Natural Pattern of Cognitive Aging

Jan S. Novotný, Juan P. Gonzalez-Rivas, Maria Vassilaki, Janina Krell-Roesch, Yonas Endale Geda, Gorazd B. Stokin

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Considering the world's rapidly increasing life expectancy, with people working and maintaining active lifestyles longer than ever before, addressing the effects of aging on cognition is of utmost importance. A greater understanding of cognitive aging may also be critical in distinguishing natural cognitive aging from pre-clinical stages of Alzheimer's disease and related cognitive disorders. Objective: To systematically examine the association between aging and cognitive performance in a cognitively and otherwise healthy probability population-based sample using a computer-based method. Methods: This cross-sectional study enrolled 673 cognitively and otherwise healthy participants aged 25-89 years (mean age 52.3±14.2 years, 52.5% of whom were female) from the Kardiovize study cohort. Mild cognitive impairment and dementia cases were excluded, followed by measurement of cognitive performance with the computer-administered Cogstate Brief Battery. We used ANCOVA and Modified Signed-Likelihood Ratio tests to examine patterns of cognition across age groups. Results: We found a gradual decrease in cognitive performance across the lifespan, which required two decades to demonstrate significant changes. In contrast to attention and learning, psychomotor speed and working memory showed the most significant age-related decrease and variability in performance. The established pattern of cognitive aging was not altered by sex or education. Conclusion: These findings corroborate, validate, and extend the current understanding of natural cognitive aging and pinpoint specific cognitive domains with the most extensive age-related interindividual differences. This will contribute to the development of strategies to preserve cognition with aging and may also serve to improve early diagnostics of cognitive disorders using computer-based methods.

Original languageEnglish (US)
Pages (from-to)1147-1155
Number of pages9
JournalJournal of Alzheimer's Disease
Volume88
Issue number3
DOIs
StatePublished - 2022

Keywords

  • Aging
  • Alzheimer's disease
  • cognition
  • physiology
  • pre-clinical diagnostics

ASJC Scopus subject areas

  • Neuroscience(all)
  • Clinical Psychology
  • Geriatrics and Gerontology
  • Psychiatry and Mental health

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