Abstract
BackgroundCognitive reserve is most commonly measured using socio-behavioural proxy variables. These variables are easy to collect, have a straightforward interpretation, and are widely associated with reduced risk of dementia and cognitive decline in epidemiological studies. However, the specific proxies vary across studies and have rarely been assessed in complete models of cognitive reserve (i.e. alongside both a measure of cognitive outcome and a measure of brain structure). Complete models can test independent associations between proxies and cognitive function in addition to the moderation effect of proxies on the brain-cognition relationship. Consequently, there is insufficient empirical evidence guiding the choice of proxy measures of cognitive reserve and poor comparability across studies.MethodIn a cross-sectional study, we assessed the validity of 5 common proxies (education, occupational complexity, verbal intelligence, leisure activities, and exercise) and all possible combinations of these proxies in 2 separate community-dwelling older adult cohorts: The Irish Longitudinal Study on Ageing (TILDA; N = 313, mean age = 68.9 years, range = 54–88) and the Cognitive Reserve/Reference Ability Neural Network Study (CR/RANN; N = 234, mean age = 64.49 years, range = 50–80). Fifteen models were created with 3 brain structure variables (grey matter volume, hippocampal volume, and mean cortical thickness) and 5 cognitive variables (verbal fluency, processing speed, executive function, episodic memory, and global cognition).ResultsNo moderation effects were observed. There were robust positive associations with cognitive function, independent of brain structure, for 2 individual proxies (verbal intelligence and education) and 16 composites (i.e. combinations of proxies). Verbal intelligence was statistically significant in all models. Education was significant only in models with executive function as the cognitive outcome variable. Three robust composites were observed in more than two-thirds of brain-cognition models: the composites of (1) occupational complexity and verbal intelligence, (2) education and verbal intelligence, and (3) education, occupational complexity, and verbal intelligence. However, no composite had larger average effects nor was more robust than verbal intelligence alone.ConclusionThese results support the use of verbal intelligence as a proxy measure of CR in cross-sectional studies of cognitively healthy older adults.
Highlights
Cognitive reserve is most commonly measured using socio-behavioural proxy variables
While education has been previously positively associated with executive function, without accounting for brain structure, in cognitively healthy older adults [108] and in a systematic review [50], our results show that this association is independent of grey matter (GM) volume, hippocampal volume, or mean cortical thickness
Our results do not support the use of physical activity as an individual cognitive reserve (CR) proxy. While this proxy has been previously associated with cognitive function in older adults without controlling for brain structure [106, 126], our results show that these associations are not independent of GM volume, hippocampal volume, or mean cortical thickness
Summary
Cognitive reserve is most commonly measured using socio-behavioural proxy variables. These variables are easy to collect, have a straightforward interpretation, and are widely associated with reduced risk of dementia and cognitive decline in epidemiological studies. Neuropathology and measures of brain structure do not fully explain cognitive decline [1] nor age-related variation in cognitive function [2]. This is evident in the finding of normal cognitive function in individuals who meet the diagnostic criteria for Alzheimer’s disease (AD) based on neuropathology [3, 4]. This well-established gap between brain and cognition may be explained by cognitive reserve (CR), wherein the effects of brain pathology or ageing on cognitive function are moderated by an individual’s ability to efficiently or flexibly use the brain’s resources to cope with task demands [5]. Socio-behavioural variables reflecting the degree of exposure to, or engagement in, various lifetime experiences are often used as proxies of CR [8]
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