Transitions in Living Arrangements of Canadian Seniors:
Findings from the NPHS Longitudinal Data
Sisira Sarma*
Gordon Hawley
Kisalaya Basu
Microsimulation Modelling and Data Analysis Division
Applied Research and Analysis Directorate
Health Policy Branch
Health Canada
Ottawa, ON
Canada K1A 0K9
Abstract
This paper examines transitions in living arrangements decisions of the seniors using the first
six cycles of the Canadian National Population Health Survey data. Transitions from
independent to intergenerational and institutional living arrangements are analyzed using a
discrete-time hazard rate multinomial logit modelling framework. After accounting for
unobserved heterogeneity, our results show: a) provision of homecare services reduces the
likelihood of institutionalization, but with no effect on intergenerational living; b) access to
and availability of social support services reduces the probability of institutional and
intergenerational living arrangements; c) higher levels of functional health status measured by
Health Utility Index scores also reduces the probability of transiting to both intergenerational
and institutional living arrangements; d) a decline in health status (self-reported) increases the
probability of institutionalization, but its effect on intergenerational living arrangements is
statistically insignificant; e) higher levels of household income tends to increase the
probability of transiting to intergenerational living arrangements; and f) the likelihood of
transiting to both intergenerational and institutional living arrangements increases with the
duration of survival. Our findings suggest that provision of homecare services, social support
services and other policies designed to foster independent living would contribute positively
towards independent living and reduce institutionalization.
JEL Classification: J14 I18 I11
Key Words: Living arrangements transitions; Discrete-time hazard rate multinomial
logit; Unobserved heterogeneity; Seniors; Canada
*
Corresponding author. E-mail: sisira_sarma@hc-sc.gc.ca , tel.: (613) 941-8221, fax: (613) 946-3166
Acknowledgements: The first author acknowledges a financial contribution from Microsimulation Modelling
and Data Analysis Division (MSDAD) of Health Canada and Post Doctoral Fellowship from the Office of Chief
Scientist, Health Canada. We thank the comments of Sameer Rajbhandary on an earlier version of this paper.
The views expressed in this paper, however, are the views of the authors and do not necessarily represent the
views of Health Canada.
1. Introduction
Like other developed countries, Canada’s population is growing older due to rising
longevity and aging of baby boomers, as well as declining fertility (United Nations, 2006).
According to Statistics Canada (2005), the proportion of those aged 65 and over in Canada
was 13.1% in 2005, comprising 4.2 million people; this proportion is expected to increase to
23% by 2031, to about 9 million people, and will further rise to some 27% by 2056. More
importantly, a subset of this group is even more rapidly growing: the very old; about one out
of ten Canadians would be 80 years and older by the year 2056, compared to one in thirty in
2005.
These demographic trends have led some to predict a growing demand for health care
services and corresponding increased health expenditures as older people are generally higher
users of health care services with growth rates ranging from 0.8% to 1% per annum. Health
Canada’s projection shows that aging alone would contribute modest pressure of an average
annual growth in total health expenditures of about 0.9% between 1998 and 2030 (Health
Canada, 2002). The Conference Board of Canada projects that the effect of aging would
increase provincial and territorial government health expenditures at an average annual
growth rate of 0.8% between 2001 and 2020 (Conference Board of Canada, 2004). A
Canadian Institute for Health Information (CIHI) study shows that the pure effect of aging
would increase total provincial and territorial health expenditures at an average annual growth
rate of about 1% between 2002 and 2026 (CIHI, 2005). The CIHI study shows that between
2002 and 2026, the average annual growth rate is highest for long-term care (2.1%), followed
by prescription drugs (1.6%), hospitals (1.1%), physicians (0.6%) and other services (0.3%).
1
At one time, elderly people could rely much more on the supplemental care provided
by family members (i.e., informal care). But, with increased participation of women in the
workforce, family dispersion in an age of great labour mobility informal care is likely to,
continue to diminish in the foreseeable future, thereby placing additional pressure on publicly
provided institutionalized health care. On the other hand, rapid expansion of public home care
services may reduce the probability of institutionalization. There are some structural
differences amongst the past, present and future elderly cohorts, however, with respect to their
living arrangements, including income, health, life-style choices and other idiosyncratic
characteristics. According to Statistics Canada (2007), the average before-tax real income (in
2003 dollars) of senior couples increased from $39,800 to $49,300 (an increase of 24%)
between 1981 and 2003 and comes from diverse sources. The incomes of seniors increased
not only in absolute terms, but also in relation to the incomes of those aged 35 to 44: for every
dollar received by a senior, an individual aged 35 to 44 received $1.29 in 2003, a decrease
from $1.57 in 1980. Improvements in the financial status of seniors are also evident in terms
of their net assets, including increased home equity in an era of rising home values during this
period.1 The improved financial and health status2 of seniors will enable greater independence
than their predecessors, which may provide a source for self-financing of long-term care and
decreased demand for institutionalized forms of living arrangements This paper investigates
the living arrangement decisions of the elderly and the underlying factors governing
transitions from independent to intergenerational and institutional forms of living
arrangements. An understanding of the determinants of the transitions in living arrangements
would assist policy developments concerning efficiency in resource allocation as well as
1
See Statistics Canada (2007) for the detailed statistics on these issues. Note that senior women do not enjoy the
same level of financial independence compared to senior men in Canada.
2
This is particularly true in term of self-reported health status (Statistics Canada, 2007).
2
effectiveness in meeting the challenges of an aging population by enabling seniors’ prolonged
residency within their communities. From a strategic and regulatory perspective, a thorough
understanding of the dynamics of the transitions in living arrangements of seniors is clearly
important. Depending on the extent to which provinces are able to shift a portion of the
burden of long-term care from institutions to the community through innovative means,
public financing of long-term care can be made easier over the period through which baby
boomers are likely to seek long-term care. Notably, an important means by which some of the
institutional care can be shifted to the community may be through the provision of formal and
informal home care services.
This paper proceeds as follows: Section 2 provides an extensive overview of the
institutional context – the continuing care sector in Canada. Following this, a brief review of
the literature surrounding elderly living arrangements is presented in Section 3. The
methodological framework for the empirical study is presented in Section 4 and Section 5
presents our data and variables construction. The empirical results of this study are discussed
in Section 6. Finally, Section 7 provides conclusions and the implications of this study for
policy.
2. The Institutional Context
In Canada, hospital and physician services, popularly known as Medicare, are publicly
insured under provincial health insurance plans and governed by the national principles of
universality, accessibility, comprehensiveness, public administration and portability as
enshrined in Canada Health Act. However, extended health care services such as nursing
home and home care services as well as out-of-hospital prescription drugs, dental and vision
3
care are not mandatory insured health services under the Act. Consequently, different
provinces have developed their own programs with respect to the provision of continuing
care, with no national standards. Although eligibility requirements, benefit levels, and
availability of continuing care services differ from jurisdiction to jurisdiction, all provinces
provide some level of continuing care to their residents through two channels: i) facility-based
long-term care and ii) home care.3
2.1 Facility-based Long-term Care in Canada
Facility-based long-term care provides long-term living accommodation and
continuous onsite professional health services to those in need of high levels of daily personal
care or supervision involving assistance with respect to basic activities of daily living, often
on a 24 hours basis. It is characterized by a wide variation in the nomenclature, institutional
design, public-private mix in financing, delivery and ownership, and charges to residents
(based on income and/or asset and the intensity of care). Most provinces set a minimum
charge for standard accommodation based on the minimum income earned by seniors, with a
higher charge for private accommodation. The minimum income is often linked to the
combined total of the Old Age Security (OAS) and the Guaranteed Income supplement (GIS).
