Occupation-related differences in cognitive aging: Comparative effects of job type, skill level, and education

Stephen Aichele, Antony Payton, Andrew C. Robinson and Patrick Rabbitt

Intelligence, 2024, vol. 107, issue C

Abstract: A century of psychometric research has shown that intelligence is robustly associated with occupational status. Despite a rapidly aging global workforce, occupational differences in cognitive decline remain under-investigated. In a large sample of middle-aged and older adults (N = 5542; age 41–97 years; 70.6 % female), we compared age-based trajectories of general fluid cognition across occupational groups (categorized both by specialization area and skill level). Occupational grouping accounted for 18.6 % of variability in baseline cognitive performance and 3.9 % of variability in rates of decline. Cognitive differences across occupational groups generally followed a skill gradient. These differences were largely retained with increasing age—although between-group variability in rates of decline were also present. Moreover, occupation-cognition associations remained significant after adjustment for education (occupation contributed an additional 5.9 % and 1.8 % to explained variation in baseline cognitive performance and decline in performance, respectively). Having more hobbies in later life accounted for an additional 2.7 % and 1.2 % in explained variation for baseline differences and declines in cognition, respectively. These associations were minimally affected by further adjustment for sociodemographic and lifestyle covariates, including retirement status. The marked contrast between the cognitive trajectories of academic professionals vs. those of other occupational groups suggests that long-term immersive intellectual engagement may provide tangible benefits for cognitive aging.

Keywords: Work; Fluid cognition, intelligence; Longitudinal; Aging; Flynn effect; Occupation sorting (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intell:v:107:y:2024:i:c:s0160289624000710

DOI: 10.1016/j.intell.2024.101877

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