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a New England Research Institutes, Watertown, MA
b Geriatric Research, Education and Clinical Center, Durham Veterans Affairs Medical Center, and School of Nursing and Department of Medicine, Duke University Medical Center, Durham, NC
c Center for Study of Aging and Human Development, Long Term Care Resources Program, Duke University Medical Center, Durham, NC
Correspondence: Stephanie J. Fonda, PhD, New England Research Institutes (NERI), 9 Galen St., Watertown, MA 02472. E-mail: sfonda{at}neri.org.
Decision Editor: Laurence G. Branch, PhD
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Abstract |
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Key Words: Functional patterns • Long-term care • Longitudinal assessment • Transition
A basic goal of much recent gerontological research is to delineate patterns of aging and to identify the many individual and environmental factors that shape these patterns. This research has suggested that there is considerable heterogeneity in patterns of aging in all studied populations; for example, some older adults experience periods of decline occasioned by episodes of partial recovery, whereas a majority experience both sustained good health and stable disability until the end of life (Beckett et al. 1996
; Clipp, Pavalko, and Elder 1992; Crimmins and Saito 1993; Maddox 1987; Manton, Corder, and Stallard 1993; Mor, Wilcox, Rakowski, and Harris 1994; Verbrugge 1989). This research has also suggested that some of the observed heterogeneity in patterns of aging is due to variation in residential milieu (e.g., Bengtson, Burgess, and Parrott 1997; Hochschild 1973; Lawton and Nahemow 1973). Assisted living housing (ALH)—defined generally as any group home-like residential program with the capacity to care for people with disabilities on an as-needed basis (Citro and Hermanson 1999; Kane and Wilson 1993; Maddox 2001; Pruchno and Rose 2000)—recently has attracted attention as a potentially beneficial milieu for the physical and mental health of older people, particularly those not in need of skilled nursing services (Fonda, Maddox, Clipp, and Reardon 1996; Moos and Lemke 1994). Empirical support for concluding that it is an especially beneficial milieu, however, has accumulated slowly. Even research simply describing the functional patterns of ALH residents has been limited. Thus, in this study, we examined the functional patterns of residents of an affordable ALH facility and evaluated comparatively whether the residents had beneficial outcomes. We focused on a unique group of ALH residents, specifically low-income residents in an affordable ALH facility, and compared them to similarly low-income elderly people residing in the community at large. The ALH residents were unique because relatively few low-income elderly people live in this type of milieu (Maddox 2001).
The growing desirability of ALH as a long-term care option for older people is evident in the rate at which it has spread throughout the United States in the past decade (Maddox 2001). Although differing terms for ALH facilities make it difficult to obtain precise estimates, it appears that ALH has grown at a rate of 15% to 20% in recent years, making it among the most rapidly growing type of age-friendly housing in the United States (American Health Care Association [AHCA], 1998; Citro and Hermanson 1999; Maddox 2001). Thirty-seven states had licensure regulations, were drafting regulations, or provided Medicaid funding for ALH facilities in the mid-1990s (Mollica and Snow 1996). Eight more states were studying ALH as a possible long-term care option. Additionally, about 1.15 million people were living in ALH as of 1998 (AHCA 1998). This number is likely to increase substantially as the Baby Boomers approach late life.
The idea that the ALH milieu could enhance well-being has its roots in ecological perspectives on aging, specifically the ecology of aging model (Lawton and Nahemow 1973) and congruence models of person–environment fit (Kahana 1982). Lawton and Nahemow, in their groundbreaking article, "Ecology and the Aging Process," (1973), developed the concepts that inform prominent environmental theories of aging—individual competence and environmental press. They defined competence as an individual's cognitive and physical capacity to meet his or her own needs. It varies from individual to individual and within individuals as well, often as a function of factors such as illness and advancing age. This variation relates to the range of experiences to which people can adapt comfortably. Environmental press refers to the aspects of settings with which people continually interact that activate their needs and that can be challenging, neutral, or supportive. Highly competent people fare better in environments that have more press and that promote autonomy, whereas less competent people fare better in environments with less press and more security (Lawton and Nahemow 1973; Parmelee and Lawton 1990). A congruence model focuses on the fit between individuals' competencies and the demands of their environments. When fit between the characteristics of the environment and the needs of older people is achieved, personal well-being results (Kahana 1982).
