Social inequality, social networks, and health: a scoping review of research on health inequalities from a social network perspective

BackgroundThis review summarises the present state of research on health inequalities using a social network perspective, and it explores the available studies examining the interrelations of social inequality, social networks, and health.MethodsUsing the strategy of a scoping review, as outlined by Arksey and O'Malley (Int J Sci Res Methodol 8:19-32, 2005), our team performed two searches across eight scientific, bibliographic databases including papers published until October 2021. Studies meeting pre-defined eligibility criteria were selected. The data were charted in a table, and then collated, summarised, and reported in this paper.ResultsOur search provided a total of 15,237 initial hits. After deduplication (n = 6,168 studies) and the removal of hits that did not meet our baseline criteria (n = 8,767 studies), the remaining 302 full text articles were examined. This resulted in 25 articles being included in the present review, many of which focused on moderating or mediating network effects. Such effects were found in the majority of these studies, but not in all. Social networks were found to buffer the harsher effects of poverty on health, while specific network characteristics were shown to intensify or attenuate the health effects of social inequalities.ConclusionsOur review showed that the variables used for measuring health and social networks differed considerably across the selected studies. Thus, our attempt to establish a consensus of opinion across the included studies was not successful. Nevertheless, the usefulness of social network analysis in researching health inequalities and the employment of health-promoting interventions focusing on social relations was generally acknowledged in the studies. We close by suggesting ways to advance the research methodology, and argue for a greater orientation on theoretical models. We also call for the increased use of structural measures; the inclusion of measures on negative ties and interactions; and the use of more complex study designs, such as mixed-methods and longitudinal studies.