Racial and Ethnic Disparities in the Treatment of
Dementia Among Medicare Beneficiaries
Ilene H. Zuckerman, Priscilla T. Ryder, Linda Simoni-Wastila, Thomas Shaffer,
Masayo Sato, Lirong Zhao, and Bruce Stuart
Lamy Center on Drug Therapy and Aging, Department of Pharmaceutical Health Services Research,
University of Maryland School of Pharmacy, Baltimore.
Objectives. Numerous studies have documented disparities in health care utilization between non-Hispanic White and
minority elders. We investigated differences in anti-dementia medication use between non-Hispanic White and minority
community-dwelling Medicare beneficiaries with dementia.
Methods. Using multivariate analysis with generalized estimating equations, we estimated prevalence ratios (PRs) for
anti-dementia medication use by race/ethnicity for 1,120 beneficiaries with dementia from years 2001 through 2003 of
the Medicare Current Beneficiary Survey.
Results. After adjusting for demographics, socioeconomics, health care access and utilization, comorbidities, and
service year, we found that anti-dementia medication use was approximately 30% higher among non-Hispanic
Whites compared to other racial/ethnic groups (PR¼0.73, 95% confidence interval [CI]¼0.59, 0.91). As for individual
racial/ethnic groups, prevalence disparities remained significant for non-Hispanic Blacks (PR ¼ 0.75, 95% CI ¼ 0.57,
0.99) and non-Hispanic others (PR ¼ 0.50, 95% CI ¼ 0.26, 0.96) but were attenuated for Hispanics (PR ¼ 0.84, 95%
CI ¼ 0.59, 1.20).
Discussion. Results provide evidence that racial/ethnic disparities in utilization of drugs used to treat dementia exist
and are not accounted for by differences in demographic, economic, health status, or health utilization factors. Findings
provide a foundation for further research that should use larger numbers of minority patients and consider dementia type
and severity, access to specialty dementia care, and cultural factors.
Key Words: Dementia—Health disparities—Anti-dementia medication—Medicare beneficiaries.
to have poorer health status, whether measured by disease
incidence, prevalence, or severity (National Center for Health
Statistics, 2007). Eliminating health disparities is one of two
overarching goals of Healthy People 2010 (U.S. Department of
Health and Human Services, 2000), the disease prevention and
health promotion agenda of the U.S. Department of Health and
Human Services. The Institute of Medicine’s 2002 ground-
breaking report Unequal Treatment: Confronting Racial and
Ethnic Disparities in Health Care (Smedley, Stith, & Nelson,
2003) and the National Healthcare Disparities Report (Agency
for Healthcare Research and Quality, 2006) documented
disparities in health care access. Disparities extend to inequal-
ities in access to medications. Older minorities are less
likely than majority elders to utilize prescription drugs or to
increase their numbers of prescriptions over time (Briesacher,
Limcangco, & Gaskin, 2003).
Dementia is a chronic and serious disease, with an estimated
worldwide societal cost of $315.4 billion in 2005 (Wimo,
Winblad, & Jonsson, 2007). According to findings from the
2002 Medicare Current Beneficiary Survey (MCBS), approx-
imately 3.4 million Medicare beneficiaries are diagnosed with
Alzheimer’s disease and related disorders, more than half of
whom (approximately 2 million) live in the community
(Gruber-Baldini, Stuart, Zuckerman, Simoni-Wastila, & Miller,
2007; Stuart et al., 2007). Non-Hispanic Blacks with dementia
N general, disease burden falls disproportionately on
minority populations. Even at older ages, minorities tend
are more likely to be undiagnosed or misdiagnosed relative to
non-Hispanic Whites (Clark et al., 2005; Leo, Narayan, Sherry,
Michalek, & Pollock, 1997); however, with population-based
sampling and careful diagnostic techniques employing neuro-
psychological and laboratory testing following National In-
stitute of Neurological and Communicative Disorders and
Stroke–Alzheimer’s Disease and Related Disorders Association
(NINCDS-ADRDA) criteria, the prevalence of dementia may
be relatively higher in minority populations. One community-
based survey, with diagnoses confirmed using clinical testing
and NINCDS-ADRDA criteria, found the prevalence of
Alzheimer’s disease among African American men to be 2.5
times greater than the prevalence among non-Hispanic White
men (Demirovic et al., 2003). Both non-Hispanic Blacks and
Latinos transition to long-term care at more advanced stages of
dementia (Stevens et al., 2004; Yaffe et al., 2002).