The model of selective optimization with compensation also emphasizes the contribution of environment to well-being. In this model, selection is the process whereby older people redefine their goals and modify their normal activities, goals, and environments in response to changes (usually losses) in their personal abilities or resources (M. M. Baltes and Carstensen 1996; P. B. Baltes and Baltes 1990). As an example, an older woman who relocates to a smaller apartment because her spouse dies or because she can no longer maintain a house engages in selection. The choices people make when they redefine their goals and choose modifications are probably shaped by their feelings of self-efficacy and agency (Bandura 1977, Bandura 1982). Compensation is the process whereby older people find new ways to maintain existing goals (i.e., they do not modify their goals, as they do in the selection process) in response to changes in their abilities or resources. Older people who purchase housekeeping services when they can no longer keep house themselves, for example, are compensating according to this model. Optimization refers to the process by which older people relearn how to do things for themselves and thereby regain functioning, health, autonomy, and so forth. Older people who behave more autonomously after moving out of overprotective settings into environments designed to enhance independence have experienced optimization (M. M. Baltes and Carstensen 1996). The idealization of ALH seems to lie in its promise to provide reliably available, as-needed compensatory care for people whose physical resources decline as well as opportunities for optimization among those who find they have physical reserves on which to draw.
A substantial literature focusing on earlier forms of congregate housing for older people suggests that the expectations of environmental models of aging and the model of selective optimization with compensation are largely realistic (e.g., Carp 1966, Carp 1974, Carp 1977; Cohn and Sugar 1991; Lawton and Cohen 1974; Moos and Lemke 1994; Sherwood, Morris, and Ruchlin 1986; Wetle 1991). Of particular relevance to our study is the research showing the relationship in the context of noninstitutional milieus. For example, in a longitudinal, quasi-experimental investigation of aged residents living in a congregate facility, Carp 1966, Carp 1974, Carp 1977 found that the facility's residents reported better mental and physical health and were more active than sociodemographically similar people living in the community. Similarly, Lawton and Cohen 1974 compared the well-being of older adults who moved to five senior housing facilities with older adults who remained in place in the community. They found that the people who relocated to the senior housing facilities had poorer physical functioning relative to the community-dwelling people, but were better off in terms of morale and satisfaction with their housing. Moos and Lemke 1994, in one of the most far-reaching studies of person–environment interaction to date, observed the health and well-being of residents in over 262 nursing homes, residential care facilities, congregate apartments, and veteran's facilities. They found that residents of settings with socioeconomically homogeneous populations and high levels of activity reported more involvement in on-site, organized events, regardless of their level of disability. In addition, residents who lived in facilities with more prosthetic features (e.g., hall railings, nonskid floor surfaces, etc.) reported higher levels of independence. Studies such as these suggest that milieu is linked to maintenance or improvements in health and individuals' abilities to adapt to problems.
Few studies have examined the relationship between the newer ALH milieu and residents' well-being, however, and studies that have are inconclusive. For example, Grayson, Lubin, and Van Whitlock 1995 compared the depressive affect of people living in an ALH facility with that of people residing in the community. They found that the depressive affect of the ALH residents was, on average, worse than that of the community residents. The cross-sectional design of that study makes it difficult to know whether the affective functioning of the people in the ALH setting had improved or would improve over time and thus was beneficial (or not) for residents. In another study, Pruchno and Rose 2000 compared the mortality rates, need for higher levels of care, cognitive status, depression, and subjective health of people in an ALH facility with people in a nursing home and found that the ALH residents were no better off than the nursing home residents were across all of the health outcomes they observed. They speculated that, because the ALH facility and the nursing home they observed were owned and operated by the same parent organization, their milieus might have been too similar to have meaningfully different effects on resident's well-being.
