Profiling Cognitive Reserve Among Community-Dwelling Older Adults: A Latent Class Analysis

Abstract Cognitive reserve (CR) is a multidimensional construct shaped by education, occupation, and leisure activities, yet traditional scoring approaches obscure heterogeneity among older adults. This study applied latent class analysis (LCA) to identify distinct CR profiles and examine their clinical correlates. A cross-sectional sample of 426 community-dwelling older adults aged ≥65 years in Beijing, China, was assessed using the Cognitive Reserve Index questionnaire (CRIq). Two CR profiles emerged: Class 1, characterized by low reading and leisure engagement (51.9%), and Class 2, defined by higher educational attainment and cognitively demanding occupations (48.1%). Compared with Class 1, Class 2 participants had higher Montreal Cognitive Assessment scores (26 vs. 25, p < 0.001), fewer subjective cognitive decline symptoms (3.5 vs. 4.5, p < 0.001), and lower frailty burden (Fried phenotype score: 0 vs. 1, p = 0.006). Class 2 membership was also associated with better chewing ability (p = 0.004), higher household income (p < 0.001), and greater likelihood of being male (p = 0.007). Age was inversely associated with Class 2 membership (β=–0.060, p = 0.024). These findings reveal meaningful heterogeneity in CR within aging populations and highlight the importance of stratifying older adults by CR profiles. Identifying subgroups at risk for cognitive decline and frailty provides new opportunities for targeted interventions to promote resilience for aging.

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Publication Details

Journal
Innovation in Aging
Published
2025-12-01
DOI
https://doi.org/10.1093/geroni/igaf122.3830
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
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article

Profiling Cognitive Reserve Among Community-Dwelling Older Adults: A Latent Class Analysis

Kairong Wang, Gabriella Engström, Wanrui Wei, Heng Zhang et al.
Innovation in Aging
Dementia and Cognitive Impairment Research
article

Profiling Cognitive Reserve Among Community-Dwelling Older Adults: A Latent Class Analysis

Kairong Wang, Gabriella Engström, Wanrui Wei, Heng Zhang, Shuaifang Wei, Azita Emami, Zheng Li
article en

Abstract

Abstract Cognitive reserve (CR) is a multidimensional construct shaped by education, occupation, and leisure activities, yet traditional scoring approaches obscure heterogeneity among older adults. This study applied latent class analysis (LCA) to identify distinct CR profiles and examine their clinical correlates. A cross-sectional sample of 426 community-dwelling older adults aged ≥65 years in Beijing, China, was assessed using the Cognitive Reserve Index questionnaire (CRIq). Two CR profiles emerged: Class 1, characterized by low reading and leisure engagement (51.9%), and Class 2, defined by higher educational attainment and cognitively demanding occupations (48.1%). Compared with Class 1, Class 2 participants had higher Montreal Cognitive Assessment scores (26 vs. 25, p < 0.001), fewer subjective cognitive decline symptoms (3.5 vs. 4.5, p < 0.001), and lower frailty burden (Fried phenotype score: 0 vs. 1, p = 0.006). Class 2 membership was also associated with better chewing ability (p = 0.004), higher household income (p < 0.001), and greater likelihood of being male (p = 0.007). Age was inversely associated with Class 2 membership (β=–0.060, p = 0.024). These findings reveal meaningful heterogeneity in CR within aging populations and highlight the importance of stratifying older adults by CR profiles. Identifying subgroups at risk for cognitive decline and frailty provides new opportunities for targeted interventions to promote resilience for aging.

Innovation in AgingVol. 9(Supplement_2)
Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Peking Union Medical College Hospital (CN), Yale University (US), Florida Atlantic University (US)
No poverty
Openalex Percentile: Top 30%
Dementia and Cognitive Impairment Research
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Profiling Cognitive Reserve Among Community-Dwelling Older Adults: A Latent Class Analysis — Kairong Wang, Gabriella Engström, et al. · Innovation in Aging (2025) | TGRS Research Map | TGRS