Minorities also may be less likely to be prescribed anti-
dementia medications. One study found that, considered
together, minority patients (non-Hispanic Blacks, Asians, and
Latinos) in Alzheimer’s disease research centers in California
had 40% lower odds of acetylcholinesterase inhibitor use
compared to Whites (Mehta, Yin, Resendez, & Yaffe, 2005).
Thus, there may be racial/ethnic disparities in dementia
incidence, prevalence, access to health care services, and
health care utilization.
The U.S. Food and Drug Administration has approved two
classes of drugs to treat symptoms of cognitive deficit in
Journal of Gerontology: SOCIAL SCIENCES
2008, Vol. 63B, No. 5, S328–S333
Copyright 2008 by The Gerontological Society of America
Alzheimer’s disease and related disorders: cholinesterase
inhibitors (donepezil, rivastigmine, galatamine, and tacrine)
and an N-methyl-D-aspartate receptor antagonist (memantine).
Using a national data set of community-dwelling Medicare
beneficiaries, we investigated the use of these prescription anti-
dementia medications to compare prevalence by non-Hispanic
White or minority race/ethnicity.
The study sample consisted of 1,606 person-years of
observation of 1,120 community-dwelling Medicare beneficia-
ries with a reported diagnosis of dementia from the MCBS for
years 2001 through 2003. The MCBS is a continuous sample
of U.S. Medicare recipients conducted by the Centers for
Medicare & Medicaid Services. Although the use of sampling
weights for single years of the MCBS would allow it to be
nationally representative of Medicare beneficiaries, we could
not use weights in our analysis because individuals may have
crossed years. Furthermore, because the MCBS oversamples
certain groups (e.g., those younger than 65 years of age), our
unweighted sample was not necessarily representative of
Medicare beneficiaries as a whole. The MCBS uses a rotating
panel design; beneficiaries or their proxies are interviewed in
their homes three times per year for a maximum of 4 years by
using computer-assisted personal interviewing technology.
Respondents are asked a battery of questions relating to
demographic characteristics, health status, pharmaceutical and
other health care utilization and expenditures, and health
insurance coverage. The MCBS links survey information to
Medicare Parts A and B claims that contain diagnostic
indicators as well as payment information. We excluded 42
observations from the analysis because of a missing value; all
observations analyzed had complete information.
The dependent variable was the annual prevalence of use of
any anti-dementia medication, namely donepezil (Aricept?),
memantine (Namenda?), by non-Hispanic Whites and minori-
ties. Respondents self-reported medication use. In addition to
querying respondents about specific medications used, inter-
viewers reviewed medication containers as part of the thrice-
yearly in-home interview during Years 2, 3, and 4. Respondents
receipts for medications, and the interviewers reviewed these
materials at each interview. If a medication named in a previous
round of interviewing was not listed, the respondent was queried
about its use during the period. Thus, prescription fills were
recorded, but actual medication use was not observed. We
determined race/ethnicity, our variable of interest, from the self-
report from the in-home computer-assisted personal interview-
ing interview. We determined dementia diagnosis status from
the presence of International Classification of Diseases–9
codes 331.0, 331.1, 331.2, 331.7, 290.xx (excluding 290.8 and
290.9), 294.xx (excluding 294.9), or 794.xx on one or more
inpatient hospital, skilled nursing facility, home health, hospital
outpatient, or physician supplier/carrier claim or from self-/
proxy report (‘‘sample person ever told had Alzheimer’s
disease or dementia’’). We determined dementia status from
claims alone for 49.9% of respondents, from self-reports only
for 23.7%, and from both sources for 26.4%. We chose
covariates from a literature review and from preliminary
analysis. Covariates included age (less than 65 years, 65–74,
75–84 and 85 years and older), gender, U.S. census region,
residence in a metropolitan statistical area, income, education,
marital status, source of dementia diagnosis (claims data, self-/
proxy report, or both), source of survey information (self-report
or proxy respondent for at least half of the interviews),
prescription drug insurance coverage, use of other medication
classes, and year of observation. We estimated comorbid
disease burden by using a count of comorbid disease classes.
