Institute for Life Course and Aging UNIVERSITY OF TORONTO Aging in Place Bridgepoint/LHIN Literature Review Prepared by: The Institute for Life Course and Aging University of Toronto Director: Dr. Lynn McDonald Research Coordinator: Julia Janes November 23, 2007
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Institute for Life Course and Aging
U N I V E R S I T Y O F T O R O N T O
Aging in Place
Bridgepoint/LHIN Literature Review
Prepared by:
The Institute for Life Course and Aging
University of Toronto
Director: Dr. Lynn McDonald
Research Coordinator: Julia Janes
November 23, 2007
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TABLE OF CONTENTS
Table of Contents.................................................................................................................................... 2
Findings ................................................................................................................................................ 6 Predisposing Characteristics............................................................................................................ 6 Enabling Characteristics .................................................................................................................. 6 Need Characteristics ........................................................................................................................ 7 Use Characteristics .......................................................................................................................... 7
Limitations............................................................................................................................................ 8 Methodological limitations in the literature: ................................................................................... 8 Content missing in the literature: ..................................................................................................... 8
2.1 Demographic Factors: Age, Gender and “Race”.................................................................... 15
2.2 Social Support......................................................................................................................... 16 2.2.1 Marital Status and Living Alone..................................................................................... 17 2.2.2 Adult Children and Other Kin Support........................................................................... 19 2.2.3 Caregiving ...................................................................................................................... 20 2.2.4 Dimensions of Social Support......................................................................................... 23
2.3 Beliefs and Expectations......................................................................................................... 25
2.4 Health Behaviours: Smoking, Alcohol Consumption and Physical Activity ......................... 27
Supportive/assisted Residential Models ......................................................................... 33 3.1.6 Type and extent of healthcare insurance ........................................................................ 40
3.2 Community, Market and Policy Resources ............................................................................ 41 3.2.1 Housing Market Conditions............................................................................................ 41 3.2.2 Neighbourhood Characteristics and Place Attachment ................................................. 41 3.2.3 Balance of Care: Availability of and Expenditure on Home and Community-Based
Services and Institutional Long-term Care..................................................................... 43
4. Need Characteristics........................................................................................................................ 49
5. Health Care Utilization ................................................................................................................... 54
5.1 Prior Nursing Home Admission and Hospitalization ............................................................. 55
5.2 Other Measures of Use: Paid Helpers, Doctors and Medications .......................................... 56
8.1 Appendix A: TABLES ........................................................................................................... 77 Table 1 Definitions of Accommodation and Care Settings ....................................................... 77 Table 2 Living Arrangements, Ontario, 1996, by Gender (65+, 65-74, 75-84, 85+) ................ 78 Table 3 Living arrangements of seniors aged 65 and over by sex and age group, 2001.......... 78 Table 4 Number of Equations (N) Reporting Positive Significant (+), Negative Significant (–),
and Non-significant (NS) Associations among Predictors and Adverse Outcomes.... 79
8.2 Appendix B: FIGURES .......................................................................................................... 82 Figure 1 Andersen’s Behavioral Model ..................................................................................... 82 Figure 2 Population Projections for Canada, Provinces, and Territories, 2005-2056 ............ 83
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Figure 3 Age of Toronto’s Senior Population ........................................................................... 84 Figure 4 Percentage of Canadians in Good Health, by Age Group, Household Population,
Aged 65 and Over........................................................................................................... 85
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EXECUTIVE SUMMARY
Aging in Place: a Review of the Literature
Background
The purpose of the literature review was to document the research that examines the predictors
of the institutionalization of the elderly. The review is grounded in the framework of “aging in place,”
which acknowledges that older adults wish to live in their own communities for as long as possible and
that home and community services will support this aim while being cost-effective.
The review is organized according to Anderson’s Behavioural Model of health services, which
groups predictors into four categories: predisposing, enabling, need and use characteristics.
Predisposing characteristics include demographics, levels and characteristics of social support, health
behaviours, beliefs and expectations. Enabling characteristics include familial and community
resources like neighbourhood context, supply of long-term care facilities and home and community-
based services, the balance of health care expenditures and health policy. Need characteristics include
indicators of self-rated and practitioner-evaluated health status. Use characteristics are essentially
indicators of health care utilization.
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Findings
Predisposing Characteristics
� Consistent predictors of institutionalization: age, Caucasian, living alone, having
fewer adult children and having low levels of community engagement;
� Modest predictors of institutionalization: lower levels of informal supports
independent of caregiver status, experience of severe loneliness;
� Interventions: targeted to those at the highest risk, as well as their caregivers, taking
advantage of existing care networks;
� Future research: aim to isolate the many dimensions of informal support and evaluate
their effect on different groups and in different contexts.
