Person:

Marden, Jessica Rachel

BACKGROUND: Although research has demonstrated that depressive symptoms predict stroke incidence, depressive symptoms are dynamic. It is unclear whether stroke risk persists if depressive symptoms remit. METHODS AND RESULTS: Health and Retirement Study participants (n=16 178, stroke free and noninstitutionalized at baseline) were interviewed biennially from 1998 to 2010. Stroke and depressive symptoms were assessed through self-report of doctors' diagnoses and a modified Center for Epidemiologic Studies - Depression scale (high was ≥3 symptoms), respectively. We examined whether depressive symptom patterns, characterized across 2 successive interviews (stable low/no, onset, remitted, or stable high depressive symptoms) predicted incident stroke (1192 events) during the subsequent 2 years. We used marginal structural Cox proportional hazards models adjusted for demographics, health behaviors, chronic conditions, and attrition. We also estimated effects stratified by age (≥65 years), race or ethnicity (non-Hispanic white, non-Hispanic black, Hispanic), and sex. Stroke hazard was elevated among participants with stable high (adjusted hazard ratio 2.14, 95% CI 1.69 to 2.71) or remitted (adjusted hazard ratio 1.66, 95% CI 1.22 to 2.26) depressive symptoms compared with participants with stable low/no depressive symptoms. Stable high depressive symptom predicted stroke among all subgroups. Remitted depressive symptoms predicted increased stroke hazard among women (adjusted hazard ratio 1.86, 95% CI 1.30 to 2.66) and non-Hispanic white participants (adjusted hazard ratio 1.66, 95% CI 1.18 to 2.33) and was marginally associated among Hispanics (adjusted hazard ratio 2.36, 95% CI 0.98 to 5.67). CONCLUSIONS:In this cohort, persistently high depressive symptoms were associated with increased stroke risk. Risk remained elevated even if depressive symptoms remitted over a 2-year period, suggesting cumulative etiologic mechanisms linking depression and stroke.

This dissertation examines the relationship between both lifecourse socioeconomic status and diabetes and memory decline and dementia using data from the Health and Retirement Study. Chapter 1 examines associations between lifecourse measures of socioeconomic status (SES) and late life memory function and decline. Memory function was modeled longitudinally from 2002-2012 and decline was modeled for the same years via growth curves. SES measures included childhood SES, high school and college education, as well as late life household income. Of our SES measures, education was the strongest predictor of level of memory function, whereas rate of decline was driven by late life income, suggesting that late life interventions focused on SES or its downstream consequences – like health behaviors – may have the potential to slow cognitive decline. Chapter 2 assesses socioeconomic status (SES) at three points in the lifecourse in order to evaluate alternative lifecourse models with respect to the association between SES and risk of dementia. We used generalized estimating equations with a logit link to model dementia probability from 2002-2012. SES measures included childhood SES, high school education, and late life household income. We found that high school completion was the strongest predictor of decreased dementia risk, consistent with either of two lifecourse models: a sensitive period in early adulthood and/or cumulative risk. Chapter 3 explores how type 2 diabetes (T2D) and blood glucose levels relate to cognitive decline, which is important for understanding the mechanisms driving higher dementia rates among individuals with T2D. Memory decline was modeled via generalized estimating equations using linear growth curves with diabetes, HbA1c, and covariates as predictors. Diabetes and higher levels of HbA1c both predicted faster memory decline after controlling for an extensive battery of potential social confounders in a large, U.S. dataset. Our results add support for a causal pathway from diabetes to risk of dementia. Blood glucose concentration may partially explain the association between diabetes and both dementia and cognitive decline, although precise biological mechanisms are still unknown.

Introduction: We hypothesized that, like apolipoprotein E (APOE), other late-onset Alzheimer's disease (LOAD) genetic susceptibility loci predict mortality. Methods: We used a weighted genetic risk score (GRS) from 21 non-APOE LOAD risk variants to predict survival in the Adult Changes in Thought and the Health and Retirement Studies. We meta-analyzed hazard ratios and examined models adjusted for cognitive performance or limited to participants with dementia. For replication, we assessed the GRS-longevity association in the Cohorts for Heart and Aging Research in Genomic Epidemiology, comparing cases surviving to age ≥90 years with controls who died between ages 55 and 80 years. Results: Higher GRS predicted mortality (hazard ratio = 1.05; 95% confidence interval: 1.00–1.10, P = .04). After adjusting for cognitive performance or restricting to participants with dementia, the relationship was attenuated and no longer significant. In case-control analysis, the GRS was associated with reduced longevity (odds ratio = 0.64; 95% confidence interval: 0.41–1.00, P = .05). Discussion Non-APOE LOAD susceptibility loci confer risk for mortality, likely through effects on dementia incidence.