Various aspects of social relationships have been examined as risk factors for mortality. In particular, most research has focused on either loneliness or social disengagement. We aimed to extend the current research by adding a group-level segregation measure utilizing the whole social network of one entire village in South Korea. The analyses were based on the Korean Social Life, Health and Aging Project data collected over eight years across five waves. Of the 679 old adults who participated throughout the entire project (to wave 5), 63 were confirmed as deceased. All three aspects of social relationships examined, loneliness, social disengagement, and group-level segregation, were associated with mortality in the traditional Cox proportional hazard model without considering health-related time-varying covariates. However, a Cox marginal structural model, a counterfactual statistical measure that is designed to control for censoring bias due to sample attrition over the eight years and time-varying confounding variables, revealed that only group-level segregation was associated with mortality. Our results strongly suggest that more attention is needed on group-level segregation for mortality studies, as well as on well-known individual-level risk factors, including social disengagement and loneliness. All methods were carried out in accordance with relevant guidelines and regulations.

No abstract

No abstract

Social exclusion occurs in various types of social relationships, from anonymous others to close friends. However, the role that social relationships play in social exclusion is less well known because most paradigms investigating social exclusion have been done in laboratory contexts, without considering the features of individuals’ real-world social relationships. Here, we addressed this gap by examining how pre-existing social relationships with rejecters may influence the brain response of individuals experiencing social exclusion. Eighty-eight older adults living in a rural village visited the laboratory with two other participants living in the same village and played Cyberball in an Magnetic Resonance Imaging scanner. Utilizing whole-brain connectome-based predictive modeling, we analyzed functional connectivity (FC) data obtained during the social exclusion task. First, we found that the level of self-reported distress during social exclusion was significantly related to sparsity, i.e. lack of closeness, within a triad. Furthermore, the sparsity was significantly predicted by the FC model, demonstrating that a sparse triadic relationship was associated with stronger connectivity patterns in brain regions previously implicated in social pain and mentalizing during Cyberball. These findings extend our understanding of how real-world social intimacy and relationships with excluders affect neural and emotional responses to social exclusion.

No abstract