Cost-effectiveness of active transport for primary school Children – Walking School Bus

Cost-effectiveness of active transport for primary school Children – Walking School Bus

program
Critical appraisal

` This article contains a study that was carried out to determine the cost effectiveness
of active transport for primary school children program which was used as a prevention measure for
obesity among school going children (Kelly et al, 2005). This study is carried out in order to
determine whether the program is effective to this specific population or not and whether the
program is cost effective. The Walking School Bus (WSB) program was conducted among the
school going children in Australia. This program was designed as part of the ACE-Obesity study so
that it could help in giving results to the study through the use of the program. This study involved
the use of consistent methods and thirteen interventions that were aimed at preventing and reducing
obesity among Australian children and adolescents (Kelly et al, 2005).
In this particular study, the target population is clearly stated and the study focuses on this
population in the right setting. This is appropriate for the facilitating proper implementation of the
program and thus providing the right results (Ogilvie et al, 2011). This helped in knowing whether
the program was effective or not based on the outcomes. The competing alternatives in this study
are clearly stated in that the program (WSB) is implemented to show the benefits of active physical
activity in young children and adolescents as compared to inactivity (Ogilvie et al, 2011). This
program provides results that show whether physical activity can reduce and prevent obesity in
school going children. This program was aimed at bringing other health benefits in addition to the
reduction in obesity. These health benefits include mental health, safety and improving and
protecting the environment for both the participating children and the society at large. The research

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question for this study is well stated in that it is answerable during the study and even after the study
(Ogilvie et al, 2011). After getting the results of the study, the researchers are able to determine
whether the research question has been answered therefore being able to determine whether the
study was effective or not. The research question is what guided the study in both the
implementation of the program and also in determining the cost effectiveness of the program
(Ogilvie et al, 2011).
The economical study design is not appropriate to the stated objective because the cost
effectiveness of the program in relation to the economic status is not emphasized (Coast, Smith, &
Lorgelly, 2008). This is one of the factors that made the study not to be effective because in as much
as the program helped in reducing and preventing obesity among school going children, it did not
reach a wide the WSB program managed to reach a total of 7,840 children between 5 to 7 years at a
cost of $AUD22.8M. This number of children involved in the walking program did not increase and
this limited the sustainability of the program (Coast, Smith, & Lorgelly, 2008). This cost was also
high for the program to be effective and sustainable without any increase in the numbers of school
going children involved. The cost benefits were amounted to 3% and this shows that the economic
study design could not lead to the achievement of the stated objective (Chalkidou et al, 2008). The
time horizon set for this study is not realistic to include relevant costs and consequences. This is
because it would be impossible to determine the long term costs and consequences of a program
before carrying out a short term analysis of the costs and consequences of the same program (Coast,
Smith, & Lorgelly, 2008). The life time or 100 years period of time that was used to determine the
consequences of the program and calculate the costs could not work on a program that was being
implemented for the first time. This is one of the reasons as to why the program did not succeed
because the program could have been analyzed on a short term basis at first so that the researchers

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can get the chance to improve on the factors that came up as challenges to implementation
(Chalkidou et al, 2008). Calculating the costs and analyzing the consequences of the program on a
sort term basis helps in predicting the sustainability of a program and giving a chance to improve on
the recommendations for the implementation of the program (Barendregt, 2006).
Why it was difficult to design and conduct an economic evaluation of this study to measure

and value the health outcomes of the intervention
The actual perspective chosen for this study was appropriate but the plans for
implementation were not focused on broader issued that surrounded the issue of cost effectiveness
and resource allocation (Barendregt, 2006). Therefore, this study was not as effective as it was
intended to be. Conducting an economic evaluation of this study to determine the health benefits of
the program was difficult because of the unavailability of data that linked the changes in BMI of the
participating children during the active period and the period when they were not active. As a result
of this, this study used other existing data about the BMI of the participants to predict the changes
that were likely to have occurred (Barendregt, 2006). Lack of the critical information and data in
determining the health benefits that were as a result of the implementation of the program made it
very difficult to come up with accurate results on how this program improve the health of the
participants (Weatherly et al, 2009). The important and relevant costs for each alternative are
identified but they are not measured and valued appropriately because there are very high
uncertainty rates in the figures provided. The costs cutting measures in this study also did not work
out because the fixed amounts of money allocated were not enough to make the obesity prevention
cost effective. Due to the lack of some data in this study, not all relevant outcomes for each
alternative identified (Weatherly et al, 2009). This is because most of the results of the study are
based on assumption other than on real information. In most of the cases, it is very difficult to

