Longitudinal associations of anticholinergic medications on cognition and possible mitigating role of physical activity.

BACKGROUND: Many older adults take at least one prescription medication with anticholinergic (ACH) activity, which can impact the central nervous system and can lead to cognitive decline and impairment especially in an aging population susceptible to cognitive changes. We examined this relationship between ACH burden and cognitive function in middle-aged and older adults. We further determined if increased activity levels mitigated the relationships between ACH burden and cognition. METHODS: Data from The Reasons for Geographic and Racial Differences in Stroke project were used. We included 20,575 adults aged ≥45 years with longitudinal cognitive testing. The anticholinergic cognitive burden (ACB) scale was used to assess for ACH use and overall burden. Cognitive data included an overall composite score, a memory, and verbal fluency composites. Mixed effects models were conducted to determine if cognitive function worsened over time for participants with higher ACB (>3) scores. The full model adjusted for age, sex, race, education, diabetes, hypertension, cardiovascular disease, congestive heart failure, and dyslipidemia, self-reported physical activity (PA) and depressive symptoms. RESULTS: A significant relationship between ACH burden and composite cognitive scores was found (p = <0.001), with those with higher ACB showing more rapid cognitive decline over time. There was an effect of age for participants with higher ACB (>3) scores and ACB as a continuous variable. Baseline PA level was associated with less cognitive decline over time and this effect was greater in older cohorts. CONCLUSIONS: We observed an effect of ACHs on cognition in adults ≥45 years old that worsened with age. ACH users showed more cognitive effects, whereas PA emerged as a possible mitigating factor.

Validity of the NIH toolbox cognitive battery in a healthy oldest-old 85+ sample.

OBJECTIVE: To evaluate the construct validity of the NIH Toolbox Cognitive Battery (NIH TB-CB) in the healthy oldest-old (85+ years old). METHOD: Our sample from the McKnight Brain Aging Registry consists of 179 individuals, 85 to 99 years of age, screened for memory, neurological, and psychiatric disorders. Using previous research methods on a sample of 85 + y/o adults, we conducted confirmatory factor analyses on models of NIH TB-CB and same domain standard neuropsychological measures. We hypothesized the five-factor model (Reading, Vocabulary, Memory, Working Memory, and Executive/Speed) would have the best fit, consistent with younger populations. We assessed confirmatory and discriminant validity. We also evaluated demographic and computer use predictors of NIH TB-CB composite scores. RESULTS: Findings suggest the six-factor model (Vocabulary, Reading, Memory, Working Memory, Executive, and Speed) had a better fit than alternative models. NIH TB-CB tests had good convergent and discriminant validity, though tests in the executive functioning domain had high inter-correlations with other cognitive domains. Computer use was strongly associated with higher NIH TB-CB overall and fluid cognition composite scores. CONCLUSION: The NIH TB-CB is a valid assessment for the oldest-old samples, with relatively weak validity in the domain of executive functioning. Computer use's impact on composite scores could be due to the executive demands of learning to use a tablet. Strong relationships of executive function with other cognitive domains could be due to cognitive dedifferentiation. Overall, the NIH TB-CB could be useful for testing cognition in the oldest-old and the impact of aging on cognition in older populations.

25 years of neurocognitive aging theories: What have we learned?

The past 25 years have provided a rich discovery of at least four fundamental patterns that represent structural and functional brain aging across multiple cognitive domains. Of the many potential patterns of brain aging, few are ever examined simultaneously in a given study, leading one to question their mutual exclusivity. Moreover, more studies are emerging that note failures to replicate some brain aging patterns, thereby questioning the universality and prevalence of these patterns. Although some attempts have been made to create unifying theories incorporating many of these age-related brain patterns, we propose that the field's understanding of the aging brain has been hindered due to a large number of influential models with little crosstalk between them. We briefly review these brain patterns, the influential domain-general theories of neurocognitive aging that attempt to explain them, and provide examples of recent challenges to these theories. Lastly, we elaborate on improvements that can be made to lead the field to more comprehensive and robust models of neurocognitive aging.