Objectives: Our main objective is to establish an association between obesity and social networks among the adult population as well as understanding the underlying mechanisms. We aim to provide suggestions for the development of future interventions to treat obesity. Methods: We carried out a literature search from 4 databases: PubMed, Embase, Scopus and Web of Science. We conducted a systematic search targeting on 3 main concept terms—“social network”, “obesity” and “adult”. A final pool of 11 articles best fitted for our topic was included. Results: We have established a clear association between obesity and social networks. Single women with the co-living arrangement have a higher waist circumference (WC), consistent with a higher predisposition to obesity seen among single individuals but lone living divorced men had lower WC compared to those with partners. Women with high incomes are less likely to be obese in comparison to highly social men with low income. The degree of the effect on social networks and obesity was inconclusive due to differences in the study population. Generally, women with low social participation tend to be obese. However, non-partnered women consistently showed a higher WC in comparison to their partnered counterparts regardless of participation rates except for divorced women. Living in a neighborhood with access to active transportation, high socioeconomic status, increased levels of social trust and social support reduces the prevalence of obesity. Mechanisms of cultural ideals, nature of employment, stress, gender, self-selection, network influence, social contagion and shared built environment may have contributed to the variation in results obtained. Conclusion: Association between social network and obesity exists. However, its overall effect on body weight is affected by a variety of factors. Sociodemographic factors and network characteristics of the population may influence the impacts on body weight. Therefore, a good understanding of the mechanisms associated will assist the development of effective network-based interventions.
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