Innovative risk score to diagnose depression using data from the UAE Healthy Future Study

Abstract Introduction Depression has been recognized as a major mental health disorder. Diagnosing depression remains a challenge due to its complex multifactorial nature. The UAE Healthy Future Study is a long-term cohort study that focuses on understanding the factors that contribute to chronic disease among Emiratis. It involves answering a comprehensive questionnaire, undergoing physical measurements such as Body Mass Index (BMI), and biological samples for analysis. We analyized the eight-item depression screening instrument Patient Health Questionnaire (PHQ-8) for this project. Methods Out of 487 participants included in the PHQ-8, 205 participants (42.1%) were included in the statistical analysis after omitting missing values. A multivariate Least Absolute Selection Shrinkage Operator (LASSO) logistic regression model was performed using gender, age, BMI, waist circumference, hip circumference, body fat percentage, high-density lipoprotein (mg/dL), lowdensity lipoprotein (mg/dL), total cholesterol (mg/dL), diastolic blood pressure, systolic blood pressure, hemoglobin A1C, as predictors. The primary outcome was the binarized total PHQ-8 using a cutoff value of ten Tenfold cross-validation was applied. Results A cutoff value that yields an approximate sensitivity of 90% was selected to maximize the ability of the novel risk score to correctly identify subjects with depression symptoms. Sensitivity and specificity were estimated with a corresponding 95% confidence interval (95% CI). A novel depression risk score was computed as the linear predictor of the selected five variables in the LASSO regression analysis, as following: Risk score = -3.284 + 0.471*gender - 0.053*age + 0.049*BMI + 0.022*HDLmgdL - 0.072*HBA1c Conclusions We have shown that a novel depression risk score provides useful information for screening of depression. Further validation studies are needed to confirm the application of the risk score in daily practice. Key messages • A novel depression risk score provides useful information for screening of depression. • If the risk score can be verified in a different population, then it can improve the screening methods for depression.