We compared use or nonuse of anti-dementia medications by
using chi-square tests and t tests. Multivariate analysis with
generalized estimating equations (GEE) estimated the condi-
tional effect of race/ethnicity on anti-dementia drug use,
controlling for the covariates listed above. This analysis yielded
prevalence ratios (PRs) rather than prevalence odds ratios. With
26% of the sample using medication, odds ratios would not
have been an accurate estimation of actual prevalence. Odds
ratios are always further from the null value of 1.0 with the
disparity increasing with higher prevalence (Rothman &
Greenland, 1998). GEE is especially useful for investigations
with binary outcomes and correlated data. With efficient
parameter estimation and accurate standard errors, GEE is
better at correcting for clustering and other types of correlation
(Hanley, Negassa, Edwardes, & Forrester, 2003). Standard
errors are recalibrated to account for similarity of measures, or
correlation, by the same individual across differing lengths of
observation (Fitzmaurice, Laird, & Ware, 2004). Logistic
regression analysis is less suited to this analysis. Logistic
regression does not consider nonindependence due to correla-
tion; it also yields prevalence odds ratios rather than PRs and
thus would have overestimated the association of race/ethnicity
and medication use. We assumed a binomial distribution and
used a log link function to report PRs. We calculated PRs and
their associated 95% confidence intervals (CIs) by using PROC
GENMOD in SAS 9.1.3 (Deddens, Petersen, & Lei, 2003).
Because the usual tests of model fit are not valid for GEE
models, we assessed goodness of fit by using an experimental
technique based on aggregates of residuals with an associated
p value of .9060, indicating a satisfactory model (SAS Institute,
The ethnic/racial distribution of the sample was 76.3% non-
Hispanic White, 11.7% non-Hispanic Black, 8.1% Hispanic,
and 3.8% non-Hispanic other (see Table 1). The mean age
of the sample was 80 years (SD ¼ 11), and nearly 60%
were female. Approximately 26% of the sample received at
least one anti-dementia medication, most commonly donepezil
and less frequently rivastigmine, galantamine, or memantine.
The sample differed significantly by race for anti-dementia
medication use, age, income, education, marital status, region,
urban residence, and proxy response. Whites most often used
RACIAL DISPARITIES IN DEMENTIA MEDICATION
anti-dementia medication (28.7%, p ¼ .0022), were in the
highest income group (27.7%, p , .0001), had education
beyond high school (35.1%, p , .0001), and were currently
married (45.6%, p , .0001); Hispanics most often were
younger than 65 years of age (19.8%, p , .0001), lived in
urban metropolitan areas (91.2%, p , .0018), lived in the South
(68.1%, p , .0001), and had a proxy respondent for at least half
of the interviews (57.1%, p ¼ .0011).
In addition to the race/ethnicity comparisons shown in
Table 1, we also performed bivariate comparisons between
Table 1. Characteristics of the Sample by Racial/Ethnic Group (N ¼ 1,120)
White (n ¼ 855; 76.3%)
Black (n ¼ 131; 11.7%)
(n ¼ 91; 8.1%)
Other (n ¼ 43; 3.8%)
(N ¼ 1,120)
n (%) Characteristic
Use of any anti-dementia drug (p ¼ .0022)
Age (p , .0001)
Less than 65 years
85 years or more
Income (p , .0001)
100% FPL or less
More than 300% FPL
Education (p , .0001)
9–12 years (no high school graduation)
High school graduate
Marital status (p , .0001)
Region (p , .0001)
Residence in urban MSA (p ¼ .0008)
Proxy respondent for half or more interviews (p ¼ .0011)
Source of diagnosis information
Claims data only
Self-/proxy report only
Both claims and self-/proxy report
Prescription drug insurance coverage
Hospitalized during study period
SNF stay during study period
Hospice utilization during period
Number of comorbid disease classes
11 or more
Use of other drug classesa
711 (83.2)112 (85.5)70 (76.9) 33 (76.7)956 (82.7)
Notes: FPL ¼ federal poverty level; MSA ¼ metropolitan statistical area; SNF ¼ skilled nursing facility.
aCardiovascular, antidepressant, or antipsychotic medication.
p ? .05 except where shown.
