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I need help with an annotated bibliography on a topic I chose for my paper.
The topic I have chosen for my annotated bibliography is the psychological impact of the re-emerging trend of multigenerational living.
I have the peer-reviewed journals I am using in pdf form. The instructions for the assignment are below.
An APA formatted Annotated Bibliography of at least 6 peer-reviewed, evidence-based academic journal articles. This assignment requires a properly formatted title page, an abstract page and a Reference citation for each article followed by a brief summary (or “annotation”) of what the article is about. An annotated bibliography is more than just a list of articles; that is what would go on Reference List. Instead each article listing in an annotated bibliography must be followed by a 2 to 3 paragraph summary of the article’s contents (i.e., what the research questions were, who the study participants were, what data was collected and in what format it was collected in (e.g., surveys or interviews), what was found in the study and what limitations of the study were highlighted by the authors.) Remember you are writing succinct, short synopses of each article since the term “Annotated” means that each source listed must include directly below its reference information the description of what the source covers. After each source description, please conclude with a short statement (2 to 3 paragraphs long) of how the respective source is related to one or more of your other sources and how they link to your overall topic. Merely copying the article’s abstract and submitting it as an annotation is prohibited, and will result in a zero score. Also quoting isn’t needed or accepted for this assignment either. Instead summarize the aforementioned information in your own words. This assignment must be completed per the course general writing standards, in APA format and show evidence of meaning making after engagement with the articles. It requires a title page and abstract. Your paper should be at least 5 pages. You will NOT include a reference page. You will have included full reference information above each annotation entry as provided for you in the week 2 lesson sample. The title page and abstract do not count in the 5 page minimum length, but if you include all of the required information, each of your annotation entries will be about 3/4ths of a page since:You will have the reference information double spaced above each annotation in proper APA format You will then have the single spaced annotations of 2 to 3 paragraphs containing the required information below each reference And then you will have a one paragraph statement of each articles relevance to each other and to your overall topic at the end of the annotation.
Sociological Perspectives, Volume 45, Number 1, pages 1–20.
Copyright © 2002 by Paci�c Sociological Association. All rights reserved.
Send requests for permission to reprint to: Rights and Permissions, University of California Press,
Journals Division, 2000 Center St., Ste. 303, Berkel
ey
, CA 94704-1223.
ISSN: 0731-1214; online ISSN: 1533-8673
IN WHOSE HOME? MULTIGENERATIONAL
FAMILIES IN THE UNITED STATES, 1998–2000
PHILIP N. COHEN*
University of California, Irvine
LYNNE M. CASPER
National Institute of Child Health and Human Development
ABSTRACT: This article examines multigenerational living arrange-
ments of white, black, and Latino individuals using data from the Current
Population Surveys. We describe people in multigenerational households
as “hosts” or “guests.” In terms of resources, guests have no home of their
own, whereas hosts maintain an important source of independence. By age,
the proportion of adults living as guests peaks in the late twenties, then
declines until the late seventies. In contrast, hosting rates peak in the
�fties. Men have higher guest rates and women have higher host rates at
almost all ages. While blacks and Latinos are more likely than whites to live
in multigenerational households, those with higher incomes are less likely
to live in multigenerational households and if they are living in multigen-
erational households are less likely to be guests, regardless of race-ethnicity.
We interpret this as consistent with the assumption that residential inde-
pendence is generally preferred.
Complex household structures, their determinants and consequences, are impor-
tant for understanding a wide variety of family-related research questions, includ-
ing inequality and well-being within and across families, caregiving arrangements,
intergenerational transfers of wealth, and the effects of family-related policy. This
article looks at multigenerational living arrangements across the life course for
white, black, and Latino individuals at the turn of this century. Its contribution is
primarily conceptual and descriptive. Descriptive work in this area is important,
as Burr and Mutchler (1993:S55) explain: “Understanding the household status of
any population is critical because households serve as a platform from which
other elements related to individual well-being and the maintenance of life chances
are channeled.” Conceptually, standard practices for identifying multigenera-
tional living arrangements and their implications remain elusive. In this article,
we develop a method for identifying one type of multigenerational household—
* Direct all correspondence to: Philip N. Cohen, Department of Sociology, University of California, Irvine, Irvine, CA
92697-5100; e-mail: cohenp@uci.edu.
2 SO CIOLO GICAL PERSPECTIVES Volume 45, Number 1, 2002
parents and adult children living together—and examine how multi
generational
living changes over the life course and across racial-ethnic groups. The method
we use here is applicable not only to the widely available Current Population
Survey but also to other U.S. government data sets and data sets with sim ilar
�le structures.
Family structure is related to several aspects of inequality, and causation runs in
both directions. Family structure is a purposeful response to hardship (Billingsley
1992), as has been shown in studies of extended households, especially for black
and Latino families (Angel and Tienda 1982; Baca Zinn 1982–83; Blank 1998;
Hogan, Hao, and Parish 1990). Multigenerational households can pool money,
labor, and other resources and extend personal networks and support systems
(Raley 1995; Tienda and Angel 1982). Marriage and divorce are also in�uenced by
economic conditions and the �nancial situation of each member of the couple
(Albrecht et al. 1997; Brines and Joyner 1999). Inequalities in the job market, incar-
ceration rates, health status, and residential segregation differentially affect mar-
riage rates and household structures by limiting options for some groups of
women (Geronimus, Bound, and Waidmann 1999; Lichter et al. 1992; Wilson
1987). On the other hand, family structure can also be a cause of income inequal-
ity across families because it connotes the number of potential earners and depen-
dents in the family, as well as their gender and age, and these characteristics, in
turn, affect economic outcomes (Bryson and Casper 1999).
Family structure and inequality issues intersect in the arena of welfare policy.
The role of the extended family has received attention in the media and policy
arenas as welfare reform takes hold (DeParle 1999; Harris 1999). For black and
Latina mothers, relying on extended support networks to raise their children is “a
traditional cultural remedy for a very modern structural situation” (Roschelle
1999:325). And, in an era of reduced welfare support, “we can assume that the kin
and nonkin support network will become more crucial than ever to the survival of
single-parent families” (p. 333). However, the bene�ts of household extension will
be conditioned by the economic situation of members of the extended household
(Hofferth 1984), as poor families �nd themselves drawing on the resources of
poor network members (Roschelle 1999; Trent and Harlan 1994).
Earlier research on multigenerational households focused on the needs of the
aged and their ability to coreside with adult children in times of need. Lower fer-
tility and mortality rates in the twentieth century meant a smaller number of
adult children on which the aged could rely (Treas 1977). However, by 1990, 90
percent of men and 84 percent of women age sixty-�ve or older were living in
their own households, re�ecting a steep increase from the middle of the century
and greatly improved conditions for the elderly (Treas and Torrecilha 1995:69). In
the 1980s the great majority of coresidence between parents and adult children
took place in the households of the parents (Aquilino 1990). The practice of host-
ing multigenerational living arrangements has led to dramatic increases in the
rates at which grandparents bring grandchildren into their homes, even without
the presence of the middle generation of parents (Bryson and Casper 1999; Casper
and Bryson 1998).
Thus, rather than a shortage of adult children with whom to live, it appears that
Multigenerational Families in the United States 3
many in today’s older population may face the opposite problem: too many
younger relatives living in their homes. Today’s older Americans are the parents
of baby boomers, so their chances of having a living adult child are relatively high
(Crimmins and Ingegneri 1990). As the baby boomers reach retirement age they
will have fewer adult children—either to lean on or to support—than previous
generations did.
However, these trends are not independent of race-ethnicity (Mutchler 1992).
The trend toward living in the homes of older parents was driven by whites and
blacks, as younger Asians and Latinos were much more likely than comparable
whites to bring older parents into their homes (Kamo 2000). Treas and Torrecilha
(1995:70) report that whites alone account for the increase in independent living
in the 1980s. Similarly, Casper and Bryson (1998:Table 2) report that only 19 per-
cent of children living with their grandmothers and without parents are non-
Hispanic whites.
CONCEPTUAL ISSUES
Researchers have suggested that the preference for independent living has
increased over the past century (e.g., Ruggles 1996). Household independence is
generally preferred to extended household structures. A widespread preference
for privacy and independence has been linked to minimalist living arrangements
(Wister and Burch 1987). Most researchers assume people will use their resources
to obtain such independence if they can (e.g., Burr and Mutchler 1993). In fact,
studies have consistently found that income is one of the most important deter-
mining factors of independent living; older Americans with more money are
more likely to live independently (Crimmins and Ingegneri 1990; Mutchler 1992).
This is also consistent with research showing higher rates of complex or multigen-
erational households among economically disadvantaged groups, such as blacks,
Latinos, and Asians (Angel and Tienda 1982; Mutchler 1992; Kamo 2000; Speare
and Avery 1993), although cultural in�uences contribute as well (Kamo 2000), and
attitudes toward multigenerational arrangements have become more accepting in
recent decades (Alwin 1996).
An important milestone event in the transition to adulthood is the ability to
establish and maintain an independent residence, either alone or with a spouse or
roommates. Young people start their careers with lower wages and may not be
able to afford to live on their own right away, but as they age, they usually acquire
more education, skills, experience, and pay and are more able to establish inde-
pendent households. Working adults in midlife typically increase their incomes
until the time they retire. On retirement, incomes drop and people eventually
begin to develop chronic age-related health problems that may make it impossible
for them to maintain independent households. Thus the ability to sustain an inde-
pendent residence as an adult is greatest in midlife and least in the early and late
years of adulthood. Indeed, Callis (1997) reports that home ownership rates are
highest among those ages �fty-�ve to sixty-four, which are the prime years for
hosting adult children (as we show below).
By the latter part of the twentieth century, adult children were much more
4 SO CIOLO GICAL PERSPECTIVES Volume 45, Number 1, 2002
likely to live with their parents and older adults were much more likely to live
alone than they had been at midcentury (Bianchi and Casper 2000; Casper and
Bianchi 2001; Fields and Casper 2001). Children were slower to move out of their
childhood households and more likely to move back in as adults, in large part
because of factors that reduced their relative independence: lower marriage rates,
increased housing costs, reduced �nancial support for college attendance, lower
real wages for some groups, and even the repeal of the military draft (Gold-
scheider and Goldscheider 1994). At the same time, government policies have
helped to improve the �nancial security of older Americans (Treas and Torrecilha
1995) and hence their ability to maintain households. The GI Bill sent many of
today’s older Americans to college. The federal government helped many—espe-
cially whites (Oliver and Shapiro 1995)—to buy homes and allowed them to take
a deduction on their interest payments; it also protected their private pension
plans and—in addition to providing Social Security—used tax laws to protect
their incomes when they reached age sixty-�ve. Patterns of intergenerational sup-
port, apparently responding to this generational balance of economic forces,
shifted so that adult children came to rely more on their older parents.
Nevertheless, Aquilino (1990) points out that researchers still commonly assume
that the coresidence of parents and adult children results from parents’ need for
assistance. When Burr and Mutchler (1993) look only at unmarried older women it
is in part because these women are more likely to need assistance of some kind.
Data on the actual transfer of resources within households, needed to resolve these
questions, frequently is unavailable. Given the preference for privacy and living in
one’s own household, householder status suggests the direction of �ow for one
important resource, the home itself. The multigenerational “guest” generally has
no home of his or her own, whereas the “host” maintains at least one important
source of independence, which she or he shares with extended family members.
Thus, even though both hosts and guests give up privacy in the arrangement—and
even though guests may provide essential assistance in the form of child care, rent,
or other contributions—hosts may be expected to have greater resources, as evi-
denced by their ability to independently maintain a home.1
Most studies have not posed the question in terms of whose home is hosting
multigenerational arrangements. For example, Crimmins and Ingegneri (1990)
look at whether older Americans live with an adult child but not at whose house
they live in. Speare and Avery (1993:S72) conclude that “when children live with
parents under age 75 they are likely to be the primary bene�ciaries of the relation-
ship” but do not report on whose home is involved in these coresidences. The atti-
tude trend data analyzed by Alwin (1996) show that adults living with their par-
ents is a living arrangement that is looked on more favorably by younger people
than by older people. However, the survey question did not ask in whose home
the hypothetical coresidence takes place.
Aquilino (1990) does examine the question of householder status. He �nds that
in the late 1980s more than 90 percent of parents living with their adult children
lived in the parents’ household. In Kamo’s (2000) study of census data, however,
more than half of Asian families with adult children were in the home of the chil-
dren, as were about one-third of such Latino families. The arrangement of adult
Multigenerational Families in the United States 5
children living in their parents’ home does not preclude the possibility that the
children are assisting the parents, of course, but the parents are contributing at
least in the provision of the household. And beyond the question of contributing
resources, those who host extended families maintain a crucial aspect of their
independence by keeping their own homes.
The observed relationship between resources and multigenerational living is
complicated, however. For example, although extended households may repre-
sent ef�cient income pooling strategies, Kamo (2000) �nds that per capita income
is lower in extended households across all racial-ethnic groups. Although better-
off people may be more able to provide support for other family members, those
same better-off hosts are presumably less likely to have relatives who need assis-
tance. Thus Aquilino (1990) �nds that parents’ education reduces the likelihood
that their adult children come to live with them, but this may be because parents
with more education have children with more education, who are more �nan-
cially independent. So hosting may be an indicator of having high levels of
resources relative to others in a particular family network but also an indicator of
a resource-poor network overall. And within a multigenerational network guests
are expected to be those in the least advantageous position.
This article focuses on a distinction between “hosts” and “guests,” which
identi�es multigenerational household members by their householder status. In
the absence of such a distinction, it makes more sense for studies to focus on
either the old (Burr and Mutchler 1992, 1993) or the young (Goldscheider 1997),
because old people tend to “host” and young people tend to “guest.” But distin-
guishing between host and guest roles enables us to describe more speci�cally the
patterns of multigenerational living arrangements across the life course. Concep-
tually, this approach is similar to that offered by Kamo (2000), who identi�es
extended households as “upward,” “downward,” or “horizontally” extended,
depending on the relationship of non-nuclear members to the household head. At
the individual level, Kamo’s measure of “dependent members” parallels our
“guest” identi�er. The host/guest model we use here sacri�ces some detail on the
type of extension among hosts but gains simplicity as well as an individual-based
measure for hosts as well as guests. This simplicity permits analysis of multigen-
erational status for individuals across the life course, allowing us to examine the
gender of hosts, for example. Other methodological issues are addressed below.
