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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 60:258-264 (2005)
© 2005 The Gerontological Society of America

Predictors of Functional Impairment in Residents of Assisted-Living Facilities: The Maryland Assisted Living Study

Daniel J. Burdick1, Adam Rosenblatt1,3, Quincy M. Samus1, Cynthia Steele1,3, Alva Baker1,3, Michael Harper4, Lawrence Mayer1, Jason Brandt2,3, Peter Rabins1,3 and Constantine G. Lyketsos1,3,

Divisions of 1 Geriatric Psychiatry and Neuropsychiatry
2 Medical Psychology, Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of Medicine, Baltimore, Maryland.
3 The Copper Ridge Institute, Sykesville, Maryland.
4 Division of Geriatrics, Department of Medicine, University of California at San Francisco.

Address correspondence to Constantine G. Lyketsos, MD, Osler 320, The Johns Hopkins Hospital, Baltimore, MD 21287. E-mail: kostas{at}jhmi.edu


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
Background. Assisted living is a popular residential option for older individuals, yet little research has been done on people choosing this option. This study examines predictors of functional impairment in assisted living residents in the domains of cognition, mood, and health.

Methods. An experienced team of neuropsychiatrists, nurses, and technicians using a number of cognitive, behavioral, health, and functional status tests and a cross-sectional study design assessed 198 residents of 22 assisted living facilities in Maryland. Data from these evaluations were used in univariate and multiple regression models to identify predictors of functional impairment, operationalized as the sum of the scores on two scales, one measuring impairment in basic activities of daily living and one measuring impairment in instrumental activities of daily living.

Results. Greater cognitive impairment, worse depression, and worse medical health were significant independent predictors of functional impairment, together explaining a sizeable portion of the variance (adjusted R2 = 0.434). None of the demographic variables examined individually, including age and education, was predictive of functional impairment. In an analysis of specific cognitive domains, executive dysfunction, impairment of visuospatial skills, and amnesia were significant predictors of impairment, whereas inattention was not.

Conclusion. Executive dysfunction, apraxia, memory impairment, depression, and general medical health are all significant predictors of functional impairment in assisted living residents, with executive dysfunction being the strongest. These results may be instrumental in developing a more efficient model of care for residents of assisted living facilities, one based on having accurate predictive models of degree of impairment.

ASSISTED living is a popular residential option for older Americans. Designed to address the needs of those requiring help with activities of daily living, assisted living facilities are now home to more than 1 million people (1). This number will grow substantially as the population over 75 climbs from 16 million in 2003 to more than 25 million by 2025 (2). One of the reasons for the attractiveness of assisted living is its goal of providing a setting to "age in place," to remain in the facility without requiring discharge to a higher level of care, while maintaining a high degree of independence (3); indeed, residing in an assisted living facility may lead to more stable functioning than would community dwelling (4).

Maximizing independence is not always possible, however, as progression of underlying causes of disability may lead to increasing impairment. The World Health Organization defines disability to include any "impairment, activity limitation, or participation restriction" (5). Practically, one aspect of disability may be measured as an inability to perform instrumental or basic activities of daily living (IADLs—such as using the telephone, driving, or handling finances—or ADLs—bathing, dressing, feeding, transferring, and toileting). Such functional impairment is predictive of hospitalization, length of stay in hospital, or discharge to a nursing home (6). Functional dependency is also a predictor of nursing home placement out of the community, and of level of care within long-term care settings (7–11). Further, ADL dependency in nursing home residents is strongly predictive of facility resource use (12). In fact, functional impairment is a strong and consistent positive predictor of a number of adverse outcomes, as noted in a review of 167 different models from 78 studies (13). Functional impairment also adversely affects quality of life (14,15). Thus, decreasing the effect of functional dependency may be instrumental in reducing transitions to higher levels of care and improving the lives of long-term-care residents.

