Keywords
cognitive aging
verbal fluency
visual memory
healthy aging
intellectual activity
lifestyle factors
older adults
neuropsychological assessment
How to Cite
Abstract
Background. Population aging has intensified interest in identifying modifiable factors that promote successful cognitive aging and reduce the risk of age-related cognitive decline. The concept of cognitive reserve suggests that lifelong educational attainment, occupational complexity, intellectual engagement, social participation, and health-related behaviors enhance the brain’s capacity to compensate for age-related neuropathological changes. Although educational and occupational factors have been extensively investigated, considerably less is known about the relative contribution of everyday lifestyle characteristics—including reading habits, social environment, pet ownership, and health-monitoring behaviors—to specific domains of cognitive functioning in later life. Understanding these multidimensional determinants is essential for developing effective preventive interventions aimed at preserving cognitive health among older adults.
Objective. This study aimed to identify social-behavioral, educational, and somatic predictors of cognitive performance in older adults, with particular emphasis on verbal fluency and visual memory, and to examine the latent multidimensional structure of cognitive reserve.
Methods. A cross-sectional study included 73 community-dwelling adults aged 60–80 years, comprising participants enrolled in the University of the Third Age and individuals not engaged in continuing education programs. Cognitive functioning was assessed using standardized neuropsychological measures of verbal fluency and face-recognition memory. Additional measures included demographic characteristics, educational attainment, occupational history, intellectual activity, social engagement, lifestyle behaviors, and health-related indicators obtained through a structured questionnaire. Exploratory factor analysis (principal axis factoring with oblimin rotation) was conducted to identify latent dimensions of cognitive reserve. Multiple linear regression analyses were performed to determine independent predictors of verbal fluency and visual memory.
Results. Exploratory factor analysis identified three relatively independent dimensions of cognitive reserve: somatic health, intellectual activity, and the educational-professional component. Verbal fluency was positively predicted by the annual number of books read (β = 0.305, p = .008) and pet ownership (β = 2.62, p = .020), whereas widowhood was associated with lower verbal fluency (β = –2.82, p = .013). Visual memory performance was positively associated with regular blood pressure monitoring (β = 0.458, p = .018) and longer professional engagement (β = 0.058, p = .017), while larger social network size demonstrated an unexpected negative association (β = –0.031, p = .033). These findings indicate that different cognitive domains are influenced by distinct combinations of behavioral, social, educational, and health-related factors rather than by a single global cognitive reserve mechanism.
Conclusions. Cognitive reserve appears to represent a multidimensional and functionally differentiated construct integrating intellectual engagement, educational and occupational experience, and health-related behaviors. The findings suggest that cognitive functioning in older adulthood may be supported through modifiable lifestyle factors, including sustained reading activity, prolonged professional engagement, maintenance of meaningful social relationships, and proactive health monitoring. These results contribute to the growing body of evidence supporting multidomain interventions for healthy cognitive aging and provide empirical guidance for designing prevention programs targeting cognitive decline in older populations.
Keywords: cognitive reserve; cognitive aging; verbal fluency; visual memory; healthy aging; intellectual activity; lifestyle factors; older adults; neuropsychological assessment.
Received: February 13, 2026
Accepted: April 21, 2026
Published: April 30, 2026
References
Bassuk, S. S., Glass, T. A., & Berkman, L. F. (1999). Social disengagement and incident cognitive decline in community-dwelling elderly persons. Annals of Internal Medicine, 131(3), 165–173. https://doi.org/10.7326/0003-4819-131-3-199908030-00002
Benton, A. L., Sivan, A. B., Hamsher, K., Varney, N., & Spreen, O. (1983). Contributions to neuropsychological assessment: A clinical manual. Oxford University Press.
Cabeza, R., Albert, M., Belleville, S., Craik, F. I. M., Duarte, A., Grady, C. L., ... & Rajah, M. N. (2018). Maintenance, reserve and compensation: The cognitive neuroscience of healthy ageing. Nature Reviews Neuroscience, 19(11), 701–710. https://doi.org/10.1038/s41583-018-0068-2
Chan, D., Shafto, M., Kievit, R., Matthews, F. E., Spink, M., Valenzuela, M., ... & Henson, R. N. (2018). Lifestyle activities in mid-life contribute to cognitive reserve in late-life, independent of education, occupation, and late-life activities. Neurobiology of Aging, 70, 180–183. https://doi.org/10.1016/j.neurobiolaging.2018.06.012
Formosa, M. (2014). Four decades of Universities of the Third Age: past, present, future. Ageing & Society, 34(1), 42–66. https://doi.org/10.1017/S0144686X12000797
Katzman, R., Terry, R., DeTeresa, R., Brown, T., Davies, P., Fuld, P., Renbing, X., & Peck, A. (1988). Clinical, pathological, and neurochemical changes in dementia: A subgroup with preserved mental status and numerous neocortical plaques. Annals of Neurology, 23(2), 138–144. https://doi.org/10.1002/ana.410230206
Launer, L. J., Ross, G. W., Petrovitch, H., et al. (2000). Midlife blood pressure and dementia: the Honolulu-Asia aging study. Neurobiology of Aging, 21(1), 49–55. https://doi.org/10.1016/S0197-4580(00)00096-8
Lezak, M. D., Howieson, D. B., Bigler, E. D., & Tranel, D. (2012). Neuropsychological assessment (5th ed.). Oxford University Press.
Lewin, C., & Herlitz, A. (2002). Sex differences in face recognition – women's faces make the difference. Brain and Cognition, 50(1), 121–128. https://doi.org/10.1016/S0278-2626(02)00016-7
Mondini, S., Pucci, V., Pastore, M. et al. s-CRIq: the online short version of the Cognitive Reserve Index Questionnaire. Aging Clin Exp Res 35, 2903–2910 (2023). https://doi.org/10.1007/s40520-023-02561-1
Nucci, M., Mapelli, D., & Mondini, S. (2012). Cognitive Reserve Index questionnaire (CRIq): a new instrument for measuring cognitive reserve. Aging Clinical and Experimental Research, 24(3), 218–226. https://doi.org/10.3275/7636
Opdebeeck, C., Martyr, A., & Clare, L. (2016). Cognitive reserve and cognitive function in healthy older people: A meta-analysis. Aging, Neuropsychology, and Cognition, 23(1), 40–60. https://doi.org/10.1080/13825585.2015.1041450
Stern, Y. (2002). What is cognitive reserve? Theory and research application of the reserve concept. Journal of the International Neuropsychological Society, 8(3), 448–460. https://doi.org/10.1017/S1355617702813248
Stern, Y. (2009). Cognitive reserve. Neuropsychologia, 47(10), 2015–2028. https://doi.org/10.1016/j.neuropsychologia.2009.03.004
Stern, Y., Arenaza-Urquijo, E. M., Bartrés-Faz, D., et al. (2019). Whitepaper: Defining and investigating cognitive reserve, brain reserve, and brain maintenance. Alzheimer's & Dementia, 16(9), 1305–1311. https://doi.org/10.1016/j.jalz.2018.07.219
Wilson, R. S., Mendes De Leon, C. F., Barnes, L. L., et al. (2002). Participation in cognitively stimulating activities and risk of incident Alzheimer disease. JAMA, 287(6), 742–748. https://doi.org/10.1001/jama.287.6.742
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright (c) 2026 Oleksandra Sayenko