# Education and cognitive resilience: what is the role of education characteristics in shaping an ability to maintain high levels of cognitive functioning after the onset of disease > **NIH NIH F31** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2022 · $17,947 ## Abstract Project Summary Incident stroke is often accompanied by acute deficits and declines in cognitive ability as well as long- term acceleration of cognitive decline. These resulting impairments and dementia drastically affect quality of life, and patients with dementia after stroke are at increased risk of death and disability. Education has been consistently identified as a predictor of cognition after stroke, but mechanisms behind this relationship are not fully understood. One hypothesis considers cognitive resilience, suggesting that education provides individuals with cognitive tools to maintain cognitive functioning amidst a clinically meaningful amount of neurodegeneration or injury. However, studies of this relationship are hindered by a lack of universally accepted definitions of cognitive resilience. Furthermore, some studies suggest that the commonly used measure of attained education may not capture variation in cognition as well as alternative measures such as educational quality and literacy. The relationship between stroke and dementia has the potential to be used to study cognitive resilience and reserve, a critical issue in cognitive aging research. By using stroke as a well-defined and clearly diagnosed disease with a known time of event onset, studies can be conducted to assess for differences between educational subgroups and to differentiate between normal-age related decline and disease-related pathological processes. Therefore, this proposal aims to investigate the influence of educational characteristics on cognitive resilience after stroke. Cognitive resilience will be conceptualized in three distinct ways: cognitive decline in years following stroke (Aim 1), risk of dementia in patients with history of stroke (Aim 2), and cognitive testing performance in relation to imaging markers of vascular injury (Aim 3). Analyses will use existing data, with education measured as self-reported years attained from study participants and state-, year-, and race- specific measures of educational quality characteristics of average term length, student-to-teacher ratio, and attendance ratio from historical data from the National Center for Education Statistics. Aim 1 will use a nationally representative dataset to maximize variation in educational experiences with biennial follow-up surveys to assess decline after stroke, and Aims 2 and 3 will include members of a large managed care organization with detailed medical histories throughout adulthood and clinical neuropathologic imaging measures. This proposal will address the gap in understanding of mechanisms behind the influence of education on cognitive resilience after stroke. Knowledge from this research will directly address the NIA’s mission of clarifying understanding of cognitive resilience and reserve, and the priority of understanding determinants of cognitive aging. The proposed training, guided by an exemplary mentorship team of experts, will enhance the applicants research com... ## Key facts - **NIH application ID:** 10417178 - **Project number:** 5F31AG062114-03 - **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO - **Principal Investigator:** Chloe W Eng - **Activity code:** F31 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $17,947 - **Award type:** 5 - **Project period:** 2020-06-01 → 2022-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10417178 ## Citation > US National Institutes of Health, RePORTER application 10417178, Education and cognitive resilience: what is the role of education characteristics in shaping an ability to maintain high levels of cognitive functioning after the onset of disease (5F31AG062114-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10417178. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*