Background The socioeconomic gradient in relation to physical and cognitive health has been already documented. However, substantial gaps remain in understanding the potential mediating pathways linking socioeconomic disparities to late-life cognitive health. We assessed the socioeconomic differentials and the biopsychosocial mechanisms associated with the late-life cognition in a representative subsample of the English population.

Methods Participants were 1,273 ELSA core members, aged 65 and older at the time of recruitment, from the Harmonised Cognitive Assessment Protocol (HCAP) a sub-study of from the English Longitudinal Study of Ageing (ELSA) completed in April 2018. The respondent interview incorporated an assessment of a broad range of cognitive domains (memory, language, executive function, psychomotor speed, and problem-solving) and complemented well the existing longitudinal data on health, cognition, biomarkers, genetics, lifestyle, health-care utilisation, and economic resources across 16 years of follow-up. We used structural equation modelling to estimate direct and indirect pathways between education (low, medium, high) and wealth (tertiles) as markers of SES, Apolipoprotein E (APOE) status, inflammatory markers (serum fibrinogen and C-reactive protein [CRP]), chronic conditions, measured in 2010 in relation to depressive symptoms (≥4 on the Center for Epidemiologic Studies Depression Scale) and the overall latent factor of cognitive performance based on multiple domains measured in 2018.

Results Our findings suggest that medium (β=2.15, standard error (SE=0.35), p≤0.001) and higher levels (β=3.33, SE=0.59, p≤0.001) of education were linked with a higher overall cognitive score in later life, while increased levels of wealth did not. Depressive symptomatology was interlinked with lower cognitive health( β=-1.01, SE=0.25, p≤0.001), while APOEe4 and inflammatory markers were not directly associated with the overall cognitive factor. However, the overall inflammation was indirectly associated with overall cognition in later life, via a positive association with chronic conditions (β=0.39, SE=0.19, p=0.042), and depressive symptoms (β=0.08, SE=0.03, p=0.020).

Conclusion We found that education and specific psychosocial risk factors were directly associated with late-life cognition. In contrast, biological factors such as overall inflammation contributed indirectly via the development of chronic conditions and depressive symptoms. These findings support evidence for the psychosocial paradigm, which may be able to explain how life gets under the skin, influencing both physical and cognitive health in later life; indicating the imperative need to reduce socioeconomic inequalities.