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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 57:M778-M784 (2002)
© 2002 The Gerontological Society of America

Effects of Cognitive Performance on Change in Physical Function in Long-Stay Nursing Home Residents

Eleanor S. McConnella,b,d, Carl F. Pieperb,c, Richard J. Sloaneb and Laurence G. Branchb

a School of Nursing, Duke University, Durham, North Carolina
b Duke University Center for the Study of Aging and Human Development, Durham
c Division of Biometry, Department of Community and Family Medicine, Duke University, Durham
d Geriatric Research Education and Clinical Center, Department of Veterans Affairs Medical Center, Durham

Eleanor S. McConnell, School of Nursing, Duke University Medical Center, Box 3322, Durham, NC 27710. E-mail mccon002@mc.duke.edu

Decision Editor: Pamela Z. Cacchione, PhD, RN


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
Background. Determining the nature and rate of change in physical function among long-stay nursing home (NH) residents classified by cognitive performance is needed to inform judgments about prognosis and design of clinical trials to minimize functional decline.

Methods. The study consisted of a longitudinal analysis using random coefficients models of 71,388 noncomatose residents aged 65 and older admitted in one of five states participating in the Health Care Financing Administration-sponsored National Case Mix and Quality Demonstration Project who stayed in the nursing home 1 year or longer. Linear effects of cognitive impairment on admission and over time on the trajectory of dependence in activities of daily living (ADLs) were estimated, adjusting for demographic status upon admission. Interaction terms were used to determine if subgroups of residents at the same cognitive level were at risk for a steeper than average rate of decline. Measures were derived from the NH Minimum Data Set (MDS+) ratings of each domain. Cognition was measured using the MDS–Cognitive Performance Scale. Physical function was determined by summing ADL dependence ratings of bathing, dressing, grooming, toileting, and eating (range 0 to 20). Demographics included age, gender, race, and marital status.

Results. On average, ADL dependence worsened 0.84 points per year among these long-stay residents. Only cognition and marital status had clinically significant effects on ADL dependence. Married residents exhibited more ADL dependence than unmarried residents. Severity of cognitive impairment on admission and over time influenced severity of ADL dependence but not rate of decline. No interaction terms were clinically significant.

Conclusions. Clinicians seeking to identify factors that accelerate ADL decline in long-stay NH residents must examine explanatory variables other than cognitive impairment and demographics.

COGNITIVE impairment sufficient to influence physical function affects more than 60% of elderly nursing home (NH) residents (1)(2); however, we lack basic information on the rate and nature of change in physical function among these older adults. Estimates from longitudinal studies of community-dwelling older adults with cognitive impairment (3)(4)(5) may not generalize, because NH residents have more extensive comorbid illness and the NH environment itself may influence function (6). Currently available estimates are based on analyses of the first 90 days of NH stay (7) or of specialized populations (8) and, therefore, are inadequate for understanding how function changes in long-stay residents. Accurate estimates of rates of change in physical function among NH residents with cognitive impairment can facilitate clinicians' ability to give accurate prognosis and to design therapeutic intervention trials.

Implementation during the 1990s of the NH Minimum Data Set (MDS), a uniform assessment instrument with reliable and valid measures of cognitive impairment and dependence in basic activities of daily living (ADLs), performed on admission with required quarterly reassessments (9), provides an opportunity to examine trajectories of change in physical function among large numbers of NH residents nationally. The purpose of this article is to describe the effects of NH residents' level of cognitive impairment, both upon admission to the NH and as it changed over time, on subsequent change in physical function, after adjusting for demographic status, in a retrospective analysis of a multistate dataset of NH resident assessments. The research questions we address in these analyses are: (i) Does the rate of change in ADL dependence differ according to level of cognitive impairment on admission? (ii) Do demographic variables influence rate of change in ADL dependence, either alone or in combination with cognitive impairment? (iii) Over the course of NH residence, do changes in cognitive impairment influence severity of ADL dependence?

By clarifying these questions, we intend to provide NH clinicians with information about whether there is a subset of residents, defined by their level of cognitive impairment or demographic characteristics, whose subsequent decline in physical function is accelerated sufficiently to merit consideration of special interventions to reduce that decline.


   Methods
Top
 Abstract
 Methods
Results
 Discussion
 References
 
Design
We obtained all MDS+ assessments (3,320,942 observations from 489,451 unique residents) from all Medicare- or Medicaid-certified facilities in five of the six states that participated in the Health Care Financing Administration (HCFA)-sponsored National Case Mix and Quality Demonstration project: Kansas, Maine, Mississippi, New York, and South Dakota. HCFA compiled into a research database full MDS+ assessments transmitted electronically from 1992 through 1997. By law, assessments occur within 14 days of admission to the NH, every 90 days thereafter, and with each significant change in condition.

