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Increasing community capacity and decreasing prevalence of overweight and obesity in a community based intervention among Australian adolescents
Preventive Medicine 56 (2013) 379–384
Contents lists available at SciVerse ScienceDirect
Preventive Medicine journal homepage: www.elsevier.com/locate/ypmed
Increasing community capacity and decreasing prevalence of overweight and obesity in a community based intervention among Australian adolescents Lynne Millar a,⁎, Narelle Robertson a, Steven Allender a, b, Melanie Nichols a, b, Catherine Bennett c, Boyd Swinburn a, d a
WHO Collaborating Centre for Obesity Prevention, Deakin University, Locked Bag 20000, Geelong, VIC 3220, Australia British Heart Foundation Health Promotion Research Group, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK School of Health and Social Development, Deakin University, 221 Burwood Highway, Burwood, VIC 3125, Australia d School of Population Health, University of Auckland, Private Bag 92019, Auckland, New Zealand b c
a r t i c l e
i n f o
Available online 26 February 2013 Keywords: Obesity Prevention Children Community Capacity Quantitative
a b s t r a c t Background. Community capacity building is a promising approach in reducing childhood obesity. The objective was to determine changes in capacity over a 3 year intervention (2005–2008) in schools and whether greater increases in capacity were associated with greater decreases in overweight/obesity. Methods. “It's your Move!” (IYM) was an obesity prevention project, in 12 Australian secondary schools (5 intervention; 7 comparison), that aimed to increase community capacity to promote healthy eating and physical activity. Capacity was assessed pre/post intervention using the ‘Community Readiness to Change (RTC)’ tool. Comparisons from baseline to follow-up were tested using Wilcoxon Signed-Ranks and results plotted against changes (Newcombe's paired differences) in prevalence of overweight/obesity (WHO standards). Results. RTC increased in intervention schools (p = 0.04) over time but not for comparison schools (p = 0.50). The intervention group improved on 5 of 6 dimensions and the three intervention schools that increased three levels on the RTC scale each had significant reductions in overweight/obesity prevalence. Conclusion. There were marked increases in capacity in the intervention schools and those with greater increases had greater decreases in the prevalence of overweight/obesity. Community-based obesity prevention efforts should specifically target increasing community capacity as a proximal indicator of success. Crown Copyright © 2013 Published by Elsevier Inc. All rights reserved.
Background A recent Cochrane Review and meta-analysis of interventions for preventing obesity in children found overall evidence of effectiveness although less than half of the individual programs were successful in preventing unhealthy weight gain (Waters et al., 2011) Despite study heterogeneity, the review found that the most effective programs included a wide range of components, and some of the promising policies and strategies incorporated building community capacity to implement health promotion strategies and activities. Community capacity refers to the potential of communities to identify, mobilize and address social and public health problems (Hawe et al., 1997; McLeroy, 1996). Building community capacity involves efforts across several domains, described in various ways (Simmons et al., 2011), but generally includes the development of knowledge, skills,
⁎ Corresponding author. E-mail addresses: [email protected] (L. Millar), [email protected] (N. Robertson), [email protected] (S. Allender), [email protected] (M. Nichols), [email protected] (C. Bennett), [email protected] (B. Swinburn).
structures, resources, and commitments to health improvement (Department of Health New South Wales, 2001; Rogers et al., 1995). Community-based health promotion and disease prevention programs need sufficient levels of community capacity to be effective (Chomitz et al., 2010; de Groot et al., 2010; Economos and Curtatone, 2010; Goodman et al., 1998), but measuring changes in community capacity remains a key issue for obesity prevention programs. Several authors have used the Community Readiness to Change method (RTC) (Oetting et al., 1995; Plested et al., 2006) as a diagnostic measure of community preparedness and capacity prior to the implementation of community programs (Findholt, 2007; Oetting et al., 1995; Sliwa et al., 2011) and others have used other instruments at the end of an obesity prevention intervention (de Groot et al., 2010). If capacity building is an objective of the project, then efforts should be made to quantify the change and relate these changes to changes in outcome variables. This paper aims to address this gap in the literature by relating the targeted, proximal changes of an intervention (increases in community capacity) to the intervention outcomes (reductions in overweight/obesity). The stronger the relationship, the greater the need to focus on and measure community capacity as it may be a powerful and direct determinant of success in communitybased obesity prevention initiatives.
0091-7435/$ – see front matter. Crown Copyright © 2013 Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ypmed.2013.02.020
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L. Millar et al. / Preventive Medicine 56 (2013) 379–384
“It's Your Move!” (IYM) was a multi-site, multi-focused, CBI to reduce adolescent overweight/obesity. The intervention was premised on the assumption that increased community capacity would lead to changes in school environments to make them more healthful and also to individual level changes in knowledge, attitudes, beliefs and behaviors in relation to healthy eating and physical activity. The community capacity framework (Department of Health New South Wales, 2001) used in IYM suggested that partnerships, leadership, resource allocation, workforce development and organizational development were key areas for intervention to build community capacity. Capacity building, in turn, would lead to changes in anthropometry (Fig. 1) (Millar et al., 2011; Swinburn et al., 2011). Community capacity was measured using the RTC tool (Oetting et al., 1995) which captured the following elements; community knowledge about obesity, community efforts, community knowledge of efforts, leadership, community attitude and resources for prevention efforts (Plested et al., 2006). The RTC tool approximated the constructs of community capacity building used in IYM as capacity was considered similar to readiness in that both are potential states that may lead to community action (Goodman et al., 1998). IYM's reported anthropometric and behavioral outcomes included a reduction in overweight/ obesity prevalence among the intervention group (Millar et al., 2011). This paper reports changes in community capacity (Plested et al., 2006) and their relationships with changes in prevalence of overweight/ obesity (Millar et al., 2011). The specific research questions were: 1. When compared to a non-intervention comparison group, did the IYM intervention increase community capacity?; and, 2. Was increased capacity related to reductions in prevalence of overweight/obesity?