Few studies have estimated the effects of medical and cognitive factors on functioning. Schultz and colleagues (16) reported that cognitive impairment and behavioral disturbances are strongly predictive of impairment in ADLs and IADLs; however, that study was done entirely in a nursing home setting and with few independent variables. Cahn-Weiner and colleagues (17) found that among community-dwelling elders executive dysfunction and severity of depression were the strongest predictors of IADL impairment.

We could find no published study of functional impairment in the assisted living setting. Because functional impairment plays a major role in determining level of care and quality of life, and because its treatment or reversal may be a crucial aspect of helping individuals remain in assisted living, it is a subject well worth studying. Functional impairment in assisted living populations may be due, in part, to modifiable factors, so identifying these factors may lead to better resident care.

The Maryland Assisted Living (MD-AL) study examined a large, random sample of residents of assisted living facilities, and used direct examination by skilled evaluators and a series of cognitive and functional measures. This article furthers our understanding of this population by examining predictors of ADL and IADL dependency. The focus was to estimate the relative contributions of key putative predictors from the cognitive, medical, and psychiatric domains to functional impairment. The research hypothesis was that cognitive impairment, depression, and general medical health are major predictors of functional impairment in assisted living residents. The first aim was to estimate the relative independent contribution of these three factors to functional impairment. The second aim was to examine whether specific aspects of cognitive function or depression more adversely impact functioning than do other aspects. It was hypothesized that the bulk of the cognitive contribution to functional impairment would be attributable to selected domains, particularly executive dysfunction. It was also anticipated that low mood would be a stronger predictor of worse functioning than would behavioral disruption in depression.


   METHODS
Top
 Abstract
 Methods
Results
 Discussion
 References
 
The study design and implementation are described in detail elsewhere (3). Briefly, eligible facilities were selected randomly from a list provided by the State of Maryland. After informed consent was obtained, a study team went to each facility to examine a random sample of residents and to obtain information from staff and records. A clinical evaluation was followed by rating standardized measures of cognition and of psychopathology. The measures most relevant to this analysis are:

  1. Cornell Scale for Depression in Dementia (CSDD) (18);
  2. Psychogeriatric Dependency Rating Scale–Physical subscale (PGDRS-P) (19), rating activities of daily living, with scores ranging from 0 (not at all impaired) to 39 (severely impaired);
  3. IADL (20), rating instrumental daily living activities, with scores ranging from 8 (not impaired) to 31 (severely impaired); and
  4. General Medical Health Rating (GMHR) (21) of medical comorbidity, with scores ranging from 4 (excellent health) to 1 (poor health).

A psychometric technician also administered a battery of neuropsychological tests to each resident, including:

  1. Mini-Mental State Examination (MMSE) (22), a measure of global cognitive functioning, with scores ranging from 0 to 30 (higher scores indicating better functioning);
  2. Hopkins Verbal Learning Test-Revised (HVLT-R) (23), yielding a measure of delayed recall used here to indicate memory functioning;
  3. Developmental Test of Visual-Motor Integration (VMI) (24), a measure of visuospatial skills and praxis;
  4. Brief Test of Attention (BTA) (25), a test of auditory working memory sensitive to early dementia; and
  5. Trails Making Test B (Trails B) (26), testing executive function.

Functional impairment was operationalized as the sum of scores on the PGDRS-P and the IADL to capture impairment across a broad range; a higher score corresponds to greater impairment. To estimate the relative independent contribution to predicting functional impairment, the total impairment score was regressed separately on scores on MMSE, total CSDD, or GMHR. The choice of these measures was hypothesis driven. Covariates included dementia status, age, years of education, race, marital status, facility size (small/large), facility setting, caregiver's years of education, and caregiver's years of work experience. These covariates were included to evaluate whether they confound the effects of the predictors of primary interest.

Only those variables that were significant marginal predictors of functional impairment in the simple regression models were then included in a multiple regression model. Variables that showed no significance were excluded from further analyses. The variables that remained were deemed to be the significant predictors of functional impairment.

