Occupational transitions across the lifecourse and dementia risk: evaluating unemployment, occupational complexity using sequence analysis

Dementia is typically diagnosed in late life, however, the disease process begins decades earlier; mid-life experiences such as work are important modifiable predictors of Alzheimer's Disease and related disorders (ADRD). Work is central to the lives of American adults, but the relationship between work, unemployment, and ADRD across the lifecourse has been understudied. This proposal advances the current literature on how occupations influence dementia risk in the United States in two ways: [1] people work from approximately ages 18 – 65, however little research evaluates age when someone has a particular job, job duration, or changes in work experiences across working years; and [2] occupational classification systems used by population-based datasets have changed to reflect the transition from a manufacturing to information and service based economy (with different physical, environmental, and cognitive demands), however physical, environmental, and cognitive characteristics of work have not been systematically applied to these shifting occupational classification systems. In this proposal, we will evaluate lifecourse work trajectories and ADRD risk through novel applications of sequence analysis, and construct a longitudinal database of physical, environmental, and cognitive demands of work to catalyze research on lifecourse work trajectories and ADRD risk. We will leverage the strengths of two large, longitudinal U.S. cohorts to evaluate the relationships between lifecourse work trajectories and ADRD risk: The National Longitudinal Survey of Youth, 1979 cohort (NLSY), and the Health and Retirement Study (HRS). Our research team has previously published using sequence analysis, and previously used both datasets, demonstrating the feasibility of our proposed project. Work is a modifiable social risk factor that spans decades; a better understanding of work trajectories and features will help identify employment interventions to slow cognitive decline and reduce ADRD disparities.