Within industrialized countries, there has been a marked increase in life expectancy since the 1970s, mainly due to improvements in cardiovascular health. However, people with severe mental disorders such as schizophrenia, bipolar disorder and major depressive disorder have not shared these improvements, and continue to face a 10 to 20 year reduction in life expectancy. Possible reasons for this include metabolic side effects of psychoactive medications, inadequate physical health care, and lifestyle factors such as smoking. More recently, two additional factors have been examined: loneliness, and shared genetics.
Feelings of loneliness affect nearly 80% of people with severe mental disorders. Surprisingly, loneliness itself increases the risk of cardiovascular disease and premature death just as much as more commonly-known risk factors like physical inactivity and smoking. Some people have genes which make them more likely to experience feelings of loneliness. Recent research has uncovered genes which increase the risk of loneliness, severe mental disorders and cardiovascular disease at the same time. This research has benefitted from new statistical techniques which allow scientists to identify genetic relationships that were previously hidden.
How can we use this information to help people with severe mental disorders? CoMorMent researcher Linn Rødevand and her colleagues suggest two key areas for improvement. Firstly, research should focus on ways to reduce loneliness. Early findings suggest that interventions which help people reframe their social experiences could be helpful, though it is essential that these are provided alongside societal efforts to reduce stigma and improve opportunities for education and employment for people with mental illness.
Secondly, prediction tools which use algorithms to predict someone’s cardiovascular risk should be tailored for people with severe mental disorders. Furthermore, researchers should seek to improve existing prediction tools by including genetic information, instead of only focusing on traditional health information such as blood pressure, family history and antidepressant use. Importantly, genetic information can highlight who is at risk of cardiovascular disease long before traditional risk factors like type-2 diabetes become apparent. These prediction tools could be used to help clinicians determine who is most in need of pharmacological or non-pharmacological interventions.
In summary, the scientific community has made inadequate progress in addressing the heightened risk of cardiovascular disease and premature death amongst people with severe mental disorders. However, this review by CoMorMent researchers highlights novel directions which could improve people’s lives, specifically a focus on reducing loneliness and using genetic information to help predict risk and target health interventions towards those who need them most.