Enabling Characteristics
� Consistent predictors of institutionalization: not owning a home, living in an area
with a greater supply of nursing home beds;
� Modest predictors of institutionalization: lower household wealth and income in
terms of perceived adequacy rather than dollar value, living in areas with few affordable
small unit rentals, less access to assistive technologies and home modifications; living
in a socially “deprived” and poorly serviced neighbourhood, having “weak ties” to the
neighbourhood;
� Interventions: develop more age-appropriate affordable supportive housing, expand
utility subsidies and emergency funds; enhance neighbourhood health and social service
infrastructure;
� Future research: investigate issues such as availability and access to supports; attempt
to isolate features of “liveable” housing and communities that foster healthy aging and
independent living.
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Need Characteristics
� Consistent predictors of institutionalization: cognitive impairment, limited activities
of daily living (ADLs); impaired instrumental activities of daily living (IADLs);
depression, dementia and Alzheimer’s disease;
� Modest predictors of institutionalization: self-reported health status, self-reported
level of functioning; stroke and heart disease, digestive systems diseases, urinary and
bowel incontinence;
� Interventions: develop programs that allow aging in place for the cognitively impaired
and the frail elderly, similar to PACE programs;
� Future research: longitudinal, panel research with multiple measures of baseline
factors at a number of time intervals including time of placement.
Use Characteristics
� Consistent predictors of institutionalization: prior nursing home admission and
hospitalization
� Modest predictors of institutionalization: presence of formal help (paid or
professional care/services by doctors, home health aides, PSWs);
� Interventions educate older adults and their caregivers about community-care options;
ensure active involvement in discharge planning and the development of comprehensive
care packages;
� Future research: clarify the explanatory effect of prior use as to whether it is due to
greater acceptance by an older adult because of a previous placement or a bias of
service providers/discharge planners; disentangle the different types of formal help and
the mechanisms that impact residential outcomes.
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Limitations
Methodological limitations in the literature:
� The prediction of change, based on single cross-sectional baseline measures;
� Predictors of a change may be different from predictors of the type of change;
� Predictors of home and community-based care may be different than those that predict
moves to institutional settings;
� Easily measured predictors (e.g. scale–based health indicators) are more commonly
investigated than those that are more complex (e.g. community, market and policy
resources);
� Few random control trials, random sampling and qualitative studies.
Content missing in the literature:
� Attention to entries and exits from nursing homes to understand what leads to
institutionalization and what facilitates returns to the community;
� Investigation of the interface between hospital discharge/rehabilitation strategies and
nursing home use;
� Examination of the factors behind over and under care, particularly the role of health
policy/expenditures;
� Consideration of the impact of caregiver well-being on the recipients’ placement
outcomes;
� Evaluation of the clinical and quality of life outcomes for various residential options to
understand why a particular setting is the best possible fit for an older adult;
� Evidenced-based evaluation of the many promising community care and supportive
housing programs.
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1. INTRODUCTION
The ability to predict what factors lead to the institutionalization of older adults is relevant to
the current policy of aging in place in Ontario. The policy for aging in place is significant because the
majority of older adults prefer to age in their own communities while maintaining their health,
autonomy and dignity. At the same time, the policy is advantageous to society as a whole because the
support of older adults with home and community services is cost-effective when compared to
expensive institutional long-term care. In contrast, the dangers of such a policy are the potential for
over or under care and the implications these inappropriate levels of care would have for older adults
and for the functioning of the health care system.
The extent of over care and under care is a clear signal that programs and policy frameworks
would benefit from more extensive implementation of evidence-based practice. The few extant studies
that explore the prevalence and pathways to inappropriate care indicate that a proportion of older
adults reside in more restrictive settings than is necessary or they do not receive the care they need.
Berthelot and colleagues, in their analysis of Canadian data from the National Population Health
Survey, found that 10 percent of adults 65 years of age and older with no disability resided in long-
term care facilities (Berthelot et al., 2000). Although this proportion is modest, it still warrants
questioning whether these individuals could be better accommodated in less restrictive settings.
In an American study that used data from a sample of 3,170 older adults residing in long-term
care facilities, it was estimated that between 15% to 70% could be appropriately cared for in less
restrictive settings (Spector, Reschovsky & Cohen, 1996). Even at the most conservative criterion
level, the proportion of older adults receiving too much care in this American sample is alarming.
Coyte and colleagues in their revision of the forecast produced for the Health Services Restructuring
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Commission in Ontario noted that "many people who currently are being admitted to Long-Term Care
facilities would be able to receive care in their own homes or in a supportive housing setting" (Coyte et
al., 2002 p.9). It may well be that some older adults find themselves in institutional settings for reasons
other than their health, functional or cognitive problems.
Under care is an equally disturbing phenomenon. A recent study by the American Association
for Retired Persons found that almost one-third of the 865 older adults surveyed reported having unmet
needs for personal assistance (AARP, 2006). Davey and colleagues found that of those Americans in
the highest risk group for nursing home placement, a high proportion (one in ten) were without any
support whatsoever (Davey et al., 2005).
This literature review was prepared for the Toronto Central Local Health Integration Network
Seniors Council. The Council is comprised of representatives from seniors’ agencies, physicians,
aboriginal health leaders, and consumers. It is the body responsible for implementing the “Plan for
Seniors”, a component of the “Integrated Health Services Plan” (Toronto Central Local Health
Integration Network, 2007). A priority is to enable seniors to live independently in the community for
as long as possible (Toronto Central Local Health Integration Network (LHIN, 2007). In considering
this priority, the Council posed the following questions, “What factors prevent seniors from remaining
in their homes and communities?” and “What are the factors that predict the move of older adults to
more restrictive settings?” This review of the literature is was undertaken in response to these
questions.
