Identifying latent classes of longitudinal change in picture naming in a population-based sample

Abstract

Although cognitive changes may not become apparent until after age 65, many factors associated with late-life decline are already well-established in midlife. In particular, deficits in picture naming have been associated with early and accelerated cognitive change. A measure of picture vocabulary, requiring participants to name drawings of objects, was collected in 4 waves (each separated by 2 years) of the Understanding America Study, a nationally representative internet panel (mean follow-up = 5.60 years). Participants were 5005 adults ranging in age from 18 to 98 at intake (mean = 48.81); 58% women. Growth mixture models were used to identify latent class structure in age-based quadratic growth models (centered at median age of 53). The best-fitting model identified 3 classes: high intercept and scores increase with age (60% of the sample), medium intercept and scores increase with age (37%), low intercept and no change with age (3%). Analyses of variance indicated that the class for which picture naming did not change with age had a significantly elevated probability of cognitive impairment. Multinomial logistic regression indicated that probability of cognitive impairment contributed to estimation of class membership even in the context of related demographic and cognitive variables. Tasks like Picture Vocabulary may be useful early indicators of onset of cognitive impairment.