The study reported in this article was motivated by the scarcity of research on the functioning of ALH residents per se. The first objective was to characterize the individual-level, longitudinal functional patterns of older residents in an affordable, defined ALH milieu. Individual-level functional patterns are the temporal changes that each person experienced in their ability to perform everyday self- and home-care tasks. The categories used in our characterization of individual-level functioning (e.g., stable high functioning, stable low functioning, etc.) were adapted from a rubric developed by Clipp, Pavalko, and Elder 1992. The second objective was to compare the ALH residents' functional patterns with those for similarly low-income people who lived in the community, thereby providing evidence for whether the ALH residents had more or less beneficial outcomes. Given the tenets of environmental models of aging, the possibilities for optimization in the ideal ALH facility, and research on earlier forms of congregate housing, one might expect the ALH residents to have better outcomes than their community-dwelling counterparts. Or, given findings from the few studies focusing on ALH residents per se as well as explanations for why people move to congregate housing (e.g., in response to current or anticipated deterioration in health; Aday and Andersen 1974; Andersen and Aday 1978; Andersen and Newman 1973; M. M. Baltes and Carstensen 1996), one might expect the ALH residents to have less beneficial outcomes. As a compromise, we posed a null hypothesis that the functional patterns of the ALH residents would be no different from those of their community-dwelling counterparts.
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Methods |
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Preliminary to characterizing the individual-level, longitudinal functional patterns of the ALH residents, we confirmed that this ALH facility was indeed supportive while also facilitating resident autonomy. We did so using the Multiphasic Environmental Assessment Procedure, which Moos and Lemke 1992, Moos and Lemke 1994 designed and used to characterize hundreds of congregate care facilities, nursing homes, and apartments for older people. We found that the ALH facility we studied had more features facilitating resident autonomy, such as prosthetic aids and availability of personal space, than the average apartment Moos and Lemke observed. It had fewer features providing social and cognitive support, such as social–recreational aids, orientation aids, safety features, and staff oversight, than did the average nursing home Moos and Lemke observed. There was more cohesion among the residents and interaction between the staff and residents at the ALH facility we studied than in the average age-segregated apartment Moos and Lemke studied, but less cohesion in the ALH facility than in the average congregate care facility. In short, the ALH facility we studied appears to provide a reasonably supportive social environment.
This article reports on the first cohort of older residents who moved into the ALH facility when it opened in 1993 (N = 92). An ALH staff member obtained information about each resident's functioning using the Duke Service Outcome Screen (SOS), which is a short form of the Older Americans Resources and Services Multidimensional Functional Assessment Questionnaire (Fillenbaum 1988; Fillenbaum, Dellinger, Maddox, and Pfeiffer 1978). The SOS asks about social demographics, general health status, functional status, social support, housing adequacy, economic status, and emotional well-being. The questions about functioning in the SOS profile were designed to be consistent with those included in population-based surveys of older people, such as the National Long Term Care Survey. This article presents SOS information obtained from ALH residents during three observations: before they moved into the facility, after 1 year of residency, and after 2 years of residency.
Comparison Samples.
We faced several challenges when selecting an appropriate benchmark for the ALH residents. First, because people with lower incomes tend to experience worse health outcomes than people with higher incomes do (e.g., Bunker, Gomby, and Kehrer 1989; Clark and Maddox 1992; House et al. 1994; Kaplan and Lynch 1997; Roberts and House 1994; Williams and Collins 1995), it was important that the comparison sample or samples be similarly low income. Second, the ALH residents were 50 years of age or older, so it was necessary that the comparison sample or samples were as well. Third, we required at least two observations of the comparison sample or samples, 2 years apart, so that we could delineate their functional patterns over the same span of time that the ALH residents were observed. Finally, it was necessary that evaluations of the comparison samples cover the same domains covered in the SOS profile, especially functional status. The Duke Established Populations for Epidemiologic Studies of the Elderly (EPESE) initially seemed an obvious choice for a comparison sample because it sampled older people residing in North Carolina; however, the Duke EPESE used a different schedule for including the full set of questions about functioning and it sampled an older cohort (i.e., people aged 65 and older at baseline). Instead, the Health and Retirement Study (HRS) and the Asset and Health Dynamics of the Oldest Old (AHEAD) study together met most of our selective criteria.