After excluding those younger than 65 years of age and those for whom data quality was poor, we constructed longitudinal files for each resident admitted from 1993 to 1996. We stratified residents according to their admission cognitive performance score and excluded those who were comatose or had severe cognitive impairment and total dependence in eating on admission. Using random coefficients modeling, we estimated trajectories of change in ADL dependence for each resident who stayed in the NH for 1 year or longer. We then examined the effects of admission cognitive impairment on linear change in ADL dependence, controlling for demographic variables. In a second step, we estimated the effects of cognitive impairment on ADL dependence as a time-varying covariate. The intercept was placed at time zero, representing mean severity of ADL dependence on admission to the NH. To control for differences in long-term care policy among states, separate analyses were conducted for each state.

Subjects
We excluded in the following order (i) any admissions prior to 1993 (33%), (ii) those who were not aged 65–99 years at intake (11%), (iii) those who had a nonstandard social security number (1%), and (iv) those who lacked an initial assessment within 21 days of admission (9%). Because many NH residents experience episodic illness requiring brief hospital stays, we treated MDS+ assessments occurring within 120 days of a prior assessment as part of a continuous NH stay, even if the stay was marked by a discharge and readmission to the NH. We defined a long-stay resident as any individual who had MDS+ assessments present 1 year after the initial admission to the NH and who contributed four or more assessments to the database. After applying these criteria, 76,016 unique residents were available for analysis. We then excluded those who were comatose or who had such severe cognitive impairment that they were totally dependent in eating (n = 4628) leaving an analytic sample of 71,388 residents. These residents had an average of 10.5 ± 3.7 assessments per resident and an average of 2.1 ± 0.8 years of follow-up.

Measures
Development of the MDS has been described extensively (9)(10)(11)(12). Reliability of cognitive and physical function ratings when made either by research or nonresearch assessors have been reported as good to excellent (13)(14)(15)(16)(17). Chance-corrected measures of agreement for ADL items ranged from .69 to .92, and for cognitive ratings ranged from .55 to .88 (13). MDS subscales have concurrent validity with established instruments for measuring cognitive function (14)(15)(16) and physical function (16)(17)(18).

Cognitive impairment was measured using a modified MDS–Cognitive Performance Scale (CPS), an ordinal rating scale ranging from 0 to 6, formed by applying decision rules to MDS+ ratings of cognitive abilities observed by NH staff over a 7-day period (19). Based on previous research demonstrating minimal differences across certain CPS levels, we created a simpler classification of cognitive impairment by CPS levels as follows: CPS 0 = no impairment, CPS 1 or 2 = mild impairment, CPS 3 = moderate impairment, CPS 4 or 5 = severe impairment (20).

Demographic status was rated based on the admission MDS+ assessment using precoded categories (21). When data were missing from the admission assessment for race and gender, we imputed a value from the modal response recorded on the remaining MDS+ assessments. For those missing marital status on admission (maximum of 1.1% in NY), we assigned the value recorded on the first observation with a nonmissing value.

Physical function was measured by the sum of MDS+ ratings denoting assistance needed from staff in each of five ADL tasks: dressing, eating, toilet use, personal hygiene, and bathing. ADL dependence scores ranged from 0 to 20 points, where 0 indicated no dependence on others at all, including no need for encouragement, cueing, or supervision to perform these tasks, and 20 denoted individuals who were completely dependent in all ADLs. Over all waves of measurement, missing data rates for ADLs were low with three exceptions: (i) in New York, 48.9% of grooming ratings were missing; (ii) in Kansas, 49.2% of bathing ratings were missing; and (iii) in Mississippi, 5.9% of dressing ratings were missing. These values were imputed by calculating a predicted value for the missing ADL element based on the ratings of the individual's performance on the four remaining ADL components present for that observation. Thus, the imputed values for ADL dependence were based on 80% of the possible data available for the ADL rating for a given observation.

Analysis
Because the design of this data set is unbalanced (subjects have differing numbers of observations due to death, movement out of the NH, and time on study), we employed mixed models as the statistical methods appropriate for unbalanced repeated continuous outcomes (22). To model trajectories of ADL dependence, we extended this model to allow for a random intercept and slope for every subject as defined by random coefficients models (23). As a final step, these individual trajectories were aggregated to provide tests of differences between groups. Trajectories of ADL dependence were modeled as a linear function only; quadratic and higher order terms were not examined because of our desire to keep the models readily interpretable for use in clinical practice.