plans were informed by a collaborative process through priority setting workshops (Mathews et al., 2010; Simmons et al., 2009). Key stakeholders including principals, teachers and students from intervention schools participated in a workshop where action plans including project aims, objectives and strategies were developed (Simmons et al., 2009). The capacity building objective included actions around partnerships, leadership, resource allocation, workforce development and organizational development. The measured dimensions of the RTC tool generally reflect these actions (Plested et al., 2006). To assess the community capacity before and after the implementation of IYM, interviews using the RTC tool were conducted in all participating schools (5 intervention; 7 comparison) at baseline (2005: intervention 22 interviews; comparison 32 interviews) and again at follow-up (2008: intervention 19 interviews; comparison 35 interviews). A range of key informant input was needed so people representing multiple roles were approached across the schools. The principals and school coordinators were involved in identifying potential participants. Differences in informant availability and agreement to participate resulted in slight differences in numbers participating but the spread across informant roles was maintained. At baseline and followup in the intervention group interviewees included: principals (n = 4; n = 5, respectively); physical education teachers (n = 4; n = 3); home economics/ health teachers (n = 1; n = 1); canteen managers (n = 5; n = 2); parents (n = 4; n = 4); and, students (n = 4; n = 4). Included in the comparison group were: principals (n = 7; n = 7); physical education teachers (n = 6; n = 7); home economics/health teachers (n = 3; n = 1); canteen managers (n = 3; n = 6); parents (n = 7; n = 7); parents (n = 7; n = 7); and, students (n = 6; n = 7). Some interviewees participated in the one-on-one interviews at both time points but, due to movement and availability, some participated at one time point only. The interviews were scored as per the guidelines and each dimension awarded a score between one and nine that corresponded to their stage of readiness (capacity) (Table 1). Informed consent was obtained from all participants and the IYM project had ethics approval from Deakin University Human Research Ethics Committee (EC 37–2004) and was registered as a trial (ACTRN#12607000257460).
Methods Measures Study design and participants Data were collected as part of the evaluation of IYM, a 3-year intervention study implemented in secondary schools in Australia (Millar et al., 2011; Swinburn et al., 2007, 2011). Intervention and comparison samples were drawn from the Barwon-South Western (BSW) region of Victoria, Australia which has a population of approximately 350,000 people and is ranked less than the state's average on an index of relative socioeconomic disadvantage (Australian Bureau of Statistics, 2001; Millar et al., 2011). Included in the catchment were 49 secondary schools (31 government, 5 catholic, 13 private). The intervention sample included all five secondary schools (60% government) in the East Geelong/Bellarine region while the comparison sample was a stratified random sample of schools (n = 7; 57% government) from the BSW region (Mathews et al., 2010; Millar et al., 2011; Swinburn et al., 2007, 2011). Detailed descriptions of the intervention design, implementation methods and anthropometric outcomes are provided elsewhere (Bell et al., 2008; Millar et al., 2011; Swinburn et al., 2007, 2011). Briefly, the project's action
The RTC tool was designed for use before, during and after prevention programs to gauge a community's understanding of and preparedness to take action on a specific issue (Plested et al., 2006). The validated tool was used to collect information via structured interviews with ‘key informants’; individuals who represented different sectors of the community and were aware of what was being done to address the problem. High levels of inter-rated reliability between scorers had been reported by the developers (92%) however consistency among respondents was not necessarily expected as each has a unique perspective of the situation. The interviews were scored using descriptive statements on anchored scales (Oetting et al., 1995) and awarded a final RTC score (Plested et al., 2006). This final score corresponded to one of the nine stages of community readiness (Table 1). The interview and questionnaire materials were adapted for use in collaboration with the original developers of the RTC tool. Interviews that followed structured questionnaires were conducted with key informants (see above) from the schools' communities. The interviews lasted approximately
Fig. 1. Logic model for the IYM intervention. The measured links are shown in the dark arrows and non-measured (modeled) links in the light arrows. Δ means ‘change in’; 1Intervention dose is either 1 or 0 (intervention, comparison); 2Capacity is leadership, partnerships, resources, workforce and organizational development; and 3Anthropometry is prevalence of overweight and obesity.
L. Millar et al. / Preventive Medicine 56 (2013) 379–384 Table 1 The nine stages of community readiness. Stage Title
Description
1
No awareness
2
Denial/resistance
3
Vague awareness
4
Preplanning
5
Preparation
6
Initiation
7
Stabilization
8
Confirmation/ expansion
9
High level of community ownership
Issue is not generally recognized by the community or leaders as a problem (or it may truly not be an issue) At least some community members recognize that it is a concern, but there is little recognition that it might be occurring locally Most feel that there is a local concern, but there is no immediate motivation to do anything about it There is clear recognition that something must be done, and there may even be a group addressing it. However, efforts are not focused or detailed Active leaders begin planning in earnest. Community offers modest support of efforts Enough information is available to justify efforts. Activities are underway Activities are supported by administrators or community decision makers. Staff are trained and experienced Efforts are in place. Community members feel comfortable using services, and they support expansions. Local data are regularly obtained Detailed and sophisticated knowledge exists about prevalence, causes, and consequences. Effective evaluation guides new directions. Model is applied to other issues
45 min and comprised 38 items that elicited information on six dimensions: community knowledge about obesity; community efforts; community knowledge of efforts; leadership; community attitude, and; resources for prevention efforts. The interviews were transcribed verbatim and verified by the participant before being scored by two independent researchers. If scores differed, agreement between the scorers was reached through consensus after discussion between the two scorers. Anthropometric data (height, weight) were collected by trained research staff using standardized protocols (Swinburn et al., 2011). Briefly, students were measured using a portable stadiometer (Surgical and Medical PE87) for height to the nearest 0.1 cm and a TANITA Body Composition Analyser (Model BC 418, Wedderburn, Australia) for body weight. BMI (weight in kg/[height in m]2) and BMI z-scores, using the World Health Organization (WHO) Reference 2007 (World Health Organization, 2010), were calculated. The WHO Reference 2007 age-specific BMI cut-offs were also used to classify student's weight status as either healthy weight or overweight/obese (World Health Organization, 2010). Statistical analysis Analyses were conducted using STATA release 12.0 (Stat-Corp., College Station, TX, USA, 2011). Demographic and RTC data were reported using descriptive statistics. Data were analyzed using non-parametric methods as the data were ordinal; the Kruskal–Wallis Test was used for cross-sectional comparisons between the intervention and comparison groups at baseline and at follow-up, and; the Wilcoxon Signed-Rank Test for within group, longitudinal comparisons. For all analyses p b 0.05 was considered statistically significant.