Table 1 outlines some basic information about the facility-based long-term care
programs across provinces, which shows that there are substantial differences across
provinces with respect to public-private funding and delivery, and out-of-pocket costs. For
example, there are no income or asset tests in Alberta, whereas British Columbia,
Saskatchewan, Manitoba and Ontario apply an income test to determine minimum charges.
3
The term “continuing care” refers to the full range of home care and institutionally-based services while the
term “facility-based long-term care” refers to the residential component of the continuing care.
4
Quebec, New Brunswick, Prince Edward Island and Newfoundland and Labrador apply both
income and asset tests based on a very complex formula to calculate co-payments.4 One of the
most fascinating aspects of the facility-based long-term care sector in Canada is that provision
of long-term care services are not covered by the Canada Health Act, yet no province denies
access to a residential long-term care facility to those needing it because of inability to pay.5
INSERT Table 1
Available information indicates that there are 4,185 long-term care residential
facilities consisting of 234,472 beds serving 219,472 residents in the fiscal year 2003/04
(Statistics Canada, 2006). Within this group, the majority of residential care activities for the
elderly individuals were found in the homes for the aged, accounting for 179,424 beds in
1,941 institutions in 2003/04. The number of full-time equivalent personnel working in
facilities for the aged increased from 84,689 in 1984/85 to 149,261 in 2003/04, a remarkable
43% increase in personnel during this period, especially in contrast to an increase of 15% in
the number of residents and the total number of patients under care of about 25% during this
period. Consequently, the number of accumulated paid-hours per-resident-day increased from
3 hours in 1984/85 to 4.4 hours in 2003/04, presumably reflecting increased intensity of care.
Increases in wage rates, inflation and the number of personnel led to increases in wages and
salaries from about $1.6 billion in 1984/85 to $5.8 billion in 2003/04. Total expenditures,
excluding capital costs, for long-term residential care during this period increased from about
$2.6 billion to $9 billion. Put another way, institutional expenditures per-resident-day
4
Note that the charges outlined in Table 1 do not depict the entire picture of all out-of-pocket payments in
residential care facilities. The cost of prescription drugs are not necessarily covered: provinces such as, Alberta,
Manitoba, Quebec and New Brunswick cover prescription drugs, while British Columbia, Saskatchewan,
Ontario, Nova Scotia and Newfoundland and Labrador apply an income-tested drug plan. Furthermore,
equipment and supplies (like assistive devices, walker, crutches, wheelchair, etc.) are not factored into the basic
charges in many provinces and residents may have to pay out-of-pocket for such things.
5
Some exceptions apply with regard to provincial residency requirements. Immigrants are not eligible for OAS
or GIS benefits to pay for minimum charges until they meet a 10 year residency requirement.
5
increased from $46 in 1984/85 to $137 in 2003/04, suggesting an average resident now costs
about $50,000 dollars per annum.6
As far as the financing of facility-based long-term care for the seniors in Canada is
concerned, the dominance of public financing is evident: the combined source of public sector
is about 70% or more of total income. The contribution of out-of-pocket payments is in the
range of 25-30%. The sundry earnings7 comprise about 2% of total income. Thus, of the
roughly $50,000 cost per annum for an average resident, the public sector contributes on
average about $36,000 and the resident himself/herself pays about $13,0008
2.2. Home Care in Canada
Home care programs are another means through which many seniors have access to longterm care services on a continuing basis. Introduction of home care into the Canadian health
care system is a relatively recent phenomenon and it has expanded rapidly in part due to the
increased pressure on health care expenditures arising from the acute care sector,
demographic challenges, hospital reforms (such as consolidation, shorter length of stay, day
surgery, etc.) and a preference to receive care at home. Advances in medical technology, new
drug treatments and cost-effective delivery of certain types of care at home facilitated
6
There are, however, significant provincial differences in terms of both the number of accumulated paid-hours
and expenditures per-resident-day. Accumulated paid hours per-resident-day is relatively higher in Nova Scotia,
Saskatchewan, Manitoba and Alberta, but lower in British Columbia and Ontario. Expenditures per-resident-day
is relatively higher in Saskatchewan, Alberta and British Columbia and lower in Prince Edward Island, Nova
Scotia and Ontario. Note that it is difficult to make any comparison of Quebec with other provinces because data
from Quebec on accumulated paid hours and financial data include certain activities that are outside the scope of
residential care.
7
The sundry earnings refer to all other earnings received from sources other than basic accommodation. These
include items such as earnings from sales or provision of services related to physical therapy, special duty
nursing, hairdressing or barber services, extra laundry, dry cleaning, employee or guest meals, vending
machines, telephone, day care and sale of crafts.
8
Much of this may be derived from the OAS and C-QPP public pensions.
6
expansion of home care to some extent as well. In Canada, home care covers services that
range from home support, to allied health, to professional nursing services delivered in a
home environment. Health Canada defines home care as, “an array of services which enables
clients incapacitated in whole or in part, to live at home, often with the effect of preventing,
delaying, or substituting for long-term residential care or acute care alternatives,” (Health
Canada, 1999). Although home care is not covered by the Canada Health Act, home care
services are now considered a de facto integral component of Canada’s health care system.
Like facility-based long-term care programs, home care programs vary across provinces
with respect to eligibility requirements, provision of services, cost-sharing, funding and
delivery. Table 2 shows some basic information on home care programs across provinces:
year of formal establishment, year of regionally-based delivery, co-payments and caps on the
hours of services or total dollars spent. Most provincial home care programs started in 1970s
and by late 1990s all provinces had implemented home care delivery programs based on
provincial standards.9 Seven provinces have implemented some form of co-payments for
some home care – primarily home support services. Manitoba and Quebec give priority to
low-income clients, clients at risk, or clients with no informal or family support; and Ontario
has the policy of first come first serve. Nursing and other professional health services (such as
acute care substitution or long-term care substitution or preventive services) do not involve
co-payments across Canadian provinces, but most professional services are capped in terms of
either the number of hours of service or total payments. The last column of Table 2 provides
information about the maximum contribution in terms of dollars or work hours.
INSERT Table 2
9
Note that the discussion on provincial home care programs is very brief in this report. A more comprehensive
outlook on home care programs across provinces can be found in Health Canada (1999).
7
Although all home care programs are publicly administered, home care services are
financed and delivered with a varying degree of public-private mix across provinces. For
instance, nursing, other professional health and home support services are predominantly
provided by publicly-funded employees in Manitoba, Saskatchewan, Quebec and Prince
Edward Island. In British Columbia, New Brunswick and Newfoundland; nursing and other
professional health services are delivered by publicly-funded employees but personal home
support services (e.g., shopping, cooking and cleaning) are contracted out to private for-profit
or private not-for-profit agencies. In Alberta and Nova Scotia, nursing and other professional
health services are delivered by a mix of public and private agencies and home support
services are contracted out to private agencies, but public employees coordinate all functions.
In Ontario, nursing, other professional health services and home support services are all
contracted out by a public authority to private for-profit or private not-for-profit agencies.
Rapid expansion of public home care programs in Canada is reflected in increased
expenditures on home care at a rate which is unparalleled to any other sector of the economy.
