current practice.
doi:10.1371/journal.pmed.1000110.t003

The interventions predominantly fall in the northeast and southeast
quadrants of the cost-effectiveness plane (Figure 1), indicating a high
probability of improvements in population health with increased expenditure
on physical activity intervention or, in some cases, with a net cost-saving
due to physical activity intervention.
thumbnail

Figure 1. Cost-effectiveness of the physical activity interventions when
compared with current practice.
doi:10.1371/journal.pmed.1000110.g001

Two interventions stand out as being most effective and most
cost-effective—the mass media campaign and the pedometer program. Both of
these interventions are dominant and have a 100% probability of being
cost-saving (Table 4).
thumbnail

Table 4. Acceptability of physical activity interventions when compared with
current practice.
doi:10.1371/journal.pmed.1000110.t004

Only the GP referral intervention has a low probability of being under the
AUS$50,000 per DALY cost-effectiveness threshold when all costs are
considered. GP referral has a substantial time and travel cost component for
patients in visiting an exercise physiologist. If these costs are excluded
from the analysis, the intervention is dominant, with a 100% probability of
being under the threshold and a 98% probability of being cost-saving.
Intervention Pathway

When all six interventions are combined in a package, the package would
avert 61,000 DALYs (95%UI 39,000–87,000 DALYs). This is 34% of what could
theoretically be achieved if all Australians (except the most disabled)
achieved the sufficient level of activity recommended by the World Health
Organization [4] and Australian Physical Activity Guidelines [33]. The
health gain from the six interventions would be achieved at a total cost of
AUS$940 million (95%UI AUS$720 million to 1,100 million), which includes
AUS$90 million in time and travel costs. However, the costs of intervention
would be more than offset by an estimated reduction of AUS$1,400 million
(95%UI AUS$790 million to 2,100 million) in the costs of treating physical
activity-related diseases. The cost-effectiveness of the pathway is
reflected by its location in the southeast quadrant of the
cost-effectiveness plane (Figure 2).
thumbnail

Figure 2. The physical activity intervention pathway.
doi:10.1371/journal.pmed.1000110.g002

In order of cost-effectiveness, a pedometer intervention program should be
implemented first, followed by a mass media campaign, an internet-based
program, GP prescription, the TravelSmart program, and, finally, GP referral
to an exercise physiologist. In this pathway, only GP referral has a low
probability of being under the AUS$50,000 per DALY threshold for
cost-effectiveness (Table 5). Exclusion of time and travel costs, which
greatly affect the cost of GP referral, shifts the intervention from last
place up to third position in the order, with the sequence of all other
interventions remaining the same. Including health care costs in added years
of life, for all diseases and injuries other than those explicitly modelled,
leads to less favourable cost-effectiveness results, but the effect is
relatively minor. This is because the average increase in life expectancy in
the whole population is relatively small (up to 6 d, with a 50% decay in
intervention effects), and the costs are incurred at the end of the
lifespan, with future costs discounted back to the baseline year. Overall,
the change in cost-effectiveness is not sufficient to alter decision-making
about implementation of the physical activity interventions.
thumbnail

Table 5. Incremental cost-effectiveness of interventions in the physical
activity pathway.
doi:10.1371/journal.pmed.1000110.t005
Pathway Sensitivity

The more quickly the intervention effects on physical activity behaviour are
assumed to decline over time, the less cost-effective the intervention
package becomes (Figure 3). At higher levels of decay, the total package is
no longer cost-saving, although it is still under AUS$50,000 per DALY.
thumbnail

Figure 3. Sensitivity of the intervention pathway to the rate of decay in
intervention health effects.
doi:10.1371/journal.pmed.1000110.g003

The first four interventions in the pathway—pedometers, mass media,
internet-based intervention and GP prescription—are under the AUS$50,000 per
DALY threshold for cost-effectiveness under all decay scenarios (Table 6).
The key differences between the sensitivity scenarios and the base case
results are that GP referral is cost-effective when decay is slower than the
50% assumed in the primary analysis, and that the TravelSmart program is no
longer cost-effective at maximum (i.e., 100%) decay.
thumbnail

