Cognition-Mortality Associations Are More Pronounced When Estimated Jointly in Longitudinal and Time-to-Event Models

Stephen Aichele; Sezen Cekic; Patrick Rabbitt; Paolo Ghisletta

doi:10.3389/fpsyg.2021.708361

Cognition-Mortality Associations Are More Pronounced When Estimated Jointly in Longitudinal and Time-to-Event Models

Front Psychol. 2021 Aug 6:12:708361. doi: 10.3389/fpsyg.2021.708361. eCollection 2021.

Authors

Stephen Aichele^{1

2}, Sezen Cekic², Patrick Rabbitt³, Paolo Ghisletta^{2

4

5}

Affiliations

¹ Department of Human Development and Family Studies, Colorado State University, Fort Collins, CO, United States.
² Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland.
³ Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom.
⁴ Swiss National Center of Competence in Research LIVES-Overcoming Vulnerability: Life Course Perspectives, Universities of Lausanne and of Geneva, Geneva, Switzerland.
⁵ Swiss Distance University Institute, Brig, Switzerland.

Abstract

With aging populations worldwide, there is growing interest in links between cognitive decline and elevated mortality risk-and, by extension, analytic approaches to further clarify these associations. Toward this end, some researchers have compared cognitive trajectories of survivors vs. decedents while others have examined longitudinal changes in cognition as predictive of mortality risk. A two-stage modeling framework is typically used in this latter approach; however, several recent studies have used joint longitudinal-survival modeling (i.e., estimating longitudinal change in cognition conditionally on mortality risk, and vice versa). Methodological differences inherent to these approaches may influence estimates of cognitive decline and cognition-mortality associations. These effects may vary across cognitive domains insofar as changes in broad fluid and crystallized abilities are differentially sensitive to aging and mortality risk. We compared these analytic approaches as applied to data from a large-sample, repeated-measures study of older adults (N = 5,954; ages 50-87 years at assessment; 4,453 deceased at last census). Cognitive trajectories indicated worse performance in decedents and when estimated jointly with mortality risk, but this was attenuated after adjustment for health-related covariates. Better cognitive performance predicted lower mortality risk, and, importantly, cognition-mortality associations were more pronounced when estimated in joint models. Associations between mortality risk and crystallized abilities only emerged under joint estimation. This may have important implications for cognitive reserve, which posits that knowledge and skills considered well-preserved in later life (i.e., crystallized abilities) may compensate for declines in abilities more prone to neurodegeneration, such as recall memory and problem solving. Joint longitudinal-survival models thus appear to be important (and currently underutilized) for research in cognitive epidemiology.

Keywords: Bayesian; cognitive decline; joint models; lifespan; longitudinal; survival.