DATA AND MEASURES
Data for this article are from the 1998–2000 March Current Population Surveys
(CPSs), which include about �fty thousand households per year. We pool three
years of data to increase reliability for the relatively small subgroups under exam-
ination here. However, because households are usually interviewed in two con-
secutive March CPSs, we include only those in the outgoing rotation from 1998,
the full sample in 1999, and in the incoming rotation in 2000. So about half of our
sample is from 1999, with a quarter each coming from the 1998 and 2000 surveys.2
These data include a lot of information about household composition and per-
sonal characteristics but do not include important contextual information such as
6 SO CIOLO GICAL PERSPECTIVES Volume 45, Number 1, 2002
whether individuals have any living children outside the home (Aquilino 1990),
the presence of nearby relatives (Logan and Spitze 1994), children ever born to
women, or economic transfers between household members. Thus, although the
CPS provides the most recent nationally representative data and is very useful for
demographic pro�les, it is not as useful as some richer data sets for developing
causal models of living arrangements and relationships.
Multigenerational households—households with two or more generations of
adults—may be maintained (hosted) by the parents of adult children or by the
adult child of older parents. All adults in these households are identi�ed as “hosts”
or “guests.” Speci�cally, we de�ne multigenerational households as those that
include an adult child of the householder3 or spouse (including cohabiting part-
ner) of the householder and/or a parent of the householder or spouse (including
cohabiting partner) of the householder. Adult children are de�ned in either of two
ways: (1) any child age eighteen or older who has ever been married or has a child
of his or her own in the household or (2) any child age twenty-�ve or older. After
multigenerational households are identi�ed, each person is categorized as either a
“host” (the householder or spouse or cohabiting partner of the householder) or
“guest” (everyone else in the household).4 This is the �rst analysis of which we
are aware that treats cohabiting partners as spouses for purposes of examining
familial household extension, an option available since 1995 with CPS data.
In the absence of data on assistance or exchange in households, measures of com-
plex or extended households broadly de�ned (Angel and Tienda 1982; Tienda and
Glass 1985) seem less desirable than a measure based on known generational rela-
tions, which may more reasonably be assumed to include resource- and labor-sharing
arrangements. Burr and Mutchler (1993) use a similar construct to identify complex
households. They exclude women from their complex household measure if they
live only with children under age 18 or with children 18 to 25 who are still in
school. Their de�nition of “adulthood” for those age 18 to 25 is school attendance
rather than subfamily construction. We do not treat 18- to 25-year-old children as
adult children, unless they have children of their own or have been married,
because most of them probably have never established an independent household.
Our de�nition of adult children is similar to Kamo’s (2000), except that we use age
25 instead of age 30 as the cutoff point. Although any age cutoff is admittedly arbi-
trary, age 25 is the usual labor force conception of independent adulthood.
We include only non-Latino white, non-Latino black, and Latino adults. Sample
sizes in the CPS are too small to look at Asian Americans, especially given their
cultural diversity and family diversity later in life (Burr and Mutchler 1993), and
Native Americans. Although we include all Latinos in one group regardless of
national origin, we would have preferred to examine the larger Latino subgroups
separately, as Mexicans and Puerto Ricans, for example, have different patterns of
family structure. Thus this analysis is only general, and �ndings for the Latino
population should be regarded as preliminary. The descriptive statistics are all
weighted with the March CPS person weight.
Two caveats are in order. First, the measure here does not include the approxi-
mately one million households in which grandchildren and grandparents live
with no parents present (Casper and Bryson 1998). On the other hand, households
Multigenerational Families in the United States 7
may be identi�ed as multigenerational even if there are no children present. Thus
“multigenerational” as used here refers to more than one generation of adults.
Second, the analysis is cross-sectional. Research that uses life histories will iden-
tify much higher rates of multigenerational living. Goldscheider and Gold-
scheider (1994), for example, report that about 40 percent of adults who left their
parents’ homes in the 1970s and 1980s at some point returned to their parents’
home. The data employed here �nds a much lower proportion of young adults
living with their parents.
RESULTS
Descriptive Analysis
To give a sense of what can and cannot be learned about households in the CPS,
three four-generation households from the data are diagrammed in Figure 1, with
�ctional names. The most simple (panel B), shows a four-generation black family.
The householder (Sophie) is a 47-year-old widow with a high school diploma. She
worked full time for part of last year as a nursing aide and reported earning
$16,000. In her home live her mother—a 76-year-old widow who did not go to
high school and is not employed—and her daughter, a 24-year-old single mother
with two young children of her own. The daughter also �nished high school only
and also worked full time for part of last year as a nursing aide, earning $15,000.
In a household such as Sophie’s it appears plausible that both the older and
younger generations are bene�ting from access to Sophie’s home, whatever other
exchanges are taking place.
A more complex, white household is shown in panel A. This home is main-
tained by a married couple (Bob and Mary). Both have elementary education and
worked in blue-collar jobs for $20,000 in the previous year. They are joined in their
home by Mary’s widowed mother, Sylvia, and their daughter Gretchen’s family.
Gretchen and her husband, Rich, both have some college education and earnings
of $23,000; he is a sewing machine operator and she is an of�ce supervisor. They
have a two-year-old daughter. In this household, again, it may be that the older
and younger generations are bene�ting from access to the home of Mary and Bob.
Maybe Sylvia helps to care for the young daughter. Gretchen and Rich may be
saving up to move out on their own.
The most complicated household (panel C) is a Latino household maintained
by a 43-year-old divorced woman (Angela), who has three children, ages 10, 13,
and 19. She is a naturalized citizen with an elementary education who worked as
a butcher for $19,000 last year. She is joined in her home by her mother, a 79-year-
old separated woman who has not become a citizen and is not employed. The old-
est child is Mike (born in the United States, he is identi�ed as white non-
Hispanic), a prison guard who did not �nish high school and earned $9,000 in
1998. He and his 17-year-old immigrant wife (still in school and a waitress) live
in Angela’s home with their one-year-old son. Finally, the family is joined by a 21-
year-old, foreign-born relative, who may work with Angela in the meat industry,
earning $21,000. Although one may imagine support running in many directions
in such a household, it is unlikely that Angela needs this many other relatives to
8 SO CIOLO GICAL PERSPECTIVES Volume 45, Number 1, 2002
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Multigenerational Families in the United States 9
help her care for her two young children. More likely, at least some of these rela-
tives are unable or not ready to establish a household of their own, for economic
or other reasons.
These are not typical multigenerational households; instead we have chosen
unusually complex households to show the reach of the data. In the terms
speci�ed above, a person who is both an adult child and a parent of adult children
hosts each of these households, since the householder (or couple) has adult chil-
dren as well as an elderly parent at home. The dark boxes indicate the hosts;
everyone else is a guest. As these partial portraits show, the CPS offers a probing
snapshot of households with a great deal of detail but little in the way of explana-
tion in terms of their history, motivations, networks of exchange and support, atti-
tudes, or beliefs. These portraits help us to see an important feature of the guest
and host roles across the life course. In each household, there are young adult
guests, middle-aged hosts, and older guests.
For a broader picture, we offer Figure 2, which shows the percent of all adults
who live in multigenerational households as hosts and guests, by race-ethnicity
and age. The �gure con�rms that blacks and Latinos are more likely than whites
to live in multigenerational homes at all ages, with the highest guest rates appar-
ent for young blacks and old Latinos. The proportion of adults living as guests
peaks for each group in the late twenties.5 It then declines until the seventies,
Figure 2
Multigenerational Host and Guest Rates by Age and Race-Ethnicity, 1998–2000
10 SO CIOLO GICAL PERSPECTIVES Volume 45, Number 1, 2002
except for Latinos, among whom guest rates rise starting in the �fties. Hosting
rates show the opposite pattern, with the highest rates reached in the �fties and
sixties. In strictly demographic terms, middle-aged people are at greatest risk of
living in multigenerational homes, because they are most likely to have living
adult children, older parents, or both. In fact, however, the great majority of middle-
aged multigenerational residents are hosts, providing homes for their adult chil-
dren rather than their older parents.6
The host/guest distribution differs by gender. Women are much more likely
than men to live with and care for young children (England 2000), and this discrep-
ancy continues for care of adults as well. Figure 3 shows the percentage of men and
women who live in multigenerational households as hosts and guests by age. For
both groups, the life course pattern is similar, but men have higher guest rates and
women have higher host rates at almost all ages. The exceptions are at the young-
est ages (under 25), when women with small children may be living with their par-
ents, and at the oldest ages, when women have higher rates of widowhood.
Although marriage is no longer the dominant reason for young adults to leave
Figure 3
Multigenerational Host and Guest Rates by Age and Gender, 1998–2000
Multigenerational Families in the United States 11
home (Goldscheider and Goldscheider 1994), men’s older age of �rst marriage—
estimated to be 26.7 in 1998, compared with 25.0 for women (Lugaila 1998)—may
account for some of the young men’s higher guest rates (especially given our age-
25 cutoff). For each racial-ethnic group, the guest rates are highest for never-married
men, reaching 27 percent for never-married black men. Welfare programs could
also play a role in women’s lower guesting rates, if the presence of young children
helps women qualify for public assistance, including housing assistance.
Multivariate Analysis
We argue that the process of landing in any multigenerational household dif-
fers from the subsequent process that differentiates hosts and guests within multi-
generational arrangements. This can be considered several ways. On the one
hand, if multigenerational arrangements are made out of necessity, the risk of
multigenerational living is increased by weakness or hardship among individuals
or their kinship networks. Among those at risk, then, members will live with those
best situated to host an extended family. On the other hand, to the extent that
multigenerational arrangements follow from cultural preferences, age structures,
or the structural conditions faced by racial-ethnic groups (such as local housing
costs [Kamo 2000]), a multigenerational population emerges, and network mem-
bers live with those best suited for hosting.7 With these data we are able to look at
the likelihood of multigenerational living—and the processes of hosting and
guesting separately—but we cannot differentiate between these two explanations.
To model this as a two-stage process, we compare the determinants of the two
statuses in nested logistic regression models. In the �rst model, we investigate the
odds of living in a multigenerational household for the entire adult sample. In the
second, we use the same variables to predict guest versus host role status among
those in multigenerational households. This differs from the approach used by
Kamo (2000), which models the odds of being a (similarly de�ned) guest versus
the combined categories of hosting an extended family, living alone, or living in a
nuclear family. It also differs from a multinomial approach, which would simulta-
neously model the odds of being hosts, guests, or not living in multigenerational
households.8 In our analysis, because we consider these as conceptually sequen-
tial processes, people are only differentiated as hosts or guests once they are in the
multigenerational population.
Variables in the model include six age categories (to capture the nonlinearity
apparent in Figures 1 and 2); a set of dummy variables indicating combined mari-
tal status/gender/own-child-under-6 status;9 the log of personal income;10 an
indicator for whether each person received any public assistance or welfare cash
payments in the previous year; an indicator for foreign-born status; an indicator
for full-time full-year employment; years of education completed; and an indica-
tor for work-limiting disabilities (the only measure of disability available in the
data). Based on previous research (e.g., Kamo 2000) and a preliminary check of
racial-ethnic interactions, we model the outcomes separately for white, black, and
Latino adults, indicating signi�cant differences where they occur.
Table 1 presents the percentage of white, black, and Latino adults living in mul-
12 SO CIOLO GICAL PERSPECTIVES Volume 45, Number 1, 2002
TABLE 1
Multigenerational Household Status, by Race-Ethnicity and Personal Characteristics,
1998–2000 (Percent)
White
Multi-
generational
Black
Multi-
generational
Latino
Multi-
generational
Characteristics Guests Guests Guests
Total 11.4 52.2 22.5 63.1 21.4 60.3
Age
15–24 9.1 87.4 19.2 89.0 18.4 86.6
25–29 16.3 91.8 29.3 91.9 21.5 82.9
30–39 8.3 81.3 18.1 86.2 13.8 66.9
40–49 9.4 52.4 20.8 54.9 18.9 44.4
50–59 14.6 20.3 26.7 28.5 34.3 34.8
60–69 14.6 17.6 28.7 22.3 36.5 32.6
701 13.3 34.0 27.9 34.1 36.7 56.4
Family status
Married man, child ,6 2.8 48.5 4.6 63.5 7.9 40.8
Married man, no child ,6 8.6 11.6 16.0 10.2 19.9 22.2
Married woman, child ,6 2.8 47.6 4.9 66.5 8.1 39.8
Married woman, no child ,6 8.6 11.9 16.1 10.3 19.3 21.0
Formerly married man 16.6 72.2 26.5 85.1 30.3 79.8
Formerly married woman, child ,6 23.4 87.9 27.4 86.9 33.0 87.5
Formerly married woman, no child ,6 18.0 45.2 29.8 34.8 33.7 57.9
Never-married man 17.5 91.0 28.7 93.3 23.9 88.9
Never-married woman, child ,6 21.9 92.0 24.4 89.6 27.0 86.6
Never-married woman, no child ,6 12 13.1 90.0 22.6 79.9 23.3 81.5
Income
None 17.3 84.6 29.4 88.1 26.3 87.3
$1–10,000 15.3 66.4 25.6 66.7 22.8 63.8
$10,001–20,000 13.3 52.0 23.0 56.0 21.0 54.7
$20,001–40,000 10.3 44.0 18.7 55.2 18.9 47.9
More than $40,000 7.1 30.3 14.9 40.6 15.8 39.1
Welfare income previous year 11.3 63.8 14.9 67.3 15.2 56.8
Full-time, full-year employed 10.3 52.3 20.2 59.2 20.0 55.9
Education
Less than high school 13.6 55.7 23.7 60.9 21.8 58.0
High school only complete 13.9 51.3 25.0 64.9 23.3 62.9
Some college 10.6 53.0 20.7 65.9 19.4 64.7
College degree only complete 8.0 54.1 17.6 63.7 17.0 54.5
Higher degree 6.4 36.1 13.9 28.5 16.3 49.2
Work-limiting disability 15.2 51.3 27.4 59.1 27.2 53.3
Foreign born 15.9 46.5 20.8 58.7 22.2 56.9
N 144,388 18,338 26,830
Note: Percent living in multigenerational households and percent of those who are guests. White and black are non-
Latino. Income is own income or one-half of married-couple income. See text for de�nitions.