1.1 Methodology
The search of the literature entailed a scan of 377 journals, books, and government documents
of which 114 were reviewed. All were published between 1993 and 2007. Excluded studies included
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those that were inappropriate for reasons such as the methodology used, they were primarily about
screening tools, they were dated, or they were not consistent with the intent of the review. The majority
of the publications were from the fields of social work, sociology, psychology, nursing, medicine, and
health economics. Databases reviewed included Google Scholar, Scholar’s Portal, and Web of
Knowledge. Where possible, the search emphasized relevant and current Canadian studies. The review
focussed on predictors of the move of older adults (65 years of age and older) to more restrictive
residential settings. The main search terms were old*, elder*, senior*, Engl*, Canad*, United States,
Europe*, Australi*, health*, predict*, factor*, aging in place, social support, informal support,
caregiving, housing, supportive or assisted, home care, paid help*, neighbourhood, home
modifications, assistive technol*, community-based healthcare, health policy, socio-economic status ,
nursing home and institutionaliz*. Searches yielded documents that dealt with health and socio-
economics status, social support, housing, community and policy environments, health service
utilization, activities of daily living, instrumental activities of daily living, chronic poor health, health
concerns, and health crises. The majority of the studies were quantitative population-based, random
control trials (RCT), and longitudinal studies.
1.2 Terminology
For the purposes of this literature review, the term “senior” refers to those aged 65 and older.
The terms “senior”, “older person”, “older adult,” and “later life” will be used interchangeably,
although in reality, older adults are a very diverse group who age at different rates and in different
ways.
Commonly, institutionalization refers to permanent admission to a more restrictive residential
setting in a healthcare setting or other facility (Hope, Keene, Gedling, Fairburn, & Jacoby, 1998),
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where there are professional and personal care services available. A facility may be a chronic care
hospital, long-term care institution, such as a nursing home, home for the aged, psycho-geriatric
setting, retirement home (if adjunct services are purchased to maintain independence), or other seniors’
institutions (please see Table 1). For the purposes of this review, the definition of institutionalization
does not include admission for respite care, the use of home care, assisted living/supportive housing, or
enrolment in day programs, although doing so may provide care levels comparable to that offered in
institutional settings
1.3 Organization of the Literature Review
The fundamental components of this literature review include a survey of pertinent contextual
and demographic information as they predict institutionalization. This literature review is organized
according to a widely used model created by Andersen and colleagues (Hancock, Arthur, Jagger, &
Matthews, 2002; Miller & Weissert, 2000) which is appropriate to the population and research
questions guiding this review. According to the model, predictors of institutionalization can be
organized in the following schema: predisposing, enabling, and need characteristics of the individual.
Predisposing characteristics include demographics, levels and characteristics of social support and
beliefs and expectations. Enabling characteristics include familial and community resources (e.g.
neighbourhood context, supply of long-term care facilities and home and community-based services,
the balance of health care expenditures and health policy). Need characteristics include indicators of
self-rated and practitioner-evaluated health such as health status, functional status or disability. More
recent versions of Andersen’s model include “use” characteristics (utilization of health care services)
in the schema (Andersen, 1995; Gelberg, Andersen, & Leake, 2000). Figure 1 describes Anderson’s
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behavioural model, while Table 4 provides an example of the model using the summary findings from
Miller and Weissert’s recent review of the literature (Miller and Weissert, 2000).
1.4 Background
1.4.1 Canada’s Aging Population
According to Statistics Canada, in 2006, Canadians aged 65 and over comprised 13.7% of
Canada’s population or 4.3 million persons (Statistics Canada, 2007a). In Canada, between 2006 and
2056 (Figure 2), the number of seniors, is expected to increase significantly. In fact, by 2031, seniors
will account for approximately one-quarter of Canada’s population (Statistics Canada, 2005).
Moreover, Toronto’s City Planning Division projects that the overall number of seniors will grow by
38% between 2006 and 2031 (Toronto, 2007b). A similar trend is evident in the Toronto Central
LHIN’s senior population whose growth trajectory until 2016 is depicted in Figure 3.
As is the case with the overall senior population, the number of people in the oldest age groups
is expected to increase in the approaching decades. Canada’s population aged 80 and over will almost
double, from 1.2 million in 2006 to 2 million in 2026 (Statistics Canada, 2007b), and will constitute
the second largest increase (+25%) in population of any age group (Statistics Canada, 2007b) between,
2001 and 2006. By comparison, over the same time period, the same age group in Toronto has grown
by 30%.(Toronto, 2007b).
