Socioeconomic Status, Race/Ethnicity, and Unexpected Variation in Dementia Classification in Longitudinal Survey Data

Abstract

Abstract Objectives As dementia affects a growing number of older adults, it is important to understand its detection and progression. We identified patterns in dementia classification over time using a longitudinal, nationally representative sample of older adults. We examined the relationship between socioeconomic status and race/ethnicity, and patterns in dementia classification. Methods Data for 7,218 Medicare beneficiaries from the 2011–2017 National Health and Aging Trends Study (NHATS) were classified into five categories: consistently no dementia, consistently cognitive impairment, “typical” dementia progression, “expected” variation, and “unexpected” variation. Multivariable multinomial logistic regression assessed relative risk of dementia classification by sociodemographic and health factors. Results Among NHATS respondents, 59.5% consistently were recorded as having no dementia, 7% consistently cognitively impaired, 13% as having typical progression, 15% as having expected variation, and 5.5% as having unexpected variation. In multivariable models, compared with consistent dementia classification, less education, Medicare–Medicaid-dual enrollment, and identifying as non-Hispanic Black were associated with increased likelihood of unexpected variation (e.g., non-Hispanic Black adjusted risk ratio: 2.12, 95% CI: 1.61–2.78, p < .0001). Discussion A significant minority of individuals have unexpected patterns of dementia classification over time, particularly individuals with low socioeconomic status and identifying as non-Hispanic Black. Dementia classification uncertainty may make it challenging to activate resources (e.g., health care, caregiving) for effective disease management, underscoring the need to support persons from at-risk groups and to carefully evaluate cognitive assessment tools to ensure they are equally reliable across groups to avoid magnifying disparities.