Results Baseline and follow-up RTC scores for each of the schools are shown in Fig. 2. The base of the arrow represents the school's baseline score and the point represents follow-up. At baseline all schools recorded low levels of readiness; either stage 2 or 3 (see Table 1 for descriptors). At follow-up, all of the intervention schools (schools I1–I5) increased their RTC score with three schools improving by three levels. School I4 reached level 6 which was the highest among intervention schools. In contrast, In contrast, only two of the seven comparison schools increased their RTC score (one school increased by one level; the other increased by two levels), while other comparison schools remained the same or decreased. Cross sectional analysis
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using the Kruskal–Wallis Test showed that there was no statistically significant difference between intervention and comparison schools at baseline (χ2 = 1.17; p = 0.19) but at follow-up intervention schools were rated significantly higher in RTC than comparison schools (χ2 = 6.33; p = 0.01). When tested using the Wilcoxon Signed-Rank Test for within group longitudinal change, intervention schools recorded a significant improvement from baseline to follow-up (z = −2.06; p = 0.04) but the comparison group remained similar in RTC levels (z = −0.067; p = 0.50). Schools' data for each of the individual dimensions were aggregated to intervention or comparison group (Fig. 3). The intervention group improved in all dimensions, with marked improvements in dimensions B to F. However, dimension A (community knowledge about the issue) improved only marginally within intervention schools and remained at a low level. Between baseline and follow-up, comparison schools recorded no change in the dimensions. Fig. 4 shows RTC results (horizontal axis) plotted against observed change in overweight/obesity prevalence (vertical axis) from baseline to follow-up in each school (Millar et al., 2011). The figure illustrates that the three intervention schools (filled markers on the extreme right hand side of the horizontal axis) that recorded the greatest increases in RTC (3 levels) were the same schools that recorded a statistically significant decrease in prevalence of overweight/obesity (− 4.7 [CI: − 8.8, − 0.7], − 5.6 [CI: − 10.7, − 0.4], and − 8.0 [CI: − 15.6, −0.3] percentage points, respectively). One comparison school remained at baseline levels of RTC (no change) and recorded a significant increase in prevalence of overweight/obese adolescents (unfilled marker on the far left on the horizontal axis). All other schools recorded non-significant changes in prevalence and changes in RTC scores ranging from −1 to +2. Discussion IYM resulted in increased RTC scores among intervention schools between baseline and follow-up while the comparison schools remained unchanged suggesting that IYM was successful in building community capacity. An association between increasing capacity and decreasing prevalence of overweight/obesity within this sample of secondary schools was observed. Individually, all intervention schools increased their overall level of readiness whereas there was little change in scores among comparison schools. All schools started at quite a low level of readiness; denial/resistance or vague awareness, which indicated that the schools may have been unaware of the problem of obesity at a local level or unaware that they could do something to combat the issue (Plested et al., 2006). These scores are between baseline scores from other childhood obesity prevention projects. Findholt and colleagues reported a score of one when assessing Union County's readiness to intervene in childhood obesity suggesting that the community had no awareness of childhood obesity as a problem (Findholt, 2007). Sliwa et al. (2011) used RTC scores to select communities for an obesity prevention intervention. The average RTC score of these communities was four, positioning them in the preplanning stage. While intervention schools increased their scores over the intervention period, none reached higher than level six, which signifies ‘initiation’ of activities. The level of initiation includes start-up of activity or efforts and some basic evaluation but does not include embedding processes to promote sustainability (Plested et al., 2006). The RTC interviews in the current study were conducted three years apart so longer interventions may be required to ensure that successful efforts are continued and intervention activities and effects are embedded in community norms. Scores for the intervention group increased for all six of the individual dimensions as expected, however the minimal increase achieved in dimension A (community knowledge about obesity) was surprising given the amount of media coverage dedicated to
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Fig. 2. RTC scores and scoring key for intervention and comparison schools at baseline (2005) and follow-up (2008).
the obesity epidemic both at national (O'Hara and Gregg, 2006) and international levels (Lawrence, 2004). Additionally, each school received feedback on their baseline anthropometric measures. That community knowledge moved minimally while attitudes and leadership recorded larger increases may suggest that a small change in knowledge can facilitate larger changes in attitudes and leadership. Additionally, expectations of levels of knowledge may have shifted as respondents became more aware of the scope of potential knowledge available. These explanations are speculative but the issue warrants future research around the types of approaches to achieve greater awareness. The increases in dimensions B to F (community efforts, community knowledge of efforts, leadership, community attitude and resources for prevention efforts) can be explained by reference to the intervention
strategies and processes (Mathews et al., 2010). Details of the capacity building activities undertaken are explained elsewhere (Mathews et al., 2010). Briefly, capacity building provided resources (e.g. grant funding, a part-time project co-ordinator and school projects officers, equipment), promoted leadership in the form of teacher and student ‘champions’ within the schools, provided workforce development for both students and teachers (e.g. students completed a tertiary certificate, canteen manager training, teacher development and project management attended workshop in social marketing), created partnerships to link with both existing and emerging projects and organizations within the region (e.g. collaborations with local government, local fitness providers and regional media); and worked with the schools to incorporate healthy eating and physical activity policies and practices into their school charter (e.g. food at school policy, color coded canteen
Fig. 3. RTC dimensions change over time (2005–2008) for the intervention and comparison groups.
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approximated the dimensions of community capacity building as used in IYM but, perhaps, did not measure the full extent of efforts. This inadequacy may be overcome through development of an evaluation tool that quantified the important aspects of capacity building in community-based interventions. Conclusion
Fig. 4. The position of each school (square markers) on the horizontal axis indicates change in RTC scores from baseline (2005) to follow-up (2008). The vertical axis represents change from baseline to follow-up in prevalence of overweight/obese adolescents in intervention (filled markers) and comparison (unfilled markers) schools; point estimates with 95% confidence intervals (controlled for duration between measures).
Schools that recorded the largest increases in community capacity also recorded significant decreases in overweight/obesity prevalence suggesting strategies to increase community capacity may be core to successful obesity prevention interventions. Building community capacity is often an aim of community-based interventions and is a valid, explicit and quantifiable target. Intervention teams are naturally drawn to focusing resources into specific nutrition and physical activity strategies, but this should not be done at the expense of de-prioritizing efforts to increase the capacity of the community to develop their own strategies to prevent obesity. Projects aimed at prevention among populations need to include evaluation of proximal indicators such as changes in capacity as well as more distal measures of individual change. Conflict of interest statement
menu) (Mathews et al., 2010). IYM was a high profile project within the intervention schools and resources were directed towards healthy eating and physical activity promotions as well as capacity building. These findings may impact on the post-project embedding of intervention strategies and should be noted in the design of future interventions. The three intervention schools that recorded the highest change score (3 levels) and the highest score at follow-up (5 or 6) in RTC also recorded a significant decrease in the prevalence of overweight/obesity between baseline and follow-up. One hypothesis warranting further attention is that a hurdle level of change in RTC scores may exist before changes in prevalence of overweight/obesity are likely to occur. These findings suggest that reaching the stages of preparation or initiation is necessary as these levels indicate implementation of prevention strategies rather than the increase of three levels being the key.