Although it is difficult to find accurate estimates of home care expenditures, several studies
do indicate a clear trend. Based on Health Canada data, Coyte and McKeever (2001) conclude
that public home care expenditures grew at an average annual rate of 17.4% between 1975/76
and 1997/98, increasing from $62 million to $2,096 million during this period. A recent CIHI
report (CIHI, 2003) suggests that total provincial home care expenditures increased by an
average annual growth rate of 15.4% between 1990/91 and 2000/01. The estimated public
home care expenditures in Canada for the fiscal year 20003/04 were about $3.4 billion in
current dollars (CIHI, 2007). There has been a secular rise in public per capita home care
8
expenditures in all jurisdictions during 1990/91 and 2003/04.10 Along with rapid expansion of
public home care expenditures, individuals also incur expenses on home care services.
Although no national level data on private home care expenditures are available at this time,
the estimate of Coyte and McKeever (2001) suggests that private home care expenditures
exceeded $500 million in 1997/98.
As far as the utilization of government subsidized home care services is concerned, the
number of home care recipients has been growing at an average rate of 1% per annum since
1994/95 (CIHI, 2007). In 2005, Statistics Canada’s Canadian Community Health Survey
reported that about 1.3 million Canadians (611,000 seniors) received some form of home care,
of which some 0.7 million Canadians (362,000 seniors) reported that they received home care
services from government sources.11 A majority of them received nursing and personal home
support services, including meal preparation/delivery and personal care. Of those who
reported they received home care from sources other than government, about half a million
Canadians (358,000 seniors) reported receiving home care from informal sources such as
spouse, neighbour, friend, family and volunteer (e.g., meals-on-wheels). The bulk of the
services received from informal sources are activities relating to household work, meal
preparation, shopping, personal care, or other home support services. About 200,000
Canadians reported that they received home care from private agencies.
Despite the appeal of home care programs throughout Canada and increased
utilization of home care services, there are certain barriers concerning access to and utilization
of certain types of home care services. In 2005, about 400,000 Canadians reported that they
10
Di Matteo and Di Matteo (2001) provide an extensive analysis of the determinants of public home care
expenditures in Canada. Among other things, they find that public home care expenditures are income elastic
and sensitive to the growth of the elderly population.
11
Authors’ calculation based on Canadian Community Health Survey, 2005.
9
could not receive home care when they perceived they needed it. A variety of reasons were
cited for self-perceived unmet needs: 26% were still on the waiting list, 20% were unable to
pay, 16% did not know where to go, 10% reported non-availability in the area, 5% did not
qualify and 5% felt the wait time was too long. Wait time, cost and lack of information
constitute the three main factors responsible for self-perceived unmet needs. Given the
extensive provision of subsidized home care services, the 20% figure for cost being a
constraint for utilization of home care services is somewhat surprising. Perhaps, tighter
rationing of home care service hours may be a contributing factor, especially for low-income
households. This is in sharp contrast with physician services, for which cost is almost never
an issue for Canadians. Arguably, self-perceived unmet needs may arise because of a possible
reduction in the availability of informal care or effective increase in demand due to increased
need or changing preferences. If reduction in informal care arises independent of the public
provision of home care, then it would be more of a change in the social structure requiring a
different kind of intervention. On the other hand, if reduction in informal care arises if
families strategically respond to publicly-available home care and home support services, then
we would have a concern as some of the burden of long-term care would be shifted from
families to government.12 However, provision of qualified and consistent home care services
might have the benefit of reducing institutionalization and so could outweigh the costs of
home care services associated with the portion of long-term care withdrawn from informal
sources.
12
A recent CIHI report (CIHI, 2007) suggests that on average each home care recipient consumed more
resources in 2003 than he/she did a decade ago. Stabile et al. (2006) find some evidence that increased
availability of publicly-provided home care is associated with increased use of home care and a decline in
informal care giving. However, robust empirical evidence on who should receive home care services and by how
much is needed in order to design an efficient and effective home care system that is responsive to the needs of
seniors while respecting the budgetary constraints.
10
3. Related Literature
A number of studies suggest that access to public home care reduces
institutionalization and enables independent living, but empirical evidence is somewhat
mixed. Utilizing data from the Channeling experiment of publicly financed home care in the
United States in early 1980s, some authors find no, or a very small effect of home care on
institutionalization (Rabiner et al., 1994; Wooldridge and Schore, 1988). By contrast, Pezzin
et al. (1995) using the same data find that public home care program increases the probability
of independent living for unmarried persons and reduces the probability of living in shared
households or nursing homes. They argue that their result arises from modelling living
arrangements and care provisions jointly, an approach that previous studies ignored. This
conclusion is supported by a number of other micro studies from the United States. For
example, Ettner (1994) finds that those who received home care under Medicaid were less
likely to use nursing homes. Picone and Wilson (1999), using a two part model, find that
increased use of formal home care reduces inpatient long-term care, but they warn about a
possible endogeneity bias associated with their results. Using Aging in Manitoba longitudinal
data from Canada and employing a random-effects multinomial logit framework, Sarma and
Simpson (2007) conclude that home care reduces the probability of living in institutions and
increases independent living in Manitoba, Canada
Other studies find opposite results. A study of Massachusetts community-dwelling
seniors found that use of formal home care was associated with increased risk of nursing
home entry (Jette et al., 1995). The authors argue that home care use could be a precursor of
institutionalization. Similarly, Naygaard and Albrektsen (1992) find that seniors using home
care services have a higher probability of nursing home admission. A similar result is found
11
in a study of Saskatchewan elders. Saskatchewan seniors receiving preventive home care
services (such as homemaking, personal care, meal preparation and other light services
designed to help them live in the community) are 50% more likely to die or 50% more likely
to lose their independence (defined as being alive and not living in a nursing home) than those
not receiving this service (Health Services Utilization and Research Commission, 2000). But,
persons who live in seniors housing are 40% less likely to die and 60% less likely to enter a
nursing home.
A number of other studies in the literature produce mixed results. Hoerger et al.
(1996) find that subsidized home health services increase the probability of independent
living but do not affect the probability of institutionalization. Newman and Strvyk (1996) find
that home care provided by anyone other than spouse is associated with a higher risk of
nursing home entry, but when they interact the measures of home care with presence of
disability, they find no effect of home care on nursing home entry. Using 1986 census data
linked to Manitoba longitudinal health care utilization data from Canada, Tomiak et al. (2000)
find that presence of the spouse does not reduce the likelihood of nursing home entry but
having an additional household member does. Using an instrumental method of estimation,
Charles and Sevak (2005) find that informal home care reduces the probability of nursing
home use, but their OLS results suggest the opposite. These conflicting results underscore the
need to choose an appropriate estimation technique.
The empirical findings summarized above generally suggest that provision of public
home care and informal care affects the probability of institutionalization and independent
living, but the evidence is mixed. Aside from mixed empirical results and methodological
considerations, the findings from non-Canadian settings may well limit insights for policy
12
formulation in Canada due to the distinct nature of the institutions and the relative generosity
of both home care and facility-based long-term care programs in Canada.
One’s social network constitutes another important dimension of personal support and
well-being during old age. Social network is defined in a variety of ways in the gerontology
literature, ranging from narrow family-based to wide-family based networks, friend – or
neighbour-based groupings, community-based networks, and private restricted networks
(Wenger, 1996). The social networks in which seniors are embedded have important
implications for healthy living in the community and healthy aging because it provides a
sense of belonging, guidance, support and assistance in fulfilling certain tasks, feeling loved
and being needed, and a sense of communal day-to-day activities. A positive relationship
between social network and self-reported health status is found in Canada (Statistics Canada,
2007).