Multigenerational Families in the United States 13
tigenerational households and of those, the percentage who are guests, in total
and in categories for each of the independent variables.11 Overall, 11 percent of
whites are in multigenerational households, compared with 23 percent of blacks
and 21 percent of Latinos. Within multigenerational households, guests are more
common among blacks (63%) and Latinos (60%) than whites (52%), re�ecting the
larger household size among black and Latino multigenerational households.
Table 2 shows the logistic regression coef�cients for the odds of living in a mul-
tigenerational household among the total adult sample. The bivariate age pattern
for multigenerational living has two peaks—early adulthood and late middle age.
However, in the multivariate model, which controls some predictors of need, the
TABLE 2
Logistic Regression Coef�cients for Living in a Multigenerational Household, 1998–2000
White Black Latino
Intercept 2.766*** 2.770*** 21.397***a
Age
15–24 21.336*** 2.823***a 2.562***a
25–29 .330*** .347*** .103a
30–39 2.151*** 2.171** 2.341***a
40–49 — — —
50–59 .521*** .330***a .762***a
60–69 .400*** .350*** .825***a
701 .011 .179*a .755***a
Family status
Married man, no child ,6 — — —
Married man, child ,6 21.042*** 21.455***a 2.838***
Married woman, child ,6 21.106*** 21.507***a 2.750***a
Married woman, no child ,6 2.218*** 2.253*** 2.197***
Formerly married man .657*** .454***a .508***
Formerly married woman, child ,6 1.399*** .747***a .927***a
Formerly married woman, no child ,6 .691*** .599*** .548***
Never-married man 1.267*** .878***a .699***a
Never-married woman, child ,6 1.797*** .971***a 1.034***a
Never-married woman, no child ,6 .997*** .594***a .637***a
Income (ln) 2.061*** 2.054*** 2.026***a
Welfare income previous year 2.547*** 2.763*** 2.564***
Full-time, full-year employed 2.080*** 2.035 .018
Education (years) 2.078*** 2.025**a 2.001a
Work-limiting disability 2.098*** 2.031 2.126*
Foreign born .364*** 2.043a .159***a
Likelihood ratio Chi-square 7,429*** 1,114*** 1,903***
N 144,388 18,338 26,830
1 p , .10; * p , .05; ** p , .01; *** p , .001 (two-tailed tests).
a different from white coef�cient at p , .05 (two-tailed test).
Note: Adults 151. White and black are non-Latino. Income is own income or one-half of married-couple income.
14 SO CIOLO GICAL PERSPECTIVES Volume 45, Number 1, 2002
odds across the life course re�ect instead something closer to the crude demo-
graphic risk, with those in their �fties and sixties having the highest odds of liv-
ing with multiple generations. Although the tests for black-white and Latino-
white differences are signi�cant in a number of age categories, the differences are
in degree, not direction of the effects. The exception is the oldest age group, in
which Latinos and to a lesser extent blacks have higher odds of multigenerational
living than do whites.
The effects of gender, marital status, and small children are also quite similar
across racial-ethnic groups despite differences in the strength of the effects. For all
three groups, married men and women have the lowest rates of multigenerational
living, and never-married women with young children have the highest rates. For
each group except never-married and formerly married women, having young
children reduces the odds of multigenerational living. In almost every category,
the signi�cant racial-ethnic interactions represent smaller effects for black and
Latino adults, except in the case of married blacks.
More income, more education, welfare receipt, and full-time full-year employ-
ment are associated with lower rates of multigenerational living (or have non-
signi�cant effects). Among whites and Latinos, the foreign born are signi�cantly
more likely to live in multigenerational households. Surprisingly, whites and
Latinos with work-limiting disabilities are less likely to live in multigenerational
households. Note that the variable identi�es disabilities only for people whose
employment is affected by their disabilities, and these people are of the ages at
which people are most likely to host.
Turning to the guest versus host distinction—the model shown in Table 3—
several different dynamics emerge. Age has a very different effect on the guest
versus host distinction. For each group, the odds of being a guest decline from the
late twenties to age seventy. This is consistent with the argument that the resource
balance favors those who are older, with the exception of those over seventy, who
through health problems and widowhood start to lose relative independence.
Because these effects persist net of some controls for economic condition, it
appears additional resources—such as home ownership and other assets—play
an important role in this balance. Despite signi�cant differences in degree, this
pattern is consistent across racial-ethnic groups.
Married people are most likely to live independent of any multigenerational
arrangement. Among those in multigenerational households, however, gender
and marital status play a further role in determining host versus guest roles. In
each group married adults are the least likely to be guests. Thus marriage is con-
sistently associated with greater odds of independent living. By contrast, the
effect of small children is not consistent across the two processes, as those with
small children are more likely to be guests than those without. Given the relative
economic well-being of divorced men compared to women (Bianchi, Subaiya, and
Kahn 1999), it is perhaps surprising that formerly married men are not hosting
more multigenerational families compared to formerly married women (except
those with small children, who may be seeking out extended family guests to help
care for their children).
The effects of income, welfare receipt, full employment, and education are gen-
Multigenerational Families in the United States 15
erally consistent with the assumed preference for independence. Although the
welfare effects may be counterintuitive, remember that the models control for
income. So, at a given level of income, those who receive welfare are more likely
to live independently or in multigenerational households of their own. The
income, employment, and education effects show that among those in multigen-
erational households, those with lower income, employment, and education lev-
els live in the homes of those with more of these assets. This may be interpreted as
those with greater resources exercising their choice to maintain their own house-
TABLE 3
Logistic Regression Coef�cients for Guest Status in Multigenerational Households,
1998–2000
White Black Latino
Intercept .367* 2.448a .015
Age
15–24 .583*** .729*** 1.384***a
25–29 1.638*** 1.569*** 1.493***
30–39 .950*** 1.252*** .646***
40–49 — — —
50–59 21.163*** 2.696***a 2.444***a
60–69 21.452*** 21.311*** 2.720***a
701 21.046*** 2.984*** .147a
Family status
Married man, no child ,6 — — —
Married man, child ,6 .3041 1.230**a 2.142
Married woman, child ,6 .065 1.264**a 2.391*
Married woman, no child ,6 2.317*** 2.316 2.330*
Formerly married man 2.556*** 3.579***a 2.380***
Formerly married woman, child ,6 3.309*** 3.203*** 2.642***
Formerly married woman, no child ,6 1.702*** 1.523*** 1.341***a
Never married man 2.886*** 3.433***a 2.159***a
Never married woman, child ,6 2.935*** 3.084*** 1.674***a
Never married woman, no child ,6 2.841*** 2.477*** 1.564***a
Income (ln) 2.094*** 2.065*** 2.108***
Welfare income previous year 2.980*** 2.933*** 2.770**
Full-time, full-year employed 2.194** 2.2501 2.109
Education (years) 2.049*** 2.046* 2.012a
Work-limiting disability .008 .094 .027
Foreign born .286** .194 .088
Likelihood ratio Chi-square 9,475*** 2,217*** 2,273***
N 15,750 3,944 5,414
1 p , .10; * p , .05; ** p , .01; *** p , .001 (two-tailed tests).
a different from white coef�cient at p , .05 (two-tailed test).
Note: Adults 151 living in multigenerational households. White and black are non-Latino. Income is own income or
one-half of married-couple income.
16 SO CIOLO GICAL PERSPECTIVES Volume 45, Number 1, 2002
holds in the face of family networks in need of help or as those with greater
resources being called on to help those with fewer resources—or both.12
In both models, black-white and Latino-white differences for employment, edu-
cation, and income, where they are signi�cant, show greater effects for whites. It is
possible that for whites these variables are serving as proxies for greater resources
including other assets. In the �rst model, the stronger effects of education and
income for whites may imply that those whites with higher education and income
are less likely to have family network members in need of multigenerational liv-
ing arrangements.
Consistent with most previous research, blacks and Latinos are more likely to
live in multigenerational households, even when personal characteristics are con-
trolled.13 These results are consistent with culture differences described by others
(Kamo 2000), but there is insuf�cient evidence here to conclude that cultural fac-
tors are decisive, because the condition of members of their family networks is not
controlled. At equal levels of income, for example, black mothers might be more
likely than white mothers to have poor older parents. Even controlling for addi-
tional factors, such as community context variables (Kamo 2000), without measur-
ing the well-being of family network members, interpretation of racial-ethnic dif-
ferences should be made cautiously.
CONCLUSION
We �nd that the proportion of adults living as guests peaks in the late twenties
and then declines until the late seventies, whereas hosting rates peak in the �fties.
Women are less likely to be guests and more likely to be hosts than men are. Con-
sistent with previous research, blacks and Latinos are more likely than whites to
live in multigenerational households, even when other factors are controlled.
Those with higher incomes and other resources are less likely to live in multigen-
erational households altogether and less likely to be guests if they are living in
multigenerational households.
The structure of multigenerational households informs us about intergenera-
tional relations, issues of privacy and independence over the life course, and strat-
egies for coping with poverty and hardship. These results present a picture of
younger adults leaning on the resources of their older relatives, who in turn
sacri�ce some of their privacy—but maintain their independence—when they
open their homes. The guest/host distinction we offer contributes to previous
research to help clarify the pattern of these relationships. The results here suggest
several areas that might bene�t from more sustained attention.
Newman (1999:194) argues in her study of the working poor that “[a]f�uence
loosens the ties that remain tight, even oppressive at times, in poor communities.”
Facing a dearth of economic capital, she argues that the working poor “preserv[e]
a form of social capital that has all but disappeared in many an American sub-
urb.” Clearly in the area of poverty and welfare, and racial-ethnic inequality
research, household structure has �gured prominently. Some who argue for the
return of the nuclear family hold patriarchal assumptions about gender relations
(Coontz 2000), but expecting extended household structure to resolve postwelfare
Multigenerational Families in the United States 17
hardships runs the risk of idealizing what may actually be the desperate measures
of the poor (Roschelle 1999). Nevertheless, the dynamics of household extension
help to explain how people respond to and compensate for the hardships and
inequities they face (Jarrett 1994; Trent and Harlan 1994).
These results offer an interesting set of �ndings regarding gender and its inter-
action with race-ethnicity. First, we have shown that women across most of the
life course have higher rates of hosting and lower rates of guesting than do men.
Perhaps it is not surprising that women are more likely to be on what we have
identi�ed as the giving end of intergenerational family support systems. But the
extent of this fact is especially striking given men’s greater economic resources.
Single men very rarely host multigenerational family members, despite their
apparent advantages in terms of resources. To illustrate this, we present Table 4.
This shows that half of white and Latino multigenerational households and less
than one-third of black multigenerational households are hosted by married or
cohabiting couples. Women alone host about one-third of white and Latino multi-
generational households and more than half of black multigenerational house-
holds. Thus, in only 11 percent (black) to 15 percent (Latino) of multigenerational
households does the primary family not include a woman. The extent of gender
inequality in caring for young children has received much more attention than the
imbalance in the provision of households to adult children and older parents,
which is clearly also dominated by women, especially black women.
Finally, this analysis has not included consideration of the characteristics of
multigenerational household members in relation to each other. For example,
black women hosting multigenerational families may get more or less �nancial or
other help from their guests than do white or Latino women. Future research
should consider these dynamics, which require attention to causal ordering and
more complex relationship measures than are possible with these data.
NOTES
1. In some cases, the householder may only be able to maintain the household because of
the contribution of guests. Nevertheless, we think it likely that the resource balance
generally favors the host over the guests.
2. For details on the survey sample and rotation scheme, see U.S. Census Bureau (2000).
TABLE 4
Gender and Hosting Multigenerational Households, 1998–2000
White Black Latino
Percent of multigenerational households hosted by
Married or cohabiting couples 50.9 30.0 51.4
Single women 35.6 59.3 33.4
Single men 13.5 10.7 15.3
Percent of single hosts who are women 72.5 84.7 68.6
Note: For de�nitions, see text.
18 SO CIOLO GICAL PERSPECTIVES Volume 45, Number 1, 2002
3. The householder is the person in whose name the house or apartment is owned or
rented.
4. Note that hosts may be parents of adult children and adult children themselves, if
there are three generations of adults present.
5. The speci�c location of the peak is partly an artifact of the coding scheme, which
identi�es children as “adults” when they reach age 25, unless they have been married
at an earlier age or have children.
6. The majority of white, black, and Latino householder-hosts are hosting adult children,
not older parents (not shown). About three-fourths of hosts in their �fties—the point at
which they are most likely to have living older parents and older children—are hosting
adult children, not elderly parents. Thus, although guest rates do climb again at
advanced ages, hosting is predominantly the behavior of parents rather than children.
7. Note that given the choice between analyzing individuals and households as the unit
of analysis, we chose individuals. Clearly, decisions regarding multigenerational living
arrangements are not made individually. So our models are not necessarily decision-
making models but rather re�ect the likelihood of the two outcomes given individual
characteristics.
8. Our second model, differentiating hosts from guests among those in multigenerational
households, is equivalent to the second model obtained in the multinomial logistic. We
ran multinomial logistic models but do not present those here because they do not model
the odds of being in a multigenerational household—that is, the odds of host or guest
versus neither. Results from these models are available from the authors on request.
9. Because of the small number of single men with small children, formerly married and
never-married men are not coded separately by the presence of children.
10. The variable represents the annual individual income for the previous year for singles
and one-half of the couple’s combined earnings for those who are married with spouse
present.
11. For ease of interpretation, the descriptive table is set up to parallel the multivariate
analysis, but it includes the information needed to derive the percentage of the total
population living as either hosts or guests. For example, the table shows that the pro-
portion of all white adults living in multigenerational households is .114, and of those
.522 are guests. Thus .114 3 .522 5 .060 of whites are guests and .114 3 (1 2 .522) 5
.054 are hosts.
12. The lack of signi�cant effects for employment, education, and nativity for Latinos may
re�ect the greater diversity within the Latino population and the need for �ner-grained
measures, such as length of stay and English �uency (Kamo 2000).