The same process was repeated for each of four cognitive battery tests and two subscales of the CSDD, mood and behavior. The four cognitive tests (described above) were the HVLT-R, measuring memory; VMI; BTA; and the Trails B. These four tests were taken to be representative of key cognitive functions.

In the multiple regression models, the significant cognitive tests replaced the MMSE, because this global scale is strongly colinear with the specific cognitive scales. The CSDD subscales score then replaced the total CSDD score to generate a final model. All data analyses were performed using Stata 7.0 (Stata Corporation, College Station, TX).


   RESULTS
Top
 Abstract
 Methods
 Results
Discussion
 References
 
Demographic characteristics of participants are shown in Table 1. Of 198 individuals under study, 134 carried a diagnosis of dementia (by criteria listed in The Diagnostic and Statistical Manual of Mental Disorders: DSM-IV-TR). Scores on cognitive measures are also shown in Table 1. As expected, the scores of those individuals with dementia were considerably lower than scores for those without dementia. The mean MMSE score for individuals with dementia was 14.6, compared to a mean MMSE score of 25.8 for individuals without dementia. The four cognitive battery tests—HVLT-R, VMI, BTA, and Trails B—all showed comparable differences. It must be noted that several participants could not complete these four tests, so the number of observations for these participants is lower than the number for the whole sample. Scores on the CSDD were similar between the groups. The mean GMHR fell between "fair" and "good," with very few participants being rated as "poor." Little difference was seen between the groups.


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  		Table 1. Characteristics of Individuals Surveyed in the Maryland Assisted Living Study*.

 
Participants with dementia showed greater functional impairment, and scored higher on both the PGDRS-P and the IADL (Table 2). The distributions of impairment measures are in Figure 1, A–C. Both ADL impairment and IADL impairment show broad distributions, offering significant variance to be explained. A visual examination of the relationship between functional impairment and scores on MMSE, CSDD, or GMHR suggests that these relationships are approximately linear (Figure 2, A–C).


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  		Table 2. Summary of Scores on the Psychogeriatric Dependency Rating Scale, Physical Subscale, and the Instrumental Activities of Daily Living, by Task.

 


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  		Figure 1. a, Distribution of scores on the Psychogeriatric Dependency Rating Scale-Physical Subscale (PGDRS-P) (a) and Instrumental Activities of Daily Living (IADL) rating (b). c, Distribution of total impairment scores (IADL + PGDRS-P)

 


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  		Figure 2. a, Impairment as a function of score on the Mini-Mental State Examination (MMSE) (a), Cornell Scale for Depression in Dementia (CSDD) (b), and General Medical Health Rating (GMHR) (c)

 
Simple regression models revealed MMSE, CSDD, GMHR, age, dementia status, and facility size to be significantly predictive of functional impairment (Table 3). Lower MMSE score was predictive of greater impairment, explaining about 36% of the variance. CSDD and GMHR scores showed weaker effects, explaining 3% and 6% of the variance, respectively. The lesser impairment predicted by residing in a large facility might be spurious, being explained by the greater prevalence of dementia in small facilities (3). All other variables examined showed no significant effect.


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  		Table 3. Results of Univariate Linear Regression: Significant Correlates of Total Impairment*.

 
When these six variables were used in a multiple regression model, only MMSE, CSDD, and GMHR remained significant predictors (Table 4, Model 1). Thus, the final model for the first aim includes only MMSE, CSDD, and GMHR (Table 4, Model 2). MMSE is the strongest correlate of functional impairment in this model, with its non-overlapping association with impairment ("rho-squared") accounting for nearly 40% of the variance. Among residents of assisted living facilities, a 10-point decline in MMSE score was predictive of a 7.4-point increase in functional impairment, or about three quarters of a standard deviation in the impairment distribution. CSDD had less explanatory power (rho-squared = 0.03), but it can still be said that depression was significantly predictive of greater functional impairment, with a 10-point increase on this scale leading to a 3-point increase in predicted impairment. Finally, worse medical health also was predictive of greater impairment. The difference between a GMHR score of 4 ("excellent") and a score of 2 ("fair") was just over 5 points on the scale of functional impairment, comparable to the effects of a 7-point drop in MMSE.


