Dr. Steven Belle: (412)624-1620
Word Count: 4038
COGNITIVE ENHANCEMENT MEDICATION UTILIZATION AMONG PERSONS WITH
ALZHEIMER’S DISEASE WHO HAVE A FAMILY CAREGIVER: RESULTS FROM THE
RESOURCES FOR ENHANCING ALZHEIMER’S CAREGIVER HEALTH (REACH)
PROJECT
S. H. Belle1, S. Zhang1, S.J. Czaja2, R. Burns3, R. Schulz4
1
Department of Epidemiology, Graduate School of Public Health, University of
Pittsburgh, Pittsburgh, PA 15261
2
Department of Psychiatry, University of Miami School of Medicine, Miami, FL 33136
3
Department of Preventive Medicine, University of Tennessee, and Regional Medical
Center
Memphis, TN 38104
4
Department of Psychiatry and University Center for Social and Urban Research,
University of Pittsburgh, Pittsburgh PA, 15261
PREVIOUS PRESENTATION: Annual Meeting of the Gerontological Society of
America. Boston, MA. November 22-26, 2002.
REPRINT REQUESTS TO: Steven Belle, PhD. Department of Epidemiology. Graduate
School of Public Health. University of Pittsburgh. 504 Parran Hall. 130 DeSoto St.
Pittsburgh, PA 15261.
ACKNOWLEDGEMENTS: This research was supported through the Resources for Enhancing
Alzheimer’s Caregiver Health (REACH) project, supported by the National Institute on Aging and
the National Institute of Nursing Research (Grants: U01-NR13269, U01-AG13313, U01AG13297, U01-AG13289, U01-AG13265, U01-AG13255, U01-AG13305). Support was also
provided by Eisai/Pfizer.
Keywords: Medication utilization
Dementia
Caregiving
Abstract:
Objective: An aging population has increased prevalence of cognitive impairment and
dementia. Recent efficacy studies report on prescription medications and herbal
preparations that affect cognitive function, but the prevalence and correlates of cognitive
enhancement (CE) medication utilization among community-dwelling elders is not well
studied. We examined the frequency and appropriateness of use, the importance of a
family caregiver in decisions about medications taken by people with dementia, and
whether there was differential access to medical care.
Method: REACH was a multi-site feasibility study of several approaches to reduce
negative impacts of caregiving on caregivers living with a family member with dementia.
Medication use by care-recipients was collected at baseline and one year later.
Results: At baseline, 31% of 1222 care-recipients (CR) were using a cognitive
enhancement (CE) medication. Factors independently related to CE use were age,
education, functional status and caregiver vigilance. Within 1 year, 14% of CR started,
and 30% quit, taking CE. Care-recipients more likely to be starters than never users had
spouse caregivers, higher education, and fewer baseline ADL impairments. Compared to
those who continued taking CE, quitters had more ADL deficits at baseline, and became
less able to perform ADL during followup.
Conclusions: CE medication use among demented people with a family caregiver is
relatively common, though there is substantial geographic variability. Our findings are
mixed with respect to appropriate use of CE medications suggesting areas for physician
education. Our data indicate the importance of the caregiver in CE medication use and
suggest that there may be disparities in access to health care among people with cognitive
impairment.
Introduction
As the number of elderly people in the population increases, so does the burden on public
health and on both medical and social services caused by age-related diseases and disabilities. In
particular, the incidence of cognitive impairment and dementing disorders increase dramatically
with age [1]. Dementia is characterized by cognitive impairment, but affected individuals often
experience behavioral and psychological symptoms such as agitation, wandering, sleep
disturbance, depression, and anxiety [2]. These manifestations may require medical or social
services for many patients who are cared for at home and can eventually lead to institutionalization
[2].
Recent reports demonstrate the efficacy of a number of medications for treating mild to
moderate Alzheimer’s Disease. These cognitive enhancement (CE) medications include
cholinesterase inhibitors (e.g., tacrine [Cognex], galantamine [Reminyl], physostigmine, donezepil
[Aricept], rivastigmine [Exelon]) and an N-methyl-aspartate (NDA)-receptor antagonist
(memantine) [3-5]. Other medications either under investigation or under consideration include
nonsteroidal anti-inflammatory drugs, estrogen, antioxidants, and chelation therapy [6]. Herbal
medications including ginkgo biloba and ginseng have also been reported to have cognitive or
concentration enhancing properties [7,8].