The HRS and AHEAD study are nationally representative, prospective studies of community-dwelling middle-aged and older Americans, designed to investigate their health transitions and how these transitions affect finances, formal and informal support, family dynamics, and health care. They surveyed several, nonoverlapping cohorts enrolled at different time points: (a) the HRS cohort of people born between 1931 and 1941 (i.e., aged 51–61 years), studied since 1992; and (b) the AHEAD cohort of people born in 1923 or earlier (i.e., aged 70 years or older), studied since 1993/1994. The HRS reinterviewed respondents in 1994, 1996, and 1998 and the AHEAD study reinterviewed respondents in 1995/1996 and 1998. Because the format of certain questions in these surveys changed between baseline and the first follow-up interview, making longitudinal analysis with those particular interviews problematic, we used the 1996 and 1998 interviews of the HRS and the 1995/1996 and 1998 interviews of the AHEAD study. The availability of only two data points over the 2-year intervals for the HRS and AHEAD study meant that we could observe only transitions (not nonlinear trajectories) for these respondents.
Our comparison samples obtained from the HRS and AHEAD consisted of Caucasian and African American respondents who completed the questions about their functional status and had household incomes of $16,000 per year or less (standardized to 1993 levels to be consistent with the ALH residents). We excluded the small number of survey respondents who were living in senior housing, retirement communities, and other types of noninstitutional housing that provided services. This yielded samples of 1,759 HRS respondents and 2,258 AHEAD respondents.
Measures
The analyses reported here measured functional patterns in terms of the participants' self-reported abilities to perform activities of daily living (ADLs) and instrumental activities of daily living (IADLs). ADL indicators common to the interviews for the ALH residents, the HRS respondents, and the AHEAD respondents included bathing, transferring in and out of bed, dressing, eating, using the bathroom, and walking. IADL indicators included preparing meals, taking medications, managing money, using the telephone, and shopping for groceries. Similar to other examinations of functional patterns (Anderson et al. 1998; Manton, Corder, and Stallard 1997), we categorized individuals' functional abilities as independent (i.e., with no IADL and ADL difficulties), as IADL disabled only, or as ADL disabled. For follow-up observations, we had measures indicating whether the participants relocated to more care-intensive milieus (e.g., rest homes, nursing homes), died, or left the study for other reasons. For the ALH residents, these other reasons included relocation to the community because they needed more care from family caregivers or they wanted to live alone. ALH staff did not always know or note which reason applied. For the community respondents, the other reasons for leaving the study included refusal or nonresponse.
Several social–demographic and health variables were incorporated into this study as well. These were age, race (Caucasian or African American), gender, household income, number of life-threatening health conditions that the participants had (i.e., cancer, stroke, heart problems, and diabetes), and number of debilitating health conditions that the participants had (i.e., arthritis, high blood pressure, hearing problems, and vision problems).
Analyses
The analysis consisted of two parts. The first was primarily descriptive, involving application of Clipp and associates 1992 scheme for characterizing individual-level, longitudinal patterns in functional status. Their scheme included constant good health, decline at the end of life, decline and recovery, constant poor health, and linear decline. Similarly, our categories included stable high functioning, stable low functioning, decline, improvement, and competing risks such as institutionalization. We identified the rates at which patterns occurred among the ALH residents using information obtained from three data points: before they moved into the facility (baseline), after 1 year of residency (Wave 2), and after 2 years of residency (Wave 3). Inasmuch as the categories refer to strictly linear patterns, they apply to patterns defined by two data points as well.
