Evolution of a Coalition Network during a Whole-of-Community Intervention to Prevent Early Childhood Obesity

Background: Community coalitions often lead and coordinate "whole-of-community" childhood obesity prevention interventions. A growing body of work suggests that coalition network ties, which facilitate transmission of information and advocacy, may be a key part of how such leadership operates. This study provides an understanding of the structure of coalition networks and how this structure changes over time. Methods: We administered semiannual network surveys during a pilot whole-of-community intervention in Somerville, MA (2015-2017). Participants included 16 multisector coalition members and their nominated discussion partners ("first-degree alters") related to childhood obesity prevention. Coalition and first-degree alter respondents named up to 20 discussion partners and reported ties' interaction frequency and perceived influence. Networks were assessed with visualization, descriptive analysis, and exponential random graph models. Results: Total network included 558 stakeholders representing community-based organizations, parents, health care, childcare, universities, among others. Size and membership varied over time. We observed the largest network (n = 256) during intervention planning, and the largest proportion of stakeholders communicating frequently (daily/weekly) about childhood obesity prevention during the peak intervention period. Networks were sparsely interconnected (1%-3% of possible ties observed) and most and least centralized at baseline and follow-up, respectively. Over time, ties were increasingly perceived as influential and siloed within community groups. Conclusions: The network's extensive evolving membership may indicate access to a wide range of resources, ideas, and an ability to broadly disseminate intervention messages. The attenuating network hierarchy over time may have supported more equal participation and control over intervention efforts. Future research should assess generalizability of network patterns, network influences on implementation processes, and possible network interventions.