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Primary Submission Category: Life-course/developmental
Life Course Trajectories of Depressive Symptomatology in the United States: Longitudinal Integrative Data Analysis of Large-Scale Population-Based Cohort Studies
Authors: Man Zhang,
Presenting Author: Man Zhang*
Objectives: To provide one of the first comprehensive life course analysis of age-related changes in depressive symptomatology and social disparities therein in the general U.S. population.
Methods: I integrate and harmonize data across five large-scale, population-based cohort studies: the National Longitudinal Study of Adolescent to Adult Health (Waves I–VI), the National Longitudinal Survey of Youth 1979 Child and Young Adult (1994–2020), the Americans’ Changing Lives Study (Waves I–VI), the National Survey of Midlife Development in the United States (Waves 2–3), and the Health and Retirement Study (1996–2022). These studies collectively cover most of the human life span from adolescence to late adulthood from age 11 through 90 years and older, offering far more extended coverage of developmental periods than any single study can allow. The analytic sample consists of 73,979 respondents and 371,241 person-year observations. Using moderated nonlinear factor analysis, I develop a commensurate measure of depressive symptomatology across contributing studies and individual characteristics. I estimate growth curve models to examine depressive symptom trajectories from adolescence to late adulthood and document variations in these trajectories by gender, race/ethnicity, and birth cohort.
Results: I expect to find significant age-related changes in both levels and rate of change in depressive symptomatology across the life course. I anticipate disparities in depressive symptom trajectories by gender, race/ethnicity, and birth cohort.
Discussion: This study demonstrates the utility of integrative data analysis as a novel data linkage approach to address fundamental data limitation in previous aging research and for studying mental health disparities across the life course. Findings will inform better timing of interventions to prevent depression progression and address detrimental social environments to mental health across diverse populations.