Integrating Characteristics of Executive Functions in Non-Demented Aging: Structure, Trajectories, Classification, and Biomarker Predictors

Abstract

In aging, executive function (EF) performance (level) and change (trajectory) are linked to multiple interacting risk factors. Structurally, EFs have previously been represented as either a unitary (e.g., unidimensional) or diverse (e.g., multidimensional) set of abilities that change across the lifespan. With EF trajectory data from the Victoria Longitudinal Study (VLS), we investigated four key characteristics of EF change and variability in non-demented aging: trajectories, classification, structure, and biomarker predictors. The source sample characteristics included: N = 914; baseline M age = 71.91 (SD = 9.18, range = 53.24 – 100.16); % female = 66.2; M education (years) = 15.09. In two sequential studies, longitudinal analyses were conducted on three waves spanning over a 40-year band of aging (53-95). Study 1 investigated EF trajectory distributions, classification of subgroups based on level and slope, and biomarker risk predictors that discriminated these groups. Study 2 investigated subgroups associated with different structural characteristics (e.g., factor solutions) and biomarker risk predictors that discriminated EF subgroups of different dimensionality. For Study 1, we found the following results: (a) significant variability in EF trajectories over a 40-year band of aging; (b) relatively gradual overall EF decline; (c) two continuous quantitatively and distinct classes (higher/stable, lower/declining); (d) EF status classification was discriminated, in order of importance, by education, novel cognitive activity, BDNF polymorphism, and age. For Study 2, we found (a) individual differences within a two-factor EF solution characterized by two classes (compressed EF aging/unidimensional, complex EF aging/multidimensional); (b) EF dimensionality was discriminated, in order of importance, by age, novel cognitive activity, education, body mass index, pulse pressure, sex, balance, and physical activity. Clinical interventions that aim to promote functional maintenance and delay cognitive decline may benefit by identifying factors that affect not only EF performance and structure, but also individualized trajectory patterns in late life.