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  		Table 4. Results of Multiple Linear Regression: Significant Correlates of Total Impairment*.

 
For the second aim, evaluating the effects of specific components of cognition and depression, results of the simple regression analyses are shown in Table 3. As mentioned, in using cognitive battery tests, several observations were lost due to the inability of some participants to complete all tests; only 131 of the total effective sample of 198 were able to complete the Trails B test. Three of the four cognitive battery tests were significantly predictive of functional impairment; only BTA score was not. HVLT-R, VMI, and Trails B each had strong explanatory power, explaining between 18% and 25% of the variance in functional impairment. Higher scores on the CSDD subscales for mood and behavior—simply portions of the full CSDD scale—were predictive of greater functional impairment in univariate analysis, although each still had low explanatory power.

The three cognitive battery tests that were significant predictors were inserted in place of MMSE in the model developed in the earlier analysis. These tests were included first with the total CSDD score before using CSDD subscales to compare the effects of using specific cognitive tests to the effects of using MMSE score. The most salient change was that total CSDD score no longer showed a significant association with functional impairment (Table 4, Model 3). Although not shown, this was also true of the CSDD subscales for mood and behavior. Therefore, although all three battery tests remained significantly predictive of functional impairment, neither depression nor any examined component of depression remained a significant predictor, leaving the final regression model to include only cognitive tests and general medical health (Table 4, Model 4) as predictors of functional impairment.

The final model thus suggests that memory, praxis, and executive function impact functional impairment, whereas attention does not. A 10-point drop on the HVLT-R yields an approximately 6-point greater predicted functional impairment, whereas a similar drop in VMI is predictive of a 7.5-point loss of functioning. Trails B scores have a smaller but still significant effect. General medical health remained a significant predictor. The non-overlapping effects of executive dysfunction were the greatest, explaining roughly 13% of the variance in functional impairment, although the other two cognitive measures and the medical health rating also had important non-overlapping associations with functioning. Overall, these four variables accounted for roughly 44% of the total variance in functional impairment.


   DISCUSSION
Top
 Abstract
 Methods
 Results
 Discussion
References
 
These results demonstrate that global cognitive function, severity of depression, and medical comorbidity independently predict functional impairment in residents of assisted living facilities, with cognitive function being the strongest predictor. None of the demographic, facility, or caregiver variables, including age and education, was a significant independent predictor. Approximately 43% of the variance in total functional impairment could be explained by these three general measures.

Second, executive function, praxis/visuospatial skills, and memory were all independent significant predictors of functional impairment in residents of assisted living facilities. The only cognitive domain not significantly associated was attention. When all three cognitive domains were included, severity of depression was no longer predictive of functional impairment. This may be an indication that cognitive dysfunction associated with depression is the critical component of depression's effects and that the MMSE does not capture depression-related cognitive impairment as well as the cognitive battery tests.

It is possible that attention is not significantly predictive of impairment because caregiver assistance may be sufficient to overcome inattentiveness. Although executive function was a slightly stronger predictor, the fact that three measures (executive function, praxis/visuospatial skills, and memory) were all significant indicates that no single aspect of cognition solely accounts for impairment.

These results are generally consistent with findings of earlier studies. Cognitive function has previously been reported to be a significant predictor of functional impairment (13,16,27), although none of these studies examined residents of assisted living facilities. Several studies, including Miller and Weissert's large-scale review, indicate that depression is also a significant predictor of functional impairment (13,17,28), consistent with this study's initial findings and contradicting the findings of Schultz and colleagues (16). Similarly, medical comorbidity has been found to be significantly predictive of functional impairment (13,17).

