Christine E Walsh1, Yang C Yang2, Katsuya Oi3, Allison Aiello4, Daniel Belsky5, Kathleen Mullan Harris6, Brenda L Plassman7. 1. Department of Health, Behavior, Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. 2. Department of Sociology, Lineberger Cancer Center, and Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. 3. Department of Sociology, Northern Arizona University, Flagstaff, Arizona, USA. 4. Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. 5. Department of Epidemiology, Mailman School of Public Health, Columbia University, New York City, New York, USA. 6. Department of Sociology, Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. 7. Department of Psychiatry and Behavioral Science, Duke University, Durham, North Carolina, USA.
Abstract
OBJECTIVES: To better understand the temporal dynamics of progression from cognitive decline to onset of dementia in the dementia-free older population in the United States. METHODS: We used longitudinal data from a diverse national population-based sample of older adults (N = 531) in the Aging, Demographics, and Memory Study from the Health and Retirement Study with repeated measures of cognitive function and dementia diagnosis during 12 years of follow-up from 1996 to 2009. We employed joint latent class mixed models to estimate the association between cognitive change and competing risks of dementia and nondementia death and identify heterogeneity in the age profiles of such association adjusting for baseline characteristics. RESULTS: Our analyses found 3 latent classes with distinct age profiles of cognitive decline and associated risk of dementia and mortality: "Rapid Cognitive Decline" (19.6%), "Moderate Progression" (44.6%), and "Optimal Cognitive Aging" (35.8%). When simultaneously accounting for cognitive trajectories and time-to-dementia/death, we also found associations of baseline covariates with slope of cognitive decline (e.g., steeper decline among non-Hispanic Blacks and more educated) and risk of dementia (e.g., greater risk for females and apolipoprotein E-4 carriers, but no difference by education level) that differ substantially from those in separate longitudinal mixed models or survival models. DISCUSSION: The differential age patterns of cognitive decline predicting dementia incidences identified in this study suggest variation in the course of cognitive aging in older adults that may inform future etiological and intervention studies.
OBJECTIVES: To better understand the temporal dynamics of progression from cognitive decline to onset of dementia in the dementia-free older population in the United States. METHODS: We used longitudinal data from a diverse national population-based sample of older adults (N = 531) in the Aging, Demographics, and Memory Study from the Health and Retirement Study with repeated measures of cognitive function and dementia diagnosis during 12 years of follow-up from 1996 to 2009. We employed joint latent class mixed models to estimate the association between cognitive change and competing risks of dementia and nondementia death and identify heterogeneity in the age profiles of such association adjusting for baseline characteristics. RESULTS: Our analyses found 3 latent classes with distinct age profiles of cognitive decline and associated risk of dementia and mortality: "Rapid Cognitive Decline" (19.6%), "Moderate Progression" (44.6%), and "Optimal Cognitive Aging" (35.8%). When simultaneously accounting for cognitive trajectories and time-to-dementia/death, we also found associations of baseline covariates with slope of cognitive decline (e.g., steeper decline among non-Hispanic Blacks and more educated) and risk of dementia (e.g., greater risk for females and apolipoprotein E-4 carriers, but no difference by education level) that differ substantially from those in separate longitudinal mixed models or survival models. DISCUSSION: The differential age patterns of cognitive decline predicting dementia incidences identified in this study suggest variation in the course of cognitive aging in older adults that may inform future etiological and intervention studies.
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