For this study, researchers wanted to identify different risk factors for insomnia using machine learning and a retrospective cross-sectional cohort study.

Looking at data from nearly 8,000 middle-aged participants, machine learning assessed everything from mental health to physical health and lifestyle factors as they relate to sleep disorders.

According to their findings, depression was the biggest risk factor for insomnia, with 31.1% of participants with insomnia also struggling with depression. The next most significant risk factors were age and physical activity.

As study author Samuel Y. Huang, MD, explains in a press release: “What sets this insomnia risk factor study apart from others is not only that depression symptoms, age, caffeine use, history of congestive heart failure, chest pain, coronary artery disease heart disease, liver disease, and 57 other variables associated with insomnia, and visualizing the contribution of each to a highly predictive model.”