Today’s cohort of seniors is aging well; they are in better physical and mental health than were
their predecessors. Moreover, their financial situation is improved, a key factor related to good health
(Statistics Canada, 2003b). As seen in Figure 4, approximately 80%, of older adults living at home rate
their health as good or better, although this perception changes as seniors age (Shields & Martel,
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2006). Regardless, academics and policymakers continue to be concerned about the impact on the
economy of the rapidly increasing 80 plus population (Dang, Antolin, & Oxley, 2001).
1.4.2 Seniors’ Living Accommodation
The increasingly large numbers of older people will likely make more demands on home and
health care services (Robson, 2001), including institutional care, notwithstanding the improvements in
health care and the concomitant increases in Canadians’ life expectancy. Although 90 percent of older
adults live in private households (National Advisory Council on Aging, 1999), and prefer not to live in
institutions (Division of Aging and Seniors, 2006), this percentage diminishes with age: with less than
one-half of seniors over the age of 85 living alone (see Table 3).
As seniors reach older ages, they are much more likely to become institutionalized as seen in
Tables 2 and 3. Approximately 7 percent of all older adults live in long-term care facilities in Canada.
Twice as many aged 75 and older live in long-term care facilities in Canada (National Advisory
Council on Aging , 2005 as cited by (Division of Aging and Seniors, 2006). The Toronto figures are
consistent with National estimates: 7 percent of senior Torontonians are institutionalized (Toronto,
2007a). In Canada (excluding Quebec), there were 5,024 more seniors in institutions1 in 2004-2005
than in 2003-2004 indicating that the number of seniors who live in institutions in Canada (excluding
Quebec), rose by 3.3 percent.
1 Homes for senior citizens, retirement homes, or lodges, where there is no care provided, are not included.
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2. PREDISPOSING CHARACTERISTICS
Predisposing characteristics are more distal influences on the use of health services and the
likelihood of residing in more restrictive (therefore service rich) settings. This review considers
demographic factors, various dimensions and levels of social support and caregiving, as well as beliefs,
expectations and health behaviours associated with residential outcomes.
2.1 Demographic Factors: Age, Gender and “Race”
A systematic review published in 2000 by Miller and Weissert which focussed on the
predictors of institutionalization among American seniors (Miller & Weissert, 2000), concluded that
gender (female) was not a significant predictor of institutionalization. However, a large (N= 2805), 14-
year Australian, longitudinal study (McCallum, Simons, Simons, & Friedlander, 2005) of non-
institutionalized older adults did find that being female, independent of the effect of advanced age,
increased the risk of institutionalization.
Inconsistent results for the effect of gender may be due to that fact that gender exerts an
influence because women have a greater life expectancy than men. For example, in Canada women, on
average, live longer than do men (82.5 years compared with 77.7 years, in 2004) and they represent
two-thirds of those over age 80 (Statistics Canada, 2005). Consequently, in Canada, gender differences
exist, with more females hospitalized (National Advisory Council on Aging, 1999) and
institutionalized than are males (Statistics Canada, 2003a).
Likewise, a National Institute of Health study (N=236) found that predictors of
institutionalization included gender and age, and specifically age of onset of dementia (Stern et al.,
1997). As well, another study of approximately 9000 Canadian seniors participating in the Canadian
Study of Health and Aging, found that age and gender predicted institutionalization, with age being the
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best of any predictors (Gutman, Stark, Donald, & Beattie, 2001). Consistent with Gutman and
colleagues findings about age, Miller and Weissert in their systematic review found, in 42 out of 55 of
the studies that age was positively associated with institutionalization, and in 29 out of 33 studies,
being “non-white” decreased the chances of institutionalization (Miller & Weissert, 2000). American
researchers studied 4,646 participants in a day program for seniors age 55 and older whom either
subsequently had been or not been institutionalized (Friedman, Steinwachs, & Rathouz, 2005). They
examined the predictors of nursing home placement occurring within 3 years, and found that among
community-dwelling seniors, advanced age and identifying as “white” were associated with greater
likelihood of institutional living.
2.2 Social Support
Social functioning and its effect on institutionalization are measured in a variety of ways in the
research literature. Informal support is often assumed if a spouse or adult child is present. Being
married (including previous marital status) and the presence of surviving adult children (including the
number of children and their gender) frequently are used as predictors of institutionalization. It is more
common to measure social support in terms of instrumental support (banking, shopping) compared to
psycho-emotional support. Similarly, it is more common to measure support in terms of direct
assistance provided by family/friends versus indirect support through the purchase of services. Other
less common measures of social support are frequency and community engagement indicators such as
casual (intermittent) versus dedicated support (continuing), and social activities such as volunteerism
and attending faith-based groups.
Most studies recognize the complexity of using social functioning as a predictor of
institutionalization (Freedman, 1996; Kersting, 2001; Wilcox, 1995) and acknowledge that the concept
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is multi-faceted and not consistently operationalized in the literature. Cox (2005) raises another issue:
that quantitative measures overlook subjective assessments of the quality of support provided. Further
complicating the interpretation of the effects of social functioning is that the presence of support or
caregiving is positively associated with the same variables that predict residing in a more restrictive
setting. As a result, some investigations have found that the presence of social support is associated
with greater risk of nursing home admission. For example, Lo Sasso and Johnson (2002) observed that
using a simple model of nursing home entry resulted in the finding that those who received informal
care were significantly more likely to use nursing home services than those who did not receive
informal care. However, when Lo Sasso and Johnson (2002) used a more complex equation, the author
found that help from adult children with ADL was associated with a 57% reduction in nursing home
admissions.
