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Assessing the Impact of Education and Cardiovascular Disease Risk Factors on Cognitive Trajectories in Older Adults

Maritza Dowling, University of Wisconsin-Madison 
*Shelley Han Liu, Harvard School of Public Health 

Keywords: Mental Health, Growth Mixture Models, Propensity Scores

Data from a large prospective longitudinal study was used to estimate propensity scores (PS) of dementia risk for older adults clinically diagnosed as cognitively normal at baseline. PS were estimated as a function of age, education, gender, APOEe4, blood pressure, diabetes, BMI, physical activity, smoking, and depression. PS, estimated by maximum likelihood logistic regression, and demographic factors were further modeled as predictors of a composite score measuring global cognition. Growth mixture models were used to estimate latent classes with distinct cognitive trajectories over time. Two latent classes emerged for global cognition - one with a subtle decline and one with a faster decline over time. Older age, higher propensity scores, and gender were significantly associated with group membership in the faster decline group; while higher education level was associated with membership in the class with subtle decline. The study provides support for the protective role of education in mitigating cognitive decline for a group with a favorable cardiovascular disease (CVD) risk profile. Level of education, however, did not protect the latent group with a higher prevalence of CVD.