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BMC Public Health
Published in: BMC Public Health 1/2017

Open Access 01-12-2017 | Research article

Joining the dots: the role of brokers in nutrition policy in Australia

Authors: Katherine Cullerton, Timothy Donnet, Amanda Lee, Danielle Gallegos

Published in: BMC Public Health | Issue 1/2017

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Abstract

Background

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.

Methods

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.

Results

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.

Conclusion

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.
Appendix
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Literature
1.
Institute for Health Metrics and Evaluation. In: Bank TW, editor. GBD profile: Australia. Seattle: IHME; 2013.
2.
Australian Institute of Health and Welfare: Australian burden of disease study: impact and causes of illness and death in Australia 2011. In: Australian burden of disease study series no 3. vol. Cat. no. BOD 4. Canberra: AIHW; 2016.
3.
Sacks G, Veerman J, Moodie M, Swinburn B. ‘Traffic-light’nutrition labelling and ‘junk-food’tax: a modelled comparison of cost-effectiveness for obesity prevention. Int J Obes. 2010;35(7):1001–9.CrossRef
4.
Cobiac LJ, Veerman L, Vos T. The role of cost-effectiveness analysis in developing nutrition policy. Annu Rev Nutr. 2013;33:373–93.CrossRefPubMed
5.
WHO. Diet, nutrition and the prevention of chronic diseases. World Health Organization technical report series 2003. WHO: Geneva. 916:i-viii, 1–149, backcover.
6.
Department of Health. Australian government 2012–13 health and ageing portfolio budget statements. Canberra: Department of Health, Australian Government; 2012.
7.
Chapman S. Intersectoral action to improve nutrition: the roles of the state and the private sector. A case study from Australia. Health Promot Int. 1990;5(1):35–44.CrossRef
8.
Dür A, De Bièvre D. The question of interest group influence. J Publ Policy. 2007;27(01):1–12.CrossRef
9.
10.
Lin N, Cook KS, Burt RS. Social capital: theory and research. New York: Transaction Publishers; 2001.CrossRef
11.
12.
Laumann EO, Knoke D. The organizational state: social choice in National Policy Domains. Wisconsin: University of Wisconsin Press; 1987.
13.
Rhodes RAW, Marsh D. New directions in the study of policy networks. Eur J Polit Res. 1992;21(1–2):181–205.CrossRef
14.
Sabatier P, Weible C. The advocacy coalition framework: innovations and clarifications. In: Sabatier P, editor. TPP. 2nd ed. USA: Westview Press; 2007. p. 189–222.
15.
Siegel DA. Social networks and collective action. Am J Polit Sci. 2009;53(1):122–38.CrossRef
16.
Cullerton K, Donnet T, Lee A, Gallegos D. Exploring power and influence in nutrition policy in Australia. Obes Rev. 2016;17(12):1218–25.CrossRefPubMed
17.
Baker P, Gill T, Friel S, Carey G, Kay A. Generating political priority for regulatory interventions targeting obesity prevention: an Australian case study. Soc Sci Med. 128:131–43.
18.
Christopoulos D, Ingold K. Distinguishing between political brokerage and political entrepreneurship. Procedia Soc Behav Sci. 2011;10:36–42.CrossRef
19.
McCullough JM, Eisen-Cohen E, Salas SB. Partnership capacity for community health improvement plan implementation: findings from a social network analysis. BMC Public Health. 2016;16(1):566.CrossRefPubMedPubMedCentral
20.
Uddin S, Hossain L, Hamra J, Alam A. A study of physician collaborations through social network and exponential random graph. BMC Health Serv Res. 2013;13(1):234.CrossRefPubMedPubMedCentral
21.
Harris JK, Luke DA, Burke RC, Mueller NB. Seeing the forest and the trees: using network analysis to develop an organizational blueprint of state tobacco control systems. Soc Sci Med. 2008;67(11):1669–78.CrossRefPubMed
22.
Oliver K, de Vocht F, Money A, Everett M. Who runs public health? A mixed-methods study combining qualitative and network analyses. J Public Health. 2013;35(3):453–9.CrossRef
23.
Börzel TA. Organizing Babylon-on the different conceptions of policy networks. Public Adm. 1998;76(2):253–73.CrossRef
24.
Hanneman R, Riddle M. Introduction to Social Network Methods. Riverside: University of California; 2005.
25.
Wasserman S, Galaskiewicz J: Advances in social network analysis: research in the social and behavioral sciences. Thousand Oaks, Calif: Sage Publications; 1994.
26.
Knoke D. Political networks: the structural perspective, vol. 4: Cambridge: Cambridge University Press; 1994.
27.
Christopoulos D, Ingold K. Exceptional or just well connected? Political entrepreneurs and brokers in policy making. Eur Political Sci Rev. 2015;7(03):475–98.CrossRef
28.
Knoke D, Yang S. Social network analysis, vol. 2nd. California: Sage Publications; 2008.CrossRef
29.
Wasserman S, Faust K. Social network analysis: methods and applications, vol. 8. Cambridge: Cambridge University Press; 1994.CrossRef
30.
Hansen D, Shneiderman B, Smith MA. Analyzing social media networks with NodeXL: Insights from a connected world. Maryland: Morgan Kaufmann; 2010.
31.
Freeman LC. Centrality in social networks conceptual clarification. Soc Networks. 1978;1(3):215–39.CrossRef
32.
Robins G. Doing social network research: network based research design for social scientists. London: Sage; 2015.
33.
Burt R. Structural holes: the structure of social capital competition. Cambridge: Harvard University Press; 1992.
34.
Morselli C. Assessing vulnerable and strategic positions in a criminal network. J Contemp Crim Just. 2010;26(4):382–92.CrossRef
35.
Lewis JM. Being around and knowing the players: networks of influence in health policy. Soc Sci Med. 2006;62(9):2125–36.CrossRefPubMed
36.
Smith M, Milic-Frayling N, Shneiderman B, Medes Rodrigues E, Leskovec J, Dunne C: NodeXL: a free and open network overview, discovery and exploration add-in for Excel 2007/2010. In.: Social Media Research Foundation; 2010.
37.
Cullerton K, Donnet T, Lee A, Gallegos D. Playing the policy game: a review of the barriers to and enablers of nutrition policy change. Public Health Nutr. 2016;19(14):2643–53.CrossRefPubMed
38.
Crammond B, Van C, Allender S, Peeters A, Lawrence M, Sacks G, Mavoa H, Swinburn BA, Loff B. The possibility of regulating for obesity prevention - understanding regulation in the commonwealth government. Obes Rev. 2013;14(3):213–21.CrossRefPubMed
39.
Kingdon J. Agendas, alternatives, and public policies. 2nd ed. New York: Harper Collins; 1995.
40.
Svensson T, Öberg P. How are coordinated market economies coordinated? Evidence from Sweden. West Eur Politics. 2005;28(5):1075–100.CrossRef
Metadata
Title
Joining the dots: the role of brokers in nutrition policy in Australia
Authors
Katherine Cullerton
Timothy Donnet
Amanda Lee
Danielle Gallegos
Publication date
01-12-2017
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2017
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-017-4217-8

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