Transition-to-retirement pathways and cognitive health
My research examines how different pathways into retirement shape cognitive health and dementia risk. While previous studies have primarily conceptualized retirement as a single event or focused on retirement age, my work using sequence analysis and data from the US Health and Retirement Study (Under Review) suggests that how people transition into retirement may matter more than when they retire. Building on this work, I aim to investigate retirement trajectories across countries with different welfare systems, examine the role of co-evolving factors such as social connectedness and income stability, and understand how retirement policies influence retirement pathways and subsequent cognitive aging.
Life transitions and long-term social connectedness
Loneliness and social isolation are increasingly recognized as major public health concerns worldwide, affecting individuals across age groups and contributing to inequalities in mental, cognitive, and cardiometabolic health. Yet, relatively little is known about how loneliness and social isolation evolve over the life course and how they intersect with major life transitions. My research aims to examine long-term trajectories of subjective loneliness and objective social isolation, and how they co-evolve with changes in employment, family formation and relationships, and retirement. By investigating differences in these trajectories across individuals, socioeconomic groups, and countries, I hope to better understand the life-course processes that contribute to inequalities in social connectedness and identify opportunities for prevention and intervention.
WORKING PAPERS AND PRE-PRINTS
Pacca, L., Hebert, J., Carr, D. C., Brenowitz, W. D., Glymour, M. M., Harrati, A., & Vable, A. M. (2026). The transition to retirement and dementia risk: An application of sequence analysis. medRxiv (preprint).
Pacca, L., Wang, G., Qian, H., Hamad, R., Glymour, M. M., & Vable, A. M. (2026). Lifetime patterns of Earned Income Tax Credit eligibility and cognition: A sequence analysis approach. American Journal of Preventive Medicine, 71(4), 108386.
Pacca, L., Dang, K. V., Koenig, L., et al. (2026). Using sequence and cluster analysis to characterize variables that unfold over time: Implementation and practical considerations for epidemiologists. American Journal of Epidemiology, 195(6), 1707–1718.
Khadka, A., Pacca, L., Hebert, J., et al. (2026). Impact of Vietnam-era G.I. Bill eligibility on the distribution of later-life memory score levels and decline: Evidence from the Vietnam draft lottery natural experiment. American Journal of Epidemiology.
Van Dang, K., Pacca, L., Weuve, J., et al. (2026). Is memory in older adulthood influenced by changes in air pollution over the previous decade? Examining concurrent trajectories in ambient PM₂.₅ and NO₂ using sequence analysis. Environmental Epidemiology, 10(1), e448.
Pacca, L., Gaye, S. A., Brenowitz, W. D., Fujishiro, K., Glymour, M. M., Harrati, A., & Vable, A. M. (2025). Do type, timing and duration of life course non-employment differentially predict dementia risk? An application of sequence analysis. Social Science & Medicine, 372, 117976.
Pacca, L., Irish, A. M., Duarte, C. dP., et al. (2025). Differential associations between education and blood pressure by gender and race. BMC Public Health, 25, 2278.
Chiang, Y. A., Pacca, L., Vable, A. M., Carton, T., Pletcher, M. J., & Hamad, R. (2025). Trajectories and patterns of US counties’ policy responses to the COVID-19 pandemic: A sequence analysis approach. SSM – Population Health, 29, 101734.