Social Isolation Could Trigger Increased Inflammation

Social Isolation Could Trigger Increased Inflammation

Social isolation is a common occurrence in adult US citizens, and it often results in loneliness. The findings of a new study reveal that there might be a link between this human contact deprivation and the development of severe health problems. According to the study authors, social isolation pertains to the risk factors contributing to morbidity and mortality. In their efforts to understand the mechanism behind this influence, they investigated the connection between social isolation and inflammation markers.

Inflammation serves as a defense mechanism that participates in detoxification, wound healing, and recovery from infections. It can be acute, lasting from several hours to a few days, or chronic, which persists for months or longer.  Two molecules related to inflammation are Interleukin-6 (IL-6) and C-reactive protein (CRP), and elevated levels of these molecules usually imply a risk of heart-related issues, adverse physical and cognitive issues, or even higher risk of death.

The study in question investigates how social isolation relates to IL-6 and CRP levels based on 2017 data from the National Health and Aging Trends Study (NHATS), including a sample of Medicare beneficiaries aged 65 or older. The data included two-hour interviews and blood samples. Results have uncovered that socially isolated participants had increased CRP levels compared to those not deprived of social contact and remained unchanged when adjusted for sociodemographic and health factors. The results were the same for IL-6. Only severely isolated elderly participants didn’t have significantly increased molecule levels when adjusted for sociodemographic and health factors.

The study is praised for being timely and interesting, particularly in light of the ongoing COVID-19 pandemic when social isolation is more widespread than ever owing to lockdowns and contact restrictions. However, it did have its limitations. Firstly, the data wasn’t extracted over a longer period which would facilitate causal inferences. Secondly, the participant sample excluded long-term care home beneficiaries and interviews with individuals acting as representatives of the actual patients. Finally, the data was self-reported, and therefore potentially unreliable and prone to bias.

Photo by Kristina Tripkovic on Unsplash

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