A quasi-experimental approach characterized the second part of the analysis (Campbell and Stanley 1963). We compared the rates at which each pattern of functioning occurred for each group, using the baseline and Wave 3 observations for the ALH residents and the baseline and Wave 2 observations for the community respondents. We then investigated the relative likelihood that the ALH residents and community respondents experienced each functional pattern adjusting for salient social–demographic and health factors. For this, the three groups were combined into a single data set (N = 4109) and their functional patterns regressed on variables denoting study membership (i.e., ALH, HRS, or AHEAD), age, gender, race, income, debilitating health conditions, and life-threatening health conditions. We estimated a multinomial logit model, using Version 7 of the STATA statistical software (Stata Corporation 2001).
Because of the disparity in sample sizes across the study groups, we were concerned that the effects of membership in the HRS or AHEAD groups would overwhelm any effects of membership in the ALH group when we estimated the multinomial logit model. To explore this issue, we created 50 data sets consisting of all the ALH residents and 5% each of the HRS and AHEAD respondents. The HRS and AHEAD respondents were selected at random and with replacement for each data set. This strategy produced reasonably similar sample sizes across the study groups. Then we regressed the ALH residents' and community respondents' functional patterns on age, gender, race, health, and dummy variables indicating study membership using each of the 50 data sets (yielding 50 repetitions) and averaged the results. This approach was similar to bootstrap sampling and estimation. In brief, the results using the 50 smaller samples were very similar to those obtained using a single data set consisting of data from all of the respondents, eliminating concerns about the disparity in sample sizes. Thus we report the results from the first multinomial logit model described above, using the full, original samples.
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Several limitations of this study require comment before we summarize the results. First, because the ALH residents we observed were from lower socioeconomic backgrounds and were cognitively intact when they moved into the facility, the generality of our results are obviously limited. The reason is that people with lower socioeconomic status (SES) tend to experience worse health than do people with higher SES (e.g., Bunker, Gomby, and Kehrer 1989; Clark and Maddox 1992; House et al. 1994; Kaplan and Lynch 1997; Roberts and House 1994; Williams and Collins 1995). Thus we do not know what our findings imply about the functional patterns of ALH residents with higher SES. This is a drawback because ALH is a much more common option for higher SES people than it is for lower SES people. Moreover, the functional patterns of people with diminished cognitive abilities are probably worse than those of their higher functioning counterparts as well (Fitzgerald, Smith, Martin, Freedman, and Wolinsky 1993; Kasper 1990). Again, we do not know what the findings of this study imply about the functional patterns of more cognitively impaired people. Generalization to all ALH residents, however, was not a chief goal of this analysis; rather, we wanted to provide a rare look at the functional patterns of this special population. To our knowledge this is the first examination of functional patterns of low-income elderly people in ALH.
Second, although the two benchmark surveys represent community-dwelling older Americans aged 51 to 61 years and 70 years or older, they do not provide perfect comparison or control groups for the ALH residents we studied. One reason is that, until the studies merged in 1998, they did not include the cohort of people born after 1923 and before 1931. Our bootstrapping test partially dealt with the nonrandom inclusion of certain age groups, however, and still yielded results consistent with those reported in Table 3 . In addition, we know little about the survey respondents' milieus. It is possible that the people who lived in the community were less predisposed toward, or in need of, ALH or other types of long-term care settings when they were sampled (see Aday and Andersen 1974; Andersen and Aday 1978; Andersen and Newman 1973). What this study reveals then, is a sense of how the functional patterns of the ALH residents living in a defined milieu compared with the functional patterns of community-dwelling people in average, undefined environments. This average was affected by variation in the physical supports to which residents had access, the safety of their settings, other people living in their settings, their access to services, and so forth. Obtaining information about community-dwelling older adults, their settings, characterizing their functional patterns, and then comparing their functional patterns to those for ALH residents represent an area of further study. This information would facilitate formal, systematic tests of the person–environment relationship.
