Context There is strong consensus that caring for an elderly individual with
disability is burdensome and stressful to many family members and contributes
to psychiatric morbidity. Researchers have also suggested that the combination
of loss, prolonged distress, the physical demands of caregiving, and biological
vulnerabilities of older caregivers may compromise their physiological functioning
and increase their risk for physical health problems, leading to increased
mortality.
Objective To examine the relationship between caregiving demands among older spousal
caregivers and 4-year all-cause mortality, controlling for sociodemographic
factors, prevalent clinical disease, and subclinical disease at baseline.
Design Prospective population-based cohort study, from 1993 through 1998 with
an average of 4.5 years of follow-up.
Setting Four US communities.
Participants A total of 392 caregivers and 427 noncaregivers aged 66 to 96 years
who were living with their spouses.
Main Outcome Measure Four-year mortality, based on level of caregiving: (1) spouse not disabled;
(2) spouse disabled and not helping; (3) spouse disabled and helping with
no strain reported; or (4) spouse disabled and helping with mental or emotional
strain reported.
Results After 4 years of follow-up, 103 participants (12.6%) died. After adjusting
for sociodemographic factors, prevalent disease, and subclinical cardiovascular
disease, participants who were providing care and experiencing caregiver strain
had mortality risks that were 63% higher than noncaregiving controls (relative
risk [RR], 1.63; 95% confidence interval [CI], 1.00-2.65). Participants who
were providing care but not experiencing strain (RR, 1.08; 95% CI, 0.61-1.90)
and those with a disabled spouse who were not providing care (RR, 1.37; 95%
CI, 0.73-2.58) did not have elevated adjusted mortality rates relative to
the noncaregiving controls.
Conclusions Our study suggests that being a caregiver who is experiencing mental
or emotional strain is an independent risk factor for mortality among elderly
spousal caregivers. Caregivers who report strain associated with caregiving
are more likely to die than noncaregiving controls.
One of society's great assets is the many family members who provide
care to ill or disabled relatives. By some estimates, more than 15 million
adults currently provide care to relatives,1,2
saving the formal health care system billions of dollars annually. The majority
of caregivers are middle-aged adult children and older spouses who care for
a parent or spouse with functional limitations. Although family caregivers
perform an important service for society and their relatives, they do so at
considerable cost to themselves. There is strong consensus that caring for
an elderly individual with disability is burdensome and stressful to many
family members,3,4 and contributes
to psychiatric morbidity in the form of increased depression. Researchers
have also suggested that the combination of loss, prolonged distress, physical
demands of caregiving, and biological vulnerabilities of older caregivers
may compromise their physiological functioning and increase their risk for
health problems.4,5 Some support
for this hypothesis is found in studies showing that caregivers are less likely
to engage in preventive health behaviors,6
decrements in immunity measures compared with controls,5,7,8
exhibit greater cardiovascular reactivity,9
and experience slow wound healing.10 Some caregivers
are at increased risk for serious illness.5,11
Overall, these studies show that a subgroup of caregivers is at risk for negative
health outcomes. They are characterized as having high levels of caregiving
demands, experiencing chronic stress associated with caregiving, and being
physiologically compromised. By extension, they may also be at risk for increased
mortality, although researchers have not been able to test this hypothesis
because study samples have been too small and follow-up periods have been
too brief.
The Caregiver Health Effects Study (CHES), an ancillary study of the
Cardiovascular Health Study (CHS), a large population-based study of the elderly,
affords an opportunity to test the relationship between caregiving and mortality
because of the relatively large sample size (approximately 400 spousal caregivers
and 400 matched controls), the availability of large numbers of objective
prevalent disease measures as well as subclinical disease indicators, and
a relatively long follow-up period of 4 years. Consistent with other studies
that have examined health outcomes among caregivers, we also explored the
association between caregiving and mortality in subgroups of caregivers who
are physiologically compromised and are exposed to varying levels of caregiving
strain.
The sample for this ancillary study was drawn from the CHS, a prospective,
observational study designed to determine the risk factors for and consequences
of cardiovascular disease in older adults. Beginning in 1989, 5201 men and
women aged 65 years or older were recruited in 4 US communities: Forsyth County,
North Carolina; Washington County, Maryland; Sacramento County, California;
and Allegheny County (Pittsburgh), Pennsylvania. Potential participants were
identified from a random sample stratified by age group (65-74, 75-84, ≥85
years) from the Health Care Financing Administration Medicare Enrollment Lists.