The authors declare that there are no conflicts of interest.
Acknowledgments The authors would like to thank the many people involved in the Pacific OPIC Project including co-investigators, other staff and postgraduate students, partner organizations, and especially the schools, students, parents and communities. The funding for the project was from the Victorian Department of Health, the National Health and Medical Research Council (in conjunction with the Health Research Council [New Zealand] and the Wellcome Trust [UK] as part of their innovative International Collaborative Research Grant Scheme), and AusAID. References
Strengths of the current study The RTC tool has been used widely used outside obesity prevention including readiness of rural communities to engage in communityinitiated traumatic brain injury prevention (Stallones et al., 2008) and youth substance abuse (Ogilvie et al., 2008; Slater et al., 2005). This is the first time RTC has been measured at baseline and follow-up as the key component in an intervention to prevent adolescent obesity or overweight. Within this study the RTC tool was informative and reliable over time as intervention schools' scores changed as expected and comparison schools' scores were relatively stable. IYM was the first community-based adolescent obesity prevention study to measure an increase in community capacity associated with reduction in unhealthy weight. Weaknesses of the current study One challenge in of the RTC tool was that it was time consuming to implement and score and as a consequence the results were not available for immediate feedback. This shortcoming can be ameliorated by conducting baseline RTC interviews during the planning phase of projects. The results can inform the development and implementation of intervention strategies. A further potential weakness is the subjective nature of the scoring process; however using two independent scorers who did not participate in data collection may have minimized this potential for bias. Additionally, the dimensions captured by the tool
Australian Bureau of Statistics, 2001. Information Paper: Socio-Economic Indexes for Areas. Australian Government, Canberra. Bell, A.C., Simmons, A., Sanigorski, A.M., Kremer, P.J., Swinburn, B.A., 2008. Preventing childhood obesity: the sentinel site for obesity prevention in Victoria, Australia. Health Promot. Int. 23, 328–336. Chomitz, V.R., McGowan, R.J., Wendel, J.M., et al., 2010. Healthy living Cambridge kids: a community-based participatory effort to promote healthy weight and fitness. Obesity 18, S45–S53. de Groot, F.P., Robertson, N.M., Swinburn, B.A., de Silva-Sanigorski, A.M., 2010. Increasing community capacity to prevent childhood obesity: challenges, lessons learned and results from the Romp & Chomp intervention. BMC Publ. Health 10. Department of Health New South Wales, 2001. A Framework for Building Capacity to Improve Health. Department of Health, Sydney, Australia. Economos, C.D., Curtatone, J.A., 2010. Shaping up Somerville: a community initiative in Massachusetts. Prev. Med. 50, S97–S98. Findholt, N., 2007. Application of the community readiness model for childhood obesity prevention. Public Health Nurs. 24, 565–570. Goodman, R.M., Speers, M.A., McLeroy, K., et al., 1998. Identifying and defining the dimensions of community capacity to provide a basis for measurement. Health Educ. Behav. 25, 258–278. Hawe, P., Noort, M., King, L., Jordens, C., 1997. Multiplying health gains: the critical role of capacity-building within health promotion programs. Health Policy 39, 29–42. Lawrence, R.G., 2004. Framing obesity: the evolution of news discourse on a public health issue. Harv. Int. J. Press Polit. 9, 56–75. Mathews, L., Moodie, M., Simmons, A., Swinburn, B., 2010. The process evaluation of It's Your Move!, an Australian adolescent community-based obesity prevention project. BMC Publ. Health 10, 1–13. McLeroy, K., 1996. Community capacity: what is it? How do we measure it? What is the role of the prevention centers and CDC? Sixth Annual Prevention Centres Conference, Centers for Disease Control and Prevention.National Center for Chronic Disease Prevention and Health Promotion, Atlanta, GA. Millar, L., Kremer, P., de Silva-Sanigorski, A., et al., 2011. Reduction in overweight and obesity from a 3-year community-based intervention in Australia: the ‘It's Your Move!’ project. Obes. Rev. 12, 20–28.
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Oetting, E.R., Donnermeyer, J.F., Plested, B.A., Edwards, R.W., Kelly, K., Beauvais, F., 1995. Assessing community readiness for prevention. Subst. Use Misuse 30, 659–683. Ogilvie, K., Moore, R., Ogilvie, D., Johnson, K., Collins, D., Shamblen, S., 2008. Changing community readiness to prevent the abuse of inhalants and other harmful legal products in Alaska. J. Community Health 33, 248–258. O'Hara, L., Gregg, J., 2006. The war on obesity: a social determinant of health. Health Promot. J. Austr. 17, 260–263. Plested, B., Edwards, R., Thurman, P., 2006. Handbook For Using The Community Readiness Model. Tri-Ethnic Center for Prevention Research, Colorado. Rogers, T., Howard-Pitney, B., Lee, H., 1995. An Operational Definition of Local Community Capacity for Tobacco Prevention and Education. Stanford Centre for Research in Disease Prevention, Stanford University, Palo Alto, CA. Simmons, A., Mavoa, H.M., Bell, A.C., et al., 2009. Creating community action plans for obesity prevention using the ANGELO (Analysis Grid for Elements Linked to Obesity) Framework. Health Promot. Int. 24, 311–324. Simmons, A., Reynolds, R.C., Swinburn, B., 2011. Defining community capacity building: is it possible? Prev. Med. 52, 193–199.
Slater, M.D., Edwards, R.W., Plested, B.A., et al., 2005. Using community readiness key informant assessments in a randomized group prevention trial: impact of a participatory community-media intervention. J. Community Health 30, 39–53. Sliwa, S., Goldberg, J.P., Clark, V., et al., 2011. Using the community readiness model to select communities for a community-wide obesity prevention intervention. Prev. Chronic Dis. 8 (6), A150. Stallones, L., Gibbs-Long, J., Gabella, B., Kakefuda, I., 2008. Community readiness and prevention of traumatic brain injury. Brain Inj. 22, 555–564. Swinburn, B., Pryor, J., McCabe, M., et al., 2007. The Pacific OPIC Project (Obesity Prevention In Communities) — objectives and designs. Pac. Health Dialog 14, 139–146. Swinburn, B., Millar, L., Utter, J., et al., 2011. The Pacific Obesity Prevention in Communities project: project overview and methods. Obes. Rev. 12, 3–11. Waters, E., de Silva-Sanigorski, A., Hall, B., et al., 2011. Interventions for preventing obesity in children. Cochrane Database of Syst. Rev. World Health Organization, 2010. WHO Reference 2007. Growth Reference Data for 5–19 years.WHO, Geneva.
