BackgroundCommunity-based obesity treatment programs for children that have a large program reach are a priority. To date, most programs have been small efficacy trials whose findings have yet to be up-scaled and translated into real-world settings. This paper reports on the process evaluation of a government-funded, translated obesity treatment program for children in Australia. It describes the characteristics and reach of children participating in the New South Wales (NSW) Ministry of Health Go4Fun® program.MethodsDelivered across the state of NSW (Australia) by Local Health Districts (LHDs), Go4Fun® is a community-based, multidisciplinary family obesity treatment program adapted from the United Kingdom Mind Exercise Nutrition Do it (MEND) program that targets weight-related behaviours. Children aged 7-13 years with a BMI ≥85th percentile and no co-morbidities were eligible at no cost. Parents/carers self-refer via a toll-free phone number, text messages, online registration or via secondary referrals. LHDs deliver a 16 to 20-session program based on length of school term, holidays and recruitment challenges. Both parent/carer and child attend bi-weekly after school sessions. Parent-reported socio-demographic and measured child weight characteristics are presented using descriptive statistics. Differences between completers (attended at least 75% of sessions) and non-completers were assessed using chi-square tests, independent sample t-tests and adjusted odds ratios. Analyses were adjusted for clustering of programs.ResultsBetween 2009 and 2012, a total of 2,499 children (54.8% girls; mean age [SD]: 10.2 [1.7 years]) participated in the Go4Fun® program. Children were mainly from low-middle socioeconomic status (76.5%), resided in major cities (63.3%), and 5.7% were Aboriginal. At baseline, 96.5% of children were overweight or obese. Mean BMI-z-score was 2.07 (0.41) and 94.5% had a waist-to-height ratio ≥0.5. More than half (57.9%) completed at least 75% of sessions. Amongst completers (N = 1,446), girls (56.8%; p = 0.02), non-Aboriginal children (95.9%; p < 0.01) and children residing in less socially disadvantaged areas (25.9%; p = 0.02) were significantly more likely to complete the program.ConclusionsThe Go4Fun® program successfully reached the targeted population of overweight/obese children at socioeconomic disadvantage and is a rare example of an up-scaled translational program.
Aim To compare food costs and variety of fresh fruits and vegetables (F&V) available at three time points in December 2006, December 2008 and July 2009. Methods Data on the cost of a 44‐item food basket across the main food groups including fresh and packaged foods were collected in 2006 (149 stores), 2008 (105 stores) and 2009 (129 stores). In addition, the number of varieties of 30 different fresh F&V was surveyed. Stores included the two major supermarket chains and smaller grocery chains using a convenience sample in NSW. The effects of rural/regional differences, socioeconomic differences, and store competition on cost and variety were assessed. Results The mean price of the food basket increased by 3.4% between December 2006 and 2008 and was lowest in July 2009, decreasing by 6.2% from December 2006. Variation between the cheapest and most expensive individual stores resulted in a $221 price difference in 2009, $148 in 2008 and $182 in 2006. Total food and F&V costs were more expensive in remote areas compared with highly accessible areas. The number of F&V varieties was influenced by increasing remoteness, low socioeconomic area and supermarket competition. Conclusions There was considerable variability in food costs by geographic areas and availability of fresh F&V also varied in both geographic and socio‐demographic areas. Monitoring of food costs may help reduce price variability, enabling identification of areas where the cost of food is disproportionately high.
BackgroundThe effectiveness of many interventions to promote health and prevent disease has been well established. The imperative has therefore shifted from amassing evidence about efficacy to scale-up to maximise population-level health gains. Electronic implementation monitoring, or ‘e-monitoring’, systems have been designed to assist and track the delivery of preventive policies and programs. However, there is little evidence on whether e-monitoring systems improve the dissemination, adoption, and ongoing delivery of evidence-based preventive programs. Also, given considerable difficulties with e-monitoring systems in the clinical sector, scholars have called for a more sophisticated re-examination of e-monitoring’s role in enhancing implementation.MethodsIn the state of New South Wales (NSW), Australia, the Population Health Information Management System (PHIMS) was created to support the dissemination of obesity prevention programs to 6000 childcare centres and elementary schools across all 15 local health districts. We have established a three-way university-policymaker-practice research partnership to investigate the impact of PHIMS on practice, how PHIMS is used, and how achievement of key performance indicators of program adoption may be associated with local contextual factors. Our methods encompass ethnographic observation, key informant interviews and participatory workshops for data interpretation at a state and local level. We use an on-line social network analysis of the collaborative relationships across local health district health promotion teams to explore the relationship between PHIMS use and the organisational structure of practice.DiscussionInsights will be sensitised by institutional theory, practice theory and complex adaptive system thinking, among other theories which make sense of socio-technical action. Our working hypothesis is that the science of getting evidence-based programs into practice rests on an in-depth understanding of the role they play in the on-going system of local relationships and multiple accountabilities. Data will be synthesised to produce a typology to characterise local context, PHIMS use and key performance indicator achievement (of program implementation) across the 15 local health districts. Results could be used to continuously align e-monitoring technologies within quality improvement processes to ensure that such technologies enhance practice and innovation. A partnership approach to knowledge production increases the likelihood that findings will be put into practice.
A family-based childhood obesity programme can be delivered OPW with no compromise to health or behavioural outcomes compared with TPW. Higher attendance, as a proportion of available sessions, leads to better outcomes for children.
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