Not surprisingly, access to social networks are known to mediate the effects of
stressful events in life, such as widowhood, retirement, incidence of an illness or disability,
etc. as evidenced by recent research: social support enhances quality of life and well-being
during times of stress (Denton et al., 2004; Shields, 2004). Conversely, low levels of social
integration or social supports are significant predictors of morbidity, mortality and
institutionalization (Arber, 2004; Prus and Gee, 2001). Thus, social support services and
access to social networks are expected to contribute positively towards independent living in
the community and so help avoid institutionalization.
A variety of other socio-demographic factors have also been found in the literature
that can affect the likelihood of institutionalization (see the discussion in Sarma and Simpson,
2007). Age, gender, marital status, low socio-economic status, decline in activities of daily
living and decline in health status are generally associated with increased institutionalization.
13
Murtaugh et al. (1997) conclude that a person who reached the age of 65 in 1995 had a 39%
higher probability of entering a nursing home during his or her remaining life-time. Some
studies find that women are more likely to be institutionalized (Lavery et al., 1997;
Rockwood et al., 1996) but this could be because they live longer than men. As expected,
married people are less likely to be institutionalized than widows and widowers (Lakdawalla
and Schoeni, 2003; Mustard et al., 1999; Hoerger et al., 1996; Freedman, 1996). Low income
and low education are associated with a higher probability of institutionalization (Tomiak et.
al., 2000; Mustard et al., 1999; Alarcon et al., 1999), but some studies in the US find that
income does not affect the risk of nursing home entry (Garber and MaCurdy, 1990; Cutler
and Sheiner, 1994; Ettner, 1994).
4. The Empirical Framework
This paper, examines the transitions in living arrangements decisions for seniors in
Canada. An elderly person (or a couple as a decision maker) living independently is assumed
to make decisions about future living arrangements after taking into account his/her health
conditions and available family financial and non-financial resources to maximize expected
utility. Let a person’s utility of choosing the living arrangement type j in time period t be Ujt
(Ft, Ct, Xt), where Ft is formal long-term care received in time t, Ct is the consumption of
other goods and services in time t and Xt is a vector of person-specific characteristics in time
t. Assume that the indirect utility for state j in time period t be Vjt(P, Y, X) where P is the price
of formal long-term care and Y is income. After solving the maximization problem subject to
relevant budget constraints, an elderly person chooses alternative j in time period t if and only
if Vjt(P, Y, X)> Vkt(P, Y, X)∀ j ≠ k. If one considers the simplified assumption that seniors
14
make a one-time decision about their living arrangements (e.g., Sarma and Simpson, 2007),
the problem becomes simpler as a multinomial logit or multinomial probit framework can be
easily utilized to model the living arrangement choices.13 But this assumption is very
restrictive since many transitions occur during the life course of seniors. It can be seen in
Table 3 below, seniors tend to change their initial living arrangements. Another problem to be
addressed is that a number of seniors died over the survey period, causing censoring from one
cycle to another. In this paper, we propose a discrete-time hazard rate model to account for
these inherent dynamic features associated with seniors’ transition in living arrangements.
The discrete nature of seniors’ living arrangement transitions make it suitable to
employ a discrete rather than a continuous-time hazard rate model. Let the time spent by
individual i in state j be described by a non-negative random variable, T, which is partitioned
into a discrete number of intervals It [1:1994/95; 2:1996/97; 3:1998/99; 4:2000/01; 5:2002/03;
6:2004/05]. If an individual dies in the interval [It-1, It], this variable takes on a value of T = t.
The destination specific hazard rate λij (t ) is the conditional probability that individual i
transits into state j in the interval It conditional on her survival until the beginning of It. For
individual i, the hazard rate is formally defined as
(
) (
)
λij t | X it , ε i m = P Ti = t , δ ij = 1 | Ti ≥ t , X it , ε i m .
(1)
Where i = 1, …, N; t = 1, …, Ti; j = 1 (remains in independent living arrangement), 2
(transition from independent living to intergenerational living arrangement), 3 (transition
from independent living to institution); δ ij is the transition indicator; X it is a vector of
13
Most of the empirical frameworks used to study elderly living arrangements decisions use multinomial logit or
multinomial probit models. See, for instance, Sarma and Simpson (2007), Börsch-Supan (1990), Börsch-Supan
et al. (1992), Pezzin et al. (1995) and Hoerger et al. (1996).
15
covariates of individual i in interval t; and ε i is the time-invariant individual effect with the
m
following assumptions:
M
( )
( ) = 1, E (ε
M
E (ε i ) = ∑ P ε i ε i = 0, ∑ P ε i
m =1
m
m
m =1
m
m
i
)
X it = 0 ∀m.
(2)
The time-invariant individual effect accounts for unobserved heterogeneity (Heckman and
Singer, 1984) in the transition rates not accounted for by the included covariates and assumed
to come from a discrete probability distribution with a small number of mass points m .
Conditional on the vector of covariates and the individual effect, transition into the
two states are assumed to be independent and hence can be viewed as competing risks. Since
the transition states are mutually exclusive, the total hazard defined as the probability of
transiting in interval It is given by
(
)
3
(
)
λ t | X it , ε i m = ∑ λij t | X it , ε i m .
j =2
(3)
The survivor function is the unconditional probability of not transiting (i.e., remain in
independent living) up to time t is given by
(
P Ti ≥ t | X it , ε i
m
) = S (t | X
ij
it , ε i
m
) = ∏ (1 − λ (t | X
t −1
τ =1
it
,εi
m
)).
(4)
In terms of the respective hazard rate and the survivor function, the probability of a transition
into state j in period t is given by
(
P Ti = t , j | X it , ε i
m
) = λ (t | X
ij
it
,εi
m
)∏ (1 − λ (t | X
t −1
τ =1
it
,εi
m
)).
(5)
Assuming that conditional on all covariates, all observations are independent, the likelihood
function is
16
N
( )∏ [λ (t | X
M
L = ∏∏ P ε i
i =1 m =1
3
m
ij
it
,εi
δ ij t −1
)] ∏ (1 − λ (t | X
m
τ =1
j =2
it
,εi
m
)).
(6)
In equation (6), δ ij = 1 if individual i makes living arrangement transition j (j = 2, 3), 0
otherwise.
For an individual with a transition into living arrangement other than independent
living, the contribution to the likelihood function is given by the respective transition
probability in equation (5), for a censored spell it is given by the survivor function in equation
(4). The survivor function not only provides information for individuals right-censored at the
end of the survey period, but also for those who died causing sample attrition. Now, it
remains to specify a hazard function, which is specified as a multinomial logit model in this
study. That is,
(
λij t | X it , ε i
m
)=
exp(α j (t )) + β j X it + ε i
'
3
∑ exp(α (t )) + β
l =1
l
'
l
m
X it + ε i
(7)
.
m
The term α j (t ) in equation (7) describes the dependence of the hazard rate on process time
and known as the baseline hazard. In order to avoid possible misspecification on the
functional form of the baseline hazard, a set of dummy variables are included to allow for
flexibility of the baseline hazard function. Substituting the hazard rate (7) into the likelihood
function (6) maximum likelihood method of estimation is used to estimate the parameters of
interest using numerical optimization procedure.14
14
We use GLLAMM, a STATA subroutine, developed by Rabe-Hesketh et al. (2004).