Contents lists available at SciVerse ScienceDirect
Preventive Medicine journal homepage: www.elsevier.com/locate/ypmed
Increasing community capacity and decreasing prevalence of overweight and obesity in a community based intervention among Australian adolescents Lynne Millar a,⁎, Narelle Robertson a, Steven Allender a, b, Melanie Nichols a, b, Catherine Bennett c, Boyd Swinburn a, d a
WHO Collaborating Centre for Obesity Prevention, Deakin University, Locked Bag 20000, Geelong, VIC 3220, Australia British Heart Foundation Health Promotion Research Group, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK School of Health and Social Development, Deakin University, 221 Burwood Highway, Burwood, VIC 3125, Australia d School of Population Health, University of Auckland, Private Bag 92019, Auckland, New Zealand b c
a r t i c l e
i n f o
Available online 26 February 2013 Keywords: Obesity Prevention Children Community Capacity Quantitative
a b s t r a c t Background. Community capacity building is a promising approach in reducing childhood obesity. The objective was to determine changes in capacity over a 3 year intervention (2005–2008) in schools and whether greater increases in capacity were associated with greater decreases in overweight/obesity. Methods. “It's your Move!” (IYM) was an obesity prevention project, in 12 Australian secondary schools (5 intervention; 7 comparison), that aimed to increase community capacity to promote healthy eating and physical activity. Capacity was assessed pre/post intervention using the ‘Community Readiness to Change (RTC)’ tool. Comparisons from baseline to follow-up were tested using Wilcoxon Signed-Ranks and results plotted against changes (Newcombe's paired differences) in prevalence of overweight/obesity (WHO standards). Results. RTC increased in intervention schools (p = 0.04) over time but not for comparison schools (p = 0.50). The intervention group improved on 5 of 6 dimensions and the three intervention schools that increased three levels on the RTC scale each had significant reductions in overweight/obesity prevalence. Conclusion. There were marked increases in capacity in the intervention schools and those with greater increases had greater decreases in the prevalence of overweight/obesity. Community-based obesity prevention efforts should specifically target increasing community capacity as a proximal indicator of success. Crown Copyright © 2013 Published by Elsevier Inc. All rights reserved.
Background A recent Cochrane Review and meta-analysis of interventions for preventing obesity in children found overall evidence of effectiveness although less than half of the individual programs were successful in preventing unhealthy weight gain (Waters et al., 2011) Despite study heterogeneity, the review found that the most effective programs included a wide range of components, and some of the promising policies and strategies incorporated building community capacity to implement health promotion strategies and activities. Community capacity refers to the potential of communities to identify, mobilize and address social and public health problems (Hawe et al., 1997; McLeroy, 1996). Building community capacity involves efforts across several domains, described in various ways (Simmons et al., 2011), but generally includes the development of knowledge, skills,
⁎ Corresponding author. E-mail addresses: [email protected] (L. Millar), [email protected] (N. Robertson), [email protected] (S. Allender), [email protected] (M. Nichols), [email protected] (C. Bennett), [email protected] (B. Swinburn).
structures, resources, and commitments to health improvement (Department of Health New South Wales, 2001; Rogers et al., 1995). Community-based health promotion and disease prevention programs need sufficient levels of community capacity to be effective (Chomitz et al., 2010; de Groot et al., 2010; Economos and Curtatone, 2010; Goodman et al., 1998), but measuring changes in community capacity remains a key issue for obesity prevention programs. Several authors have used the Community Readiness to Change method (RTC) (Oetting et al., 1995; Plested et al., 2006) as a diagnostic measure of community preparedness and capacity prior to the implementation of community programs (Findholt, 2007; Oetting et al., 1995; Sliwa et al., 2011) and others have used other instruments at the end of an obesity prevention intervention (de Groot et al., 2010). If capacity building is an objective of the project, then efforts should be made to quantify the change and relate these changes to changes in outcome variables. This paper aims to address this gap in the literature by relating the targeted, proximal changes of an intervention (increases in community capacity) to the intervention outcomes (reductions in overweight/obesity). The stronger the relationship, the greater the need to focus on and measure community capacity as it may be a powerful and direct determinant of success in communitybased obesity prevention initiatives.
0091-7435/$ – see front matter. Crown Copyright © 2013 Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ypmed.2013.02.020
380
L. Millar et al. / Preventive Medicine 56 (2013) 379–384
“It's Your Move!” (IYM) was a multi-site, multi-focused, CBI to reduce adolescent overweight/obesity. The intervention was premised on the assumption that increased community capacity would lead to changes in school environments to make them more healthful and also to individual level changes in knowledge, attitudes, beliefs and behaviors in relation to healthy eating and physical activity. The community capacity framework (Department of Health New South Wales, 2001) used in IYM suggested that partnerships, leadership, resource allocation, workforce development and organizational development were key areas for intervention to build community capacity. Capacity building, in turn, would lead to changes in anthropometry (Fig. 1) (Millar et al., 2011; Swinburn et al., 2011). Community capacity was measured using the RTC tool (Oetting et al., 1995) which captured the following elements; community knowledge about obesity, community efforts, community knowledge of efforts, leadership, community attitude and resources for prevention efforts (Plested et al., 2006). The RTC tool approximated the constructs of community capacity building used in IYM as capacity was considered similar to readiness in that both are potential states that may lead to community action (Goodman et al., 1998). IYM's reported anthropometric and behavioral outcomes included a reduction in overweight/ obesity prevalence among the intervention group (Millar et al., 2011). This paper reports changes in community capacity (Plested et al., 2006) and their relationships with changes in prevalence of overweight/ obesity (Millar et al., 2011). The specific research questions were: 1. When compared to a non-intervention comparison group, did the IYM intervention increase community capacity?; and, 2. Was increased capacity related to reductions in prevalence of overweight/obesity?