13. This is based on the regression result for a multigenerational living model with black
and Latino dummy variables and no interaction terms (not shown).
REFERENCES
Albrecht, Carol M., Mark A. Fossett, Cynthia M. Cready, and K. Jill Kiecolt. 1997. “Mate
Availability, Women’s Marriage Prevalence, and Husbands’ Education.” Journal of
Family Issues 18(4):429–52.
Alwin, Duane F. 1996. “Coresidence Beliefs in American Society—1973 to 1991.” Journal of
Marriage and the Family 58(2):393–403.
Angel, Ronald and Marta Tienda. 1982. “Determinants of Extended Household Structure—
Cultural Pattern or Economic Need.” American Journal of Sociology 87(6):1360–83.
Multigenerational Families in the United States 19
Aquilino, William S. 1990. “The Likelihood of Parent Adult Child Coresidence: Effects of
Family-Structure and Parental Characteristics.” Journal of Marriage and the Family
52(2):405–19.
Baca Zinn, Maxine. 1982–83. “Familism among Chicanos: A Theoretical Review.” Humboldt
Journal of Social Relations 10(1):224–38.
Bianchi, Suzanne M. and Lynne M. Casper. 2000. “American Families.” Population Bulletin
55(4):3–43.
Bianchi, Suzanne M., Lekha Subaiya, and Joan R. Kahn. 1999. “The Gender Gap in the Eco-
nomic Well-Being of Nonresident Fathers and Custodial Mothers.” Demography
36(2):195–203.
Billingsley, Andrew. 1992. Climbing Jacob’s Ladder the Enduring Legacy of African-American
Families. New York: Simon & Schuster.
Blank, Susan. 1998. “Hearth and Home: The Living Arrangements of Mexican Immigrants
and U.S.-born Mexican Americans.” Sociological Forum 13(1):35–59.
Brines, Julie and Kara Joyner. 1999. “The Ties That Bind: Principles of Cohesion in Cohabi-
tation and Marriage.” American Sociological Review 64(3):333–55.
Bryson, Kenneth R. and Lynne M. Casper. 1999. “Co-Resident Grandparents and Their
Grandchildren.” U.S. Census Bureau Current Population Reports P23(198).
Burr, Jeffrey A. and Jan E. Mutchler. 1992. “The Living Arrangements of Unmarried Elderly
Hispanic Females.” Demography 29(1):93–112.
———. 1993. “Nativity, Acculturation, and Economic Status: Explanations of Asian-American
Living Arrangements in Later Life.” Journals of Gerontology 48(2):S55–S63.
Callis, Robert R. 1997. “Moving to America: Moving to Homeownership.” U.S. Census
Bureau, Current Housing Reports H121(97-2).
Casper, Lynne M. and Suzanne M. Bianchi. 2001. Continuity and Change in the American
Family. Thousand Oaks, CA: Sage.
Casper, Lynne M. and Kenneth R. Bryson. 1998. “Co-Resident Grandparents and Their
Grandchildren: Grandparent Maintained Families.” Population Division Working Paper
No. 26. Washington, DC: U.S. Census Bureau.
Coontz, Stephanie. 2000. “Historical Perspectives on Family Studies.” Journal of Marriage
and the Family 62(2):283–97.
Crimmins, Eileen M. and Dominque G. Ingegneri. 1990. “Interaction and Living Arrange-
ments of Older Parents and Their Children: Past Trends, Present Determinants,
Future Implications.” Research on Aging 12(1):3–35.
DeParle, Jason. 1999. “Life after Welfare: The Grandmothers; As Welfare Rolls Shrink, Load
on Relatives Grows.” New York Times, February 21, p. 1.
England, Paula. 2000. “Marriage, the Costs of Children, and Gender Inequality.” Pp. 320–42
in The Ties That Bind: Perspectives on Marriage and Cohabitation, edited by L. J. Waite.
New York: Aldine de Gruyter.
Fields, Jason and Lynne M. Casper. 2001. “America’s Families and Living Arrangements.”
Washington, DC: U.S. Census Bureau.
Geronimus, Arline T., John Bound, and Timothy A. Waidmann. 1999. “Health Inequality
and Population Variation in Fertility Timing.” Social Science & Medicine 49(12):1623–
36.
Goldscheider, Frances. 1997. “Recent Changes in U.S. Young Adult Living Arrangements in
Comparative Perspective.” Journal of Family Issues 18(6):708–24.
Goldscheider, Frances and Calvin Goldscheider. 1994. “Leaving and Returning Home in
20th-Century America.” Population Bulletin 48(4):2–35.
Harris, Craig. 1999. “State’s Welfare Windfall to Go to Child Care.” Courier-Journal (Louis-
ville, KY), August 31, p. A1.
20 SO CIOLO GICAL PERSPECTIVES Volume 45, Number 1, 2002
Hofferth, Sandra L. 1984. “Kin Networks, Race, and Family Structure.” Journal of Marriage
and the Family 46(4):791–806.
Hogan, Dennis P., Ling-Xin Hao, and William L. Parish. 1990. “Race, Kin Networks, and
Assistance to Mother-headed Families.” Social Forces 68(3):797–812.
Jarrett, Robin L. 1994. “Living Poor: Family Life among Single-Parent, African-American
Women.” Social Problems 41(1):30–49.
Kamo, Yoshinori. 2000. “Racial and Ethnic Differences in Extended Family Households.”
Sociological Perspectives 43(2):211–29.
Lichter, Daniel T., George Kephart, Diane K. McLaughlin, and David J. Landry. 1992. “Race
and the Retreat from Marriage—A Shortage of Marriageable Men?” American Socio-
logical Review 57(6):781–99.
Logan, John R. and Glenna D. Spitze. 1994. “Family Neighbors.” American Journal of Sociol-
ogy 100(2):453–76.
Lugaila, Terry A. 1998. “Marital Status and Living Arrangements: March 1998 (Update).”
U.S. Census Bureau Current Population Reports P20-514.
Mutchler, Jan E. 1992. “Living Arrangements and Household Transitions among the
Unmarried in Later Life.” Social Science Quarterly 73(3):565–80.
Newman, Katherine S. 1999. No Shame in My Game: The Working Poor in the Inner City. New
York: Knopf and the Russell Sage Foundation.
Oliver, Melvin L. and Thomas M. Shapiro. 1995. Black Wealth/white Wealth: A New Perspec-
tive on Racial Inequality. New York: Routledge.
Raley, R. K. 1995. “Black-white Differences in Kin Contact and Exchange among Never
Married Adults.” Journal of Family Issues 16(1):77–103.
Roschelle, Anne R. 1999. “Gender, Family Structure, and Social Structure: Racial Ethnic
Families in the United States.” Pp. 311–40 in Revisioning Gender, edited by M. M. Fer-
ree, J. Lorber, and B. B. Hess. Thousand Oaks, CA: Sage.
Ruggles, Steven. 1996. “Living Arrangements of the Elderly in America: 1880–1990.” Pp.
254–63 in Aging and Generational Relations: Historical and Cross-Cultural Perspectives,
edited by T. Harevan. New York: Aldine de Gruyter.
Speare, Alden and R. Avery. 1993. “Who Helps Whom in Older Parent-Child Families.”
Journals of Gerontology 48(2):S64–S73.
Tienda, Marta and Ronald Angel. 1982. “Headship and Household Composition among
blacks, Hispanics, and Other whites.” Social Forces 61(2):508–31.
Tienda, Marta and Jennifer Glass. 1985. “Household Structure and Labor-Force Participa-
tion of black, Hispanic, and white Mothers.” Demography 22(3):381–94.
Treas, Judith. 1977. “Family Support Systems for the Aged: Some Social and Demographic
Considerations.” Gerontologist 17(6):486–91.
Treas, Judith and Ramon Torrecilha. 1995. “The Older Population.” Pp. 47–92 in State of the
Union: America in the 1990s, Vol. 2: Social Trends, edited by R. Farley. New York: Rus-
sell Sage Foundation.
Trent, K. and S. L. Harlan. 1994. “Teenage Mothers in Nuclear and Extended Households:
Differences by Marital Status and Race Ethnicity.” Journal of Family Issues 15(2):309–
37.
U.S. Census Bureau. 2000. Current Population Survey Technical Paper 62: Design and Methodol-
ogy. Washington, DC.
Wilson, William J. 1987. The Truly Disadvantaged: The Inner City, the Underclass, and Public
Policy. Chicago: University of Chicago Press.
Wister, Andrew V. and Thomas K. Burch. 1987. “Values, Perceptions, and Choice in Living
Arrangements of the Elderly.” Pp. 180–98 in Critical Issues in Aging Policy, edited by
E. F. Borgatta and R. J. V. Montgomery. Newbury Park, CA: Sage.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
Psychology and Aging
1997, Vol. 12, No. 1 , 1 1 5 – 1 2 4
Copyright 1997 by the Am i Psychological Association, Inc.
0882-7974/97/S3
.00
Coping Strategies of People Living in Multigenerational Households:
Effects on Well-Being
Rachel A. Pruchno
Philadelphia Geriatric Center
Christopher J. Burant
Myers Research Institute of Menorah Park
Center for the Aging
Norah D. Peters
Philadelphia Geriatric Center
Analyses examined whether information about the coping strategies used by family memberc adds
to an understanding about the psychological well-being of individuals. Data from 140 women and
their husbands and children who were living in multigenerational households that included a disabled
older relative indicated that for the women and children, the best predictors of depression, positive
affect, and mastery were their own coping strategies; the coping strategies used by other family
members did not add significantly to the predictive equation. For husbands, however, depression was
predicted by both their own coping strategies and the coping strategies of their wives. Husbands’
positive affect was predicted only by the coping strategies of their wives and children, and their
mastery was predicted by their own coping strategies and those of their wives and
children.
Coping strategies and their relationship to outcomes such as
psychological well-being typically have been approached from
the perspective of the individual, with little consideration given
to the interpersonal contexts in which people cope (Coyne,
Aldwin, & Lazarus, 1981; Folkman & Lazarus, 1986; Mitchell,
Cronkite, & Moos, 1983; Pearlin, Lieberman, Menaghan, &
Mullan, 1981; Pearlin & Schooler, 1978). Yet, because most
individuals who cope with stressful situations do so within the
context of interpersonal relationships, it is important to under-
stand the ways in which coping strategies used by family mem-
bers can affect the relationship between an individual’s coping
strategies and his or her psychological well-being. In this study,
we focused on three family members—women, their husbands,
and a child—and investigated the ways in which coping strate-
gies used by family members affected the psychological well-
being of the involved individuals.
Coping Strategies and Outcomes Among
Caregiving Families
A rich tradition of studies focusing on coping strategies
within the arena of caregiving suggests trends that may be
useful for understanding coping within these families. First,
greater use of emotion-focused coping strategies (strategies
Rachel A. Pruchno and Norah D. Peters, Philadelphia Geriatric Center,
Philadelphia, Pennsylvania; Christopher J. Burant, Myers Research Insti-
tute of Menorah Park Center for the Aging, Beachwood, Ohio. Norah
D. Peters is now at the Department of Sociology and Anthropology,
Beaver College.
This research was supported by Grant PO1 MH43371 from the Na-
tional Institute of Mental Health.
Correspondence concerning this article should be addressed to Rachel
A. Pruchno, who is now at the Center on Aging, Bradley University,
141 Jobst Hall, Peoria, Illinois 616
25.
directed toward regulating the individual’s emotional re-
sponse to the problem) has been found to be significantly
related to increased psychological symptoms (Quayhagen &
Quayhagen, 1988; Stephens, Norris, Kinney, Ritchie, &
Grotz, 1988; Wright, Lund, Pratt, & Caserta, 1987). Second,
strategies in which the individual accepts the situation or
reframes the situation have been associated with decreased
levels of psychological symptoms (Pratt, Schmall, Wright, &
Cleland, 1985; Stephens et al., 1988). Finally, planful prob-
lem solving, instrumental action, or approach coping, an ac-
tive problem-solving approach, has been shown to have nega-
tive relationships with psychological symptoms (Aldwin &
Revenson, 1987; Billings & Moos, 1981; Haley, Levine,
Brown, & Bartolucci, 1987).
Multigenerational households that include a dependent older
adult provide an important context in which to study the rela-
tionship between coping strategies and well-being, because re-
search has shown that it is in these households that the highest
level of caregiver strain exists (Brody, Hoffman, Kleban, &
Schoonover, 1989; Brubaker & Brubaker, 1981; Cantor, 1980;
Noelker & Poulshock, 1982). Households shared by disabled
older people and their younger family members are associated
with “heavier care” (Horowitz, 1982; Lang & Brody, 1983;
Reece, Waltz, & Hageboeck, 1983), greater likelihood of de-
terred labor-force participation for the caregiver (Brody et al.,
1989; Soldo & Myllyluoma, 1983), poorer health on the part of
the older person (Lawton, Moss, & Kleban, 1984), and greater
likelihood of intergeneradonal conflict (Shanas, 1979). There
is also evidence suggesting that caregiving situations can be
disruptive to the husbands of primary caregivers living in multi-
generational households (Kleban, Brody, Schoonover, & Hoff-
man, 1989; Pruchno, Peters, & Burant, 1995). These high levels
of strain make the multigenerational household an optimal envi-
ronment for testing the relationship between coping strategies
and psycholog
ical well-being.
115
116 PRUCHNO, BURANT, AND PETERS
Coping Strategies and Families
Examining the relationship between coping strategies and
outcomes within the context of the family is based on sugges-
tions made by interpersonal and systems theorists who contend
that depression derives from, or can be maintained by, maladap-
tive patterns of interaction between the depressed person and
others in the social environment (Hautzinger, Linden, & Hoff-
man, 1982; Hinchliffe, Hooper, Roberts, & Vaughan, 1975;
Kahn, Coyne, & Margolin, 1985). Feldman (1976), for exam-
ple, viewed depressive symptoms as part of a nialadaptive nega-
tive feedback system between spouses, while Coyne (1976)
described a “downward depressive spiral” that develops be-
tween the depressed person and others in the social environment.
Similarly, Kahn et al. (1985) proposed that depression derives
from disturbed patterns of emotion and coping between hus-
bands and wives.
