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Cognitive reserve, brain reserve, and cognitive performance in old age: A population‐based study
Author(s) -
Li Yuanjing,
Wang Xiang,
Hou Tingting,
Song Lin,
Wang Mingqi,
Zhang Jingwen,
Ren Yifei,
Shi Lin,
Wang Yongxiang,
Du Yifeng,
Qiu Chengxuan
Publication year - 2020
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1002/alz.040271
Subject(s) - cognitive reserve , cognition , effects of sleep deprivation on cognitive performance , hyperintensity , population , cognitive decline , medicine , brain size , psychology , dementia , magnetic resonance imaging , cognitive impairment , psychiatry , radiology , environmental health , disease
Background The reserve theory has been proposed to account for the discrepancies between the load of brain pathologies and cognitive phenotypes in aging. We sought to explore the interplay of cognitive reserve and markers of brain reserve and brain lesions in determining cognitive performance in old age. Methods This population‐based cross‐sectional study included 215 people (age ≥65 years; 43.7% women; 28.4% illiterate) who were living in the rural communities of Yanggu County, Shandong Province, China. We used the Mini‐Mental State Examination to assess global cognitive function. We evaluated markers of brain reserve and brain lesions from the structural MRI scans, i.e., total intracranial volumes (ICV), deep white‐matter hyperintensity (DWMH) volumes, and cerebral microbleeds (CMBs). We used the structural equation modeling to generate a composite score of cognitive reserve capacity from multiple cognitive‐enhancing factors over the lifespan. We used the general linear regression model and the marginal effect model to disentangle the relations of cognitive reserve and brain reserve markers with MMSE score. Results The composite cognitive reserve score ranged from 6.80 to 16.55. Overall, a higher cognitive reserve score was associated with multiple‐adjusted β‐coefficient of 0.04 (95% CI 0.03−0.76) for MMSE score. There was a stronger relationship between cognitive reserve score and MMSE score in people with lower ICV (β=1.16; 95% CI 0.99−2.24) than in those with larger ICV (β=0.44; ‐0.01−0.89, p=0.053). Furthermore, the association of cognitive reserve score with MMSE score was statistically significant in people with severe DWMH load (β=0.84; 95% CI 0.22−1.45) and CMBs (β=1.50; 0.60−2.40), but not in those with mild DWMH load or without CMBs. Compared to people with a higher cognitive reserve score, those with lower cognitive reserve capacity showed stronger correlations of MMSE score with ICV (β=2.66; 95% CI 0.08−5.25) and presence of CMBs (β=‐0.24; ‐0.43−‐0.04). Conclusion Higher cognitive reserve is associated with better cognitive performance among rural‐dwelling older adults with limited education, and such association is stronger in people with lower brain reserve. In addition, lower brain reserve is associated with poorer cognitive performance, and such association is stronger among people with lower cognitive reserve capacity.