The effects of study design characteristics on dementia assessment: Recommendations for future epidemiologic studies

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PROJECT SUMMARY Significance: Alzheimer’s disease and related dementias (ADRD) are a major public health challenge. Epidemiologic research on ADRD relies on the diagnosis of dementia via cognitive testing and survey questions on functional limitations in daily activities (i.e difficulty bathing). However, there is wide variability in the implementation of assessments. Across 237 scientific publications on ADRD prevalence and incidence, researchers used 230 different measurement methods. Methods varied widely in the specific tests, questions, and algorithmic approaches used. This heterogeneity poses challenges, and is likely responsible for observed inconsistencies in the estimation of both prevalence and the effects of modifiable risk factors such as diabetes, a risk that will grow in importance with anticipated increases in exposure prevalence. The overarching goal of this research is to develop guidelines to improve dementia measurement in future epidemiologic studies. Specific Aims: We aim to characterize the effect of study design characteristics on the association between ADRD and individual survey questions on cognition and functional impairment. Specifically, in Aim 1, we will assess how geographic setting affects measurement in cross-national dementia research. In Aim 2, we will assess differences between dementia measurement in cross-sectional studies focused on the ascertainment of prevalent dementia and longitudinal studies focused on the ascertainment of incident dementia. Both Aims will: (1) characterize variations in the associations between specific questions administered on surveys and either cognitive functioning or dementia, and (2) quantify the impact of improvements in measurement on the association between diabetes (an established risk factor for ADRD) and cognitive functioning or dementia. Approach: For Aim 1 we will use data from the Harmonized Cognitive Assessment Protocol (HCAP) surveys in the United States, Mexico, England, South Africa, and India. We will compare the associations between each survey question with cognitive functioning, using both confirmatory factor analysis and logistic regression. We will also use logistic regression to evaluate the association between diabetes and traditional vs. improved short measures of cognitive functioning. Aim 2 will leverage rich longitudinal data from the Religious Orders Study-Memory and Aging Project (ROSMAP) studies. First, we will use logistic regression models with generalized estimating equations to assess differences in the associations between each survey question and prevalent versus incident dementia. Second, we will assess the impact of improvements to dementia algorithms for use in longitudinal time-to-event models for the association between diabetes and dementia risk. Fellowship Training: Emma Nichols is a PhD student in the Department of Epidemiology at the Johns Hopkins Bloomberg School of Public Health. Through mentored research, coursework, and professional skills development, the proposed training plan will equip Ms. Nichols with the tools and skillset required to become an innovative, independent researcher in the epidemiology of cognitive aging and dementia.