Empirical studies of the relationship between depression and
the interpersonal context generally indicate that the responses
of spouses in couples with a depressed member are similar to
one another and different from those in couples without a de-
pressed partner. Kahnetal.(1985) found that spouses in couples
with a depressed member withdrew more frequently; used more
aggressive coping strategies; and responded to stress with higher
levels of emotional responsivity, negative tension, and control-
ling behavior. Hautzinger et al. (1982) found that couples having
a depressed member expressed more negative feelings about
their psychological and physical conditions and both demanded
and offered more help than did spouses in couples in which
neither member was depressed.
Although limited research has addressed the relationship be-
tween interpersonal processes studied at the dyadic or family
level and individual outcomes such as psychological well-being
or physical health, a study by Eaker, Haines, and Feinleib (1983)
focused on the personality characteristics of husbands and wives
and the progression of coronary heart disease in the husbands.
When couples were grouped into typologies based on whether
each person was Type A or Type B personality, results indicated
that Type A men married to Type B women were significantly
more likely to develop coronary disease over a 10-year period
than were husbands in any of the other groups.
Gruen, Folkman, and Lazarus (1987) examined whether in-
formation about the couple as a dyad added to the understanding
of depressive symptoms beyond that obtained by focusing on
the individual. Using data from 30 married couples, they identi-
fied three dyadic patterns based on emotions evoked in response
to recent events. Wives who were members of couples in which
they, but not their husbands, were characterized as feeling “dis-
gusted and worried” had lower self-esteem and mastery than
did wives in either the group in which only the husbands felt
disgusted or the group in which both spouses felt disgusted.
They also experienced significantly more depression during the
past week as well as significantly more long-term depression
than did wives in the other two groups. Furthermore, a series
of hierarchical regression analyses controlling for wives’ initial
emotion demonstrated that the dyadic emotion patterns ac-
counted for an additional 24% of the variance on weekly depres-
sion and an additional 13% of the variance on long-term depres-
sion. Gruen et al., drawing conclusions based on work by Von
Bertalanffy (1968), suggested that dyadic emotion patterns rep-
resent an important level of analysis that cannot be understood
by looking at the component parts in isolation.
One of the first empirical studies to examine coping strategies
from a dyadic perspective was reported by Cronkite and Moos
(1984). Using data from 267 married couples, they were sur-
prised to find that after controlling for factors such as social
status, stressors, social resources, and own coping, the more the
husband used avoidance coping strategies, the less depressed
was his wife. These investigators also examined interaction ef-
fects based on combinations of the partners’ personal coping
strategies. They found that when both husbands and their wives
used avoidance coping strategies, the depression experienced
by husbands, but not by wives, increased.
Finally, in a more recent study Giunta and Compas (1993)
used data from 153 married couples to determine the association
between couples’ coping and psychological symptoms in each
spouse and found that a pattern of dyadic coping marked by
strong reliance on escape-avoidance coping by both husband
and wife was associated with high levels of symptoms in both
spouses. Hierarchical regression analyses using each spouse’s
psychological symptoms as the criterion variable revealed that
wives’ symptoms were predicted by their own use of escape-
avoidance coping. Husbands’ symptoms were predicted by both
their own use of escape-avoidance coping and their wives’ use
of this coping strategy. Dyadic patterns of coping did not add
unique variance to either husband or wife outcomes.
The central question addressed by the present analyses was
whether information about the coping strategies used by family
members adds to our understanding of psychological well-being
above and beyond that provided by information about an indi-
vidual’s coping strategies. More specifically, the hypotheses
tested were as follows:
1. People who use emotion-focused coping strategies more
frequently will be more depressed, have less mastery, and enjoy
less positive affect than people who use these strategies less
frequently.
2. People who use acceptance coping strategies more fre-
quently will be less depressed, have greater mastery, and have
more positive affect than people who use acceptance strategies
less frequently.
3. People who use instrumental coping strategies more fre-
quently will be less depressed, have greater mastery, and enjoy
more positive affect than people who use these strategies less
frequently.
4. People whose family members use emotion-focused cop-
ing strategies more frequently will be more depressed, have less
mastery, and enjoy less positive affect than people whose family
members use these strategies less frequently.
5. People whose family members use acceptance coping
strategies more frequently will be less depressed, have greater
mastery, and have more positive affect than people whose family
members use acceptance strategies less frequently.
6. People whose family members use instrumental coping
strategies more frequently will be less depressed, have greater
mastery, and enjoy more positive affect than people whose fam-
ily members use these strategies less frequently.
Method
Respondents
As part of a larger investigation, data were collected between 1988
and 1991 from families residing within 50 miles of Philadelphia, Penn-
PATTERNS OF FAMILY COPING 117
sylvania. One focus of the investigation was to examine the effects that
caregiving has on the lives of members of coresident multigenerational
family members. Criteria for inclusion in these analyses are as follows:
(a) The older relative was 65 years of age or older and not married, (b)
the middle generation was a married daughter or daughter-in-law, with
her husband living in the household, (c) the third generation was a child
of the marriage, (d) the older relative required assistance with at least
one activity of daily living, and (e) the three generations had lived
together for at least 1 month at the time of the interview with the first
family member. When there were multiple children in the household who
fulfilled study eligibility requirements, the middle-generation daughter/
daughter-in-law was asked to select the child whose life was “most
affected” by the older relative’s presence in the household.
The present analyses were based on data collected from 140 multigen-
erational families. For each family, personal interviews were conducted
with the daughter or daughter-in-law, her husband, and one of their
children. Respondents were identified through a range of community
outreach techniques, including announcements in newspapers; talks to
community groups; and outreach through schools, religious organiza-
tions, and workplaces. Attempts were made to include older persons
with both physical and cognitive impairments. Preliminary analyses re-
vealed no significant differences between daughters (n = 102) and
daughters-in-law (n = 38), and therefore daughters and daughter-in-law
were treated as a single group and are referred to as “wives” throughout
this article.
The sample was primarily White (92.1%), with 9 families identifying
themselves as African American and 2 as Hispanic. Wives ranged in age
from 33 to 67 (M = 49.39 years). The majority (55.7%) were Catholic,
whereas 35.0% were Protestant, and 6.4% were Jewish. The women
were highly educated, with 59.3% having more than a high school
education. The majority (64.3%) were working for pay. The husbands
of these women ranged in age from 32 to 75 (M = 52.16). Most (87.3%)
were currently working. The mean age for the older relatives living in
these multigenerational households was 81.97 (range = 65-100). The
third-generation members who participated in the study ranged in age
from 11 to 33 (M = 19.72), with 58.7% being female. Preliminary
analyses examining the role of age of the child revealed no significant
differences on any variable between children under 18 and those 18 or
older, and therefore in the present analyses age of the child was not
controlled. Family income ranged from less than $10,000 to more than
$75,000 (M * $50,000). The three generations had been living together
for a mean of 7.53 years (range = 1 month to 59 years). Most (82.9%)
of the older people had moved in with their younger family members,
although 10.7% had had their younger family members move in with
them, 5.0% had always lived with their younger family members, and
1.4% had moved with the younger generation into a new home. The
primary reason cited for the older adult’s joining the household was a
decline in his or her physical or mental health (67.5%). Other reasons
included the illness or death of the older adult’s spouse (13.2%), the
lack of a place for the older adult to live for reasons that included
financial considerations and the quality of the neighborhood in which
the older person lived (11.7%), and a family preference to live together
(3.9%).
Measures
Selection of a measure of the behaviors characterizing the older rela-
tive was guided by the work of Zarit, Reever, and Bach-Peterson (1980);
Lawton, Rajagopal, Brody, and Kleban (1992); and Lieberman and
Fisher (1995). Because the goal was to represent overall behaviors, the
composite developed included physical problems (e.g., having trouble
breathing and experiencing pain or discomfort), cognitive problems
(e.g., hearing or seeing things that were not there, being unable to
recognize others, and not knowing the day of the week), and disruptive
problems (e.g., yelling, swearing, cursing, or threatening; doing harmful
things; and losing his or her temper). More specifically, a variable repre-
senting the extent to which the person’s behavior was characterized as
stressful was created on the basis of family members’ responses to a
question asking them to indicate the frequency with which 19 negative
behaviors characterized their older relative. Each family member inde-
pendently rated each behavior on a 5-point scale from never (1) to
almost everyday (5). Scores reported by wives ranged from 21.0 to
81.0 (M = 45.64), those reported by husbands ranged from 20.0 to
73.0 (M = 42.62), and those reported by children ranged from 21.0 to
73.0 (M = 45.52).
In order to assess the extent to which each family member was in-
volved in helping activities with the older relative, each respondent was
asked the following question: “On the average, about how many hours
a week did you actually help with the tasks we have been talking about?”
Tasks included seven activities of daily living and eight instrumental
activities of daily living. Wives reported spending a mean of 27.89 hr
(range = 0-168.0), husbands a mean of 9.4 hr (range = 0-60.0), and
children a mean of 9.62 hr (range = 0-50.0) on such tasks.
Although Lazarus and Folkman (1984) made a theoretical distinction
between coping efforts and adaptational outcomes, many items on tradi-
tional coping scales confound coping efforts with emotional outcome
(Stanton, Danoff-Burg, Cameron, & Ellis, 1994). It is possible that this
redundancy in measurement may account at least in part for obtained
relations of dysfunctional cognitions and catastrophizing coping with
depressive symptoms (Coyne & Gotlib, 1983; Sullivan & D’Eon, 1990).
For the present analyses, coping strategies were assessed using the 16-
item index developed by Pruchno and Resch (1989). Items selected for
inclusion in the index were based on earlier work by Kiyak, Montgomery,
Borson, and Teri (1985). Items were those that had been both theoreti-
cally described and empirically identified (Kahana, Kahana, & Young,
1987; Lazarus & Folkman, 1984; Pearlin & Schooler, 1978) and included
coping strategies that are not inherently confounded with distress. This
scale, rather than one of the better known indices, was used to assess
coping strategies because of its brevity and usefulness in related studies
(Pruchno & Kleban, 1993; Pruchno & Resch, 1989) and because of the
applicability of the coping strategies to the demands of caregiving
(Stone, Greenberg, Kennedy-Moore, & Newman, 1991). Respondents
were asked to indicate how often during the past month they had used
each strategy in dealing with the stresses of caregiving. A Likert scale
was used to record responses of never ( 1 ) , rarely*/seldom (2), some-
times (3), often (4), or most of the time (5). Scores are interpreted
with higher values being associated with more frequent use of each
coping strategy. No information about the effectiveness of the coping
strategies is included in the score value.
The items as responded to by the sample of women, men, and children
were subjected to separate confirmatory factor analytic procedures using
Amos (Arbuckle, 1995), which provides a maximum-likelihood solu-
tion. Although previous analyses by Pruchno and Resch (1989) and
Pruchno and Kleban (1993) identified a four-factor model, including
intrapsychic, wishfulness, acceptance, and instrumental coping strate-
gies, a three-factor model, including Emotion-Focused Coping, Accep-
tance, and Instrumental Coping, was posited here for the following rea-
sons. First, the findings from previous studies indicated that although
intrapsychic and wishfulness coping strategies were distinct from one
another in factor analysis, they behaved similarly to one another when
examined in terms of various outcome variables. Second, the relatively
small sample size required that no more than 10 independent variables
be included. Results suggested that a three-factor solution provided a
good fit for these data. As in Pruchno and Kleban’s study, all items,
with the exception of “You knew what had to be done, so you tried
harder to make things work,” loaded on predicted factors. This item
was deleted from further analyses. Results from the wives yielded a
goodness of fit (GFI) of .84, x2(87, N = 134) = 193.34, p < .001.
Results from the husbands yielded a GFI of .86, X2(87, N = 127) =
157.57, p < .001. Results from the children yielded a GFI of .86, x2(87,
N = 133) = 162.35, p < .001.
In order to assess more carefully the stability of the latent paths across
118 PRUCHNO, BURANT, AND PETERS
Table 1
Coping Strategies: Maximum-Likelihood Estimates, Scale Means, and Factor Reliabilities
Factor loadings Wives Husbands Children
Acceptance
1 . Made the best of it.
2. Accepted the situation.
3. Refused to let it get to you.
M
Reliability
0.45
0.81
0.32
12.50
0
.47
0.31
0.82
0
.23
12.88
0.43
0.64
0.65
0.39
11.72
0.56
Emotion-Focused Coping
1. Wished you could change the way you felt. 0.52 0.64 0.58
2. Daydreamed or imagined a better time or place than the one you were in. 0.86 0.57 0.73
3. Wished you could change what had happened. 0.70 0.69 0.62
4. Hoped a miracle would happen. 0.58 0.52 0.57
5. Wished you were a stronger person to deal with it better. 0.66 0.68 0.64
6. Told yourself things to help you feel belter. 0.26 0.66 0.59
7. Had fantasies about how things might turn out. 0.62 0.58 0.63
M 20.75 18.78 20.58
Reliability 0.79 0.81 0.81
Instrumental Coping
1. Did something totally new to solve the problem. 0.77 0.86 0.75
2. Felt inspired to be creative in solving the problem. 0.61 0.48 0.61
3. Came up with a couple of different solutions to the problem. 0.67 0.59 0.64
4. Made a plan of action and followed it. 0.41 0.40 0.50
5. Changed something about yourself so you could deal with the situation
better. • 0.48 0.57 0.49
M 13.56 11.86 13.46
Reliability 0.73 0.70 0.72
the groups of caregivers, husbands, and children, the hypothesized three-
factor model was simultaneously tested on the caregivers, husbands, and
children. Multisample Amos analysis (Arbuckle, 1995) was first used
to test a model in which the same parameter pattern was freely estimated
within each group. This chi-square value of 513.25 (df = 261, N –
140, Root Mean Square Residual = .130) was the starting point for
each nested sequential analysis. The magnitudes of the regression
weights across samples were compared by equating their parameters
across the three groups one at a time. These analyses indicated that the
factor loadings for Acceptance, ^2(95, N = 140) = 514.88, GFI = .85,
RMR = .131, and Instrumental Coping, x2(91, N – 140) = 517.50,
GFI = .85,RMR= .131, were identical across groups. Minor differences
were found between loadings for wives and those for husbands and
children on the Emotion-Focused Coping Factor, x2(87, N = 140) =
545.55, GFI – .85, RMR = .150, with the variable “Told yourself
things to help you feel better” having a loading with a smaller valence
for wives and the variable “daydreamed or imagined a better time or
place than the one you were in” having a higher valence for wives than
for husbands and children. These findings suggest that the value of the
parameters was similar across the groups of women, husbands, and
children. Factor loadings, scale means, and factor reliabilities are pre-
sented in Table 1.