2.2.1 Marital Status and Living Alone
The majority of studies reviewed measure “within household support” such as existence of a
spouse and number of adult children, as well as some analyses of the gender and family status of adult
children. The two most consistent predictors are marital status (being married or not) and living alone
(the presence or absence of other adults in the household). However, some authors caution that these
two measures are frequently co-linear and poorly constructed. For example, Kersting (2001) notes that
“being married” and “not living alone” may tap the same underlying construct of dedicated support in
the home. If this is the case, it may be redundant to include them both in the analyses. Furthermore,
there have been few analyses that have investigated whether the presence of a spouse necessarily
implies instrumental support or whether none or other types of support are provided.
Nevertheless, as predisposing factors, being married and having adult children typically are
associated with a lower risk of nursing home placement, while living alone is a consistently strong
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predictor of increased risk of institutionalization. One study found that living alone was a powerful
predictor of discharge from a non-acute geriatric hospital to a nursing home (Aditya, Sharma, Allen, &
Vassallo, 2003). Other authors have found a similar significant effect for living alone (Akamigbo &
Factors that were predictive of institutionalization at discharge were scores on the Red Cross Hospital
Functional Disability Scale, a measure of functional ability.
Strain et al.’s ( 2003) previously mentioned 5-year longitudinal study using 123 cognitively
impaired seniors and their caregivers from the Manitoba Study of Health and Aging resulted in the
identification of risk profiles for institutionalization – high, medium and low. In the screening stage,
cognitive status was assessed using the Modified Mini-Mental State Examination. Those with a score
of 78 or lower were asked to participate in the study. The group at highest risk of institutionalization
were the most cognitively impaired, required the most assistance with IADLs/ADLs and were the most
likely to exhibit behavioural problems. Both the high and medium group tended to wake up at night for
no apparent reasons and slept during the day. Their findings indicated that 75% of the most cognitively
impaired were most likely to be institutionalized 5 years later. While the study had a small sample size,
did not collect information at the time of institutionalization or measured the services used prior to
institutionalization, the predictive value of the risk profiles was established. Strain et al. (2003) note
that the findings suggest the need to target assessments and services differently to the various risk
groups.
5. HEALTH CARE UTILIZATION
Another cluster of predictors, embedded in the Anderson model, that have been shown to affect
residential outcomes is measures of health care utilization. The most common measures utilized in the
research are measures of prior nursing home use, rates of hospitalization , use of paid helpers (home
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care support), and doctors and medications. By far the most robust findings are for prior nursing home
admissions.
5.1 Prior Nursing Home Admission and Hospitalization
Akyan (2002) found a very strong effect for having been in a nursing home in the year prior to
the baseline interviews for the AHEAD study. The odds of entering into a nursing home almost
quadrupled for women and tripled for men who were previously institutionalized. A similar outcome
for prior nursing home admission was found in a study where a significantly greater rate of
institutional placement was associated with previous institutionalization (Russell et al., 1997). Miller
and Weissert’s (2000) review of the literature found that the majority of studies demonstrated a
significantly greater risk of institutional living for those with a history of nursing home admission and
hospitalization. Likewise, a meta-analysis found a robust effect for prior nursing home placement: a
3.47 times greater likelihood of subsequent admission and a 1.19 times odds ratio of nursing home
placement following hospitalization (Gaugler et al., 2007).
Although prior nursing home and hospital use were strong predictors of nursing home
placement, Akamigbo and Wolinsky (2006) found that neither of the variables were associated with
reported expectations of nursing home placement at baseline. The researchers suggest that
understandings of nursing home placement may be ambiguous, especially as to whether the placement
is short term or permanent. Future research could examine placement time intervals and exits to more
clearly understand what predicts duration of institutionalization.
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5.2 Other Measures of Use: Paid Helpers, Doctors and Medications
Miller and Weissert’s (2000) review found ambiguous results for the effects of paid helpers on
institutionalization. In thirty-two studies, seventeen found significant positive relationships, four
significant negative effects and eleven studies were non-significant. Gaugler and colleagues’ meta-
analysis found a moderate increase in the likelihood of nursing home placement associated with the
use of formal services (Gaugler et al., 2007). Interestingly, in this meta-analysis, the pooled odds of
institutionalization for formal supports were equal to those for informal support. Finlayson’s analysis
of the Aging in Manitoba longitudinal data found that changes in service use predicted moves to more
restrictive settings and discriminated between expansions of home care and moves to nursing home
care (Finlayson, 2002).
Other studies investigating the role of formal healthcare supports have looked at number of
doctor’s visits and the number of prescription medications as a proxy for disease and chronic
conditions and as a measure of contact with healthcare providers. The number of doctors’ visits was a
significant predictor of nursing home admission in Russell and colleagues study of the role of
loneliness in predicting community versus institutional tenure (Russell et al., 1997). The researchers
also found, that as the number of prescriptions increased, so did the odds of nursing home placement.