17
5. Data and Variables
Data for this study were obtained from the first six cycles (1994/95-2004/05) of the
National Population Health Survey (NPHS) conducted by Statistics Canada. The NPHS is an
ongoing longitudinal survey of a nationally representative sample. The NPHS collects
detailed health and socio-economic information about Canadian population every two years
since 1994/95. In this paper, we use responses of individuals who were aged 65 or above in
1994/95 survey.15
A sample of 2,514 individuals 65 years of age and over was available in the NPHS
1994/95. However, 50 of individuals did not respond in all subsequent cycles and hence
excluded from our analysis. In 1994/95, those living in intergenerational living arrangements
(274 observations) are also excluded from our analysis because our focus in this paper is on
transitions from independent to intergenerational and institutional living arrangements. After
deleting incomplete records, 2,033 suitable observations are available for analysis. Incomplete
records, if any, arising in subsequent cycles of these individuals are statistically imputed from
their previous survey response.
The living arrangements variable takes three possible outcomes: a) independent living
arrangements (living alone or living with a spouse/partner), b) intergenerational living
arrangements (living with children or siblings or others aged 12 years or above) and c) living
in an institution. Since the analysis in this paper is restricted to those seniors living in an
independent living arrangement in 1994/95, we are able to focus on two key transitions:
15
Since there are severe restrictions on the use of NPHS longitudinal data due to confidentiality reasons, we use
NPHS longitudinal share file in this study. The share file consists of those individuals who agreed to share their
responses with Health Canada. However, 93% or more individuals agreed to share their responses with Health
Canada, so any bias arising from use of shared data would be extremely small.
18
transition from independent to intergenerational and institutional living arrangements. Table 3
provides information on transitions in living arrangements of seniors.
Insert Table 3
Consistent with the extant literature, four categories of explanatory variables are used
to explain transitions in living arrangements: public home care, social support services,
individual characteristics and household income. The NPHS consistently collects information
on whether a respondent received partial or fully subsidized home care services. The first
difference of this variable is used to analyze the impact of subsidized home care services on
living arrangement transitions of seniors.
The social support variables reflecting access to hitherto social networks are
constructed to analyze the impact of access to community or social support services on
seniors’ living arrangement transitions. The social support variables in the first two cycles of
NPHS are based on yes/no response to the following four questions: i) Do you have some one
you can confide in or talk to about your private feelings or concerns?, ii) Do you have
someone you can really count on to help you out in a crisis situation?, iii) Do you have
someone you can really count on to give you advice when you are making important personal
decisions? and iv) Do you have someone who makes you feel loved and cared for? Since
1998/99 cycle, the NPHS changed aspects of the social support questionnaire. Although
similar questions as in the first two cycles are also asked, instead of yes/no response the
survey asked how often social support services are available if someone needs them. In order
to be consistent with social support variables for our analysis, we constructed an equivalent
yes/no response. If the response to the similar question is ‘all of the time’ or ‘most of the
time’ we classified the response in the Yes category and if the response is ‘none of the time’
or ‘a little of the time’ or ‘some of the time’ we classify the response in the No category.
19
Since responses to these four questions are often correlated, we created three dummy
variables based on the degree of access to social support services: if yes response to all four
questions, yes response to 2 or 3 questions, and yes response to 1 or no question.
Health status ought to be an important factor contributing to living arrangements
decisions of seniors. Fortunately, the NPHS consistently collects information on a Health
Utility Index (HUI) in all 6 cycles. The HUI is a health status index variable which is able to
combine both qualitative and quantitative dimensions of health. This index, developed at
McMaster University’s Centre for Health Economics and Policy Analysis, captures an
individual’s overall functional health based on eight attributes: vision, hearing, speech,
mobility (ability to get around), dexterity (use of hands and fingers), cognition (memory and
thinking), emotion (feelings), and pain and discomfort. A higher HUI score indicates better
health status; its value ranges between -.36 to 1.0, 1 being rated as perfect health, death is
rated 0, and negative values indicate worse than death!
We also include gender, age, educational status, marital status, immigration status,
household income, baseline hazard dummies and control for provincial fixed effects. Gender
is represented by a dummy variable (female= 1, male = 0). Two dummy variables capture
differences in age: 75-84 years and 85 or older, leaving 65-74 as the reference group.
Educational status of the respondent is characterized by dummies for those respondents who
have some post-secondary education and who completed a post-secondary degree, leaving
those with secondary education or less as the reference category. Marital status is
characterized by two dummy variables (currently married = 1, 0 otherwise, and widows,
separated and divorced = 1, 0 otherwise), which implies that singles are the reference
category. Immigration status of the respondent is represented by a dummy variable
(immigrant = 1, Canadian born = 0). Differences in annual household incomes are represented
20
by four dummy variables: $15,000-$29,999, $30,000-$49,999, $50,000-$79,999 and $80,000
or more, leaving less than $15,000 as the reference category. Table 4 provides the definitions
of the list of explanatory variables used and Table 5 presents the corresponding descriptive
statistics for all cycles.
Insert Tables 4-5
6. Discussion of Results
In this section, we discuss the empirical results of this study. As expected, a higher
number of senior survivors in our sample are females; their proportion has increased from
60% in 1994/95 to 65% in 2004/05. This is expected since women survive longer than men.
Those aged 65–74 years in 1994/95 survived in subsequent cycles and those who passed away
were on average older. Those who passed away are more likely to have received home care
services and social support services on average in the previous period compared to the
survivors. However, this does not necessarily imply causation. One of the important life cycle
events of seniors is becoming a widow/widower. In 1994/95, married and widows/widowers
were about 47% each, but by 2004/05 widows/widowers increased to 60% of total survivors
while those married declined to 34%.
Another important life-cycle event is the decline in health status of seniors. A
consistent decrease in health utility index (HUI) score on average from one cycle to another
cycle is seen, which reflects overall decline in functional health status of aging seniors. Those
who passed away did exhibit lower HUI score in the previous period on average compared to
the survivors in that period. A similar pattern of decline in health is also seen in terms of self-
21
reported health status. Seniors in low income households seem to die more rapidly on average
compared to those in high income households.
Although the above descriptive statistics reveal useful information, a number of key
variables are not controlled for to provide insight into policy. We therefore use the regression
framework of the preceding section to disentangle the effects of key variables explaining
transitions in seniors’ living arrangements.
For model identification, the expected utility from the reference alternative (i.e.,
independent living arrangements) has been normalized to zero so that the results are
interpreted in relation to the independent living arrangement. We find that our estimated
model that accounts for unobserved heterogeneity is preferred16 and so the discussion of
results below are thus based on the preferred specification. The estimated results after
accounting for unobserved heterogeneity (with three mass points) are presented in Table 6.17
Insert Table 6
The estimated mass probabilities (or latent class probabilities) and the coordinates of
the three mass points (intercept, slope) are reported at the bottom of Table 6. The latent class
probabilities can be interpreted as proportions of individuals with given observed
characteristics belonging to one of the three heterogeneity groups (perhaps representing the
underling long-term health status or preferences of seniors).
16
The estimated results without controlling for unobserved heterogeneity are available from the corresponding
author upon request. Note that standard likelihood ratio test cannot be used in this case because under the null
hypothesis of no unobserved heterogeneity, this test violates certain regularity conditions and its distribution is
unknown. Akaike Information Criterion (AIC) was therefore used to assess the preferred model specification.
AIC is defined as lnL–K, where lnL is the log likelihood at the maximum and K is the number of estimated
parameters in the model. The model with the largest AIC value is preferred. After being able to estimate the
model with three mass points, the Gateaux derivative method suggested that a further mass point does not
maximize the likelihood. Thus, the three mass points represent the non-parametric maximum likelihood solution
(Heckman and Singer, 1984).
