Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Feb 17;76(3):596-606.
doi: 10.1093/geronb/gbaa083.

Sex, Race, and Age Differences in Prevalence of Dementia in Medicare Claims and Survey Data

Affiliations

Sex, Race, and Age Differences in Prevalence of Dementia in Medicare Claims and Survey Data

Yingying Zhu et al. J Gerontol B Psychol Sci Soc Sci. .

Abstract

Objectives: This study provides the first comparison of trends in dementia prevalence in the U.S. population using 3 different dementia ascertainments/data sources: neuropsychological assessment, cognitive tests, and diagnosis codes from Medicare claims.

Methods: We used data from the nationally representative Health and Retirement Study and Aging, Demographics, and Memory Study, and a 20% random sample of Medicare beneficiaries. We compared dementia prevalence across the 3 sources by race, gender, and age. We estimated trends in dementia prevalence from 2006 to 2013 based on cognitive tests and diagnosis codes utilizing logistic regression.

Results: Dementia prevalence among older adults aged 70 and older in 2004 was 16.6% (neuropsychological assessment), 15.8% (cognitive tests), and 12.2% (diagnosis codes). The difference between dementia prevalence based on cognitive tests and diagnosis codes diminished in 2012 (12.4% and 12.9%, respectively), driven by decreasing rates of cognitive test-based and increasing diagnosis codes-based dementia prevalence. This difference in dementia prevalence between the 2 sources by sex and for age groups 75-79 and 90 and older vanished over time. However, there remained substantial differences across measures in dementia prevalence among blacks and Hispanics (10.9 and 9.8 percentage points, respectively) in 2012.

Discussion: Our results imply that ascertainment of dementia through diagnosis may be improving over time, but gaps across measures among racial/ethnic minorities highlight the need for improved measurement of dementia prevalence in these populations.

Keywords: Cognitive tests; Diagnosis codes; Neuropsychological assessment; Racial/ethnic minorities; Trends.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
Dementia prevalence for the U.S. population and by race, gender, and age in neuropsychological assessment (ADAMS), cognitive tests (HRS), and diagnosis codes (Medicare claims), aged 70 and older, 2004 with 95% confidence intervals. ADAMS = the Aging, Demographics, and Memory Study; HRS = Health and Retirement Study; Claims = Medicare claims. Values in ADAMS are weighted by the ADAMS sampling weights. Values in HRS are weighted by the HRS sampling weights.
Figure 2.
Figure 2.
Predicted values of dementia prevalence based on cognitive tests (HRS) and diagnosis codes (claims) from logistic models adjusting for race, sex, age group, and wave in HRS and claims, aged 67 and older, 2006 and 2012. HRS = Health and Retirement Study; Claims = Medicare claims; predicted values of dementia prevalence in HRS are weighted by the HRS sampling weights; 95% confidence intervals (CIs) are included in the figure and 95% CI adjusted by Bonferroni correction.
Figure 3.
Figure 3.
Dementia prevalence by sex (A), age (B), and race (C) based on cognitive tests (HRS) and diagnosis codes (claims) from logistic models adjusting for race, sex, age group, and wave in HRS and claims, aged 67 and older, 2006 and 2012. (A) Dementia prevalence by sex, 2006 and 2012; (B) dementia prevalence by age, 2006 and 2012; and (C) dementia prevalence by race, 2006 and 2012. HRS = Health and Retirement Study; Claims = Medicare claims; predicted values of dementia prevalence in HRS are weighted by the HRS sampling weights; 95% confidence intervals (CIs) are included in the figure and 95% CI adjusted by Bonferroni correction.

Similar articles

Cited by

References

    1. Amjad, H., Roth, D. L., Sheehan, O. C., Lyketsos, C. G., Wolff, J. L., & Samus, Q. M (2018). Underdiagnosis of dementia: An observational study of patterns in diagnosis and awareness in US older adults. Journal of General Internal Medicine, 33(7), 1131–1138. doi:10.1007/s11606-018-4377-y - DOI - PMC - PubMed
    1. Blessed, G., Tomlinson, B. E., & Roth, M (1968). The association between quantitative measures of dementia and of senile change in the cerebral grey matter of elderly subjects. The British Journal of Psychiatry, 114(512), 797–811. doi:10.1192/bjp.114.512.797 - DOI - PubMed
    1. Bradford, A., Kunik, M. E., Schulz, P., Williams, S. P., & Singh, H (2009). Missed and delayed diagnosis of dementia in primary care: Prevalence and contributing factors. Alzheimer Disease and Associated Disorders, 23(4), 306–314. doi:10.1097/WAD.0b013e3181a6bebc - DOI - PMC - PubMed
    1. Brandt, J., Spencer, M., & Folstein, M (1988). The telephone interview for cognitive status. Neuropsychiatry, Neuropsychology and Behavioral Neurology, 1(2), 111–117. https://journals.lww.com/cogbehavneurol/Abstract/1988/00120/The_Telephon...
    1. Brookmeyer, R., Evans, D. A., Hebert, L., Langa, K. M., Heeringa, S. G., Plassman, B. L., & Kukull, W. A (2011). National estimates of the prevalence of Alzheimer’s disease in the United States. Alzheimer’s & Dementia, 7(1), 61–73. doi:10.1016/j.jalz.2010.11.007 - DOI - PMC - PubMed

Publication types

MeSH terms