Applications of social network analysis to obesity: a systematic review.
People's health behaviours and outcomes can be profoundly shaped by the social networks they are embedded in. Based on graph theory, social network analysis is a research framework for the study of social interactions and the structure of these interactions among social actors. A literature search was conducted in PubMed and Web of Science for articles published until August 2017 that applied social network analysis to examine obesity and social networks. Eight studies (three cross-sectional and five longitudinal) conducted in the US (n = 6) and Australia (n = 2) were identified. Seven focused on adolescents' and one on adults' friendship networks. They examined structural features of these networks that were associated with obesity, including degree distribution, popularity, modularity maximization and K-clique percolation. All three cross-sectional studies that used exponential random graph models found individuals with similar body weight status and/or weight-related behaviour were more likely to share a network tie than individuals with dissimilar traits. Three longitudinal studies using stochastic actor-based models found friendship network characteristics influenced change in individuals' body weight status and/or weight-related behaviour over time. Future research should focus on diverse populations and types of social networks and identifying the mechanisms by which social networks influence obesity to inform network-based interventions.
['Zhang|S|S|', 'de la Haye|K|K|', 'Ji|M|M|', 'An|R|R|0000-0001-9632-0209']
D003430:Cross-Sectional Studies D005247:Feeding Behavior D015438:Health Behavior D006801:Humans D007398:Interpersonal Relations D008137:Longitudinal Studies D009765:Obesity D012931:Social Environment D060756:Social Networking
social network analysis Obesity systematic review