A recent study conducted by researchers at the Mayo Clinic unveils a striking correlation between social isolation and signs of accelerated aging, alongside an increased risk of mortality from various causes. Published in the Journal of the American College of Cardiology: Advances, the study underscores the critical role of social connections in maintaining physical health and extending life expectancy, emphasizing the need to integrate social determinants of health into medical assessments and interventions.
The impetus for this new research stems from an increasing recognition of the detrimental effects of social isolation on health outcomes. Prior studies have highlighted how social isolation can lead to poorer health, higher medical expenses, and increased hospitalization rates.
While the emotional and mental health impacts of isolation are well-documented, its role in physical health, particularly in relation to biological aging and its consequences across different age groups, remains less explored. Given this gap, the Mayo Clinic researchers embarked on this study to delve into how social isolation might accelerate biological aging, utilizing an innovative AI-enabled algorithm for estimating biological age through electrocardiograms (ECGs).
The study was an observational cross-sectional analysis involving over 280,000 adults who sought outpatient care at Mayo Clinic from June 2019 to March 2022. The average chronological age of participants was 59.8 years, and the gender distribution was nearly even, with 50.9% females.
Participants were selected based on their completion of the Social Network Index (SNI) questionnaire and the availability of a 12-lead ECG record. The questionnaire aimed to gauge various aspects of the participants’ social lives, including their level of social interaction and engagement in community activities.
To estimate biological age, the researchers utilized an advanced AI-enabled algorithm applied to ECG records, known as AI-ECG. This innovative approach allowed for a comparison between the biological age estimated by the AI model and the participants’ actual chronological age, with the difference between these two ages (referred to as the “Age-Gap”) serving as a key indicator of accelerated or decelerated biological aging.
The results showed a significant difference in the mean Age-Gap between individuals with the highest level of social isolation and those with the least social isolation. Specifically, the study found that individuals with the lowest SNI scores (representing the highest degree of social isolation) had an average Age-Gap of 0.64 years, suggesting that they were slightly biologically older than their chronological age. In contrast, those with the highest SNI scores (indicating strong social connections) had an average Age-Gap of -1.2 years, implying that they were biologically younger than their actual age.
During the median follow-up period of 24 months, the total incidence of mortality was 4.9%, with the study observing a marked variation in mortality risk based on social network status. Higher mortality rates were significantly associated with lower SNI scores, indicating that those who were more socially isolated had a higher risk of death. The study’s survival analysis reinforced this finding, with the Cox proportional hazard analysis demonstrating that individuals with the most substantial social connections had a 53% lower risk of mortality compared to those with the least, after adjusting for demographics and comorbid conditions.
“This study highlights the critical interplay between social isolation, health and aging,” says Amir Lerman, M.D., a cardiologist at Mayo Clinic and senior author of the paper. “Social isolation combined with demographic and medical conditions appears to be a significant risk factor for accelerated aging. But we also know that people can change their behavior — have more social interaction, exercise regularly, eat a healthy diet, stop smoking, get adequate sleep, etc. Making and sustaining these changes may go a long way toward improving overall health.”
The researchers controlled for factors such as age, sex, and clinical comorbidities (such as hypertension, diabetes, chronic kidney disease, cancer, and other conditions). But the study, like all research, includes limitations. These include a lack of diverse racial representation and the inherent challenges of using AI-ECG for age estimation, which might not capture all nuances of biological aging. Furthermore, the findings are based on a cohort seeking medical care, which may not be entirely representative of the general population.
The researchers call for future studies to explore whether improving social connections can delay or reverse biological aging and highlight the need for interventions targeting the negative health impacts of social isolation.
The study, “Association Between Social Isolation With Age-Gap Determined by Artificial Intelligence-Enabled Electrocardiography,” was authored by Nazanin Rajai, Jose R. Medina-Inojosa, Bradley R. Lewis, Mohammad Ali Sheffeh, Abraham Baez-Suarez, Mark Nyman, Zachi I. Attia, Lilach O. Lerman, Betsy J. Medina-Inojosa, Paul A. Friedman, Francisco Lopez-Jimenez, and Amir Lerman.