Cullerton Katherine, Donnet Timothy, Lee Amanda, Gallegos Danielle
School of Exercise and Nutrition Sciences, Queensland University of Technology, Victoria Park Rd, Kelvin Grove, QLD, 4059, Australia.
School of Management, Queensland University of Technology, 2 George St, Brisbane, QLD, 4000, Australia.
BMC Public Health. 2017 Apr 8;17(1):307. doi: 10.1186/s12889-017-4217-8.
Poor diet is the leading preventable risk factor contributing to the burden of disease in Australia. A range of cost-effective, comprehensive population-focussed strategies are available to address these dietary-related diseases. However, despite evidence of their effectiveness, minimal federal resources are directed to this area. To better understand the limited public health nutrition policy action in Australia, we sought to identify the key policy brokers in the Australian nutrition policy network and consider their level of influence over nutrition policymaking.
A social network analysis involving four rounds of data collection was undertaken using a modified reputational snowball method to identify the nutrition policy network of individuals in direct contact with each other. Centrality measures, in particular betweenness centrality, and a visualisation of the network were used to identify key policy brokers.
Three hundred and ninety (390) individual actors with 1917 direct ties were identified within the Australian nutrition policy network. The network revealed two key brokers; a Nutrition Academic and a General Health professional from a non-government organisation (NGO), with the latter being in the greatest strategic position for influencing policymakers.
The results of this social network analysis illustrate there are two dominant brokers within the nutrition policy network in Australia. However their structural position in the network means their brokerage roles have different purposes and different levels of influence on policymaking. The results suggest that brokerage in isolation may not adequately represent influence in nutrition policy in Australia. Other factors, such as direct access to decision-makers and the saliency of the solution, must also be considered.
不良饮食是导致澳大利亚疾病负担的主要可预防风险因素。有一系列具有成本效益的、以人群为重点的综合策略可用于应对这些与饮食相关的疾病。然而,尽管有证据表明这些策略有效,但联邦政府在这方面投入的资源却极少。为了更好地理解澳大利亚公共卫生营养政策行动的局限性,我们试图确定澳大利亚营养政策网络中的关键政策中介,并考量他们对营养政策制定的影响程度。
采用改良的声誉滚雪球法进行了四轮数据收集的社会网络分析,以确定彼此直接接触的个人的营养政策网络。使用中心性度量,特别是中介中心性,以及网络可视化来识别关键政策中介。
在澳大利亚营养政策网络中识别出390个个体参与者,他们之间有1917条直接联系。该网络显示出两个关键中介:一位营养学界人士和一位来自非政府组织的普通健康专业人员,后者在影响政策制定者方面处于最具战略意义的位置。
这项社会网络分析的结果表明,澳大利亚营养政策网络中有两个主要中介。然而,他们在网络中的结构位置意味着他们的中介角色具有不同的目的,对政策制定的影响程度也不同。结果表明,孤立地看待中介作用可能无法充分体现其对澳大利亚营养政策的影响。还必须考虑其他因素,例如直接接触决策者的机会以及解决方案的显著性。