Table 6. Sensitivity of the median ICERs to the rate of decay in
intervention health effects.
doi:10.1371/journal.pmed.1000110.t006
Discussion Top

Intervention to encourage an increase in physical activity participation is
highly recommended in Australia. Potential reductions in costs of treating
ischaemic heart disease, stroke, diabetes, breast cancer, and colon cancer
mean that there is a high probability of cost-savings from a health sector
perspective. Taken as a package of interventions, all six physical activity
interventions could lead to a substantial improvement in population health
at under AUS$50,000 per DALY.

Cost-effectiveness of the package is not highly sensitive to the
sustainability of behavioural changes (total package is under AUS$50,000 per
DALY at maximum rates of decay). However, it is likely that some
interventions will lead to a more sustained effect than others, and this
could affect the order of implementation in the pathway. It is also possible
that there will be synergistic effects with implementation of multiple
interventions, which could improve the sustainability of intervention
effects on physical activity over time, thus increasing cost-effectiveness
of the intervention package. However, this may well be countered by a
decrease in effectiveness of each additional intervention, due to the
increasing proportion of the population less willing or able to change their
physical activity behaviour.

When modelled from the selected studies of intervention effectiveness,
intervention programs that encourage use of pedometers and mass media-based
community campaigns are the most cost-effective strategies to implement and
are very likely to be cost-saving. We found that these interventions have
the potential to deliver large health benefits to the population, despite
the seemingly small or nonsignificant effects on physical activity behaviour
when measured at a population level [34],[35].

Overall, our intervention cost-effectiveness ratios, which ranged from
dominant up to AUS$75,000 per DALY, were not as favourable as the entirely
dominant results reported by NICE for ten GP prescription and referral
interventions in the United Kingdom [21]. This may be because the NICE
analysis did not include patient costs of time and travel, and assumed a
slower decay in physical activity behaviour change (50% of participants
assumed to maintain change in behaviour long enough to experience health
benefits e.g. 20 y for a 25-y-old), but there were also other differences in
modelling methods and assumptions (e.g., discount rates) that may have
influenced the more favourable NICE results.

Conversely, our cost-effectiveness ratios were mostly more favourable than
the cost-effectiveness ratios recently reported for seven physical activity
intervention programs in the US [25]. Costs per QALY ranged from US$14,000
(2003AUS$19,000) to US$69,000 (2003AUS$91,000) for the physical activity
promotion interventions, which included two community-wide campaigns, two
social support walking programs, two individually adapted behaviour change
programs, and one program to enhance access to a more active environment
(e.g., new bicycle paths, fitness centre, etc.). Some additional costs were
included in the US analysis (e.g., patient out-of-pocket expenses for
physical activity clothing and equipment) contributing to relatively high
intervention costs per person, which may have led to the less favourable US
results, but there were also many other differences in analysis methods and
assumptions, such as a shorter time horizon (40 y), additional medical
inflation on disease costs (8% per annum), and more sustained effects on
behaviour (33% to 50% decay in the second year, with maintenance of effect
thereafter), which complicate interpretation of the contrasting results.

However, the NICE results, the US study, and our own analyses together
provide good evidence that physical activity intervention can be
cost-effective in the UK, US, and Australia. Over 20 different intervention
programs have now been evaluated in these countries, with only four programs
exceeding a cost-effectiveness threshold of AUS$50,000.

To our knowledge, no other studies have evaluated cost-effectiveness of this
package of interventions. However, two studies have previously evaluated GP
prescription intervention based on the randomised controlled trial of New
Zealand's Green Prescription program [36], reporting costs per QALY of
NZ$2,100 (2003AUS$2,000) [19] and dominant [21]. Although not directly
comparable to each other or to our cost per DALY of AUS$11,000 due to
different analysis methods and assumptions (e.g., discount rates), the
growing number of analyses reporting cost-effectiveness under varying
methods and assumptions strengthens the argument for this particular
physical activity intervention as a cost-effective measure for improving
public health. However, the results for the Green Prescription program do
not necessarily reflect the cost-effectiveness of all physical activity
prescription programs (many of which have not shown a significant effect on
physical activity behaviour [37]–[40]).