Third, it is difficult to know how to interpret the patterns we observed for the ALH residents. Are the patterns unique to these ALH residents or did residence in the ALH really have a favorable effect? Ambiguity regarding our findings is due to the homogeneity of the ALH residents at baseline. That is, 73% were independent and only 10% had ADL limitations (Table 2 ). Given the potential for ceiling and floor effects in our dependent variable (i.e., respondents with functional limitations had more opportunity to improve than did those with none and vice versa) and the observation that most people who are independent tend to remain so over time (Crimmins and Saito 1993; Manton et al. 1993), how much change can we expect to see? Still, there was sufficient variability in the ALH residents' functional patterns over time to suggest that they were more heterogeneous at baseline than indicated by the baseline data. Also, there were sufficient differences between the ALH residents and community respondents, despite their similarities with respect to baseline health and sociodemographics, to suggest reasonable causal inferences about the relationship of milieu to the ALH residents' functional trends.
Turning to our initial characterization of the ALH residents' functional patterns, we documented that most of the residents experienced favorable outcomes of some sort. These favorable outcomes included stable high functioning, improvements in IADL and ADL functioning, and stable low functioning. We counted residents who experienced stable low functioning among those who have favorable outcomes because we believe their continued tenure in the facility suggests that the ALH milieu enabled this at-risk group to live independently (possibly through compensation) and to avoid further deterioration in functioning and institutionalization. Together, stable high functioning (by far the most common pattern of the three), improvement, and stable low functioning accounted for at least 52% of the ALH residents' experiences. We suspect that this percentage would have been higher if there were more information available about the residents who returned to the community during the study. The other functional patterns of the ALH residents included decline in functioning, relocation to more care-intensive milieus, and death. These patterns together accounted for the remainder of the ALH residents' experiences. Their high prevalence was not particularly surprising; people at risk of worsening health tend to move into milieus where they can live more comfortably with those problems and/or receive care (Andersen and Newman 1973; Wolinsky and Johnson 1991). Thus many of the ALH residents probably were at elevated risk from the outset and the prevalence of these patterns captured some of that. We know from the prevalence of improvement and stable low functioning, however, that in spite of being at risk of worsening health, optimization was possible.
Although it was important to characterize the functional patterns of the ALH population, it was unclear, without benchmarks, what those patterns indicated about the comparative well-being of the ALH residents. One of the most important contributions of this study is its juxtaposition of the ALH residents' patterns with those identified among community-dwelling people. The (adjusted) results indicate that the ALH residents were no more or less likely to have experienced improvement, decline, and death than were their community-dwelling counterparts. This was consistent with our null hypothesis and can be considered a comparatively beneficial outcome assuming the ALH residents were indeed at higher risk from the outset. But contrary to the null hypothesis, the ALH residents fared better than their community-dwelling counterparts in some ways; specifically, the ALH residents were more likely than the community respondents to have maintained high functioning during the 2-year interval of observation. This finding was consistent with environmental models of aging (e.g., Kahana 1982; Lawton and Nahemow 1973; Parmelee and Lawton 1990) and previous studies of earlier congregate housing for older adults and resident well-being (e.g., Carp 1966, Carp 1974, Carp 1977; Cohn and Sugar 1991; Lawton and Cohen 1974; Moos and Lemke 1994).
An important question underlying this study is whether or not the ALH model should be generalized to other older people seeking congregate housing with services. The implicit criterion for making this determination is whether the ALH milieu can be shown to have some positive effect on the well-being of its residents, including, among many components, physical functioning. Given the rapid expansion of ALH in the past decade (AHCA 1998; Citro and Hermanson 1999; Maddox 2001), however, it is clear that the ALH model already has been generalized without evidence demonstrating its positive effects. Therefore the utility of results such as those reported here lies in their ability to show for whom and under what circumstances the ALH model should be generalized. This study suggests that the ALH model holds utility for low-income older adults by helping them maintain stable high functioning at rates that reflect at least two normative samples of older, community-living people, by providing opportunities for improvement and by helping functionally impaired persons attain the goal of independent living through the provision of as-needed compensatory care.
Practice Concepts
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Acknowledgments |
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Received for publication May 8, 2001. Accepted for publication September 28, 2001.
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