The mixed model procedure described above was performed separately for each state, because demographic characteristics and long-term care policies differ by states. A summary weighted average of these individual state estimates was then calculated using the inverse of the squared standard error as the weight, while the standard error for this estimate was calculated as the square root of the sum of inverse squared standard errors (24). To learn whether demographic variables influenced the rate of worsening ADL dependence for those at different levels of cognitive impairment on admission to the NH, we first modeled ADL dependence as a linear function of demographic variables, modified CPS score upon admission, time since admission to the NH, measured in months, each pairwise interaction between demographic variables and modified CPS, demographic variables and time, and the three-way interactions between demographic variables, modified CPS, and time. Interactions were computed as a product term between time (months) and all available levels of the independent variables included in the model. Presence of such interactions would indicate that increases in ADL dependence over time differ by demographic status as well as level of cognitive impairment. Owing to different rates of decline, selected groups of residents would possibly need a different preventive approach. However, we would only want to draw this conclusion if interactions were observed in the majority of states and if the effect was clinically significant. We therefore established the following criteria a priori for determining a clinically significant interaction: (i) effect statistically significant at p < .05 in four of five states, (ii) direction of effect consistent across all states, (iii) magnitude of effect results in a difference in the rate of decline in ADL dependence of one point per year or more.


   Results
Top
 Abstract
 Methods
 Results
Discussion
 References
 
Demographic and cognitive status upon admission to the NH is presented in Table 1 . The age, race, and gender distributions of this cohort are comparable to that of NH residents nationally (1)(2)(25). Between 17% and 26% of residents were married; the majority of unmarried residents were widows (59.9%–68.3%). Most residents (76.7%–89.4%) had some degree of cognitive impairment.


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  		Table 1. Admission Characteristics of a Cohort of Long-Stay Nursing Home Residents Admitted During Calendar Years 1993–1996, Excluding Comatose Residents and Those With Very Severe Cognitive Impairment (N = 71,388)

 
Shown in Table 2 is the distribution of the prevalence of selected chronic diseases and dependence in specific ADLs. After Alzheimer's disease and other dementing disorders, the most common disorder was arthritis, followed by stroke, diabetes mellitus, congestive heart failure, and chronic obstructive pulmonary disease. This cohort was more dependent in ADLs than NH residents nationally, reflecting the absence of short-term rehabilitation residents.


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  		Table 2. Admission Clinical Characteristics of a Cohort of Long-Stay Nursing Home Residents Admitted During Calendar Years 1993–1996, Excluding Comatose Residents and Those With Very Severe Cognitive Impairment (% Occurrence)

 
To understand the variability in trajectories of change in ADL dependence, we examined histograms of the frequency of occurrence of each of the slopes of change in physical function, unadjusted for cognition or demographics (Fig. 1). Using a change in ADL point of one or more per year as a criterion for change, between 30% and 34% remain unchanged, 13% to 23% improved, and 43% to 57% declined, depending upon state of residence. Although the unadjusted average change in ADL dependence among the long-stay NH residents is relatively small (0.95 + 3.0 ADL points on the 20-point scale), between 56% and 80% of residents experience greater change.



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  		Figure 1. Distribution of trajectory of ADL dependence in a cohort of long-stay nursing home residents admitted during calendar years 1993–1996, excluding comatose residents and those with very severe cognitive impairment. Distribution truncated for 98 (0.10% of sample) at ADL score = +14, and 15 (0.02% of sample) at ADL score -14. ADL = activity of daily living.

 
Table 3 displays results from the random coefficients model, where ADL dependence is estimated as a function of the resident's demographic status, admission level of cognitive impairment, time in months, and the interaction between time and cognitive impairment on admission. No clinically significant three-way interactions were identified, nor any two-way interactions involving demographic variables. We therefore reestimated the model without these interaction terms and present data from the simplified model.


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  		Table 3. Effects of Cognitive Impairment on Admission on Trajectory of ADL Dependence Among Long-Stay Nursing Home Residents in Five States Admitted to the Nursing Home Between 1993 and 1996, Controlling for the Effects of Demographic Variables on Admission and the Interaction Between Cognition and Time

 
After adjusting for demographic status and cognitive impairment, the average ADL dependence level for residents with CPS levels 4 and 5 on admission was 11.84 ± 0.17. The average rate of decline was 0.07 ± 0.005 ADL points per month, approximately 0.84 points per year. On admission, the most important predictor of ADL dependence was cognitive impairment, influencing ADL scores five to six points between the worst cognitive score and the best. Examination of the interaction between CPS score and time shows that severity of cognitive impairment on admission does not influence rate of ADL decline. The rate of ADL change between those with no cognitive impairment and those with severe cognitive impairment differed overall by only -0.02 ADL points per month. Thus, during 1 year, those with CPS scores of four to five on admission would have an expected rate of decline from admission of 0.84 ADL points per year. In contrast, those without cognitive impairment would be expected to decline only 0.24 points per year less rapidly.