To date, studies of CE medication use in this population have primarily focused on
treatment efficacy. Relatively little is known about the prevalence of CE use in communityresiding populations. The purpose of this paper is to examine the prevalence of use of CE
medications and herbal products with putative cognitive enhancement properties in a wellcharacterized cohort of people with Alzheimer’s Disease. Since caregivers play a central role in
managing patients’ medications, it is important to identify both caregiver and care-recipient
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characteristics associated with using these medications and herbal products. The availability of
longitudinal data also enabled us to examine changes in patterns of use.
Utilization data are also important for helping to answer questions about appropriate use of
medications. For example, cholinesterase inhibitors are beneficial for community-living patients
with mild to moderate dementia [5], though they may soon be considered for people with more
severe dementia [4]. Thus, at present, one may characterize use of cognitive enhancement
medications by people with moderate to severe dementia as inappropriate. Characteristics of users
compared to non-users can also help to identify disparities in access to potentially costly medical
treatments. Finally, knowing characteristics of medication users can inform design and analytical
strategies for randomized or observational efficacy studies.
Methods
The sample was enrolled in the Resources Enhancing Alzheimer’s Caregiver Health
(REACH) project, a 6-site study with a central Coordinating Center funded jointly by the National
Institute on Aging and the National Institute for Nursing Research. REACH was designed to
investigate the feasibility of various interventions in alleviating the burden of family caregivers
with Alzheimer’s Disease or a related disorder. Recruitment strategies and sources varied by site
with the latter including community, health, and social agencies. Special attention was given to
enrolling ethnically and racially diverse participants. Details about recruitment strategies and the
interventions at each site can be found in Wisniewski, Belle, Coon et al [9].
Briefly, after obtaining informed consent as required by Institutional Review Boards (IRB)
at each site, eligible caregiver/care-recipient dyads were randomly assigned to either a control
condition or one of either one or two active treatment groups that varied by site. To be eligible,
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care-recipients had to have a diagnosis of Alzheimer’s Disease or a related dementia, and at least
one limitation in basic activities of daily living (ADL; [10]) or two dependencies in Instrumental
Activities of Daily Living (IADL; [11]).
Medication utilization was recorded by trained personnel during study visits (baseline and
6 months, 12 months, and 18 months following randomization) after examining containers of all
medications being taken by care-recipients and by caregivers. Medications were initially classified
using the Instant Drug Index [12]. Those classified as Psychiatric, and all herbals, were examined
by the study pharmacist to determine whether they were cognitive enhancement (CE) medications.
Measures
Caregiver: Baseline CE use was examined by site, caregiver relationship to care recipient,
and by demographics (age, sex, race, educational level and family income). Additional caregiver
factors studied were burden (Revised Memory and Behavior Problems Checklist; [13]), depression
(CES-D; [14]), a measure of the positive aspects of caregiving, anxiety [15], self-rated health and
health behaviors (adapted from [16,17]), and vigilance [18]. Changes in medication use were
examined by the baseline characteristics and by changes in these characteristics.
Care-recipient characteristics included demographics, functional abilities (ADL, IADL)
and cognitive status (MMSE; [19]). Changes in medication use were examined by the baseline
characteristics and by changes in both ADL and IADL. Change in MMSE was not examined
because of the relatively large amount of missing data at follow-up assessment times.
Analytical methods
3
The prevalence of CE use at baseline by caregiver and care-recipient characteristics was
assessed. Chi-square tests for differences in proportions were performed to identify statistically
significant differences in prevalence for the categorical factors. A p-value less than 0.05 was used
to determine statistical significance for all tests. A simple generalized linear model with log link
and binomial error was used for continuous factors [20]. From this model, we obtained relative
risk estimates. Multiple regression models were fit to identify caregiver and care recipient
demographic characteristics, and other measures, that were independently associated with CE-use.
Stepwise selection was used to determine which explanatory variables to keep in the fitted models.
To characterize changes in CE medication use over time, four groups were created: never
users did not use CE at baseline or at the 12-months follow-up, starters did not use CE at baseline
but did at 12-months, quitters used CE at baseline but not at 12-months and maintainers used CE
at both baseline and 12-months. To examine factors associated with changes in medication use,
starters were compared to never users (the two groups of baseline non-users) and quitters were
compared to maintainers (the two groups of baseline users). Proportions of care-recipients
changing (starting or quitting) use were calculated by caregiver and care-recipient characteristics.