All persons thus identified and age-eligible household members who were planning
to reside in the community for at least 3 years were eligible to participate.
Exclusion criteria included being confined to a wheelchair in the home, being
unable to participate in the examination at the field centers, or undergoing
cancer treatment. Additional sampling and recruitment information has been
published previously.12,13 A supplemental
cohort of 685 black men and women aged 65 years or older was recruited prior
to the fourth wave of CHS data collection using the same sampling methods.
These participants were from all of the CHS communities, except Washington
County.
The CHES ancillary study was initiated before the fourth wave of CHS
data collection with the goal to recruit approximately 400 caregivers and
400 noncaregiver controls matched for age and sex. Caregivers were defined
as individuals whose spouse had difficulty with at least 1 activity of daily
living or instrumental activity of daily living "due to physical or health
problems or problems with confusion." The noncaregiving group included individuals
whose spouse did not have any difficulty with activities of daily living or
instrumental activities of daily living. A total of 819 persons (392 caregivers,
427 noncaregivers) distributed evenly across the 4 recruitment sites were
enrolled into the CHES study.
Sociodemographic and physical health status indicators were collected
as part of the CHS assessment protocol, while caregiving status was assessed
during the CHES interview. Table 1
provides a description of the variables included in these analyses, as well
as descriptive statistics. All CHS data reported were collected during the
fourth wave of the study at approximately the same time as the initial CHES
interview was conducted. Physical health status was measured as the presence
of various prevalent clinical disease and subclinical disease indicators strongly
associated with mortality in the elderly. Three mutually exclusive categories
of physical health status were created: (1) prevalent disease, participants
who entered the CHES study with at least 1 of 6 prevalent disease indicators
present (Table 1); (2) subclinical
disease, participants with no prevalent disease, but with at least 1 of 5
subclinical indicators of prevalent disease present (Table 1); and (3) no prevalent or subclinical disease. Caregiving
status was determined by first asking participants whether their spouse had
difficulty with 6 activity of daily living and 6 instrumental activity of
daily living tasks. For each task with which their spouses had difficulty,
respondents were asked a simple yes or no question: "Do you help your spouse
with this task?" They were also asked, "How much of a mental or emotional
strain is it on you to either provide the help directly, or to arrange for
help to be provided for this activity?" (There was a separate item asking
about physical strain). Response options to the strain questions were "no
strain," "some strain," and "a lot of strain." Based on this battery of questions,
4 mutually exclusive categories of caregiving status were created: (1) spouse
not disabled (control subjects), (2) spouse disabled but not helping, (3)
spouse disabled and helping but with no reports of caregiving strain, and
(4) spouse disabled and helping and reports of caregiving strain (Table 1). This categorization was intended
to capture increasing levels of caregiving demands.
Study participants were followed up for an average of 4.5 years (range,
3.4-5.5 years). Confirmation of deaths was conducted through reviews of obituaries,
medical records, death certificates, and the Health Care Financing Administration
health care utilization database for hospitalizations. As a result, there
was 100% follow-up ascertainment of mortality status.
The major focus of the analyses was the relationship between caregiving
status and 4-year mortality, after controlling for other known demographic
and physical health status predictors. Caregiving status and the other covariates
were assessed at CHES baseline, and Cox regression was used to model their
effects on mortality. Survival time was the number of years between the baseline
interview and the last interview or death. Table 1 presents information for all variables used in the analysis,
including coding schemes and descriptive statistics. Table 2 presents results from the Cox regression model and shows
both adjusted and unadjusted relative risk (RR) ratios (from a Cox model with
only that variable as a predictor). Caregiving status effects were tested
by entering 3 dummy variables (with respondents whose spouses had no disability
serving as control subjects, which also serves as the referent category),
while physical health status effects were tested with 2 dummy variables (with
no prevalent or subclinical disease as the reference category). All variables
were entered on a single step.
Data were missing on several subclinical disease indicators (eg, 45
participants did not have electrocardiogram data). To preserve sample size
and to be cautious, we treated participants with missing data as not having
that particular subclinical disease.
To test the proportional hazards assumption of the Cox model, interactions
between caregiving status and physical health status and survival time were
computed and allowed to enter a model with all covariates. Neither term was
significant, thus the assumption appeared to be met for these predictors.