In Gaugler and colleagues’ meta-analysis of the literature, the number of medications had a small but
significant positive association with institutional living (Gaugler et al., 2007). Although only two
studies examining medication use were included in Miller and Weissert’s (2000) review, both found a
significant positive association with the probability of nursing home placement. The challenge to
understanding the effects of service use on residential outcomes is that it is difficult to disentangle the
potential protective effect of reducing health declines from the negative risks associated with greater
monitoring of health status.
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In this vein a, a study of Adult Protective Service (APS) use and nursing home placement in the
United States found that an APS referral for self-neglect was the highest risk factor for placement in a
nursing home, net demographic, medical, functional and social factors associated with nursing home
placement (Lachs et al., 2002). The sample was 2,812 community-dwelling older adults who were 65
years of age or older in the1982 cohort in the New Haven Established Populations for Epidemiologic
Studies in the Elderly. A subset of this cohort (N=202) was referred to protective services over a nine
year follow-up period from cohort inception. Nursing home placement over that time period was also
determined. The rates for nursing home placement was 69.2 percent for self-neglecting respondents,
52.3 percent for mistreated respondents and 31.8 percent for respondents who had no contact with
APS. Proportional hazard models were estimated controlling for the usual factors such as dementia,
urinary incontinence, functional disability and poor social networks. Surprisingly, the most potent
predictor of institutionalization was APS referral for self-neglect followed by APS referral for
mistreatment (Lachs et al., 2002). This finding replicates an earlier and equally rigorous study by
Blenkner (1971) over thirty years ago. While Canada has a different legal framework for neglect and
elder abuse, the outcomes are likely to be much the same since service providers still have to find
alternative housing or community team care in an environment with shrinking resources. The findings
underscore the need for alternative housing and for community team-based care such as that offered by
PACE.
6. CONCLUSION
6.1 Limitations of the Literature
Although this review utilizes Andersen’s model of health service utilization, other models
highlight additional dimensions such as knowledge of services, and still others acknowledge the role of
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accessibility and acceptability. This review, where possible, has included research in the area of
knowledge of resources and of endorsements/expectations around different residential outcomes but is
nonetheless, limited by the boundaries of the model.
There are many methodological problems with the extant research. Hays et al., (2003)
demonstrated that the single decision of moving into a nursing home is really a two-stage decision-
making process: the decision whether to make a change and if so, what change should be made. For
example, the researchers contend that adult children increase the probability of change to parental
households (early detection of need for greater care). However, once the household is destabilized, the
presence of adult children (options for co-residency) reduces the odds of institutionalization. The
researchers also note that while marital status reduces the probability of change, once the change is
underway married older adults are at greater risk of institutionalization. The latter issue could be due to
either overwhelming caregiver burden or to the greater challenge of making alternative living
arrangements for two persons as compared to one. The researchers recommend that when examining
predictors of institutionalization it is critical to look at factors that led up to a change in living
arrangements, independent from factors that predict a particular type of change.
Hays et al., (2003) also found that different factors exerted distinct effects on various
residential outcomes. For example, smaller household size and impaired social interaction did not
significantly predict risk of household expansion but did predict greater odds of institutionalization.
Finlayson (2002) found similar varied effects which challenge the assumption that moves to
progressively more restrictive settings are associated with increasing or decreasing values of a
predictor. For example, Finlayson (2002) found that a decline in social support was a significant
predictor of home care but not of nursing home care. Studies such as these suggest that much of the
literature may be oversimplifying the complexity of factors that predict residential outcomes and speak
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to the need for professional judgement. The implications for the development of appropriate
assessments are that a single set of predictors will not always effectively discriminate between
appropriate residential outcomes.
Another limiting factor is that some predictors are more easily quantified than others.
Therefore, they appear more frequently in the literature and limit the understanding of the effects of
variables that are more difficult to measure. Miller and Weissert’s (2000) review of the literature
concludes with a notation of the serious skew toward measuring easily quantifiable factors. The
authors, drawing on the Andersen framework, note that enabling and predisposing factors are
examined far less frequently than need-based factors, particularly those that are scale-based measures
such as ADL and cognitive assessments using the SPMSQ and MMSE. Consequently, the authors
recommend that future studies attend to the more neglected community-wide factors such as housing,
market and policy resources that may be important explanatory mechanisms for determining residential
outcomes.
At the same time, a difficulty with the assessment of market, community, and policy
environments is that a multitude of policies intersects in the provision of community and institutional
long-term care. Further, as Diez Roux (2004) notes, the influence of contextual variables is often
apparent primarily through their effect on micro level factors such as health or socio-demographic
indicators. The author suggests that this hinders understanding of the direct pathways of influence for
macro level factors but that quantitative RCTs and/or qualitative methodologies may help clarify the
interaction of micro and macro level factors in determining residential outcomes. This researcher
concludes that despite the challenges of examining the effects of macro factors, a more crucial question
is how much evidence is required before health policy planning includes interventions aimed at
housing, community, and policy environments, as well as interventions targeted to individual factors.
