Who has undiagnosed dementia? A cross-sectional analysis of participants of the Aging, Demographics and Memory Study

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Abstract

Background: delays in diagnosing dementia may lead to suboptimal care, yet around half of those with dementia are undiagnosed. Any strategy for case finding should be informed by understanding the characteristics of the undiagnosed population. We used cross-sectional data from a population-based sample with dementia aged 71 years and older in the United States to describe the undiagnosed population and identify factors associated with non-diagnosis.

Methods: the Aging, Demographics and Memory Study (ADAMS) Wave A participants (N = 856) each underwent a detailed neuropsychiatric investigation. Informants were asked whether the participant had ever received a doctor's diagnosis of dementia. We used multiple logistic regression to identify factors associated with informant report of a prior dementia diagnosis among those with a study diagnosis of dementia.

Results: of those with a study diagnosis of dementia (n = 307), a prior diagnosis of dementia was reported by 121 informants (weighted proportion = 42%). Prior diagnosis was associated with greater clinical dementia rating (CDR), from 26% (CDR = 1) to 83% (CDR = 5). In multivariate analysis, those aged 90 years or older were less likely to be diagnosed (P = 0.008), but prior diagnosis was more common among married women (P = 0.038) and those who had spent more than 9 years in full-time education (P = 0.043).

Conclusions: people with dementia who are undiagnosed are older, have fewer years in education, are more likely to be unmarried, male and have less severe dementia than those with a diagnosis. Policymakers and clinicians should be mindful of the variation in diagnosis rates among subgroups of the population with dementia.
Original languageEnglish
Pages (from-to)642-647
Number of pages6
JournalAge and Ageing
Volume44
Issue number4
Early online date29 Mar 2015
DOIs
Publication statusPublished - 2015

Keywords

  • frailty
  • ageing
  • risk stratification
  • care planning
  • older people

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