ZUCKERMAN ET AL.
anti-dementia medication users and nonusers (data not shown).
Compared to those not receiving anti-dementia medication,
anti-dementia medication users were older (M ¼ 81.3 years vs
79.7, t ¼?2.89, p ¼ .0040), were more often currently married
(53.6% vs 38.5%, v2¼ 40.2, p , .0001), used more
cardiovascular (80.1% vs 74.1%, v2¼ 4.2, p ¼ .0401) and
antidepressant medications (38.1% vs 29.1%, v2¼ 8.2, p ¼
.0041), more frequently had prescription drug insurance (79.4%
vs 71.1%, v2¼ 7.6, p ¼ .0058), and were more likely to have
their dementia status ascertained both from claims data and
from self-report (52.2% vs 17.4%, v2¼ 134.7, p , .0001).
Relative to nonusers, anti-dementia medication users were less
likely to use the services of hospitals (27.9% vs 40.4%, v2¼
14.6, p¼.0001), hospices (2.1% vs 6.9%, v2¼9.4, p¼.0022),
or skilled nursing facilities (7.2% vs 15.0%, v2¼ 11.5, p ¼
.0007). They were also less likely to live in poverty (13.1% vs
27.0%, v2¼ 24.7, p , .0001). There were no other significant
differences between medication users and nonusers.
We compared the prevalence of anti-dementia medication by
racial/ethnic group (see Table 2). In the unadjusted model, the
PR comparing all minorities to non-Hispanic Whites was 0.61
(95% CI ¼ 0.48, 0.77). The adjusted model included de-
mographics (gender, age, marital status, and geographic
location), socioeconomic status (income and education), source
of diagnosis (claims data, self-report, or both), self- or proxy
reporting, comorbidity count, health care utilization variables
(prescription insurance status, hospital, skilled nursing facility
and hospice stay, use of other drug classes), and year. The PR
for the adjusted model was 0.73 (95% CI ¼ 0.59, 0.91). In the
final model, urban or suburban residence (PR¼1.30, 95% CI¼
1.09, 1.57) and use of other drug classes (PR¼1.50, 95% CI¼
1.16, 1.95) were associated with higher prevalence of use.
Being never married, divorced, or separated (PR ¼ 0.33, 95%
CI¼0.17, 0.61); having a single source for dementia diagnosis
(PR ¼ 0.37, 95% CI ¼ 0.31, 0.44, for claims data only; PR ¼
0.35, 95% CI ¼ 0.28, 0.44, for self-report only); being a proxy
respondent rather than a self-report (PR¼0.82, 95% CI¼0.71,
0.95); lacking supplemental prescription insurance coverage
(PR ¼ 0.76, 95% CI ¼ 0.63, 0.92); and using hospice services
(PR ¼ 0.49, 95% CI ¼ 0.27, 0.89) predicted lower prevalence
of anti-dementia drug use. We repeated the analyses with
individual minority racial/ethnic groups entered simultaneously
in both models (see Table 3). Prevalence disparities remained
significant for non-Hispanic Blacks (PR¼0.75, 95% CI¼0.57,
0.99) and non-Hispanic others (PR ¼ 0.50, 95% CI ¼ 0.26,
0.96) but were attenuated for Hispanics (PR ¼ 0.84, 95% CI ¼
Table 2. Multivariate Analysis of Prevalence Ratios for
Anti-Dementia Medications for Non-Hispanic
White Versus Minority Medicare Beneficiaries
(N ¼ 1,606 person-years of observation)
Unadjusted Model Adjusted Model
Variable PR 95% CIPR 95% CI
Minority race vs non-Hispanic
White0.610.48, 0.77 0.730.59, 0.91
Less than 65 years
Female gender 0.990.85, 1.14
Urban/suburban residence 1.301.09, 1.57
100% FPL or less
8 years or fewer
9–12 years (no high
High school graduate
1.00 0.93, 1.07
Proxy respondent 0.82 0.71, 0.95
Source of diagnosisf
Claims data only
Self-/proxy report only
Number of comorbid conditionsg
No supplemental prescription drug
Skilled nursing facility stay
Use of other drug classesh
Notes: PR ¼ prevalence ratio; CI ¼ confidence interval; FPL ¼ federal
a85 years or older is the reference group.