plans were informed by a collaborative process through priority setting workshops (Mathews et al., 2010; Simmons et al., 2009). Key stakeholders including principals, teachers and students from intervention schools participated in a workshop where action plans including project aims, objectives and strategies were developed (Simmons et al., 2009). The capacity building objective included actions around partnerships, leadership, resource allocation, workforce development and organizational development. The measured dimensions of the RTC tool generally reflect these actions (Plested et al., 2006). To assess the community capacity before and after the implementation of IYM, interviews using the RTC tool were conducted in all participating schools (5 intervention; 7 comparison) at baseline (2005: intervention 22 interviews; comparison 32 interviews) and again at follow-up (2008: intervention 19 interviews; comparison 35 interviews). A range of key informant input was needed so people representing multiple roles were approached across the schools. The principals and school coordinators were involved in identifying potential participants. Differences in informant availability and agreement to participate resulted in slight differences in numbers participating but the spread across informant roles was maintained. At baseline and followup in the intervention group interviewees included: principals (n = 4; n = 5, respectively); physical education teachers (n = 4; n = 3); home economics/ health teachers (n = 1; n = 1); canteen managers (n = 5; n = 2); parents (n = 4; n = 4); and, students (n = 4; n = 4). Included in the comparison group were: principals (n = 7; n = 7); physical education teachers (n = 6; n = 7); home economics/health teachers (n = 3; n = 1); canteen managers (n = 3; n = 6); parents (n = 7; n = 7); parents (n = 7; n = 7); and, students (n = 6; n = 7). Some interviewees participated in the one-on-one interviews at both time points but, due to movement and availability, some participated at one time point only. The interviews were scored as per the guidelines and each dimension awarded a score between one and nine that corresponded to their stage of readiness (capacity) (Table 1). Informed consent was obtained from all participants and the IYM project had ethics approval from Deakin University Human Research Ethics Committee (EC 37–2004) and was registered as a trial (ACTRN#12607000257460).
Methods Measures Study design and participants Data were collected as part of the evaluation of IYM, a 3-year intervention study implemented in secondary schools in Australia (Millar et al., 2011; Swinburn et al., 2007, 2011). Intervention and comparison samples were drawn from the Barwon-South Western (BSW) region of Victoria, Australia which has a population of approximately 350,000 people and is ranked less than the state's average on an index of relative socioeconomic disadvantage (Australian Bureau of Statistics, 2001; Millar et al., 2011). Included in the catchment were 49 secondary schools (31 government, 5 catholic, 13 private). The intervention sample included all five secondary schools (60% government) in the East Geelong/Bellarine region while the comparison sample was a stratified random sample of schools (n = 7; 57% government) from the BSW region (Mathews et al., 2010; Millar et al., 2011; Swinburn et al., 2007, 2011). Detailed descriptions of the intervention design, implementation methods and anthropometric outcomes are provided elsewhere (Bell et al., 2008; Millar et al., 2011; Swinburn et al., 2007, 2011). Briefly, the project's action
The RTC tool was designed for use before, during and after prevention programs to gauge a community's understanding of and preparedness to take action on a specific issue (Plested et al., 2006). The validated tool was used to collect information via structured interviews with ‘key informants’; individuals who represented different sectors of the community and were aware of what was being done to address the problem. High levels of inter-rated reliability between scorers had been reported by the developers (92%) however consistency among respondents was not necessarily expected as each has a unique perspective of the situation. The interviews were scored using descriptive statements on anchored scales (Oetting et al., 1995) and awarded a final RTC score (Plested et al., 2006). This final score corresponded to one of the nine stages of community readiness (Table 1). The interview and questionnaire materials were adapted for use in collaboration with the original developers of the RTC tool. Interviews that followed structured questionnaires were conducted with key informants (see above) from the schools' communities. The interviews lasted approximately
Fig. 1. Logic model for the IYM intervention. The measured links are shown in the dark arrows and non-measured (modeled) links in the light arrows. Δ means ‘change in’; 1Intervention dose is either 1 or 0 (intervention, comparison); 2Capacity is leadership, partnerships, resources, workforce and organizational development; and 3Anthropometry is prevalence of overweight and obesity.
L. Millar et al. / Preventive Medicine 56 (2013) 379–384 Table 1 The nine stages of community readiness. Stage Title
Description
1
No awareness
2
Denial/resistance
3
Vague awareness
4
Preplanning
5
Preparation
6
Initiation
7
Stabilization
8
Confirmation/ expansion
9
High level of community ownership
Issue is not generally recognized by the community or leaders as a problem (or it may truly not be an issue) At least some community members recognize that it is a concern, but there is little recognition that it might be occurring locally Most feel that there is a local concern, but there is no immediate motivation to do anything about it There is clear recognition that something must be done, and there may even be a group addressing it. However, efforts are not focused or detailed Active leaders begin planning in earnest. Community offers modest support of efforts Enough information is available to justify efforts. Activities are underway Activities are supported by administrators or community decision makers. Staff are trained and experienced Efforts are in place. Community members feel comfortable using services, and they support expansions. Local data are regularly obtained Detailed and sophisticated knowledge exists about prevalence, causes, and consequences. Effective evaluation guides new directions. Model is applied to other issues
45 min and comprised 38 items that elicited information on six dimensions: community knowledge about obesity; community efforts; community knowledge of efforts; leadership; community attitude, and; resources for prevention efforts. The interviews were transcribed verbatim and verified by the participant before being scored by two independent researchers. If scores differed, agreement between the scorers was reached through consensus after discussion between the two scorers. Anthropometric data (height, weight) were collected by trained research staff using standardized protocols (Swinburn et al., 2011). Briefly, students were measured using a portable stadiometer (Surgical and Medical PE87) for height to the nearest 0.1 cm and a TANITA Body Composition Analyser (Model BC 418, Wedderburn, Australia) for body weight. BMI (weight in kg/[height in m]2) and BMI z-scores, using the World Health Organization (WHO) Reference 2007 (World Health Organization, 2010), were calculated. The WHO Reference 2007 age-specific BMI cut-offs were also used to classify student's weight status as either healthy weight or overweight/obese (World Health Organization, 2010). Statistical analysis Analyses were conducted using STATA release 12.0 (Stat-Corp., College Station, TX, USA, 2011). Demographic and RTC data were reported using descriptive statistics. Data were analyzed using non-parametric methods as the data were ordinal; the Kruskal–Wallis Test was used for cross-sectional comparisons between the intervention and comparison groups at baseline and at follow-up, and; the Wilcoxon Signed-Rank Test for within group, longitudinal comparisons. For all analyses p b 0.05 was considered statistically significant.
