Abstract
Community social networks (CSN) include individuals and groups, and those with strong partnerships and relationships are well situated for implementing community-based interventions. However, information on the nature of CSN relationships required for multilevel community-based interventions is not present in the literature. Using data from the multi-level Children’s Healthy Living (CHL) trial to reduce child obesity in nine Pacific communities, this study aimed to develop a methodology based on Social Network Analysis (SNA) to understand how CSN evolved over the course of a two-year trial, as well as the characteristics of CSN most successful in impacting indicators of childhood obesity. 
 The two-year trial was considered in four six-month intervals. Within each interval, implemented activities, as recorded in CHL monthly reports, were coded by activity implementer(s), e.g. government agency, school, or community-based group, as well as for collective efficacy impact of the activity, e.g. to leverage resources from outside the CSN or to facilitate civic engagement. Coded data were used to create CSN maps for the four time intervals, and SNA techniques examined the CSN characteristics. CSN density increased over time, as measured by the number of ties within the network. Schools, community-based groups and large organizations were identified as the primary implementers of the CHL intervention and formed a community implementer backbone. Social leveraging, i.e. linking local groups to people with authority over outside resources, was shown to be a central component in intervention success. It took time to develop strong CSN, and stronger (denser) CSN were more successful in building social cohesion and enacting community change. Findings illustrate a methodology that can be useful for tracking the development and impact of CSN.
Highlights
Making changes to improve health in low-income communities is a challenging task requiring community partners to work together at the local level
Using data from the multi-level Children’s Healthy Living (CHL) trial to reduce child obesity in nine Pacific communities, this study aimed to develop a methodology based on Social Network Analysis (SNA) to understand how Community social networks (CSN) evolved over the course of a two-year trial, as well as the characteristics of CSN most successful in impacting indicators of childhood obesity
The third social network analysis identified interactions between the Collective Efficacy (CE) building blocks. These three social network analyses allowed for the mapping and exploration of community partners who assisted in implementing the CHL intervention over the two-year period, grouped into sixmonth intervals
Summary
Making changes to improve health in low-income communities is a challenging task requiring community partners to work together at the local level. Coalitions of diverse organisations that work towards strengthening communities offer opportunities to leverage resources, expand reach and develop skills to impact the health of communities (Butterfoss 2007). The broad reach of diverse groups offers opportunities to increase public support for policies and community action, creating a potential for larger collective impact (Kendall et al 2012). Social Network Analysis (SNA) is a systems approach to understanding the dynamics of multi-level interventions that identifies the networks of social relationships that make up the system and the variety of roles that exist and can be created within networks (Hawe, Shiell & Riley 2009). SNA has been used to explore workplace change processes and resource sharing networks (Callon 1984; Orlikowski & Robey 1991). Valente, Chou & Pentz 2007 examined the density of community coalition networks and the uptake of evidence-based interventions; the use of SNA with multi-level, community-based interventions is still in the early stages
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