17
As per convention, the estimated coefficients and standard errors are presented in this paper. The exponent of
the estimated coefficients, however, has the interpretation of the “relative risk,” and it gives the change in the
relative probability to independent living for a unit change in the explanatory variable (i.e., a change in the
“odds”)
22
The estimated coefficients of the baseline hazard dummies are positively significant
and higher at longer durations for transition to institutional living arrangements. For transition
to intergenerational living arrangements, the baseline hazard dummies are also positively
significant except the first dummy. This suggests that the hazard of entering intergenerational
and institutional living arrangements increases with the duration of survival – evidence of a
positive duration dependence. These results suggest that as seniors survive longer there would
be increased demand for both intergenerational and institutional living.
Turning to the effects of explanatory variables in the model, we find that the impact
of home care has a negative effect on institutionalization, but statistically insignificant effect
on intergenerational living arrangements.18 This supports the notion that publicly-provided
home care and publicly-provided long-term care in facility-based institutions are substitutes to
some degree. The negative effect of publicly provided homecare on institutionalization is
consistent with the findings of Sarma and Simpson (2007), Ettner (1994), Pezzin et al. (1995)
and Picone and Wilson (1999). The social support variables have a negative effect on
institutional living, but only one social support variable has a negative effect, at the 10% level
of significance, on intergenerational living arrangements. Taken together, these results show
that public provision of home care services and social support services would reduce
institutionalization. From a policy perspective, these results offer important insights into the
role of formal home care services as well as informal social support services in reducing
institutionalization and encouraging prolonged residency within the community.
We also find that gender has no effect on transitions in living arrangements after
unobserved heterogeneity is accounted for. The effect of age on the probability of transiting to
18
Note that receiving home care and institutional living are mutually exclusive. Moreover, home care received in
the current period may be endogenous with respect to community living. Thus, we use the first difference of the
home care.
23
both intergenerational and institutional living arrangements is positive at the 1% level of
significance, a result that is consistent across studies in the literature. Although elderly
immigrants seem to be less likely to seek institutional care (perhaps due to a traditional
extended family sense of obligations), this effect becomes statistically insignificant after
unobserved heterogeneity is accounted for.
The effect of education on the probability of transiting to both intergenerational and
institutional living arrangements is negative, but statistically significant for post-graduate
degree holders only. This finding suggests that highly educated seniors are more likely to live
independently and less likely to cohabit or institutionalize. Low education levels associated
with a higher probability of institutionalization were found in earlier Canadian studies
(Mustard et al., 1999; Tomiak et. al., 2000).
Being married also decreases the probability of transiting to both intergenerational and
institutional living arrangements. However, being widowed/divorced/separated (rather than
single) has no effect on transitions to intergenerational and institutional living arrangements.
Married seniors are less likely to institutionalize in the literature (Sarma and Simpson, 2007;
Freedman, 1996; Hoerger et al., 1996; Mustard et al., 1999; Lakdawalla and Schoeni, 2003).
The negative effect of marital status on intergenerational living is also found in some of the
previous studies (Sarma and Simpson, 2007; Hoerger et al., 1996).
HUI score has a negatively significant effect on the probability of transiting to both
intergenerational and institutional forms of living arrangements. This suggests that those who
are healthy (in terms of HUI score) are, as expected, more likely to live independently in the
community. Conversely, those who experienced deterioration in their self-reported health
status are more likely to move into institutions. But, a decline in self-reported health status is
statistically insignificant for transition to intergenerational living arrangements.
24
The effect of household income on the probability of transiting to intergenerational
living arrangements is positively significant except for the first category. This shows that
those families who are financially well-off are more likely to move to intergenerational living
arrangements. Alternatively, having enough financial resources at the household level would
allow seniors to stay independently or co-reside with family. The effect of household income
on the probability of institutionalization, however, is negative for two low income dummies.
This suggests that seniors in low-income households are less likely to move to
institutionalized living arrangements. This result arises perhaps because low-income families
may not be willing to sacrifice family financial resources as seniors are required to pay all
fees associated with long-term care provision as long as they are able to pay, regardless of
dependency situation at home. This result is in contrast to some studies in the United States
that find that income does not affect the risk of nursing home entry (Garber and Macurdy,
1990; Ettner, 1994; Cutler and Sheiner, 1994). However, Headen (1993) finds that individuals
with pension income and real estate income have lower risk of nursing home entry in the
United States.
7. Conclusions
With the aging of Canada’s population, concerns are growing about organizing,
financing and delivering continuing care services to our seniors. Much of this concern is
based on linear abstractions of past experience. All provinces and territories provide some
form of continuing care to their residents with preponderance of public sector financing, albeit
with varying degrees of generosity and coverage. There are two important public programs
through which seniors gain access to continuing care services in Canada’s health care
25
continuum: facility-based long-term care and home care (including personal home support
services). Facility-based long-term care provides higher levels of nursing care and other
assistance with respect to basic activities of daily living for those who can no longer be
adequately cared for at home. Home care provides generally less intense nursing services and
other home support services in the home environment. In recent years, home care programs
expanded rapidly across provinces, partly in response to aging of the population coupled with
seniors’ increased preference to stay at home.
Given the aging population, demand for both home care and facility-based
institutional care are likely to increase in the foreseeable future. Home care is relatively less
expensive than institutional care and its appropriate provision could meet the needs of
relatively young healthy seniors in a cost-effective way. On the other hand, facility based
institutional care is highly expensive but it may well be the only alternative to meet the
greater needs of the frail elderly who often suffer from multiple ailments. Given the increased
costs and greater demand for continuing care services, a potentially important means to ease
anticipated pressure on both publicly-provided institutional care and home care could be
through greater access to and availability of informal care (i.e., care provided by friend,
family, spouse, neighbour and community).
From an efficiency perspective, it would be preferable to facilitate independent living
or intergenerational living of seniors within their communities with appropriate provision of
both formal and informal home care and other support services. It is in this context, this paper
analyzes the effect of subsidized home care, social support and a host of other factors
influencing transitions in living arrangements decisions of seniors with the view to informing
policy development. Using data from Canadian National Population Health Survey, our
econometric study employs a discrete-time hazard rate multinomial logit model to account for
26
presence of unobserved individual heterogeneity in the data. After accounting for unobserved
individual heterogeneity, the empirical analysis finds that in relation to independent living,
ceteris paribus:
•
the impact of home care decreases the probability of institutionalization, but no
statistically significant effect on intergenerational living;
•
access to and availability of social support variables have a negative effect on the
probability of transiting to institutional and intergenerational living arrangements,
but the effect is stronger for institutionalization;
•
higher levels of functional health status measured by HUI score negatively affects
the probability of transiting to both intergenerational and institutional forms of
living arrangements;
•
decline in self-reported health status has a positive effect on the probability of
institutionalization, but no effect on transition to intergenerational living
arrangements;
•
higher levels of household income is associated with a higher probability of
transiting to intergenerational living and low levels of household income is
associated with a lower probability of institutionalization;
•
post-graduate holder seniors are less likely to transit to both intergenerational and
institutional living arrangements;
•
gender has no effect on the living arrangements, but age has a positive effect on
the probability of transiting to institutionalization and cohabiting;
•
being married rather than single decreases the probability of transiting to
intergenerational and institutional living arrangements; and
27
•
the hazard of entering both intergenerational and independent living increases with
the duration of survival.
Provision of home care services, social support services and promoting healthy lifestyles would be the most important factors that would contribute positively towards
independent living and reduce institutionalization in the next two decades or so. This
approach would foster an efficient, effective and sustainable health care system, one that
meets the heterogeneous needs of seniors. Additional research is required to determine
optimal-mix of long-term institutional care and home care, as well as optimal public-private
financing.