Results Baseline and follow-up RTC scores for each of the schools are shown in Fig. 2. The base of the arrow represents the school's baseline score and the point represents follow-up. At baseline all schools recorded low levels of readiness; either stage 2 or 3 (see Table 1 for descriptors). At follow-up, all of the intervention schools (schools I1–I5) increased their RTC score with three schools improving by three levels. School I4 reached level 6 which was the highest among intervention schools. In contrast, In contrast, only two of the seven comparison schools increased their RTC score (one school increased by one level; the other increased by two levels), while other comparison schools remained the same or decreased. Cross sectional analysis
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using the Kruskal–Wallis Test showed that there was no statistically significant difference between intervention and comparison schools at baseline (χ2 = 1.17; p = 0.19) but at follow-up intervention schools were rated significantly higher in RTC than comparison schools (χ2 = 6.33; p = 0.01). When tested using the Wilcoxon Signed-Rank Test for within group longitudinal change, intervention schools recorded a significant improvement from baseline to follow-up (z = −2.06; p = 0.04) but the comparison group remained similar in RTC levels (z = −0.067; p = 0.50). Schools' data for each of the individual dimensions were aggregated to intervention or comparison group (Fig. 3). The intervention group improved in all dimensions, with marked improvements in dimensions B to F. However, dimension A (community knowledge about the issue) improved only marginally within intervention schools and remained at a low level. Between baseline and follow-up, comparison schools recorded no change in the dimensions. Fig. 4 shows RTC results (horizontal axis) plotted against observed change in overweight/obesity prevalence (vertical axis) from baseline to follow-up in each school (Millar et al., 2011). The figure illustrates that the three intervention schools (filled markers on the extreme right hand side of the horizontal axis) that recorded the greatest increases in RTC (3 levels) were the same schools that recorded a statistically significant decrease in prevalence of overweight/obesity (− 4.7 [CI: − 8.8, − 0.7], − 5.6 [CI: − 10.7, − 0.4], and − 8.0 [CI: − 15.6, −0.3] percentage points, respectively). One comparison school remained at baseline levels of RTC (no change) and recorded a significant increase in prevalence of overweight/obese adolescents (unfilled marker on the far left on the horizontal axis). All other schools recorded non-significant changes in prevalence and changes in RTC scores ranging from −1 to +2. Discussion IYM resulted in increased RTC scores among intervention schools between baseline and follow-up while the comparison schools remained unchanged suggesting that IYM was successful in building community capacity. An association between increasing capacity and decreasing prevalence of overweight/obesity within this sample of secondary schools was observed. Individually, all intervention schools increased their overall level of readiness whereas there was little change in scores among comparison schools. All schools started at quite a low level of readiness; denial/resistance or vague awareness, which indicated that the schools may have been unaware of the problem of obesity at a local level or unaware that they could do something to combat the issue (Plested et al., 2006). These scores are between baseline scores from other childhood obesity prevention projects. Findholt and colleagues reported a score of one when assessing Union County's readiness to intervene in childhood obesity suggesting that the community had no awareness of childhood obesity as a problem (Findholt, 2007). Sliwa et al. (2011) used RTC scores to select communities for an obesity prevention intervention. The average RTC score of these communities was four, positioning them in the preplanning stage. While intervention schools increased their scores over the intervention period, none reached higher than level six, which signifies ‘initiation’ of activities. The level of initiation includes start-up of activity or efforts and some basic evaluation but does not include embedding processes to promote sustainability (Plested et al., 2006). The RTC interviews in the current study were conducted three years apart so longer interventions may be required to ensure that successful efforts are continued and intervention activities and effects are embedded in community norms. Scores for the intervention group increased for all six of the individual dimensions as expected, however the minimal increase achieved in dimension A (community knowledge about obesity) was surprising given the amount of media coverage dedicated to
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Fig. 2. RTC scores and scoring key for intervention and comparison schools at baseline (2005) and follow-up (2008).
the obesity epidemic both at national (O'Hara and Gregg, 2006) and international levels (Lawrence, 2004). Additionally, each school received feedback on their baseline anthropometric measures. That community knowledge moved minimally while attitudes and leadership recorded larger increases may suggest that a small change in knowledge can facilitate larger changes in attitudes and leadership. Additionally, expectations of levels of knowledge may have shifted as respondents became more aware of the scope of potential knowledge available. These explanations are speculative but the issue warrants future research around the types of approaches to achieve greater awareness. The increases in dimensions B to F (community efforts, community knowledge of efforts, leadership, community attitude and resources for prevention efforts) can be explained by reference to the intervention
strategies and processes (Mathews et al., 2010). Details of the capacity building activities undertaken are explained elsewhere (Mathews et al., 2010). Briefly, capacity building provided resources (e.g. grant funding, a part-time project co-ordinator and school projects officers, equipment), promoted leadership in the form of teacher and student ‘champions’ within the schools, provided workforce development for both students and teachers (e.g. students completed a tertiary certificate, canteen manager training, teacher development and project management attended workshop in social marketing), created partnerships to link with both existing and emerging projects and organizations within the region (e.g. collaborations with local government, local fitness providers and regional media); and worked with the schools to incorporate healthy eating and physical activity policies and practices into their school charter (e.g. food at school policy, color coded canteen
Fig. 3. RTC dimensions change over time (2005–2008) for the intervention and comparison groups.
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approximated the dimensions of community capacity building as used in IYM but, perhaps, did not measure the full extent of efforts. This inadequacy may be overcome through development of an evaluation tool that quantified the important aspects of capacity building in community-based interventions. Conclusion
Fig. 4. The position of each school (square markers) on the horizontal axis indicates change in RTC scores from baseline (2005) to follow-up (2008). The vertical axis represents change from baseline to follow-up in prevalence of overweight/obese adolescents in intervention (filled markers) and comparison (unfilled markers) schools; point estimates with 95% confidence intervals (controlled for duration between measures).
Schools that recorded the largest increases in community capacity also recorded significant decreases in overweight/obesity prevalence suggesting strategies to increase community capacity may be core to successful obesity prevention interventions. Building community capacity is often an aim of community-based interventions and is a valid, explicit and quantifiable target. Intervention teams are naturally drawn to focusing resources into specific nutrition and physical activity strategies, but this should not be done at the expense of de-prioritizing efforts to increase the capacity of the community to develop their own strategies to prevent obesity. Projects aimed at prevention among populations need to include evaluation of proximal indicators such as changes in capacity as well as more distal measures of individual change. Conflict of interest statement
menu) (Mathews et al., 2010). IYM was a high profile project within the intervention schools and resources were directed towards healthy eating and physical activity promotions as well as capacity building. These findings may impact on the post-project embedding of intervention strategies and should be noted in the design of future interventions. The three intervention schools that recorded the highest change score (3 levels) and the highest score at follow-up (5 or 6) in RTC also recorded a significant decrease in the prevalence of overweight/obesity between baseline and follow-up. One hypothesis warranting further attention is that a hurdle level of change in RTC scores may exist before changes in prevalence of overweight/obesity are likely to occur. These findings suggest that reaching the stages of preparation or initiation is necessary as these levels indicate implementation of prevention strategies rather than the increase of three levels being the key.
The authors declare that there are no conflicts of interest.