bEast is the reference group.
cGreater than 300% FPL is the reference group.
dPostsecondary education is the reference group.
eCurrently married is the reference group.
fDiagnosis from both claims data and self-report is the reference group.
g11 or more comorbid conditions is the reference group.
hCardiovascular, antidepressant, or antipsychotic medications.
i2003 is the reference group.
Table 3. Multivariate Analysis of Prevalence Ratios for
Anti-Dementia Medications for Non-Hispanic
White Versus Specific Racial/Ethnic
Groups of Medicare Beneficiaries
Unadjusted ModelAdjusted Model
GroupPR95% CI PR 95% CI
Note: Non-Hispanic Whites is the reference group. PR ¼ prevalence ratio;
CI ¼ confidence interval.
RACIAL DISPARITIES IN DEMENTIA MEDICATION
Relative to non-Hispanic Whites, community-dwelling
minority Medicare beneficiaries with dementia had an ap-
proximately 30% lower prevalence of anti-dementia medication
use in the years 2001 through 2003. The finding of lower
prevalence among minority Medicare beneficiaries was ex-
tremely robust, persisting even after we adjusted for demo-
graphic, economic, health status, health care access, and
utilization factors. Our findings are similar in magnitude to
the 40% lower prevalence for non-Whites found by Mehta and
colleagues (2005) in their investigation of acetylcholinesterase
inhibitor use in California Alzheimer’s disease centers in the
years 1999 through 2003. Our study reinforces their findings by
using a national community-dwelling sample rather than one
from a specialty clinical setting. When we examined racial/
ethnic groups individually, PRs remained statistically signifi-
cant for non-Hispanic Blacks and non-Hispanic others but lost
significance for Hispanics, possibly because of the small
numbers in each minority group. Of interest is that the smallest
group, the heterogeneous ‘‘non-Hispanic other’’ category, had
the greatest disparity in prevalence. In our sample, the 43 non-
Hispanic others included those reporting more than one race/
ethnicity (n ¼ 16), Asian or Pacific Islander (n ¼ 15), North
American native (n¼7), don’t know (n¼3), and other (n¼2).
Numbers were too small within this group to determine whether
prevalence was similar across these subcategories or whether
one or two subcategories strongly influenced the disparity.
Although we cannot fully explain this disparity from our
investigation, our findings suggest that between-race differ-
ences are not due to demographic, economic, health status,
access, or utilization variables. Disparities may be due to
differences in attitudes toward dementia in diverse cultures in
the United States, as well as cultural bias in cognitive
measurement (Manly & Espino, 2004). They might arise also
from differences in psychosocial environment (e.g., neighbor-
hood effects) or discrimination experienced by members of
minority groups, both of which have been proposed to be
important determinants of the mental health of non-Hispanic
Blacks (Williams & Earl, 2007). If dementia is less often
correctly diagnosed in minorities, as reported by Clark and
colleagues (2005) and Leo and associates (1997), our disparity
findings may underestimate the unmet treatment need among
minorities with dementia that has not been diagnosed.
Differences in prescribing patterns for non-Hispanic Whites
and other groups might arise in several ways. Minority patients
have relatively poorer access to health care, beyond the
variation in hospital, skilled nursing facility, and hospice use
and prescription drug insurance coverage accounted for by this
analysis (Smedley et al., 2003). Less contact with physicians
would likely result in fewer prescriptions being written. In our
sample, non-Hispanic Whites had an average of 7.7 office visits
during the observation period, whereas minorities made 6.9
visits; this difference is nearly statistically significant at the a¼
.05 level (t¼?1.90, p¼.058). Additionally, minority elders are
placed in long-term care at more advanced stages of dementia
(Stevens et al., 2004; Yaffe et al., 2002), perhaps leading to
a disproportionate number of more severely demented minority
elders remaining in the community. With the exception of
memantine, approved in 2003 for moderate to severe dementia
of the Alzheimer’s type, anti-dementia medications were
indicated for use in only mild to moderate disease during our
study years (U.S. Food and Drug Administration, 2003);
therefore, medication might have been considered inappropriate
for community-dwelling minority elders with more advanced
dementia and thus not prescribed.
