Initiatives and partnerships in an Australian metropolitan obesity prevention system: a social network analysis
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© The Author(s). 2021 Published in BMC Public Health. This article is published under the Open Access publishing model and distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/. Please refer to the licence to obtain terms for any further reuse or distribution of this work.
Background: Limited resources make prevention of complex population-level issues such as obesity increasingly challenging. Collaboration and partnerships between organisations operating in the same system can assist, however, there is a paucity of research into how relationships function at a local level. The aim of this study was to audit initiatives, explore networks, and identify potential opportunities for improving the obesity prevention system in a Health Service area of Western Australia (WA).
Methods: A mixed-methods study was undertaken in a metropolitan Health Service in Perth, WA in 2019–20. Structured face-to-face interviews (n = 51) were conducted with organisations engaged in obesity prevention, to identify prevention initiatives and their characteristics using a Systems Inventory tool. The Research Team identified the 30 most active organisations during the Systems Inventory, and an online Organisational Network Survey was administered to explore: relationships across six domains; partnership duration; frequency of interaction with other organisations; barriers to implementation; and key contributions to obesity prevention. Descriptive statistics were used to summarise barriers, contributions and Systems Inventory data. Organisational Network Survey data were analysed using social network analysis through UCINET 6 for Windows and Netdraw software. Whole network and cohesion scores were calculated: average degree; density; diameter; and degree centralization. Core-periphery analysis was conducted to identify densely connected core and sparsely connected periphery organisations.
Results: The Systems Inventory identified 189 unique prevention initiatives, mostly focusing on individual-level behaviour change. Fifty four percent (n = 15) of the Organisational Network Survey respondent organisations and most core organisations (67%, n = 8) were government. The information and knowledge sharing network had a density of 45% indicating a high level of information and knowledge exchange between organisations. The lowest densities were found within the receiving (3.3%), providing (5.5%) and sharing (5.6%) funding networks, suggesting that these formal relationships were the least established.
Conclusion: Applying a systems thinking lens to local obesity prevention revealed that initiatives conducted focused on individual-level behaviour change and that collaboration and communication between organisations focused on information sharing. Capturing the extent and nature of initiatives and the way partnerships operate to improve obesity prevention can help to identify opportunities to strengthen the networks.
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