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Other limitations in the research include the lack of attention to duration of nursing home stays,
the lack of investigation of policy interventions to reduce over and under care, and the neglect of
quality of life measures. Few studies measure the length of stay in and/or exits from nursing homes.
The research indicates that nursing homes are being used for rehabilitation purposes to offset costs for
hospital care which, as Kavanagh (1993) proposes, skew the data on nursing home placement.
Although studies have documented the extent of over and under care, the literature tends to focus on
reducing errors in either direction via improved assessment tools but neglects macro policy options
(e.g. careful planning, monitoring and development of new nursing home beds and expanded home
care programs). A flaw in the research highlighted by Miller and Weissert (2000) is that quality of life
outcomes such as care recipient and caregiver satisfaction, or the degree of self-determination are
rarely evaluated in the research. What is more, much of the focus on the consequences of providing
personal care has been on the impact of caregiving on the caregiver, rather than the predictors of
institutionalization as related to caregiving.
Further, the research seldom questions the impact of residential outcomes on the health and
well-being of older adults and misses an important opportunity to understand what settings convey
benefits to particular groups. In one of the few studies that posed this type of research question, Marek
et al., (2005), compared clinical outcomes of older adults in a community-based long-term care
program to matched older adults in institutional-based long-term care. Using a quasi-experimental
methodology, with a matched intervention and control, they compared various measures of health and
well-being at 6-month intervals over a 30-month period. The older adults in the community-based
intervention program, called Aging in Place (AIP), had significantly better mental health, functional,
and cognitive status, as well as better bladder control than the nursing home group. In absence of more
research about the consequences of one residential setting over another and for what groups, the
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literature will only be able to tell us that a predictor is associated with a particular outcome but not why
this is the case. Further, without understanding the pathways by which a predictor influences an
outcome, it will be very difficult to construct interventions to support older adults in the least
restrictive settings possible.
From a methodological perspective, many of the studies are subject to problems. The prediction
of change, based on single cross-sectional baseline measures of selected factors is one of the more
serious issues. The disadvantage with this type of analyses is that the factors can be unstable and are
known to evolve over time. Few of the studies untangle the many steps in the decision-making process,
information is not collected at time of institutionalization or about service usage prior to placement and
the effect of different time intervals on placement are ignored. In addition, a number of the studies do
not have random assignment or random sampling and different measures of the predictors are used,
making cross study comparisons impossible. As a result, the function of a number of predictors of
institutionalization remains inconclusive.
6.2 Summary: Predisposing Characteristics
The importance of social support in determining institutionalization is modest at best and its
effects may mediated by health predictors. Nevertheless, Beland and colleagues suggest that though
social support interventions are not typically employed in health and social service settings, they are, in
fact, amenable to policy and program interventions (Beland et al., 2004). Further, Russell and
colleagues note that while social support interventions may delay moves to more restrictive settings, it
may be better to remove barriers and enhance existing relationships rather than try to foster new
relationships (Russell et al., 1997).
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It would also appear that social support has different effects for different groups of older
adults. For example, those residing in poor neighbourhoods may be more reliant on family networks
(Beland et al., 2004) or those who are at the highest risk of institutionalization due to isolation may
experience the greatest benefits from interventions aimed at extending their community tenure
(Eloniemi-Sulkava et al., 2005).
Finally, the inconsistent and often contradictory results associated with informal
supports/caregiving highlight the need for more careful, fine-grained analysis of the mechanisms by
which caregiving impacts residential outcomes. Although there is significant public and private interest
in “aging in place,” as Wiles (in Andrews and Phillips, 2003) cautions, it should not be presumed to be
an ideal goal without examining what must be in place and what is transformed in the process of
achieving this goal. As homes increasingly become sites for the provision and consumption of care, it
is critical that health planners recognize and accommodate the fact that these resources are typically
provided by women.
6.3 Summary: Enabling Characteristics
Of the enabling characteristics, the most prevalent predictors of residential outcomes are
household or individual income and the supply of nursing home beds available. The results for income
are mixed and appear to be better understood through more subjective measures, such as perceived
adequacy of income, rather than absolute measures of dollar value or income range as determined by
various poverty measures. Homeownership has a moderate protective effect on moves to more
restrictive settings but it is unclear whether the pathway of the effect is through place attachment to
housing and/or neighbourhood or through its function as a proxy for wealth. Although there is an
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emergent literature (especially grey literature) and a great deal of “best practice” documentation of the
role of various human and structural supports (supportive housing, home care, home modifications and
assistive technologies) in sustaining older adults in less restrictive settings, research directly evaluating
the effect of various housing characteristics on residential outcomes for older adults is limited.
While expenditures on the balance of healthcare determine the availability of community- and
home-based care versus institutional care, currently the only clear predictor of this balance and its
effect on residential outcomes is the supply of nursing home beds (Burr et al., 2005; Hoerger et al.,
1996; Miller and Weissert, 2000). As Coyte and colleagues contend, greater spending on institutional
care and consequently greater supply does translate into greater risk of nursing home placement (Coyte
et al, 2002).