Table 1 reports descriptive
statistics for all variables. In terms of sociodemographic variables, participants
ranged in age from 66 to 96 years at baseline, with a mean age of approximately
80 years; 51% were women and 49% were men. Among those participants with disabled
spouses, about 81% were providing care and about 56% of those reported caregiver
strain. There was substantial variability on most of the prevalent disease
and subclinical disease indicators. In terms of prevalent disease, there were
particularly high levels of angina pectoris (21.5%), while the most frequent
subclinical disease indicators were carotid stenosis (45.1%) and major electrocardiogram
abnormalities (33.7%). Slightly more than 27% of the sample had at least 1
prevalent disease at CHES baseline, while an additional 41% had at least 1
subclinical disease. Thirty-two percent had neither. The distribution of prevalent
and subclinical disease across the 4 caregiving groups was roughly equal with
the exception of 1 group. Individuals with a disabled spouse who were not
providing care had higher rates of prevalent disease compared with the other
3 caregiving groups (40.0% vs 24.6%, 27.5%, and 27.4% for the control group,
help with no strain, and help with strain groups, respectively; χ26, 13.8, P<.032).
After 4 years of follow-up, 103 deaths (12.6%) occurred among the total
sample. Death occurred in 40 (9.4%) of the 427 participants whose spouses
were not disabled at baseline, in 13 (17.3%) of the 75 subjects whose spouses
were disabled but who were not providing help, in 19 (13.8%) of the 138 subjects
who were providing care but were not strained, and in 31 (17.3%) of the 179
who were providing care and reported caregiver strain ( χ23, 9.38; P<.025). As would be expected,
there was a strong linear trend (χ21, 31.59; P<.001) in mortality rates for physical health status:
no prevalent or subclinical disease (14/261 [5.4%]); subclinical (no prevalent)
disease (39/336 [11.6%]); and prevalent disease (50/222 [22.5%]).
Table 2 shows that after
adjusting for sociodemographic factors (ie, age, sex, race, education, and
stressful life events) and physical health status (ie, prevalent disease and
subclinical disease), participants who were providing care and experiencing
caregiver strain had mortality risks that were 63% higher than those whose
spouse was not disabled (RR, 1.63; 95% confidence interval [CI], 1.00-2.65).
Note that the other 2 groups with disabled spouses did not have significantly
higher adjusted mortality risks. The higher unadjusted mortality rate among
the group whose spouses were disabled but did not help appeared to be explained
by their higher rates of prevalent disease. In addition, participants who
were older, male, black, or had at least 1 prevalent disease had higher 4-year
mortality rates.
To further explore the caregiving status–mortality link and to
test predictions derived from a diathesis-stress model, we examined mortality
rates within each combination of caregiving status and disease status. We
were particularly interested in whether the associations between levels of
caregiving and mortality were stronger among those who were already physically
compromised. We constructed 11 dummy variables that captured membership in
the disease (3 levels) by caregiving (4 levels) cells (participant with no
disease and whose spouse was not disabled served as the referent category).
These were entered as predictors in a Cox regression model that also controlled
for sociodemographic variables. Results from the Cox regression, as well as
crude death rates across cells, are presented in Table 3. Note that, compared with the control group, there were
elevated mortality rates for all participants in the prevalent disease group,
regardless of caregiving status. Although the highest percentage of mortality
(32.7%) and the highest relative RR (7.25; 95% CI, 2.61-20.14) were observed
for the prevalent disease–strained caregiver group, this analysis does
not allow us to conclude that the combination of prevalent disease and caregiver
strain is differentially associated with mortality. A more definitive test
of the diatheses-stress hypothesis will require a larger number of observations.
To our knowledge, this is the first study to show that caregiving is
an independent risk factor for mortality. Controlling for sociodemographic
factors and baseline prevalent and subclinical disease, our data indicate
that caregivers who provide support to their spouse and report caregiving
strain are 63% more likely to die within 4 years than noncaregivers. Those
with disabled spouses but providing no help and those helping a disabled spouse
but reporting no strain did not have significantly higher mortality rates
than noncaregivers. The analyses also revealed that, as expected, mortality
rates were highest among those with prevalent disease (22.5%), followed by
those with subclinical disease (11.6%), and those with no disease (5.4%).
Although the number of deaths in our sample is too few to permit definitive
tests of the combined effects of caregiving and biological vulnerability,
the data are consistent with the notion that strained caregivers with prevalent
disease may be at particular risk of mortality. Thirty-three percent of strained
caregivers with prevalent disease in our sample died within the 4-year follow-up
period.