Acknowledgments The authors would like to thank the many people involved in the Pacific OPIC Project including co-investigators, other staff and postgraduate students, partner organizations, and especially the schools, students, parents and communities. The funding for the project was from the Victorian Department of Health, the National Health and Medical Research Council (in conjunction with the Health Research Council [New Zealand] and the Wellcome Trust [UK] as part of their innovative International Collaborative Research Grant Scheme), and AusAID. References
Strengths of the current study The RTC tool has been used widely used outside obesity prevention including readiness of rural communities to engage in communityinitiated traumatic brain injury prevention (Stallones et al., 2008) and youth substance abuse (Ogilvie et al., 2008; Slater et al., 2005). This is the first time RTC has been measured at baseline and follow-up as the key component in an intervention to prevent adolescent obesity or overweight. Within this study the RTC tool was informative and reliable over time as intervention schools' scores changed as expected and comparison schools' scores were relatively stable. IYM was the first community-based adolescent obesity prevention study to measure an increase in community capacity associated with reduction in unhealthy weight. Weaknesses of the current study One challenge in of the RTC tool was that it was time consuming to implement and score and as a consequence the results were not available for immediate feedback. This shortcoming can be ameliorated by conducting baseline RTC interviews during the planning phase of projects. The results can inform the development and implementation of intervention strategies. A further potential weakness is the subjective nature of the scoring process; however using two independent scorers who did not participate in data collection may have minimized this potential for bias. Additionally, the dimensions captured by the tool
Australian Bureau of Statistics, 2001. Information Paper: Socio-Economic Indexes for Areas. Australian Government, Canberra. Bell, A.C., Simmons, A., Sanigorski, A.M., Kremer, P.J., Swinburn, B.A., 2008. Preventing childhood obesity: the sentinel site for obesity prevention in Victoria, Australia. Health Promot. Int. 23, 328–336. Chomitz, V.R., McGowan, R.J., Wendel, J.M., et al., 2010. Healthy living Cambridge kids: a community-based participatory effort to promote healthy weight and fitness. Obesity 18, S45–S53. de Groot, F.P., Robertson, N.M., Swinburn, B.A., de Silva-Sanigorski, A.M., 2010. Increasing community capacity to prevent childhood obesity: challenges, lessons learned and results from the Romp & Chomp intervention. BMC Publ. Health 10. Department of Health New South Wales, 2001. A Framework for Building Capacity to Improve Health. Department of Health, Sydney, Australia. Economos, C.D., Curtatone, J.A., 2010. Shaping up Somerville: a community initiative in Massachusetts. Prev. Med. 50, S97–S98. Findholt, N., 2007. Application of the community readiness model for childhood obesity prevention. Public Health Nurs. 24, 565–570. Goodman, R.M., Speers, M.A., McLeroy, K., et al., 1998. Identifying and defining the dimensions of community capacity to provide a basis for measurement. Health Educ. Behav. 25, 258–278. Hawe, P., Noort, M., King, L., Jordens, C., 1997. Multiplying health gains: the critical role of capacity-building within health promotion programs. Health Policy 39, 29–42. Lawrence, R.G., 2004. Framing obesity: the evolution of news discourse on a public health issue. Harv. Int. J. Press Polit. 9, 56–75. Mathews, L., Moodie, M., Simmons, A., Swinburn, B., 2010. The process evaluation of It's Your Move!, an Australian adolescent community-based obesity prevention project. BMC Publ. Health 10, 1–13. McLeroy, K., 1996. Community capacity: what is it? How do we measure it? What is the role of the prevention centers and CDC? Sixth Annual Prevention Centres Conference, Centers for Disease Control and Prevention.National Center for Chronic Disease Prevention and Health Promotion, Atlanta, GA. Millar, L., Kremer, P., de Silva-Sanigorski, A., et al., 2011. Reduction in overweight and obesity from a 3-year community-based intervention in Australia: the ‘It's Your Move!’ project. Obes. Rev. 12, 20–28.
384
L. Millar et al. / Preventive Medicine 56 (2013) 379–384
Oetting, E.R., Donnermeyer, J.F., Plested, B.A., Edwards, R.W., Kelly, K., Beauvais, F., 1995. Assessing community readiness for prevention. Subst. Use Misuse 30, 659–683. Ogilvie, K., Moore, R., Ogilvie, D., Johnson, K., Collins, D., Shamblen, S., 2008. Changing community readiness to prevent the abuse of inhalants and other harmful legal products in Alaska. J. Community Health 33, 248–258. O'Hara, L., Gregg, J., 2006. The war on obesity: a social determinant of health. Health Promot. J. Austr. 17, 260–263. Plested, B., Edwards, R., Thurman, P., 2006. Handbook For Using The Community Readiness Model. Tri-Ethnic Center for Prevention Research, Colorado. Rogers, T., Howard-Pitney, B., Lee, H., 1995. An Operational Definition of Local Community Capacity for Tobacco Prevention and Education. Stanford Centre for Research in Disease Prevention, Stanford University, Palo Alto, CA. Simmons, A., Mavoa, H.M., Bell, A.C., et al., 2009. Creating community action plans for obesity prevention using the ANGELO (Analysis Grid for Elements Linked to Obesity) Framework. Health Promot. Int. 24, 311–324. Simmons, A., Reynolds, R.C., Swinburn, B., 2011. Defining community capacity building: is it possible? Prev. Med. 52, 193–199.
Slater, M.D., Edwards, R.W., Plested, B.A., et al., 2005. Using community readiness key informant assessments in a randomized group prevention trial: impact of a participatory community-media intervention. J. Community Health 30, 39–53. Sliwa, S., Goldberg, J.P., Clark, V., et al., 2011. Using the community readiness model to select communities for a community-wide obesity prevention intervention. Prev. Chronic Dis. 8 (6), A150. Stallones, L., Gibbs-Long, J., Gabella, B., Kakefuda, I., 2008. Community readiness and prevention of traumatic brain injury. Brain Inj. 22, 555–564. Swinburn, B., Pryor, J., McCabe, M., et al., 2007. The Pacific OPIC Project (Obesity Prevention In Communities) — objectives and designs. Pac. Health Dialog 14, 139–146. Swinburn, B., Millar, L., Utter, J., et al., 2011. The Pacific Obesity Prevention in Communities project: project overview and methods. Obes. Rev. 12, 3–11. Waters, E., de Silva-Sanigorski, A., Hall, B., et al., 2011. Interventions for preventing obesity in children. Cochrane Database of Syst. Rev. World Health Organization, 2010. WHO Reference 2007. Growth Reference Data for 5–19 years.WHO, Geneva.