The 20-item Center for Epidemiological Studies Depression scale
(CES-D; Radloff, 1977) was used to measure the overall level of de-
pression experienced by each family member during the past week. Item
responses ranging from rarely (0) to most of the time (3) were scored
according to procedures described by Radloff (1977). Scores ranged
from 0 to 60, with higher scores indicating greater depression. Wives
had a mean of 12.76 (SD = 11.33), husbands had a mean score of 7.72
(SD = 7.62), and children had a mean score of 12.76 (SD = 9.36).
Coefficient alphas for the scale were .93 for wives, .86 for husbands,
and .89 for children.
The five-item Bradburn Affect Scale (Positive Affect) derived from
the Affect Balance Scale (Bradbum, 1969) was used in accordance with
Jahoda’s (1958) concern with the need to focus on positive mental
health- Positive Affect scores ranged from 0 to 5, with higher scores
indicating more positive affect. For wives, M = 3.67, SD = 1.41; for
husbands, M = 3.52, SD = 1.53: and for children, M = 4.20, SD = 1.05.
Coefficient alphas for the scale were .73 for wives, .63 for husbands, and
.45 for children.
Mastery represents the extent to which an individual regards his or
her life chances as being under his or her control in contrast to being
ruled by fate. Mastery was measured using the seven-item Personal
Mastery Scale devised by Pearlin and Schooler (1978). Items include
“I have little control over the things that happen to me,” “There is
really no way I can solve some of the problems I have,” “What happens
to me in the future mostly depends on me,” “There is little I can do to
change many of the important things in my life,” “I often feel helpless
in dealing with the problems of life.” “Sometimes I feel that I’m being
pushed around in life,” and “I can do just about anything I really set
my mind to do.” Each item is rated on a 5-poinr Likert scale, with
responses ranging from agree a lot (5) to disagree a (of ( 1 ) . Scores
ranged from 7 to 35, with higher scores indicating a diminished sense
of personal mastery. The mean score for wives was 17.05 (SD = 6.37);
the mean for husbands, 14.02 (SD = 5.33); and the mean for children,
14.09 (SD = 4.63). Coefficient alphas for the scale were .78 for wives,
.74 for husbands, and .69 for children.
Results
Bivariate correlations among the coping and outcome mea-
sures for wives, husbands, and children are presented in Table
2. (Not shown in this table are the relationships between family
PATTERNS OF FAMILY COPING 119
coping strategies, outcomes, and elder characteristics.) The cor-
relations between the older relative’s behaviors and depression
as reported by the wives, husbands, and children were signifi-
cant. In addition, for the wives, the correlation between the
number of hours per week spent helping the older relative and
depression was significant. For the children, the correlation be-
tween the number of hours of help and mastery was significant.
The remaining correlations of older relative behaviors and help
hours with the outcome variables were not significant.
Separate hierarchical regression analyses using each family
member’s outcomes as the criterion variable were conducted to
identify the relative contributions of stressor, own coping, and
other family members’ coping. In predicting the wives’ out-
comes, for example, older relative stressors were entered first,
the wives’ scores on the three individual coping scales were
entered next, and the six coping strategies of the husbands and
children were entered last.
The results of these analyses are presented in Table 3. Wives’
depression was predicted by more use of emotion-focused cop-
ing strategies and less use of acceptance strategies (adjusted R2
= .29). Positive affect was predicted by less use of emotion-
focused strategies and more use of instrumental strategies (ad-
justed/?2 = .12). Mastery was predicted by less use of emotion-
focused strategies and more use of acceptance strategies (ad-
justed R2 = .29). The coping strategies used by either their
husbands or children did not affect any of the outcome equations
for the caregiving wives.
For husbands, depression was predicted by greater use of
emotion-focused coping strategies on their own part and less
use of emotion-focused coping strategies and acceptance strate-
gies on the part of their wives (adjusted R2 – .24). Positive
affect was predicted by greater use of acceptance coping on
the part of their wives and less use of emotion-focused coping
strategies and greater use of instrumental coping strategies on
the part of their children (adjusted R2 = .08). Mastery was
predicted by less use of emotion-focused coping strategies and
greater use of acceptance strategies on their own part, greater
use of emotion-focused coping on the part of their wives, and
greater use of instrumental coping strategies on the part of their
children (adjusted R2 = .19).
Finally, children’s depression was predicted by their greater
use of emotion-focused coping and less use of acceptance cop-
ing (adjusted R 2 = .30).Children’spositiveaffectwaspredicted
by their greater use of instrumental coping and their mother’s
less use of instrumental coping (adjusted A2 = .10). Children’s
mastery was predicted by their less use of emotion-focused
coping strategies and greater use of acceptance (adjusted
R1 = .24).
In order to evaluate whether the strength of the predictors
was significantly different for the women, their husbands, and
their children, the model was tested simultaneously on the three
groups. For each dependent variable (depression, positive affect,
and mastery) multisample Amos analysis was used to test a
model that posited that the regression weights were equal across
the three groups. This omnibus test was followed by examina-
tion of the equivalency of each regression path individually.
Testing the omnibus model for depression yielded a chi-
square of 78.60 (df = 212, N = 140, p < .01, RMR = 2.81),
suggesting that for the women, their husbands, and their chil-
dren, there were differences in the strength of the regression
paths. Specifically, significant differences were found for the
paths from wives’ emotion-focused coping, x2(2, N = 140) =
30.75, p < .01, RMR = 1.42; husbands' emotion-focused cop-
ing, x
!(2, N = 140) = 17.38, p < .01, RMR = .90; children's
Table 2
Bivariate Correlations
Wives’ coping
Wives’ coping
A. Acceptance
B. Emotion focused
C. Problem focused
Wives’ outcome
D. Depression
E. Positive affect
F. Mastery
Husbands’ coping
G. Acceptance
H. Emotion focused
I. Problem focused
Husbands’ outcome
J. Depression
K. Positive affect
L. Mastery
Children’s coping
M. Acceptance
N. Emotion focused
O. Problem focused
Children’s outcome
P. Depression
Q. Positive affect
R. Mastery
A
—
-.27*
.26′
-.35*
.26*
-.33*
.09
–
.04
.01
-.22*
.16
.01
.02
–
.08
.02
–
.10
-.01
.02
B
—
.10
.50**
-.30**
.51**
-.01
.41**
.15
-.04
.03
-.03
.01
.14
-.14
.12
-.09
.05
C
_
.03
.20*
–
.13
-.09
.09
.17
-.12
.09
-.02
.17
–
.06
.07
-.14
-.15
-.15
Wives’ outcome
D
—
-.46**
.61**
-.03
.19*
-.01
.02
-.19*
-.02
-.08
.23**
-.05
.30**
-.20*
.11
E
—
-.41**
.09
-.12
-.09
.06
.19*
.07
.10
-.12
.05
-.14
.01
-.03
F
—
.05
.19*
.01
-.01
-.16
-.01
-.08
.18*
-.16
.18*
-.10
.18*
Husbands’ coping
G
—
-.02
-.02
-.16
.16
-.27**
-.02
.01
.04
.08
.10
.02
H
—
.36**
.37**
.01
.29**
.06
.22*
-.02
.07
-.06
.02
I
—
.05
.17
-.08
.18*
.04
.17
-.05
.05
-.12
Children’s
Husbands’ outcome Children’s coping outcome
J K L M N O P Q R
—
-.34** —
.47** -.26** —
-.01 .19* -.01 —
.23** -.16 .01 -.09 —
.02 .17 -.21* .06 .31** —
.20* -.22* -.03 -.36** .48** .03 —
.03 .06 -.07 .05 -.06 .29** -.29″ —
.09 -.06 .09 -.40** .38* .01 .57** -.15 —
*p < .05. **p < .01.
120 PRUCHNO, BURANT, AND PETERS
Table 3
Summary of Hierarchical Regression Analysis for Variables Predicting the Well-Being of Wives, Husbands, and Children
Variable
Wives’ depression
Step 1
Older adult’s behavior
Help hours
Step 2
Wives’ acceptance
Wives’ emotion-focused coping
Wives’ instrumental coping
Step 3
Husbands’ acceptance
Husbands’ emotion-focused coping
Husbands’ instrumental coping
Children’s acceptance
Children’s emotion-focused coping
Children’s instrumental coping
Wives’ positive affect
Step 1
Older adult’s behavior
Help hours
Step 2
Wives’ acceptance
Wives’ emotion-focused coping
Wives’ instrumental coping
Step 3
Husbands’ acceptance
Husband’s emotion-focused coping
Husbands’ instrumental coping
Children’s acceptance
Children’s emotion-focused coping
Children’s instrumental coping
Wives’ mastery
Step 1
Older adult’s behavior
Help hours
Step 2
Wives’ acceptance
Wives’ emotional-focused coping
Wives’ instrumental coping
Step3
Husbands’ acceptance
Husbands’ emotion-focused coping
Husbands’ instrumental coping
Children’s acceptance
Children’s emotion-focused coping
Children’s instrumental coping
Husbands’ depression
Step 1
Older adult’s behavior
Help hours
Step 2
Husbands’ acceptance
Husbands’ emotion-focused coping
Husbands’ instrumental coping
Step 3
Wives’ acceptance
Wives’ emotion-focused coping
Wives’ instrumental coping
Children’s acceptance
Children’s emotion-focused coping
Children’s instrumental coping
Husbands’ positive affect
Step 1
Older adult’s behavior
Help hours
Step 2
Husbands’ acceptance
Husbands’ emotion-focused coping
Husbands’ instrumental coping
B
0.13
0.04
-1
.33
0.66
0.16
0.06
-0.10
-0.16
-0.37
0.23
-0.22
0.00
0.00
0.09
-0.06
0.07
0.07
0.01
-0.04
0.05
–
0.01
0.01
-0.01
0.01
-0.58
0.45
-0.14
0.19
-0.01
–
0.03
-0.12
0.14
-0.23
0.05
-0.05
-0.51
0.58
-0.14
-0.91
-0.38
-0.11
0.00
.20
-0.09
0.00
0.01
–
0.01
-0.02
0.03
SE
.07
.03
.47
.16
.23
.42
.17
.26
.41
.15
.24
.01
.00
.07
.02
.03
.06
.02
.04
.06
.02
.03
.04
.02
.27
.09
.13
.24
.10
.15
.23
.09
.14
.05
.06
.30
.12
.18
.33
.11
.15
.29
.11
.17
.01
.01
.05
.02
.03
ft
.15
.09
-.23**
.37**
.06
.01
–
.05
-.05
-.07
.13
-.07
.01
-.09
.12
-.27**
.20*
.10
.04
-.09
.08
-.06
.03
-.01
.03
-.18
.44
-.09
.06
-.01
-.02
-.04
.14
-.14
.10
-.07
-.13
.46**
-.06
-.23″
-.32**
-.06
.00
.16
-.04
.04
.12
-.01
-.08
.09
R1 R2 change
.10**
.33** .22**
.35** .03
.01
.17** .15**
.19** .02
.02
.32** .30**
.35** .03
.04
.17** .13**
.31** .13**
.02
.05 .03
PATTERNS OF FAMILY COPING 121
TVible 3 (continued)
Variable
Husbands’ positive affect (continued)
Step 3
Wives’ acceptance
Wives’ emotion-focused coping
Wives’ instrumental coping
Children’s acceptance
Children’s emotion-focused coping
Children’s instrumental coping
Husbands’ mastery
Step 1
Older adult’s behavior
Help hours
Step 2
Husbands’ acceptance
Husbands’ emotion-focused coping
Husbands’ instrumental coping
Step3
Wives’ acceptance
Wives’ emotion-focused coping
Wives’ instrumental coping
Children’s acceptance
Children’s emotion-focused coping
Children’s instrumental coping
Children’s depression
Step 1
Older adult’s behavior
Help hours
Step 2
Children’s acceptance
Children’s emotion-focused coping
Children’s instrumental coping
Step3
Wives’ acceptance
Wives’ emotion-focused coping
Wives’ instrumental coping
Husbands’ acceptance
Husbands’ emotion-focused coping
Husbands’ instrumental coping
Children’s positive affect
Step 2
Olders adult’s behavior
Help hours
Step 2
Children’s acceptance
Children’s emotion-focused coping
Children’s instrumental coping
Step3
Wives’ acceptance
Wives’ emotion-focused coping
Wives’ instrumental coping
Husbands’ acceptance
Husbands’ emotion-focused coping
Husbands’ instrumental coping
Children’s mastery
Step 1
Older adult’s behavior
Help hours
Step 2
Children’s acceptance
Children’s emotion-focused coping
Children’s instrumental coping
StepS
Wives’ acceptance
Wives’ emotion-focused coping
Wives’ instrumental coping
Husbands’ acceptance
Husbands’ emotion-focused coping
Husbands’ instrumental coping
B
0.12
0.03
-0.01
0.09
-0.04
0.08
0.01
0.01
-0.64
0.36
-0.23
0.01
-0.16
-0.02
0.05
-0.01
-0.29
0.04
-0.04
-1
.34
0.72
-0.25
-0.12
0.08
-0.10
0.37
-0.08
0.05
-0.01
0.01
0.01
-0.02
0.09
-0.01
0.00
-0.05
0.02
0.00
0.00
0.01
0.02
-0.73
0.27
-0.10
0.18
0.02
-0.09
0.02
-0.02
-0.07
SE
.06
.02
.03
.05
.02
.03
.03
.04
.21
.09
.13
.23
.08
.11
.21
.07
.12
.06
.07
.34
.13
.20
.41
.13
.18
.35
.14
.21
.01
.01
.04
.01
.02
.05
.01
.02
.04
.02
.02
.03
.03
.17
.07
.10
.21
.07
.09
.18
.07
.11
ft
.19*
.15
-.04
.15
-.21*
.23*
.03
.03
-.25**
.41**
-.15
.00
-.19*
-.01
.02
-.01
-.21
.05
-.05
-.30**
.48**
-.10
-.03
.06
-.04
.08
-.05
.02
-.08
.11
.03
-.15
.37**
-.02
.00
-.20*
.05
.01
.01
.03
.06
-.33″
.36**
-.08
.08
.03
-.08
.01
-.03
-.05
R* K2 change
.16* .12*
.03
.19** .16**
.26** .07
.03
.35** .32**
.36** .01
.02
.13** .12**
.18»» .04
.03
.30** .26**
.31** .01
Note. * p < . 0 5 . * * p < . 0 1 .