The chi-square test for differences in proportions were performed to identify statistically
significant differences in the proportions changing pattern of use for the categorical factors Two
sets of regression models (as described above) were used to identify caregiver and care-recipient
factors associated with starting (vs. never using) and quitting (vs. maintaining), respectively.
These models were built in a stepwise manner with probabilities of 0.05 required for keeping a
variable in the model. Relative risks of the change in patterns of use (i.e., starting vs. never using,
quitting vs. maintaining) are reported.
Results
4
The six REACH sites randomized 1222 care-recipient/caregiver dyads between
October, 1996 and May, 2001. The caregivers averaged 62.3 (SD = 13.6) years of age,
ranging from 22 to 95 years old. Reflecting the intent to recruit a sizeable number of
minority caregivers, the sample of caregivers was racially and ethnically diverse, 24.2%
were African-American/Black and 19.0% were Hispanic/Latino. Over 80% of the
caregivers were female with approximately three-quarters of the caregivers being either
wives (35.7%) or daughters or daughters-in-law (39.0%) of the care-recipients. The carerecipients averaged 79.1 (SD = 8.2) years of age (range 44-101 years), 72.3% were at
least 75 years old and the majority was female (55.6%). Mini-Mental State Examination
(MMSE) scores ranged from 0-29 with an average of 12.6. On average, care-recipients
had 3.3 (out of 6) ADL deficits and needed assistance with 7.3 (out of 8) IADL
Cognitive Enhancement Medication Utilization at Baseline
Cognitive enhancement medications were used by 382 (31%) of the carerecipients at baseline. The most common CE medication was Aricept (Donepezil), used
by 320 of the care-recipients who were using any CE (84%). Ginkgo biloba or ginseng
was used by 80 care-recipients, 36 of whom were also using Aricept (Table 1).
In unadjusted analysis, baseline CE medication use differed (p<.05) by site, CG/CR
relationship and caregiver demographic factors (age, sex, education, and income). Over half of the
care-recipients at Miami used CE compared to only 11.7% at Palo Alto. Utilization ranged
between 22.0% and 36.4% at the other 4 sites. Care recipients who were married to their
caregiver were more likely to be CE users than care-recipients who had another relationship
(usually parent) to their caregiver. CE use at baseline was higher if the caregiver was older, male,
better educated, or had a higher income. The care-recipients of caregivers reporting higher levels
5
of positive aspects of caregiving, fewer hours doing things for the care-recipient, or fewer hours
being “on duty” were also more likely to use CE at baseline. Care-recipient characteristics
associated with increased baseline CE use were age (use was highest among care-recipients 70 to
84 years old), more education, less cognitive impairment and less functional impairment.
Multiple regression models were used to identify which of the baseline factors were
independently associated with CE use (Table 2). Relative risks greater than one, indicating more
CE use, were found for higher educated care recipients, those requiring assistance with fewer
ADLs, and those whose caregivers spent less time “on duty”. CE utilization increased with carerecipient age up to 74 years of age, declining for older care-recipients. CE use was also
significantly lower in Palo Alto than at the other five sites. There were no statistically significant
interaction terms.
Change in Cognitive Enhancement Medication Utilization
Due to care-recipient death (n=130), placement (n=135), a missed visit (n=154),
dropout (n=119) or a missing form (n=3), care-recipient medication utilization was
available at 12 months for 681 participants (56% of the baseline cohort). These carerecipients included 467 who did not use CE at baseline (56% of non-users) and 214 who
did use CE at baseline (56% of users). There were 67 starters (14% of baseline nonusers) and 64 quitters (30% of baseline users).
Starting vs. Never Using
The incidence of starting use varied by site, relationship, CG race, age, education, income,
CG CES-D, CG self-rated health, and the amount of time a CG provided help to their care-
6
recipient. Miami (32.4%) had the highest percentage of starters and Philadelphia (8.4%) had the
lowest percentage. Starting was more frequent if the caregiver was married to the care-recipient, if
caregivers were older, Caucasian, higher educated, had higher incomes, lower CES-D scores,
better self-rated health, or spent less time doing things for the CR. Care recipient characteristics
associated with higher incidence of starting were being Caucasian, having more education and
better functional and cognitive function
The final multiple regression model included site, care recipient education, relation and
ADL baseline score as independently associated with starting CE use (Table 3). Care recipients
from Miami were most likely to be starters. Starting was also associated with higher CR
education, having a spouse caregiver, and better ADL function at baseline.