Non-Hispanic Blacks make proportionately more mental
health visits to primary care providers rather than to special-
ists and thus receive fewer prescriptions for psychotropics
(Snowden, 2001). Poorer access to specialty dementia care may
explain some of the disparity with regard to dementia medi-
cations. In addition, non-Hispanic Blacks have higher relative
rates of vascular dementia, and medications considered in this
investigation were approved for use in Alzheimer’s disease
rather than for vascular and other types of dementia during the
study years. Thus, non-Hispanic Blacks in particular may have
received proportionately fewer prescriptions for anti-dementia
medications, because the use of these medications was not
indicated for dementia types other than Alzheimer’s disease.
However, even if taken together, it seems unlikely that
dementia type and disease severity could account for the entire
30% differential between majority and minority use of anti-
Our study has several limitations. Specific anti-dementia
medications and their indications changed within the study
years 2001 through 2003 and continue to do so; therefore,
findings relating to this class of medications during those years
may not hold true for the present or future. Numbers within
each specific race/ethnicity group were relatively small; thus,
our ability to look at individual groups is limited. We lacked
information on caregivers of people with dementia. Caregiver
factors may have influenced access to health care for people
with dementia; for instance, caregiver psychological distress is
associated with a decreased likelihood of receipt of influenza
vaccine by the person being cared for (Thorpe et al., 2006).
Issues of disparities need investigation using data sources
that contain higher numbers of minorities, thereby allowing for
detailed examination of prevalence and use patterns by specific
racial and ethnic populations. Further investigation needs to be
undertaken with larger numbers of minority participants,
accounting for issues of dementia type and severity, medication
dose and duration of use, access to specialty dementia care, and
consistency in treatment disparities across settings of care. As
well, dementia prevalence is greatest in nursing homes and
other institutions, and evaluation of racial and ethnic disparities
should be considered in this vulnerable population, especially
because a recent study reported significant racial disparities in
quality nursing home placement (Smith, Feng, Fennell, Zinn, &
Mor, 2007). Additionally, the influence of cultural and
environmental factors in dementia treatment remains a fertile
area worthy of future exploration.
This study was funded by a Grant 20050634 from the Commonwealth
Fund. Dr. Zuckerman was supported by Award K01AG22011 from the
National Institute on Aging. Dr. Ryder was supported by Training Grant
T32AG000262 in the epidemiology of aging from the National Institute on
Aging. We are grateful for the assistance of Dr. Ann L. Gruber-Baldini and
the helpful comments of three anonymous reviewers. A previous version of
this work was presented at the AcademyHealth Annual Research Meeting,
June 2007, Orlando, Florida.
ZUCKERMAN ET AL.
I. H. Zuckerman planned the study, wrote and revised the manuscript, Download full-text
supervised data analysis and interpretation, and performed data analysis and
interpretation. P. T. Ryder wrote and revised the manuscript and performed
data analysis and interpretation. L. Simoni-Wastila contributed to
interpreting the analytic results and revising the manuscript. T. Shaffer
assisted with data analysis, provided statistical expertise, and revised the
manuscript. M. Sato contributed to writing the paper and revising the
manuscript. L. Zhao provided statistical expertise and contributed to
revising the manuscript. B. Stuart acquired the data, helped plan the study,
and contributed to revising the manuscript.
Address correspondence to Ilene Zuckerman, PharmD, PhD, Department
of Pharmaceutical Health Services Research, University of Maryland
School of Pharmacy, 220 Arch Street, Baltimore, MD 21201. E-mail:
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Received November 15, 2007
Accepted June 11, 2008
Decision Editor: Kenneth F. Ferraro, PhD
RACIAL DISPARITIES IN DEMENTIA MEDICATION