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30
Table 1
Information on Provincial Facility-based Long-term Care Programs
Province Name of the Facility-based Income
Asset
Monthly Charges for
Long-term Care Institution Testing
Testing
Regular Accommodation
Minimum Maximum
B.C.
Residential Care Facility
Yes
No
$864
$2,076
Alta.
Continuing Care Centre
No
No
$1,188.601 $1,188.60
Sask.
Special Care Home
Yes
No
$911
$1,727
Man.
Personal Care Home
Yes
No
$825
$1,938
1
Long-term Care Facility
Yes
No
$1,480.99 $1,480.99
Ont.
Complex Continuing Care
Yes
No
Que.
N.B.
N.S.
Centre d’hébergement et de soins
de longue durée (CHSLD)
CHSLD privés non
conventionnés
Yes
Yes
$949.20
$1,527.60
N/A
N/A
Nursing Home
Yes
Yes
$35401
$5,220
Nursing Home
Yes
No
$2,2351
$2,235
Government Manor Home
Yes
Yes
$3,6902
$3,9603
2
P.E.I.
Private Manor Home
N/A
N/A
$3,555
$4,8323
Nfld.
Nursing Home
Yes
Yes
$2,800
$2,800
Source: Annual Guide to Canadian Health Care Facilities, Canadian Healthcare
Association, 2006. http://www.cha.ca/publishing.html
1
Low-income seniors with a monthly income less than basic charge receive supplementary
benefit.
2
Level 4 care as defined by the PEI government
3
Level 5 care as defined by the PEI government
31
Province
B.C.
Alta.
Sask.
Man.
Ont.
Que.
N.B.
N.S.
P.E.I.
Nfld.
Table 2
Information on Provincial Home Care Programs
Maximum Amount of Services
Home Care
Regionally Income
or Dollars
Program
Based
Testing1
Established
Delivery
1978
1997
Yes
40-98 hours per month
1978
1995
Yes
$3,000 per month
1978
1992
Yes
$2,500-$3,500 per month
1974
1992
No2
Institutional care formula
1972
1997
No
60 hours per month (80 hours
first month)
1972
1991
No2
40 hours per week
1981
1996
Yes
$2,040 per month
1988
1996
Yes
$2,200 per month
$4,000 per month
1986
1996
Yes
28 hours per week
1975
1992
Yes
$2,268 per month
Source: Di Matteo and Di Matteo (2001) and Stabile et al. (2006)
1
Income testing is used to determine co-payments for home support services only.
Priority is given to low-income clients, clients at risk, or clients with no informal or family support.
32
Table 3
Living Arrangements of Those Aged 65 and Older in 1994/95 NPHS
Independent
Intergenerational
Institution
Cycle/Year
Total
New*
Total
New*
Cycle 1 (1994/95)
2,033
0**
0
0 0
Cycle 2 (1996/97)
1,799
38
38
44 44
Cycle 3 (1998/99)
1,589
50
33
86 56
Cycle 4 (2000/01)
1,332
65
33
126 71
Cycle 5 (2002/03)
1,149
57
18
143 70
Cycle 6 (2004/05)
957
58
22
131 56
* Transition from independent living arrangements
** Note that 274 individuals lived in intergenerational form of living arrangement during 1994/95,
but excluded from our analysis.
33
Dead
0
152
156
202
174
203
Table 4
Explanatory Variable Definitions
Variable
Definition
Female
Age (65-74 yrs in 1994)
Age (75-84 yrs in 1994)
Age (≥ 85 yrs in 1994)
Edu: secondary or less
Female = 1, male = 0
Age group: 65 – 74 years in 1994/95
Age group: 75 – 84 years in 1994/95
Age group: 85 or older in 1994/95
Education: secondary school graduation or less = 1,
otherwise = 0
Edu: some post-secondary
Education: some post-secondary education = 1,
otherwise = 0
Edu: post-secondary grad
Education: post-secondary graduation = 1, otherwise =
0
Immigrant
Immigrant = 1, Canadian born = 0
Home care received
Home care received = 1, otherwise = 0
Social support a
Social Support Index: receive no or one type of social
support when needed = 1, otherwise = 0
Social support b
Social Support Index: receive two or three types of
social support when needed = 1, otherwise = 0
Social support c
Social Support Index: receive all four types of social
support when needed = 1, otherwise = 0
Married
Currently married or common law = 1, otherwise = 0
Widows/divorced/separated Widows, separated, and divorced = 1, otherwise = 0
Single
Single =1, otherwise = 0
HUI
Health Utility Index
Decline in SHS
Self-reported health status changes from excellent or
very good or good to fair or poor = 1, otherwise = 0
Income (< $15,000)
Annual Household Income: < $15,000 = 1, otherwise
=0
Income ($15,000- $29,999) Annual Household Income: $15,000-$29,999 = 1,
otherwise = 0
Income ($30,000- $49,999) Annual Household Income: $30,000-$49,999 = 1,
otherwise = 0
Income ($50,000- $79,999) Annual Household Income: $50,000-$79,999 = 1,
otherwise = 0
Annual Household Income: $80,000 or more = 1,
Income (≥ $80,000)
otherwise = 0
Survived up to 2 years
Survival Time: survived up to two years from the date
of interview in 1994/95 = 1, otherwise = 0
Survived 3-4 years
Survival Time: survived three to four years from the
date of interview in 1994/95 = 1, otherwise = 0
Survived 5-6 years
Survival Time: survived five to six years from the date
of interview in 1994/95 = 1, otherwise = 0
Survived 7-8 years
Survival Time: survived seven to eight years from the
date of interview in 1994/95 = 1, otherwise = 0
Survived 9-10 years
Survival Time: survived nine to ten years from the
34
Survived 11 years or more
Nfld., P.E.I., N.S. and N.B.
Que.
Man. and Sask.
B.C.
Alta.
Ont.
date of interview in 1994/95 = 1, otherwise = 0
Survival Time: survived 11 years or more from the
date of interview in 1994/95 = 1, otherwise = 0
Province: Newfoundland, Prince Edward Island, Nova
Scotia, and New Brunswick = 1, otherwise = 0
Province: Quebec = 1, otherwise = 0
Province: Manitoba and Saskatchewan = 1, otherwise
=0
Province: British Columbia = 1, otherwise = 0
Province: Alberta = 1, otherwise = 0
Province: Ontario = 1, otherwise = 0
35
Table 5
Summary Statistics for Explanatory Variables
Variable
Cycle1
Cycle2
Cycle3
(1994/95)
(1996/97)
(1998/99)
N = 2,033
N = 1,881
N = 1,725
Mean
Std.
Mean Std.
Mean
Std.
Dev.
Dev.
Dev.
