Artificial intelligence shows that social isolation impacts cardiovascular age and mortality rate

April 20, 2024

Despite advances in early diagnosis and disease management, cardiovascular disease has remained the leading cause of mortality worldwide for decades. It particularly affects minorities and underprivileged populations. To address the gap, the American Heart Association recommends screening for social determinants of health (SDoH) and addressing biological factors in patients.

Stress and physical activity are well-recognized SDoH. But is there more to consider? "Could connecting with community and family be important for cardiac health? We sought to investigate the impact of social isolation on cardiac health, particularly the cardiac aging process," says Nazanin Rajai, M.D., M.P.H., a Cardiovascular Medicine research fellow at Mayo Clinic in Rochester, Minnesota, and lead author of a new study published in JACC: Advances. Dr. Rajai worked with Amir Lerman, M.D., a cardiologist at Mayo Clinic in Rochester and principal investigator and senior author of the study.

Mayo Clinic Cardiovascular Medicine researchers explored the connection between social isolation and biological aging using artificial intelligence-enabled electrocardiography (AI-ECG). They also evaluated the association of social isolation with all-cause mortality. The AI-ECG technology, previously developed by Mayo Clinic, provides the cardiac age estimate based on the electrocardiogram record.

AI cardiac scores

The study included more than 280,000 adults who received outpatient care at Mayo Clinic between June 2019 and March 2022. The large group was 50.9% women and 86.3% non-Hispanic white.

Mayo Clinic researchers performed a social isolation assessment using questions based on the Berkman and Syme Social Network Index (SNI). Participants answered the multiple-choice questions and had a 12-lead ECG within one year of completing the questionnaire. A higher SNI score shows a stronger social network.

Biological age was estimated with AI-ECG. Age-Gap was defined as AI-ECG age minus chronological age. Positive values reflected an older cardiac age than expected.

Social engagement slows aging

The results found slower cardiac aging in patients with higher SNI scores. In more socially isolated patients, the heart age estimation was higher than the calendar age, with more than two years of deviation.

"Our analysis showed that the observed association is independent of a patient's biological condition such as preexisting cardiovascular disease. We also found that highly isolated patients have a nearly 47% higher risk of death compared with those who are socially engaged," says Dr. Rajai. The results were consistent across all gender and age groups, with women having higher cardiac age estimation.

"This is the first study showing the association of social isolation with cardiac age and in assessing cardiac age estimated with the method of AI," says Dr. Rajai. "Our findings suggest that fostering community engagement and strong social networks could potentially slow down the aging process. This information is invaluable for designing interventions and strategies to promote social connections, especially within vulnerable populations."

What's next?

The researchers plan to conduct a more extended longitudinal study on the long-term effects of social isolation on cardiac aging. "It is crucial to include more diverse racial, ethnic and socioeconomic groups to ensure that the findings are representative and applicable across a broad spectrum of the population," says Dr. Rajai. "Ultimately, by addressing these social determinants of cardiac aging, we have the potential to enhance quality of life and reduce the burden on healthcare systems."

For more information

Rajai N, et al. Association between social isolation with age-gap determined by artificial intelligence-enabled electrocardiography. JACC: Advances. In press.

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