Postponed retirement delays cognitive decline: Using counterfactual causal inference to disentangle life-course risk factors

• In Event: 3460 - Health, Aging, and the Life Course

Abstract

There is a growing body of research showing later-life cognitive function is affected by demographic, social, and behavioral factors throughout the life course. Because cognitive stimulation and engagement are associated with cognitive function, we hypothesize that postponing labor market exit may be cognitively beneficial in slowing cognitive decline. We model the association between a measure of fluid cognitive function constructed from the U.S. Health and Retirement Study (1998-2014) and life-course factors, including early-SES, education, occupation, health behaviors, and labor force participation. We employ methodological innovations in counterfactual causal inference to disentangle the effect of labor market exit from other risk factors, focusing on the effects of retiring at the new full retirement age of 67 compared with younger retirement. The parametric g-formula allows us to interpret causal effects, separate conditional and population-averaged effects, and adjust for intermediate confounders. Results suggest the population-averaged benefit of delaying labor market exit until age 67 (compared with younger retirement) is maintaining approximately a 10% higher cognitive function score, net of time-invariant characteristics like race/ethnicity and education and accounting for the bidirectional association between retirement and time-varying confounders like alcohol consumption and exercise. The effect holds in the short-term (age 62 to 67), but also beyond age 67 until at least age 75. This operates not through boosting cognitive function, but by slowing decline. This work makes progress in understanding the association between labor market exit and cognitive function by using innovative models that better reflect the empirical reality of interconnected life-course processes.

Authors

• Jo Mhairi Hale, University of St Andrews

• Maarten Jacob Bijlsma, Max Planck Institute for Demographic Research

• Angelo Lorenti, Max Planck Institute for Demographic Research