Female
0.599
0.490 0.615 0.487
0.624
0.485
Age (65-74 yrs in 1994)
0.579
0.494 0.598 0.490
0.626
0.484
Age (75-84 yrs in 1994)
0.347
0.476 0.341 0.474
0.321
0.467
Age (≥ 85 yrs in 1994)
0.074
0.261 0.061 0.239
0.053
0.225
Edu: secondary or less
0.660
0.474 0.654 0.476
0.645
0.479
Edu: some post-secondary
0.171
0.377 0.174 0.379
0.177
0.382
Edu: post-secondary grad
0.169
0.375 0.172 0.378
0.179
0.383
Immigrant
0.178
0.383 0.177 0.382
0.174
0.380
Home care receiveda
0.135
0.342 0.143 0.350
0.157
0.364
a
Social support a
0.033
0.180 0.041 0.198
0.113
0.317
Social support ba
0.178
0.383 0.146 0.354
0.259
0.438
a
Social support c
0.751
0.432 0.806 0.396
0.624
0.484
Married
0.467
0.499 0.445 0.497
0.413
0.493
Widows/divorced/separated 0.467
0.499 0.490 0.500
0.525
0.500
Single
0.066
0.248 0.065 0.246
0.061
0.240
HUI
0.758
0.270 0.766 0.274
0.716
0.314
Decline in SHS
0.088 0.283
0.123
0.328
Income (< $15,000) b
0.352
0.478 0.325 0.468
0.334
0.472
Income ($15,000-$29,999) b 0.421
0.494 0.440 0.496
0.419
0.493
Income ($30,000-$49,999) b 0.159
0.366 0.174 0.379
0.166
0.373
b
Income ($50,000-$79,999)
0.045
0.208 0.047 0.212
0.060
0.237
Income (≥ $80,000) b
0.023
0.150 0.014 0.119
0.021
0.145
Nfld., P.E.I., N.S. and N.B.
0.253
0.435 0.252 0.434
0.253
0.435
Que.
0.126
0.332 0.126 0.332
0.126
0.332
Man. and Sask.
0.180
0.384 0.180 0.384
0.181
0.385
B.C.
0.111
0.314 0.111 0.314
0.107
0.310
Alta.
0.067
0.251 0.067 0.251
0.067
0.251
Ont.
0.263
0.440 0.264 0.441
0.266
0.442
36
Variable
Female
Age (65-74 yrs in 1994)
Age (75-84 yrs in 1994)
Age (≥85 yrs in 1994)
Edu: secondary or less
Edu: some post-secondary
Edu: post-secondary grad
Immigrant
Home care receiveda
Social support aa
Social support ba
Social support ca
Table 8 (Contd.)
Cycle4
Cycle5
(2000/01)
(2002/03)
N = 1,523
N = 1,349
Mean Std.
Mean
Std.
Dev.
Dev.
0.638 0.481
0.643
0.479
0.654 0.476
0.681
0.466
0.303 0.460
0.288
0.453
0.043 0.204
0.032
0.176
0.640 0.480
0.634
0.482
0.179 0.383
0.179
0.384
0.182 0.386
0.187
0.390
0.177 0.381
0.143
0.381
0.180 0.384
0.156
0.363
0.120 0.325
0.128
0.334
0.231 0.422
0.289
0.453
0.647 0.478
0.582
0.493
0.387 0.487
0.363
0.481
0.549 0.498
0.573
0.495
0.064 0.244
0.063
0.243
0.712 0.320
0.686
0.334
0.147 0.354
0.127
0.333
0.316 0.465
0.306
0.461
0.408 0.492
0.401
0.490
0.184 0.387
0.182
0.386
0.066 0.249
0.080
0.271
0.026 0.160
0.030
0.172
0.251 0.434
0.249
0.433
0.125 0.331
0.128
0.334
0.173 0.378
0.172
0.380
0.106 0.308
0.107
0.309
0.074 0.261
0.073
0.261
0.271 0.445
0.271
0.444
Married
Widows/divorced/separated
Single
HUI
Decline in SHS
Income (< $15,000) b
Income ($15,000- $29,999) b
Income ($30,000- $49,999) b
Income ($50,000- $79,999) b
Income (≥ $80,000) b
Nfld., P.E.I., N.S. and N.B.
Que.
Man. and Sask.
B.C.
Alta.
Ont.
a
Excludes those residing in institutions
b
Annual household income from all sources
37
Cycle6
(2004/05)
N = 1,146
Mean Std.
Dev.
0.647 0.478
0.726 0.446
0.251 0.434
0.023 0.149
0.620 0.485
0.190 0.393
0.189 0.392
0.179 0.383
0.156 0.363
0.131 0.338
0.275 0.447
0.593 0.491
0.339 0.474
0.597 0.491
0.064 0.244
0.673 0.335
0.127 0.333
0.271 0.444
0.441 0.497
0.166 0.372
0.092 0.289
0.031 0.174
0.247 0.431
0.131 0.337
0.164 0.370
0.112 0.315
0.076 0.265
0.271 0.444
Table 6
Discrete Hazard Multinomial Logit with Unobserved Heterogeneity
-------------------------------------------------------------------------------------------------------------Transition to
Transition to
Intergenerational Living
Institution
-------------------------------------------------------------------------------------------------------------Home care received (t) - Home
-0.331
-0.534***
(0.225)
(0.168)
care received (t-2)a
Social support a:
reference category
Social support c a
-0.045
-0.483***
(0.266)
(0.186)
a
-0.531*
-0.711***
Social support b
(0.306)
(0.212)
Female
0.245
0.212
(0.233)
(0.176)
Age (65-74 yrs in 1994):
reference category
Age (75-84 yrs in 1994)
0.728***
1.153***
(0.233)
(0.170)
Age (≥85 yrs in 1994)
0.995**
1.653***
(0.439)
(0.274)
Education: secondary or less:
reference category
Education: some post-secondary
-0.305
-0.194
(0.277)
(0.205)
Education: post-secondary grad
-0.749**
-0.485**
(0.309)
(0.235)
Immigrant
0.213
-0.174
(0.267)
(0.196)
Single:
reference category
Married
-0.897*
-0.813***
(0.484)
(0.309)
Widows/separated/divorced
0.421
-0.307
(0.451)
(0.275)
HUI
-3.188***
-3.526***
(0.286)
(0.204)
Decline in SHS
0.305
0.352**
(0.209)
(0.159)
Income (< $15,000):
reference category
Income ($15,000- $29,999)
0.305
-0.431***
(0.213)
(0.156)
Income ($30,000- $49,999)
0.851***
-0.442*
(0.289)
(0.242)
Income ($50,000- $79,999)
1.023***
-0.473
(0.378)
(0.349)
Income (≥ $80,000)
1.770***
0.521
(0.679)
(0.562)
Survived up to 4 years:
reference category
Survived 5-6 years
0.388
0.694***
38
Survived 7-8 years
Survived 9-10 years
Survived 11 years or more
Ont.:
Nfld., P.E.I., N.S. and N.B.
Que.
Man. and Sask.
B.C.
Alta.
Constant
P(ε 1 )
P(ε 2 )
P(ε 3 )
(Intercept, Slope)ε
(Intercept, Slope)ε
(Intercept, Slope)ε
1
(0.257)
1.018***
(0.253)
1.108***
(0.264)
1.516***
(0.273)
reference category
0.316
(0.285)
-0.032
(0.337)
-0.306
(0.341)
0.090
(0.376)
-0.358
(0.463)
-4.224***
(0.684)
0.5874
0.3221
0.0905
(-1.462, -0.809)
(0.223)
1.335***
(0.221)
1.576***
(0.226)
1.675***
(0.239)
-0.006
(0.206)
-0.339
(0.262)
-0.424*
(0.235)
-0.439
(0.281)
-0.396
(0.328)
-1.705***
(0.415)
(1.414, 0.626)
2
(4.457, 3.026)
3
Log Likelihood
-2088.4163
Number of Individuals
1881
Number of Observations
7624
-------------------------------------------------------------------------------------------------------Robust standard errors in parentheses
* significant at 10%; ** significant at 5%; *** significant at 1%
a
Refers to previous period’s response for those living in institutions
39