Allostatic load, stress Response to Social Stress, frequency of Stress Exposure, and social Network structure/function (ARSEN) - This project tests how various forms of social stress contribute to allostatic load and related health risk, and how aspects of social support networks may mitigate negative health effects of stress by reducing stress contagion. Our project focuses on two critical types of social stress: “day-to-day” stressful interactions and severe forms of social stress (e.g., experiences of violence), which may represent forms of stress resulting in acute and chronic changes to stress response, respectively. Changes in stress responding may contribute to worsening allostatic load, or the chronic “wear and tear” from stress that has consistently been linked to the development of chronic diseases such as diabetes and cardiovascular disease. This proposal will be among the first to test mechanisms of how social stress contributes to allostatic load; we will extend this work beyond the individual to understand how stress acts on a social network. Social support may improve several stress-related outcomes, including allostatic load, but data are lacking to explain how. Prior research does not account for how social support may perpetuate stress across a network: that is, when one person experiences stress, their supportive others will also experience stress. Put simply, when we experience social stress, we tend seek support from others with similar experiences, because they uniquely understand what we are going through: but when we do, we remind others of their own stressful experiences and stress “spills over” to them. However, some qualities of support networks may mitigate this spillover. The current study seeks to identify these qualities, which may be targeted in interventions that reduce stress not only in the individual, but across the social network. First, we will determine the extent to which social stress response and social stress exposure frequency combine to predict changes in allostatic load, and in turn predicts risk for the chronic health outcomes identified as priorities for the Presidential Make America Healthy Again agenda. Second, we will determine the social network qualities that mitigate stress “spilling over” from one person to another. Finally, we determine how social stress transmits across a network to predict changes in the networks’ allostatic load. To achieve this, we will use sampling designs (respondent-driven sampling; RDS) and social network analyses that allow us to understand how the connections across people influence health. We will examine social support; biomarkers of allostatic load, acute and chronic stress, and inflammation; and daily diary assessments of social stress frequency. Using novel Bluetooth technology developed by our team we will also assess how often participants interact with one another, linking that data to each participant’s reports of social stress and whether they discussed social stress experiences with supportive others. The combination of these measures and network-based approach allows us to test how social environments influence health. These data will inform how to best target social support interventions to limit the negative effects of stress.