The current study's results in examining specific domains of cognition differ slightly from previously published results. Cahn-Weiner and colleagues (17) found that, of the cognitive domains, only executive function was significantly predictive of functional status; other domains such as memory, language, and spatial skills were not. By contrast, in this study, executive function, visuospatial skills, and memory all significantly predicted functioning. Furthermore, Cahn-Weiner and colleagues (17) found depression to be a significant predictor of functional status, which was not the case here when specific cognitive functions were accounted for. These differences may be explained by differences in the populations studied and in the power of the two studies. Whereas the Cahn-Weiner study examined 27 community-dwelling individuals, the current study examined 198 assisted-living residents. In addition to differences in sample size, residents of assisted living facilities are likely more disabled and more cognitively impaired than are community-dwelling individuals, on average, and thus may display different relationships between cognition and functional status. Related to this point, the Cahn-Weiner study only examined IADL impairment, whereas here impairment was assessed across both IADLs and ADLs.

Richardson and colleagues (29) reported that executive dysfunction does not predict ADL impairment, but that visuospatial and memory skills do. This result contrasts slightly with the results presented herein, but the contrast may be explained by the greater power of our study. The results of the current study do agree with earlier findings, however, in that executive dysfunction is the strongest predictor of functional impairment. Apparently, this is true both for community-dwelling individuals (17,30) and for residents of assisted living facilities.

This study has several advantages over earlier studies in terms of understanding the assisted living population. In a PubMed search for articles on functional impairment, only one was found to have focused on an assisted living population. That study was of limited generalizability, focusing on a single assisted living facility designed to be affordable for individuals of lower socioeconomic status, biasing the results compared to the general assisted living population (4). The MD-AL study, by contrast, examines a random sample of residents in 22 assisted living facilities in Maryland, which is likely representative of the assisted living population nationally (3). Furthermore, in the earlier study, Fonda and colleagues (4) looked only at patterns of functioning, not at predictors of functional impairment, the primary aim of this study. No study was found that examined predictors of functional impairment specifically in a population of residents of assisted living facilities.

Limitations of the current study include its cross-sectional nature, the use of a single scale combining IADL and ADL, the study sample's concentration in one state, and the fact that a substantial proportion of participants were not able to complete a subset of the neuropsychological tests.

The next logical step in this research may be to extend these results from a cross-sectional study to a longitudinal study. This extension will allow the determination of factors that are most predictive of changes in functional impairment, a more powerful result than knowing which factors are cross-sectionally predictive of levels of functioning. This step is anticipated as more data from the MD-AL study become available in the study's longitudinal phase, currently underway. It will also be possible and desirable to investigate the impact of functional impairment on caregiver burden, often a critical factor in moving residents of assisted living facilities to higher levels of care.

Ultimately, the goal of the MD-AL study is to contribute to the design of strategies to improve functioning and quality of life of residents of assisted living facilities. Such strategies may then be tested in randomized controlled trials. With the results presented here, assisted living facilities may be able to contemplate care plans that use facility time and money more efficiently in targeting the impairments that most significantly impact functioning. Strategies may either take the form of assigning more intensive care or more extensively trained caregivers to residents of assisted living facilities with greater executive dysfunction, memory impairment, and apraxia or simply of allowing those with greater impairment more time to complete difficult tasks. At the very least, a better understanding of a resident's impairment may help to alleviate much frustration on the part of the resident and the caregivers; this frustration is often responsible itself for many more problems that may lead to lower quality of life or earlier discharge to a nursing home. It is the authors' hope that this study and its continuations will lead to an improvement in the care of residents of assisted living facilities.


   Acknowledgments
 
This study was supported by a John A. Hartford Scholar grant from the American Federation for Aging Research, by a grant from the Office of the Dean of Students at the Johns Hopkins University School of Medicine, and by grant RO1 MH 60626 from the National Institute of Mental Health. We are grateful to the study participants and their families for their participation, to the management and staff of the participating assisted living facilities, and to the staff at Copper Ridge for their dedication and assistance in the development of the MD-AL study.


   Footnotes
 
Decision Editor: John E. Morley, MB, BCh

Received September 16, 2003

Accepted November 13, 2003


   References
Top
 Abstract
 Methods
 Results
 Discussion
 References
 

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