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determine the exact outcomes and only predictions are provided. The outcomes of the program
implemented are not measured and valued appropriately because some of the information needed in
doing this is not available and some of the available information is not 100% correct (Evers et al,
2005). Most of the outcomes are based on prediction. For example, the incremental costs
effectiveness results are not reliable because there was no certainty on the range used on the number
of days that the participating children walked per week (Evers et al, 2005).
An incremental analysis of costs and outcomes of alternatives is performed. The incremental
costs that were linked to the intervention totaled up to $22.8M and this was an average of $2,900
per child every year and the child walking one day per week to school (Evers et al, 2005). The
fixed costs for the program totaled up to 86% of the total amount for the entire program. The future
costs and outcomes did not discount appropriately because of the high assumptions that were
involved in the program. There was a high rate of ICER uncertainty and this was mainly because of
the uncertainty in the number of active physical movements per week. Moreover, the number of
active transport estimated was very low as compared to the assumptions. In the sensitivity tests
results, allocating a section of the total cost of the prevention program to non-obesity objectives and
annuitisation of fixed costs were the main variable considered in the cutting costs of the project
(Nemet et al, 2005). However, these variables alone could not lead to cost effectiveness of the
program. In order to ensured that cost cutting was carried out, improved capacity utilization
measures were added the cost cutting measures to ensure that cost effectiveness was possible.
Moreover, this was possible “only under the very optimistic scenario” (Nemet et al, 2005). This
means that an increase in the number of children participating in the intervention program would
lead to cost effectiveness of the program. Therefore, with the small numbers of children involved in
the program, cost-effectiveness was not possible even when strong cost-cutting measures are put

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into place. The sensitivity analysis provides results based on the variables used and also reflects the
uncertain values and the results that would be expected when either the two or the three variables
are used (Nemet et al, 2005). Therefore, these results give a condition of optimism when cost
effectiveness is possible for the intervention program (Evers et al, 2005).
In this study, the conclusions are drawn from the data reported. The conclusion shows the cost
effectiveness of this study and compares it to the current economic situations (Kahn et al, 2002).
The intervention program is not cost effective in the fight against obesity but it can be effective if its
economic credentials are revised and improved to more realistic ones. The implementation can also
be improved to increase effectiveness. Therefore, this intervention program has a very high potential
of reducing and preventing obesity but in order for it to achieve this, it needs to be restructured
within current infrastructure conditions (Kahn et al, 2002).
The study does not provide generalizabilty of the results to other settings and patient/client
groups because the settings may be different and the results may not be the same of the intervention
program is restructured in another way (Bravata et al, 2007). Moreover, this intervention has not
been approved as an obesity prevention initiative but as strategy that encourages behavior change
mostly in schools promoting physical activity. The results may be different in different populations
and settings different from the ones in this particular study. This article clearly indicates that there is
no conflict of interest of the study (Bravata et al, 2007). This indication is of importance to the
readers because they can tell that the information contained in the article if not affected in any way
by competing interests of the authors and the funders. The ethical and distribution issues are
discussed appropriately in the article thus guiding the leader on how it can be accessed and
distributed (Bravata et al, 2007). The article is an open access and it is under unrestricted use and
distribution. Reproduction of the article is allowed but the original work must be cited appropriately.

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The users of the article therefore, know how much freedom they have on the use of its contents
(Bravata et al, 2007).

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References

Barendregt, J. (2006) Economics and public health: an arranged marriage. European Journal of
Public Health. 17(2) p.124.
Bravata, D. M., Smith-Spangler, C., Sundaram, V., Gienger, A. L., Lin, N., Lewis, R., … &
Sirard, J. R. (2007). Using pedometers to increase physical activity and improve health.
JAMA: the journal of the American Medical Association, 298(19), 2296-2304.
Chalkidou, K., Culyer, A., Naidoo, B. and Littlejohns, P. (2008) Cost-effective public health
guidance: asking questions from the decision-maker’s viewpoint. Health Economics. 17(3)
pp. 441-448.
Coast, J. Smith, R. Lorgelly, P. (2008) Should the capability approach be applied in health
economics? Health Economics, 17: 667-670.
Evers, S., de Vet, H., van Tulder, M. and Ament A. (2005) Criteria list for assessment of
methodological quality of economic evaluations: Consensus on Health Economic
Criteria, Maastricht University, International Journal of Technology Assessment in
Health Care, 21:2 (2005), 240–245.
Kahn, E. B., Ramsey, L. T., Brownson, R. C., Heath, G. W., Howze, E. H., Powell, K. E., … &
Corso, P. (2002). The effectiveness of interventions to increase physical activity: A
systematic review1, 2 1The names and affiliations of the Task Force members are listed
in the front of this supplement and at www. thecommunityguide. org. 2Address
correspondence and reprint requests to: Peter A. Briss, MD, Community Guide Branch,
Centers for Disease Control and Prevention, 4770 Buford Highway, MS-K73, Atlanta,
GA 30341. E-mail: PBriss@ cdc. gov. American journal of preventive medicine, 22(4),
73-107.

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