Quitting vs. Maintaining
In unadjusted analyses, non-spouse CR were more likely to quit using CE than CR with a
spouse caregiver. This may explain why the probability of CR quitting was also higher for
younger CG. Female CR were more likely to quit than male CR. Higher levels of disability (ADL,
IADL) and worse cognitive function at baseline (MMSE) were associated with a greater
probability of quitting as was an increase in ADL disability between baseline and the12 month
follow-up.
A multiple regression model was built to identify independent factors that distinguished
maintainers from quitters (Table 4). Since there was considerable geographic variability in
baseline CE use, site was included, even though rates of quitting did not differ significantly across
sites in unadjusted analyses. Quitting was associated with higher ADL at baseline and with greater
deterioration in ADL function between baseline and 12 month follow-up.
7
Discussion
The longitudinal data available from the REACH project allowed us to examine patterns of
CE medication use, and changes in use, in a large and diverse sample of AD patients. These are
important data because they allowed us to address critical issues such as appropriateness of
medication use, disparities in access to medical services, issues related to study design and analysis
of efficacy studies and because of the importance of the CG in managing the care of patients with
dementia.
CE medication use varied geographically, as has been reported for Medicare health care
spending [21,22]. The quadratic age effect is similar to that of many prescription drugs used by
an elderly population. For example, a study of prescription medication use in Sweden [23] found
increasing use between the age groups 65-74 years and 75-84 years, and then a decline among
those 85 years of age and older. The finding that the peak use of CE medications in the REACH
cohort occurred at a younger age (74 years) than that for other medications in Sweden may be due
to decreasing effectiveness with increasing severity of dementia. Baseline medication use was also
more common among the better educated, less functionally impaired care-recipients, and those
whose caregivers reported spending less time on duty. The finding that CE medication use was
less common among less educated care-recipients, even adjusting for functional status, may
indicate a disparity in access to health care. People with lower education may have less knowledge
of treatments for dementia and may not be able to afford medications that are available.
The findings with respect to appropriateness of use are mixed. Since CE medications are
most commonly indicated for people with mild to moderate dementia, the findings that CE
medication use was more common among less impaired CR and those whose caregivers reported
8
spending less time “on duty” are consistent with appropriate use of the medications. However, the
data also suggest that CE medications may be inappropriately used for some patients. At baseline,
26% of the patients with severe cognitive impairment (MMSE score less than 10) were using a CE.
Among severely cognitively impaired patients, 21% were using donepezil at baseline even though
study populations on whom cholinesterase inhibitors were tested were not as severely impaired,
with MMSE of 10-26 [24]. Furthermore, 6% of severely impaired patients (MMSE score less than
10) began using cognitive enhancement medications within a year of baseline, despite the
aforementioned recommendation. This may indicate that physician education concerning
indications for these drugs needs to be improved. It should be noted, on the other hand, that 13%
of those with MMSE scores less than 10 quit using cognitive enhancement medications prior to
their next follow-up.
The same relationships with site, education, and functional status were found for those CR
who started using CE medications between baseline and 12 months later. The relationship
between quitting within 12 months of baseline and functional status was consistent with the
findings among users and starters in that those who were more impaired and those who got worse
over time were more likely to quit.
These data also provide guidance for designing and interpreting CE efficacy studies.
Factors associated with CE medication utilization may be important confounding variables that
need to be accounted for, particularly in non-randomized studies of outcomes comparing users and
non-users of CE-medications. Furthermore, that utilization patterns change over a period of time
as short as 12 months may have implications for studies of medication use, or even other nonpharmaceutical intervention studies in which CE-medication use may be a confounding factor.
9
Although one might expect CE use to be determined by patient characteristics, our findings
show that CG factors also play an important role even after adjusting for the CR functional status.
Specifically, CR of CG reporting less time on duty were more likely to be using CE at baseline,
and CR of spouse caregivers were more likely to start use.