A number of limitations must be taken into account when evaluating the
results of this research. For example, because of inconsistent physical
activity outcome measures and a limited number of randomised controlled
trials, for some interventions we selected single intervention studies for
cost-effectiveness analysis rather than combining multiple trials in a
meta-analysis. Therefore, while the results reflect the cost-effectiveness
of the interventions that were evaluated, and based on the best available
evidence, they should not be generalised to all interventions of a similar
type.

In addition, although interventions were evaluated as if implemented for one
year, in some cases it was necessary to include studies of less than
one-year duration. While it would be preferable to include only those
studies with follow-up data at one year, this would exclude a number of
interventions from cost-effectiveness analysis (e.g., active transport
interventions, community mass media and pedometer programs, etc.), and
potentially bias cost-effectiveness analyses toward the more targeted
interventions (e.g., general practice interventions) for which longer-term
studies are more readily available. We have included shorter-duration
studies in the interests of modelling a wide range of interventions, but
acknowledge that these interventions may not prove to be as cost-effective
if subsequent intervention studies find a significant drop in effectiveness
at one year.

Furthermore, the level of evidence underlying the measures of intervention
effect is relatively weak. For example, evaluation of the mass media
campaign effect on population health was based only on the results of a
single quasi-experimental study, and evaluation of the pedometer program
effect on population health was based on a meta-analysis that included only
277 participants in total. In addition, it is likely that those who
volunteered to participate in the pedometer trials were more active or more
motivated to change their activity behaviour than the general population,
leading to a more favourable estimate of cost-effectiveness than might
actually occur with rollout of a pedometer program across Australia. Further
randomised controlled trials, using consistent measures of physical activity
behaviour, would improve our confidence in both the relative position of
interventions in the pathway and the overall magnitude of the health gain
that could be achieved.

There are a number of other unknowns in modelling physical activity that may
have influenced our cost-effectiveness results. Due to the reliance on
(mainly) observational studies in the meta-analyses of relative risks of
disease by Bull et al. [1], it is possible that the risk would not be fully
reversible for those increasing their physical activity in response to an
intervention. It is also plausible that there is a time lag between change
in physical activity behaviour and change in risk, which may be relatively
short for cardiovascular diseases [41], but longer for cancers [42]. These
factors could lead to an overestimate of cost-effectiveness ratios. We do,
however, incorporate an attenuation of cancer risk by age (see Table I in
Text S2), which Bull et al. [1] based on ischaemic heart disease data, that
might be an overestimate of attenuation and may, therefore, offset risk
reversibility and lag effects.

Nevertheless, the research illustrates how combining physical activity
interventions in a cost-effectiveness expansion pathway can provide guidance
to policymakers in identifying the most cost-effective approaches to
decreasing the burden of disease due to physical inactivity, based on the
best available evidence. For Australia, based on current evidence, it is
likely that the package of interventions would not only be cost-effective
but very likely cost-saving to the health sector, leading to substantial
improvements in health for the Australian population.
Supporting Information Top

Text S1.

Physical activity interventions.

(0.18 MB DOC)

Text S2.

Cost-effectiveness modelling methods.

(0.16 MB DOC)

Text S3.

Input parameters and uncertainty.

(0.15 MB DOC)
Acknowledgments Top

Thanks to C. Jackson and P. Van Baal for their comments on the manuscript.
Author Contributions Top

ICMJE criteria for authorship read and met: LJC TV JJB. Agree with the
manuscript's results and conclusions: LJC TV JJB. Designed the
experiments/the study: LJC TV. Analyzed the data: LJC. Collected data/did
experiments for the study: LJC TV. Wrote the first draft of the paper: LJC.
Contributed to the writing of the paper: LJC TV JJB. Developed the modelling
methods: JJB.
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