122 PRUCHNO, BURANT, AND PETERS
emotion-focused coping, X 2 (2, N = 140) = 11.66, p < .01,
RMR = 1.00; children’s acceptance, x2(2, N = 140) = 9.89,
p < .01, RMR = .389; and depression. Wives' emotion-focused
coping was significantly related to their own depression and
their husbands’ depression and was not significantly associated
with their children’s depression. Husbands’ emotion-focused
coping was significantly associated with their own depression
but was not significantly associated with either their wives’ or
children’s depression. Finally, children’s emotion-focused cop-
ing and acceptance coping were significantly associated with
their own level of depression but not with that of either the
wives or husbands. The remaining paths (between behaviors,
hours of help, wives’ problem-focused coping, wives’ accep-
tance coping, husbands’ problem-focused coping, husbands’ ac-
ceptance coping, and children’s problem-focused coping) had
similar relationships to individual depression across the three
groups of people.
Examination of the paths for positive affect across the three
groups indicated that there were differences at the omnibus level,
X'(2U, N = 140) = 42.83,p < .01, RMR = .387. Significant
differences were found for the paths between wives’ emotion-
focused coping, x 2 ( 2 , N = 140) = 10.15, p < .01, RMR =
.12, and problem-focused coping, *2(2, N = 140) = 9.89, p
< .01, RMR = .08, and positive affect. Wives' emolion-focused
coping was associated with their own positive affect but not
with that of their husbands or children. Wives’ use of problem-
focused coping was significantly associated with both their own
positive affect and that of their children but was unrelated to
husbands’ positive affect. The remaining paths were similar
across the samples of women, their husbands, and their children.
Results for mastery indicated that several of the paths were
significantly different across the three groups. The omnibus test
yielded a chi-square of 84.97 (df = 212, N = p < .01, RMR
— 1.53). Differences were found for the paths from wives’
emotion-focused coping, x 2 (2, N = 140) = 27.68, p < .01,
RMR = .84; husbands’ emotion-focused coping, X 2 ( 2 , N =
140) = 13.25, p < .01, RMR = .46; children's use of acceptance
coping, x2(2, N = 140) = 10.04, p < .01, RMR = .19; and
mastery. Wives’ emotion-focused coping was associated with
both their own mastery and that of husbands’ but was unrelated
to children’s mastery. Husbands’ emotion-focused coping was
associated with their own mastery but not with that of either
their wives or children. Children’s use of acceptance coping was
associated with their mastery but not with that of either the
wives or husbands.
Discussion
The present data support the findings reported by others re-
garding the relationship between individual coping strategies
and psychological well-being (e.g., Haley, Levine, Brown,
Berry, & Hughes, 1987; Pratt et al., 1985; Quayhagen & Quay-
hagen, 1988). Supporting Hypothesis 1,greater use of emotion-
focused coping was associated with more depression and less
mastery. For the wives only, greater use of emotion-focused
coping was associated with less positive affect. Supporting Hy-
pothesis 2, greater use of acceptance strategies was associated
with greater mastery for the wives, husbands, and children and
less depression for the wives and children. Use of acceptance
was not related to positive affect for the wives, husbands, or
children. Hypothesis 3 was partially supported by data from
both the wives and children, with those who used instrumental
coping strategies more frequently having greater positive affect.
Use of instrumental coping strategies, however, was not related
to either depression or mastery for the wives, husbands, or
children.
The data yield mixed results regarding the usefulness that
studying the coping strategies used by family members has for
understanding individual psychological well-being. For the
women and children in this study, information about the coping
strategies used by other family members did not add significant
information to the predictive equations focusing on depression,
positive affect, and mastery above and beyond that provided by
the individual’s own coping strategies.
For the husbands, however, a very different picture emerged.
Whereas Hypothesis 4 predicted that people whose family mem-
bers used emotion-focused coping strategies would be more
depressed, the data indicate that less use of emotion-focused
coping on the part of wives was associated with increases in
depression and decreases in mastery on the part of their hus-
bands. On the other hand, in partial support of Hypothesis 4,
less use of emotion-focused coping on the part of the children
was associated with greater positive affect on the part of the
husbands. The data provide partial support for Hypothesis 5,
with greater use of acceptance coping on the part of wives being
associated with less depression among the husbands. Finally,
Hypothesis 6 was also partially supported, with husbands whose
children used greater instrumental coping strategies experienc-
ing higher levels of positive affect and greater mastery.
The findings regarding the relationships between emotion-
focused coping strategies used by wives and depression and
mastery experienced by their husbands are especially surprising,
because emotion-focused coping, when studied at the level of
individuals, generally has a positive association with depression.
Although this relationship requires further study in order lo
understand [he dynamics involved, it is interesting to speculate
about what these relationships might mean. First, it is possible
that the statistical relationship between wives’ emotion-focused
coping strategies and husbands’ depression and mastery was
influenced by a third variable and the negative relationship is
spurious. It is also possible that husbands whose wives are
using emotion-focused coping strategies less frequently become
depressed and experience less mastery because they give some
positive value to the use of emotion-focused coping strategies.
For example, in the context of living with a dependent older
person, failure to wish you could change the way you felt,
failure to hope for a miracle, and failure to have fantasies about
how things might turn out might be associated with greater
depression because they represent a lack of hopefulness on the
part of the individual. These data may also be interpreted as
indicating that the husbands’ overall sense of depression in-
creases when their wives have more realistic interpretations of
the situation, that is, when they are less likely to be hoping for
a miracle and less likely to have fantasies and positive hopes
about how the situation with the older adult might turn out.
The finding that husbands’ positive affect was not signifi-
cantly predicted by their own coping strategies but was pre-
dicted by their wives’ greater use of acceptance coping and their
children’s greater use of instrumental coping and less use of
emotion-focused coping is a significant departure from the rela-
PATTERNS OF FAMILY COPING 123
tionships that were predicted. It was expected that the coping
strategies used by family members would enhance the predictive
capacity of the coping strategies used by individuals, not replace
them. That individual coping strategies did not predict positive
affect in the husbands, however, is consistent with a general
inability to predict the psychological well-being of men, as com-
pared with that of women (e.g., Brody, Dempsey, & Pruchno,
1990), and suggests that in order to understand men’s positive
affect, information about their family members may be useful.
It is interesting to speculate about why the psychological well-
being of the wives and children was not related to the coping
strategies used by family members. It is possible that the chil-
dren were so involved in their own lives that the coping strate-
gies used by their parents had little effect on them. On the other
hand, the wives participating in the study were the primary
caregivers of the dependent, frail older people with whom they
were living. It is likely that the coping strategies used by the
other family members did not influence their psychological well-
being because they viewed the caregiving responsibility as pri-
marily theirs and the coping strategies used by other family
members were unimportant.
Interpretation of the present findings must acknowledge the
methodological problems of the low reliability for the measures
of acceptance coping strategies (all family members) and posi-
tive affect (children) used. Future research in this area would be
strengthened by development of a better indicator of acceptance
coping. Within the realm of indicators of psychological well-
being, attention should be given to why the Positive Affect scale
had such low reliability among the sample of children and was
a better indicator of positive emotional health developed. In
addition, given the relatively small sample size and the White,
middle-class nature of the sample, the generalizability of the
findings is limited to White, middle-class families in which
three generations share a household. While the sample is small
compared with those of studies focusing on individuals, it is
large compared with those of other studies that have examined
the perspectives of multiple family members.
Despite these limitations, the findings from this research raise
some important issues. First, the direction of causality between
coping strategies used by family members and well-being re-
mains unclear. It is possible, for example, that emotion-focused
coping strategies contributed to the lowered sense of well-being
experienced by family members. On the other hand, people who
are depressed and burdened by the demands of caregiving could
turn to emotion-focused coping as a way of expressing their
frustration. It is most likely that the relationship between coping
strategies and outcomes involves both scenarios; that is, that
the relationship is reciprocal. The issue of causality is complex
and requires longitudinal study. Second, although this study fo-
cused on the coping strategies used by three members of each
family, it would be intriguing to add to these equations the ways
in which other family members cope with the stresses associated
with caregiving. Finally, this study demonstrates a method of
analysis that is useful for studying coping strategies at the dyadic
level. Designs involving data collected from multiple family
members have the potential to yield rich new information above
and beyond that provided by individuals. These data support
the view that it is informative to study coping strategies using
data provided not only by individuals but also by family mem-
bers, because both contribute to our understanding of psycholog-
ical well-being.
References
Aldwin, C. M., & Revenson, T. A. ( 1987). Does coping help? A reexam-
ination of the relation between coping and mental health. Journal of
Personality ami Social Psychology, 53, 337-348.
Arbuckle, J. L. (1995). Amos users’guide. Chicago: SmallWaters.
Billings, A. G., & Moos, R. H. (1981). The role of coping responses in
alternating the impact of stressful lire events. Journal of Behavioral
Medicine, 4, 139-157.
Bradburn, N. (1969). The structure of psychological well-being. Chi-
cago: Aldine.
Brody, E. M., Dempsey, N. P., & Pruchno, R. A. (1990). Mental health
of sons and daughters of the institutionalized aged. The Gerontologist,
30, 212-219.
Brody, E. M., Hoffman, C., Kleban, M. H., & Schoonover, C. B. (1989).
Caregiving daughters and their local siblings: Perceptions, strains, and
interactions. The Gerontologist, 29, 529-538.
Brubaker, T. H., & Brubaker, E. (1981). Adult children and elder parent
households: Issues in stress for theory and practice. Alternative Life-
styles, 4, 242-256.
Cantor, M. (1980, November). Caring for the frail elderly: Impact on
family, friends, and neighbors. Paper presented at the annual meeting
of the Geromological Society of America, San Diego, CA.
Coyne, J. C. (1976). Toward an interactional description of depression.
Psychiatry, 39, 28-40.
Coyne, J. C., Aldwin, C., & Lazarus, R. S. (1981). Depression and
coping in stressful episodes. Journal of Abnormal Psychology, 90,
439-447.
Coyne, J. C., & Gotlib, 1. H. (1983). The role of cognition in depression:
A critical appraisal. Psychological Bulletin, 99, 36-51.
Cronkite, R. C., & Moos, R. H. (1984). The role of predisposing and
moderating factors in the stress-illness relationship. Journal of
Health and Social Behavior, 25, 372-393.
Eaker, E. D., Haines, S.G., & Feinleib, M. (1983). Spouse behavior
and CHD in men: Prospective results from Framingham Heart Study:
11. Modification of risk in Type A husbands according to social and
psychological status of their wives. American Journal of Epidemiol-
ogy, 118, 23-41.
Feldman, L. B. (1976). Depression and marital interaction. Family Pro-
cess, 15, 389-395.
Folkman, S., & Lazarus, R. S. (1986). Stress processes and depressive
symptomatology. Journal of Abnormal Psychology, 95, 107-113.
Giunta, C. T., & Compas, B. E. (1993). Coping in marital dyads: Pat-
terns and associations with psychological symptoms. Journal of Mar-
riage and the Family, 55, 1011-1017.
Gruen, R. J., Folkman, S., & Lazarus, R. S. (1987). Dyadic response
patterns in married couples, depressive symptoms, and somatic dys-
function. Journal of Family Psychology, I, 168-186.
Haley, W. E., Levine, E.G., Brown, S.L., & Bartolucci, A. A. (1987).
Stress, appraisal, coping, and social support as predictors of adapta-
tional outcome among dementia caregivers. Psychology and Aging, 2,
323-330.
Haley, W. E., Levine, E. G., Brown, S. L., Berry, J. W., & Hughes, G. H.
(1987). Psychological, social, and health consequences of caring for
a relative with senile dementia. Journal of the American Geriatrics
Society, 35, 405-411.
Hautzinger, M., Linden, M., & Hoffman, N. (1982). Distressed couples
with and without a depressed partner: An analysis of their verbal
interaction. Journal of Behavioral Therapy and Experimental Psychi-
atry, 13, 307-314.
Hinchliffe, M., Hooper, D., Roberts, F. J., & Vaughan, P. W. (1975). A
study of the interaction between depressed patients and their spouses.
British Journal of Psychiatry, 126, 164-172.
124 PRUCHNO, BURANT, AND PETERS
Horowitz, A. (1982). The role of families in providing long-term care
to ike frail elderly living in the community. Washington, DC: U.S.
Department of Health and Human Services, Health Care Financing
Administration.
Jahoda, M. (1958). Current concepts of positive mental health. New
York: Basic Books.
Kahana, E., Kahana, B., & \bung. R. (1987). Strategies of coping and
postinstitutional outcomes. Research on Aging, 9, 182-199.
Kahn, J., Coyne, J. C., & Margolin, G. (1985). Depression and marital
disagreement: The social construction of despair. Journal of Social
and Personal Relationships, 2, 447-461.
Kiyak, H. A., Montgomery, R., Borson, S., & Teri, L. (1985, Novem-
ber). Coping patterns among patients with Alzheimer’s disease and
non-demented elderly. Paper presented at the annual meeting of the
Gerontological Society of America, New Orleans, LA.
Kleban, M. H., Brody, E. M., Schoonover, C. B., & Hoffman, C. (1989).
Family help to the elderly: Perceptions of sons-in-law regarding parent
care. Journal of Marriage and the Family, 51, 303-312.
Lang, A. M., & Brody, E. M. (1983). Characteristics of middle-aged
daughters and help to their elderly mothers. Journal of Marriage and
the Family, 45, 193-202.
Lawton, M. P., Moss, M., & Kleban, M. H. (1984). Marital status, living
arrangements, and the well-being of older people. Research on Aging,
6, 323-345.