6.4 Summary: Need Characteristics
The needs of older persons are complex and depend on the circumstances of the older adult.
For example, urinary incontinence may be a risk factor in rural areas and not in urban areas where
there is likely to be more preventive services. IADLs or instrumental functioning may be more
important for those living alone in the community in public housing than those living with a caregiver
where activities of daily living are more important (ADLs). Using Miller and Weissert’s (2000) article
as a guide, there are only a few strong predictors among the “need” characteristics. The most striking
finding is the importance of cognitive function in predicting institutionalization. In 25 of the 33 articles
reviewed, lower cognitive function was a predictor of institutionalization. Nevertheless, only in one-
half of the ten articles was dementia/Alzheimer’s Disease a predictor of institutionalization. Lower
ADL and IADL were both strong predictors of institutionalization but did depend on the context in
which the older person lived. Digestive system diseases, proved to have significant associations with
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institutionalization. The research on co-morbidity is inconclusive. Although there is general acceptance
that self-reported health ratings are reliable measures of health, replication of studies of this factor are
required. All of the studies reviewed suffered from a number of methodological issues but it is
important to note that there was a consistency in the findings.
6.5 Summary: Use Characteristics
The most significant “use” predictor of institutional residence is prior admission to a nursing
home (Akyan, 2002; Akamigbo & Wolinsky, 2006; Miller and Weissert, 2000). However, it is unclear
whether the explanatory effect is due to greater endorsement or acceptance by an older adult because
of a previous placement or a bias of service providers/discharge planners to move someone to an
institutional setting because it has been done successfully in the past. Formal help, sometimes referred
to as “paid helpers,” has been widely evaluated with inconsistent results (Gaugler et al., 2007; Miller
and Weissert, 2000) which may be due to the fact, that the measure covers such a broad spectrum of
support (e.g. personal support workers to meal delivery services).
Overall, this review affirms that that older adults with lower levels of informal support (as
measured by absence of a spouse or other adults in the household and having fewer adult children), and
less economic resources (as measured by an absence of housing assets and lower income) are at
increased risk of moves into more restrictive settings. The presence of cognitive impairment or limits
to ADLs and IADLS, as measured by scale thresholds, is significantly associated with living in more
restrictive settings. Other factors that are consistently and significantly associated with higher rates of
institutionalization are prior admissions to a nursing home or hospital and residing in areas with a
greater supply of nursing home beds.
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7. REFERENCES
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Aykan, H. (2002). Do state Medicaid policies affect the risk of nursing home entry among the elderly?
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8. APPENDICES
8.1 Appendix A: TABLES
Table 1
Definitions of Accommodation and Care Settings
Accommodation
Government Funding
Services Client Groups
Boarding/Lodging Homes No room/board
minimal supervision socially disadvantaged people
Home for Special Care Provincial care/supervision adults with developmental handicaps, adults with mental illness
Supportive Housing Provincial care/supervision
seniors, adults with physical disabilities, or mental health problems, people living with HIV/AIDS
Retirement Homes No care/supervision predominantly seniors (average age 82)
Long-term Care Facilities Provincial care/supervision therapies
predominantly seniors (average age 85)
Emergency Hostels/ Women’s’ Shelter
Municipal Provincial
counselling, standards, care management
women & children in transition from abusive situations homeless people people on public assistance
Source: Government of Ontario, 2005
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Table 2
Living Arrangements, Ontario, 1996, by Gender (65+, 65-74, 75-84, 85+)
*Special care homes include chronic care hospitals, long-term care settings, and residences for seniors that provide minimal assistance and supervision for seniors who are independent in most activities of daily living.
Table 3
Living arrangements of seniors aged 65 and over by sex and age group, 2001
Source: Statistics Canada, General Social Survey, Cycle 16, 2002
Age Gender In Private Households
Hospitals Special Care Homes
Religious Institutions
Total in Institutions
65+ Men 95.9% 0.5% 3.4% 0.1% 4.1%
65+ Women 91.8% 0.4% 7.5% 0.25% 8.2%
65+ Total 93.5% 0.5% 5.8% 0.1% 6.4%
85+ Men 76.9% 1.5% 21.4% 0.1% 23.1%
85+ Women 62.8% 1.5% 35.3% 0.5% 37.2%
85+ Total 66.8% 1.5% 31.4% 0.3% 33.2%
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Table 4
Number of Equations (N) Reporting Positive Significant (+), Negative Significant (–), and Non-significant (NS) Associations among Predictors and
Adverse Outcomes
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8.2 Appendix B: FIGURES
Figure 1
Andersen’s Behavioral Model
Source: Adaptation from Gelberg, Andersen, and Leake (2000).
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Figure 2
Population Projections for Canada, Provinces, and Territories, 2005-2056
Source: Statistics Canada, 2005
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Figure 3
Age of Toronto’s Senior Population
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Figure 4
Percentage of Canadians in Good Health, by Age Group, Household Population, Aged 65 and