Adding measures of anxiety and depression to a commonly used cardiovascular risk predictor would have little effect on predicting risk of new cases of cardiovascular disease (CVD) at the population level, according to new research published in CMAJ (Canadian Medical Association Journal).

Anxiety and depression are the most common mental health issues worldwide, and evidence has shown an association with CVD. To determine whether adding measures of these mental health conditions to the American Heart Association Predicting Risk of Cardiovascular Disease Events (PREVENT) predictors can improve risk prediction of CVD, researchers in the United Kingdom developed models to investigate this question.

The study, which included 325 815 participants, found that including mental health predictors showed only a modest improvement in the model’s ability to predict CVD.

“Our findings suggest that the inclusion of measures of depression and anxiety in PREVENT would have little additional effect on the risk classification of CVD at the population level and may not be worthwhile,” writes Shinya Nakada, University of Glasgow, Glasgow, United Kingdom, with coauthors. “Investigating broader mental health conditions using more established tools or diagnostic interview data could be the focus of future studies to further refine CVD risk classification.”

“Refining PREVENT prediction models for 10-year risk of cardiovascular disease using measures of anxiety and depression” is published January 13, 2025.