These findings are consistent with other outcomes reported for this
cohort showing that strained caregivers compared with age- and sex-matched
noncaregiving controls have significantly higher levels of depressive symptoms,
higher levels of anxiety, and lower levels of perceived health. They are also
much less likely to get enough rest in general, have time to rest when they
are sick, or have time to exercise.6 All of
these factors, and others not assessed in this study, are possible mediators
of the association between caregiving and mortality.
It is important to emphasize that the caregiver-mortality link applies
only to a subset of the caregiving population. This study focuses on elderly
caregiving spouses who are living with the care recipient. The literature
consistently shows that caregivers who live with the care recipient experience
higher levels of strain and burden.3 It would
be interesting to see if a caregiving-morality link is also present for nonspousal
caregivers or those not residing with the care recipient. More generally,
larger sample sizes would permit a more thorough exploration of both moderators
(ie, relevant subgroups) and mediators (ie, causal mechanisms) of the association
between caregiving and mortality.
Primary care physicians who care for community-residing older adults
may be in the best position to identify caregivers at risk. Older married
couples should be evaluated as a unit, both in terms of their health status
as well as the caregiving demands that exist in the home environment. To the
extent that caregiving demands are high, opportunities for restorative behaviors
are limited, and the caregiver is physically compromised, an intervention
that reduces caregiving demands such as the provision of respite services
may be needed. Under extreme circumstances, it may be appropriate to relieve
a vulnerable older person from caregiving responsibilities permanently by
finding an alternative caregiver or institutionalizing the care recipient.
In general, it is essential that we develop treatment approaches for older
marital dyads that focus on the needs of both individuals simultaneously.
1.Schulz R, Quittner AL. Caregiving for children and adults with chronic conditions: introduction
to the special issue.
Health Psychol.1998;17:107-111.Google Scholar 2.Ory MG, Hoffman III RR, Yee JL, Tennstedt S, Schulz R. Prevalence and impact of caregiving: a detailed comparison.
Gerontologist.In press.Google Scholar 3.Schulz R, O'Brien AT, Bookwala J, Fleissner K. Psychiatric and physical morbidity effects of dementia caregiving:
prevalence, correlates, and causes.
Gerontologist.1995;35:771-791.Google Scholar 4.Vitaliano P. Physiological and physical concomitants of caregiving: introduction
to special issue.
Ann Behav Med.1997;19:75-77.Google Scholar 5.Kiecolt-Glaser J, Glaser R, Gravenstein S, Malarkey W, Sheridan J. Chronic stress alters the immune response to influenza virus vaccine
in older adults.
Proc Natl Acad Sci U S A.1996;93:3043-3047.Google Scholar 6.Schulz R, Newsom J, Mittelmark M, Burton L, Hirsch C, Jackson S. Health effects of caregiving: the Caregiver Health Effects Study: an
ancillary study of the cardiovascular health study.
Ann Behav Med.1997;19:110-116.Google Scholar 7.Kiecolt-Glaser JK, Dura JR, Speicher CE, Trask OJ, Glaser R. Spousal caregivers of dementia victims: longitudinal changes in immunity
and health.
Psychosom Med.1991;53:345-362.Google Scholar 8.Glaser R, Kiecolt-Glaser JK. Chronic stress modulates the virus-specific immune response to latent
herpes simplex virus type 1.
Ann Behav Med.1997;19:78-82.Google Scholar 9.King AC, Oka RK, Young DR. Ambulatory blood pressure and heart rate responses to the stress of
work and caregiving in older women.
J Gerontol A Biol Sci Med Sci.1994;49:239-245.Google Scholar 10.Kiecolt-Glaser JK, Marucha PT, Malarkey WB, Mercado AM, Glaser R. Slowing of wound healing by psychological stress.
Lancet.1995;346:1194-1196.Google Scholar 11.Shaw WS, Patterson TL, Semple SJ.
et al. Longitudinal analysis of multiple indicators of health decline among
spousal caregivers.
Ann Behav Med.1997;19:101-109.Google Scholar 12.Fried LP, Borhani NO, Enright P.
et al. The Cardiovascular Health Study: design and rationale.
Ann Epidemiol.1991;1:263-276.Google Scholar 13.Tell GS, Fried LP, Hermanson B.
et al. Recruitment of adults 65 years and older as participants in the Cardiovascular
Health Study.
Ann Epidemiol.1993;3:358-366.Google Scholar