Predicting Depressive Symptoms from Demographic, Social, Psychological, Behavioural, and Genetic Factors in Middle-Aged and Older Adults: A Trajectory Analysis of the Health and Retirement Study

Depressive symptoms in middle aged and older adults are common, persistent, and are associated with cardiovascular disease, cognitive impairment, as well as earlier mortality. Previous research has identified risk factors for depressive symptoms in midlife and older adulthood such as increasing age, female sex, racial and ethnic minority status, major life stressors, lack of social connectedness, neuroticism, physical inactivity, and polygenic risk scores. However, these multidisciplinary predictors have not been compared to determine their relative contribution to depressive symptoms in older adulthood. Furthermore, previous research has only assessed depressive symptoms and their predictors cross-sectionally or prospectively (i.e., 2 time points), which misconstrues the dynamic temporal nature of depressive symptoms. Therefore, using data from the Health and Retirement Study (2006/2008-2016/2018), this project has three aims: 1) assess 10-year trajectories of depressive symptoms in middle aged and older adults (i.e., aged 50+) using growth mixture modelling, 2) identify predictors of trajectory groups in order of importance using random forest analysis, and 3) compare how trajectory groups differ in relation to the most important predictors with multinomial logistic regression. The significance of this project is that it may extend the literature by identifying top predictors of depressive symptom trajectories in middle aged and older adults, which may then serve as grounds for hypothesis generation and provide candidates for targeted interventions.