Age was associated with worse ADL dependence in four of the five states, but the magnitude of the effect was small (beta = 0.03 ± 0.005); each decade difference in age resulted in only 0.3 points difference in ADL dependence. Marital status was related to ADL dependence (beta = 1.04 ± 0.04). Married residents were rated one ADL dependence point higher than those who were not married, with no difference in rate of change in ADL dependence between married and unmarried residents. Neither gender nor race influenced ADL dependence.

We also examined the effects of cognitive impairment as a time-varying covariate. In this approach, rather than using admission performance only to predict function, we evaluated the effects of cognitive impairment on ADL dependence at each time cognition was measured (Table 4 ). As expected, cognitive performance is highly associated with ADL dependence. Each increment in severity of cognitive impairment is associated with a one- to two-point increase in ADL dependence throughout the NH stay, after adjusting for admission cognition and demographics.


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  		Table 4. Effects of Changes in Cognitive Performance on Trajectory of ADL Dependence in a Cohort of Long-Stay Nursing Home Residents Admitted During Calendar Years 1993–1996, Excluding Comatose Residents and Those With Very Severe Cognitive Impairment

 

   Discussion
Top
 Abstract
 Methods
 Results
 Discussion
References
 
Using a trajectory analysis approach, we assessed the contributions of cognitive impairment and demographic variables to the severity of dependence and rate of change in physical function among an admission cohort of elderly, long-stay NH residents from five states. Cognitive impairment is associated with ADL dependence both on admission to the NH and throughout the stay; however, cognitive impairment does not significantly affect rate of decline. After taking into account changes in cognition over the course of the NH stay, the average annual decline attributed to severe cognitive impairment on admission is 0.24 points per year. In addition to cognitive impairment, marital status and age both significantly affect ADL dependence on admission, but their effects are quite modest relative to the influence of cognition.

This analysis adds to our understanding of change in physical function in these residents by adjusting the estimates of admission dependence in ADL for age, race, gender, and marital status and by demonstrating the influence of cognitive performance over time. Clinicians can conclude from these analyses that among elderly long-stay NH residents, there is no reason to expect that subgroups based on age, race, gender, marital status, or severity of cognitive impairment will decline in ADL dependence more rapidly than the average long-stay NH resident.

Three limitations of our analysis warrant mention. First, although the estimates presented are based on assessments of virtually all long-stay NH residents in a carefully constructed admission cohort drawn from geographically diverse states, they are not based on a national random sample of NH residents and, therefore, may not be representative of all states. The fact that, from a demographic standpoint, these residents are quite similar to those in national surveys strengthens our confidence in the generalizability of these results. Second, our analytic models are biased toward showing less rapid decline in function than is true for NH residents as a whole, for four reasons: (i) because residents who died prior to living one year in the NH were excluded from these analyses; (ii) nonlinear changes in ADL dependence were not examined; (iii) our imputation methods for ADL dependence are conservative, using an average of remaining ADL ratings within the individual to estimate the missing value, although the individual may have experienced more severe loss of function on that one item; and (iv) measures of central tendency, while necessary for summarizing large amounts of information, tend to obscure differences among individuals whose values lie along the extremes of statistical distributions. Maddox and Clark (26) have demonstrated nonlinear trajectories of age-related functional impairment among community-dwelling elders, so analyses of these trends in nursing home residents may be similarly revealing.

Third, the MDS+ does not measure educational attainment, and thus we were unable to adjust our estimates for educational level, a factor known to be associated with rates of decline in health status (27)(28)(29).

Across five states and three calendar years, we have described a general pattern of change in physical function over 1 year or longer characterized by slow linear decline among elderly long-stay NH residents. Although on admission dependence in ADLs is worse among married older residents with the most severe cognitive impairment, their rate of decline is unaffected by gender, age group, race, marital status, and level of cognitive impairment.

Clinicians seeking to identify factors that accelerate decline in this population to develop and test interventions to reduce its rate must consider explanatory variables other than cognitive impairment and demographics.


   Acknowledgments
 
This work was supported by the following grants from the National Institutes of Health: R29 NR04765: Disability in Nursing Home Residents with Dementia; 2 P60 AG 11268: Claude D. Pepper Older Americans Independence Center; and 1 P20 NR07795-01: Trajectories of Aging and Care in Nursing Science.

Received January 8, 2002

Accepted May 14, 2002


   References
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 Results
 Discussion
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