Given that the focus of the REACH project was not on medication use, there are some
limitations of these data. Though medications were carefully recorded and categorized, utilization
was not validated and neither length of use nor dosages were recorded. Also, longitudinal data
were available for only 56% of the baseline cohort, though a large portion of the missing data was
for care-recipients who either died or were institutionalized. Therefore, even assuming that carerecipients of caregivers who dropped out or missed a visit were all living at home, longitudinal
data were available for over 70% of the care-recipients living at home 1 year after entry into
REACH. If drop outs or missing visits were unrelated to medication utilization, then the results
should still be generalizable to those caregiver/care-recipient dyads for which the care-recipient is
living at home. When generalizing these results, it is also important to note that these dyads were
enrolled in a study to provide support to caregivers and as such may have been more burdened or
more aware of alternative treatments, including medications, than other caregivers.
These data provide information concerning CE medication use in a burdened, but aware,
sample of family caregivers of people with Alzheimer’s Disease in 6 regions across the United
States. An important next step in this research area is to link utilization data of the type reported
here to efficacy of CE medications. For example, since these data show that severely impaired
patients are using CE, a rigorously designed and implemented efficacy study may be warranted.
Another important area of investigation is the interaction of prescription and herbal CE
medications with other medications commonly used by an elderly population.
10
Table 1 Care Recipient Use of Cognitive Enhancement Drugs at Baseline
(n=1222)
Use of Cognitive Enhancement drugs
Use 1 Cognitive Enhancement drug
Aricept (Donepezil)
Ginkgo
Cognex (Tacrine)
Hydergine
Ginseng
Exelon (Rivastigmine)
“Mental Alertness”
Use 2 Cognitive Enhancement drugs
Aricept (Donepezil) plus Ginkgo
Aricept (Donepezil) plus Ginseng
Aricept plus Cognex (Tacrine)
Ginseng plus Ginkgo
Use 3 Cognitive Enhancement drugs
Aricept (Donepezil) plus Ginseng and Ginkgo
Aricept (Donepezil) plus two separate
Ginsengs
11
N (%)
382 (31.3)
343 (28.1)
282
42
12
3
1
2
1
37 (3.0)
33
1
2
1
2 (0.2)
1
1
Table 2. Multiple Regression Model for Prevalence of Cognitive
Enhancement Drug (CE) Use among Care Recipients at Baseline (n=1216*)
Risk Factor
Care recipient education level
< High School
>= High School
Care recipient age
Linear function
Quadratic function
ADL score at baseline (per
fewer impairment)
Time on duty at baseline (per
hour less)
Site
Birmingham
Boston
Memphis
Miami
Palo Alto
Philadelphia
Relative
Risk
95% Confidence
Interval
P-value
---1.28
----, ---1.10, 1.50
0.002
----
1.23
0.999
1.08
1.07, 1.42
0.998, 0.9995
1.04, 1.02
0.004
0.003
<0.0001
1.01
1.004, 1.02
0.03
2.72
1.60
1.98
3.81
----2.64
1.89, 3.91
1.01, 2.53
1.39, 2.84
2.77, 5.25
-----,----1.87, 3.73
<0.0001
0.045
0.0002
<0.0001
---<0.0001
* 6 subjects were excluded from analysis due to missing explanatory data.
12
Table 3 Multiple Regression Model for Starting CE Use by 12 Months (n=467)
Risk Factor
Site
Birmingham
Boston
Memphis
Miami
Palo Alto
Philadelphia
Care recipient education
level
< High School
>= High School
Caregiver relationship to
care recipient
Spouse
Non-spouse
ADL score at baseline (per
fewer impairment)
Relative
risk
95% Confidence
Interval
P-value
1.49
1.69
1.01
3.01
1.20
----
0.65, 3.43
0.74, 3.83
0.45, 2.26
1.42, 6.40
0.57, 2.50
----, ----
0.34
0.21
0.99
0.004
0.63
---1.71
----, ---1.07, 2.75
0.02
1.67
-----
1.11, 2.51
-----
0.01
1.22
1.11, 1.35
<0.0001
13
Table 4. Multiple Regression Model for Quitting CE use by 12 Months (n=214)
Risk Factor
Odds
ratio
95% Confidence
Interval
P-value
Site
Birmingham
Boston
Memphis
Miami
Palo Alto
Philadelphia
1.01
1.25
1.78
---1.83
1.63
0.42, 2.66
0.54, 2.88
0.99, 3.19
----, ---0.93, 3.62
0.91, 2.92
0.98
0.60
0.05
---0.08
0.10
ADL score at baseline
1.25
1.11, 1.41
0.0003
ADL change score
1.20
1.04, 1.38
0.01
14
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