Markers of Immune System Health

Research involving stress and the immune system has typically taken one of two paths—an evaluation of inflammation and overall immune health or of iimnune reactivity. As part of the body’s natural immune response, the immune system activates inflanunation partly with the release of pro-inflammatory cytokines (Boren & Veksler, 2011). HPA activity from the endocrine system can impact the way that the body responds to antigens, by inhibiting the production of certain cytokines (such as interleukin-12 and tumor necrosis factor-alpha) and can increase the amounts of other chemicals (e.g., interleukins 4 and 10, and C-reactive protein) (Segerstrom & Miller, 2004). Therefore, researchers can analyze the underlying pathways by which social support processes interact with HPA activity linking to inflammatory function. As an example, Boren and Veksler (2018) found that trait co-rumination was positively associated with C-reactive protein and negatively associated with interleukin-6. From an iimnune health perspective, researchers typically gauge various functional metrics of the immune system. Working within this framework does require using multiple immune system markers beyond just cytokines, including natural killer cells, granulocytes, antibodies, monocytes, and C- and T-cells. Recently, Floyd and colleagues (2018) correlated social support with eight different immune markers. They found that perceived social support was associated with IgM, CD3+, and CD4+ and expressed support was associated with IgG, IgM, CD3+, CD4+, CD8+, and CD19+.

Other research programs have explored immune system health by looking at immune reactivity. From this perspective, scholars typically determine antibodies associated with a latent virus (instead of exposing someone to viruses). For instance, both the Epstein-Вахт virus (EBV) and Cytomegalovirus (CMV) are present in latent forms in up to 80% of adults over the age of 40 (Boren & Veksler, 2011); therefore, evaluating how well the iimnune system suppresses these viruses can serve as a metric to immune health. For instance, Floyd, Hesse, Boren, and Veksler (2014) found that affectionate communication can be linked with increasing levels of latent-EBV titers, thereby indicating a reduction in the immune system’s ability to suppress the virus. Taken together, we suggest that researchers explore the immune system by evaluating various metrics of immune health, including metrics of inflammation and reactive measures of immunosuppression as they relate to social support.

Interaction Outcomes for the Support Provider

Consistent with taking a dyadic perspective on the support process, the use of multiple markers could also provide insight into the effects of providing support on the support provider, an area of research currently lacking in communication work. One exception is a recent observational study in which paiticipants observed a peer in distress, while their responses to the situation, both behavioral (i.e., whether they provided support or not), physiological, and emotional, were measured (Priem, Giles, & Rigau, 2016). Compared to controls who did not observe a distressed peer, potential support providers reported that the interaction was more stressful and showed increased markers of physiological stress. Although this extremely preliminary research supports the notion that providing support is stressful, it does not provide insight into the effects of that stress on the provider. Furthermore, research has argued that although providing support can be difficult, resulting in issues such as caregiver burnout, provision of support can also be salubrious (Faw, 2016).

Expanding the examination to include multiple physiological markers suggests ways in which the stress associated with providing support may have positive outcomes for the support provider. A study of the Changing Lives in Older Couples dataset (a decades long multi-wave study of over 1,500 married men and women) found that, controlling for the impact of receiving support, giving emotional support to spouses is associated with improved mortality over a 5-year period and receiving support has no effect on mortality after adjusting for giving support (Brown, Nesse, Vinokur, & Smith, 2003). One explanation for this is that providing support creates eustress or gives one positive feelings and fulfilment (Loving & Wright, 2013). To the extent that individuals can perceive the act of providing support to a loved one as a challenge, they may benefit from the adaptive physiological responses to stress. For example, feelings of fulfillment and happiness may be the result of elevated oxytocin.

Looking at immune system health may also help explain this phenomenon. For instance, a recent study of healthy adults found that expressed support within the context of non-distressed relationships was positively associated with multiple markers of innnunocompetence. Further- more, the relationship between immune health and support expression remained significant even when controlling for received support (Floyd et al., 2018). However, the mechanism through which providing support has positive or negative effects on providers is not frilly understood. Given that the effects of various biomarkers are known, one objective way of assessing this may be to examine a variety of physiological outcomes for support providers and/ or the dyad as a whole.

 
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