Lawton, M. P., Rajagopal, D., Brody, E., & Kleban, M. H. (1992). The
dynamics of caregiving for a demented elder among Black and White
families. Journal of Gerontology: Social Sciences, 47, S156-S164.
Lazarus, R. S., & Fnlkman, S. (1984). Stress, appraisal, and coping.
New York: Springer.
Lieberman, M. A., & Fisher, L. (1995). The impact of chronic illness
on the health and well-being of family members. The Gerontologist,
35, 94-102.
Mitchell. R. E., Cronkite, R. C., & Moos, R. H. (1983). Stress, coping,
and depression among married couples. Journal of Abnormal Psychol-
ogy. 92, 433-448.
Noelker, L. S., & Poulshock, S. W. (1982). The effects on families of
caring for impaired elderly in residence. Washington, DC: Adminis-
tration on Aging.
Pearlin, L. L, Lieberman, M. A., Menaghan, E. G., & Mullan, J. T
(1981). The stress process. Journal of Health and Social Behavior,
22, 337-356.
Pearlin, L. I., & Schooler, C. (1978). The structure of coping. Journal
of Health and Social Behavior, 19, 2-21.
Pratt, C., Schmall, V., Wright, S., & Cleland, M. (1985). Burden and
coping strategies of caregivers to Alzheimer’s patients. Family Rela-
tions, 34, 27-33.
Pruchno, R. A., & Kleban, M. H. (1993). Caring for an institutionalized
parent: The role of coping strategies. Psychology and Aging, 8, 18-
25.
Pruchno, R, A., Peters, N. D., & Burant, C. J. (1995). Mental health of
co-resident family caregivers: Examination of a two-factor model.
Journal of Gerontology: Psychological Sciences, SOS, P247-P256.
Pruchno, R. A., & Resch, N. L. (1989). Mental health of caregiving
spouses: Coping as mediator, moderator, or main effect? Psychology
and Aging, 4, 454-463.
Quayhagen, M. P., &Quayhagen, M. (1988). Alzheimer’s stress: Coping
with the caregiving role. The Gerontologist, 28, 391-396.
Radloff. L. (1977). The CES-D Scale: A self-report depression scale
for research in the general population. Applied Psychological Mea-
surement, 1, 385-401.
Reece, D., Waltz, T, & Hageboeck, H. (1983). Intergenerational care
providers of non-institutionalized frail elderly: Characteristics and
consequences. Journal of Gerontological Social Work, 5, 21—34.
Shanas, E. (1979). The family as a social support system in old age.
The Gerontologist, 9, 169-174.
Soldo, B., & Myllyluoma, J. (1983). Caregivers who live with dependent
elderly. The Gerontologist, 23, 605-611.
Stanton, A. L,, Danoff-Burg, S., Cameron, C. L., & Ellis, A. P. (1994).
Coping through emotional approach: Problems of conceptualization
and confounding. Journal of Personality and Social Psychology, 66,
350-362.
Stephens, M. A. P., Morris, V. K., Kinney, J. M., Ritchie, S. W., & Grotz,
R.C. (1988). Stressful situations in caregiving: Relations between
caregiver coping and well-being. Psychology and Aging, 3, 208-209.
Stone, A. A., Greenberg, M. A., Kennedy-Moore, E., & Newman, M. G.
(1991). Self-report, situation-specific coping questionnaires: What
are they measuring? Journal of Personality and Social Psychology,
61, 648-658.
Sullivan, M. S., & D’Eon, J. L. (1990). Relation between catastrophiz-
ing and depression in chronic pain patients. Journal of Abnormal
Psychology, 99, 260-263.
Von Bertalanffy, L. (1968). General systems theory. New Ifork: Braziller.
Wright, S. D., Lund, D. A., Pratt, C., & Caserta, M. S. (1987, Novem-
ber). Coping and caregiver well-being: The impact of maladaptive
strategies or how not to make a situation worse. Paper presented at
the annual meeting of the Gerontological Society of America, Wash-
ington, DC.
Zarit, S. H., Reever, K. E., & Bach-Peterson, J. (1980). Relatives of the
impaired aged: Correlates of feelings of burden. The Gerontologist,
20, 649-655.
Received February 21, 1996
Revision received June 25, 1996
Accepted June 25, 1996 •
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Does a House Divided Stand? Kinship and the Continuity of Shared Living Arrangements
Glick, Jennifer E;Van Hook, Jennifer
Journal of Marriage and Family; Oct 2011; 73, 5; ProQuest
pg. 1149
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Growing Parental Economic Power in Parent–Adult
Child Households: Coresidence and Financial
Dependency in the United States, 1960–2010
Joan R. Kahn & Frances Goldscheider &
Javier García-Manglano
Published online: 21 February 2013
# Population Association of America 2013
Abstract Research on coresidence between parents and their adult children in the
United States has challenged the myth that elders are the primary beneficiaries,
instead showing that intergenerationally extended households generally benefit the
younger generation more than their parents. Nevertheless, the economic fortunes of
those at the older and younger ends of the adult life course have shifted in the second
half of the twentieth century, with increasing financial well-being among older adults
and greater financial strain among younger adults. This article uses U.S. census and
American Community Survey (ACS) data to examine the extent to which changes in
generational financial well-being over the late twentieth and early twenty-first cen-
turies have been reflected in the likelihood of coresidence and financial dependency
in parent–adult child U.S. households between 1960 and 2010. We find that younger
adults have become more financially dependent on their parents and that while older
adults have become more financially independent of their adult children, they never-
theless coreside with their needy adult children. We also find that the effect of
economic considerations in decisions about coresidence became increasingly salient
for younger adults, but decreasingly so for older adults.
Keywords Living arrangements . Intergenerational coresidence . Multigenerational
households . Financial dependency
Demography (2013) 50:1449–1475
DOI 10.1007/s13524-013-0196-2
Electronic supplementary material The online version of this article (doi:10.1007/s13524-013-0196-2)
contains supplementary material, which is available to authorized users.
J. R. Kahn (*) : J. García-Manglano
Department of Sociology and Maryland Population Research Center, University of Maryland, College
Park, MD 20742, USA
e-mail: jkahn@umd.edu
F. Goldscheider
Departments of Sociology and Family Science, and Maryland Population Research Center, University
of Maryland, College Park, MD 20742, USA
http://dx.doi.org/10.1007/s13524-013-0196-2
Introduction
Research on coresidence between parents and their adult children has increas-
ingly challenged the long-held view that elders benefit most from this type of
arrangement. Whether they focus on relatively contemporary households (Choi
2003; Kotlikoff and Morris 1990; Speare and Avery 1993; Ward et al. 1992) or
on a broad sweep of more than a century (Ruggles 2007), studies have shown
that intergenerationally extended households benefit the younger generation
disproportionately. Such studies imply not only that the normal structure of
parent–adult child households includes dependent adult children but also that
there has been little if any change over time in this structure.
We expect to see changes in recent decades because of important changes in the
factors affecting intergenerational coresidence for both generations. In addition to the
improvements in health among older adults that have increased their ability to live
independently, there have been substantial increases in their financial well-being,
with the implementation and growth of Social Security in the United States and
spread of private pensions (McGarry and Schoeni 2000), although this trend has
slowed or even reversed in recent decades (O’Rand et al. 2009). Young adults in the
US have experienced increases in education, and delays in marriage and childbearing,
as well as high rates of union disruption which have led to large numbers of young
adults who are unmarried and at increased risk of living with their parents
(Furstenberg et al. 2004). Analyses of intergenerational households have not
accounted for these changes.
The increasing financial well-being among older adults has not been matched,
however, among the younger generation. Young adults have in fact experienced
greater financial strain (Levy 1999; Preston 1984). Hence, the younger generation
is likely to have become more financially dependent on their parents’ generation in
recent decades, making it important to examine change during this period. Further,
this pattern of increased financial independence among the elderly might have
reversed, as the cohorts entering late middle age have suffered financial reversals
during the Great Recession (Gustman et al. 2010).
Nevertheless, in many cases, parents are indeed dependent on their adult children.
Thus, the question remains, Has the balance shifted such that many fewer parents
need to coreside while the opposite is the case for young adults? The question of
recent changes in coresidence patterns has not been systematically addressed in
previous studies and highlights the importance of considering changes in the resour-
ces of both generations when attempting to understand intergenerational coresidence.
This article examines the extent to which changes in financial well-being over the
past half-century (between 1960 and 2010) have been reflected in both the likelihood
of intergenerational coresidence as well as in the relative economic dependency of
both generations in parent–adult child households. Using census and American
Community Survey (ACS) data, we examine whether the economic balance of power
in intergenerational households has changed—and if so, how. We examine change in
the determinants of living in an intergenerationally extended household from the
perspective of both the older parent generation and the younger adult-child genera-
tion. Although not an ideal data source for studying the reasons for coresidence or the
duration of such arrangements, the census and ACS data allow us to learn a great deal
1450 J.R. Kahn et al.
about changes in both the characteristics of who coresides as well as who is support-
ing whom in coresidential households. Specifically, we examine the changing effects
of the key socioeconomic characteristics of education, employment status, and
income on the likelihood of living with either adult children or older parents.
Moreover, we compare the economic resources of each generation within multigen-
erational households to determine whether indeed the balance of financial power and
dependency within intergenerational households has changed over time. Although we
recognize that there are many noneconomic factors that encourage intergenerational
coresidence, including health and companionship needs, our focus is on trends in how
financial needs shape decisions to coreside.
Background
The shift in living arrangement patterns in the United States toward greater residential
independence in the period since World War II is well documented (see, e.g., Costa
1999; McGarry and Schoeni 2000; Santi 1990; Schoeni 1997). Adults of all ages are
increasingly living in simple households, either in two-adult, married-couple house-
holds or in one-adult households, with children or alone (Kobrin 1976). The percent-
age of elderly widows living alone rose from 18 % in 1940 to 62 % in 1990 (McGarry
and Schoeni 2000).
These changes in living arrangements have been linked to demographic, economic,
and normative changes. Demographically, mortality declines have resulted in a growing
number of persons surviving into the later years of the life course, with surviving parents
and children, thereby increasing the availability of relatives with whom to live (Schoeni
1997). However, the concomitant increase in good health of older persons and the
availability of home-based services (Krivo and Mutchler 1989) have also increased their
option of living independently and caring for their own needs.
In addition to changing demographic factors, we know from McGarry and Schoeni
(2000) that between 1940 and 1990, expanding Social Security benefits and private
pensions made independent living possible for many older persons. Lifestyle and
normative changes may have reinforced these demographic and economic patterns
(Alwin et al. 1985; Pampel 1983) by increasing the priority given to privacy,
independence, and age-segregated leisure-time activities (Goldscheider and
Goldscheider 1987). Few older persons want or expect to become dependent on their
family, residentially or otherwise (Burch and Mathews 1987; Lopata 1973).
It is increasingly clear, however, that complex households reflect the needs not just
of older people but also of younger adults. Ruggles (2007) showed that the decline in
intergenerational coresidence between 1850 and 2000 was due primarily to increasing
opportunities for the young and declining parental control over their children, rather
than the rising economic independence of the older generation. In a study of the early
1980s, Speare and Avery (1993) also found that intergenerational coresidence
depended more on the economic needs of the younger generation than on those of
the aged. Hence, the fact that the economic position of young adults has been
declining since the 1970s and 1980s (Easterlin 1978; Levy 1999) means that although
it has become increasingly feasible for older persons to be independent and to
purchase privacy, their resources have become more important to their adult
Growing Parental Economic Power in Parent–Adult Child Households 1451
children. Hence, our first hypothesis is that between 1960 and 2010, younger
adults living in parent–adult child households became increasingly dependent,
financially, on their parents.
In addition to expecting greater dependency among the young, our second hy-
pothesis is that over time, economic resources will play an increasing role in the
decision about whether to form a multigenerational household. This angle on family
extension has been even less researched. Although there is substantial research on the
determinants of intergenerational coresidence, relatively little has focused on how the
determinants may have changed. Most studies focus on a single period of time (e.g.,
Glick and Van Hook 2002; Mutchler and Burr 2003; Schmertmann et al. 2000; White
1994). Those who have taken advantage of the long historical sweep made possible
by the Integrated Public Use Microdata Series (IPUMS) (Ruggles et al. 2010) have
taken the broadest possible view, so the challenges of measurement comparability
overwhelm behavioral change (e.g., Ruggles 2007).
An important pair of studies, however, focused on the question of whether the
effect of income for elderly widows has intensified, with Costa (1999) arguing that it
has, and McGarry and Schoeni (2000) disagreeing. This is an important theoretical
issue: the increasing importance of income for decisions about coresidence suggests
that such a living arrangement may have become an undesired default for those
unable to purchase their desired privacy, and also that the value of privacy may have
increased relative to companionship and mutual exchange. By focusing on elderly
widows, neither Costa (1999) nor McGarry and Schoeni (2000) considered changes
in the characteristics of adult children or changes over time in the effects of each
generation’s economic resources on the likelihood of coresidence. Without account-
ing for adult children’s characteristics, it is difficult to know whether economic
resources have become more important determinants of coresidence over time.
Given coresidence, however, the research on which generation is more likely to
benefit (e.g., Choi 2003; Cohen and Casper 2002; Speare and Avery 1993) has
established that it is the younger generation, not the older, that typically benefits.
These studies have generally found, not surprisingly, that those experiencing financial
difficulties are more likely to be financially dependent in an intergenerational house-
hold, and that those at the youngest and oldest ages are also more likely to be
dependent, as are the unmarried and, more surprisingly, sons. This research, however,
has not focused on how the factors affecting financial dependency in intergenera-
tional households might have changed over time. Thus, our analysis of this issue is
exploratory; we have no expectations on how the effects of resources, age, marital
status, or gender might have changed as predictors of experiencing financial depen-
dency in such households.
In this analysis, we address these intergenerational issues by examining the
determinants of coresidence from the perspectives of both older and younger gen-
erations in order to assess whether, on the basis of changes in their characteristics, the
young have become increasingly “needy” relative to older generations (our first
question). Then we consider changes over time in factors affecting the likelihood
that younger adults will live with their parents, or that older adults will live with their
adult children or other younger relatives. This analysis provides valuable information
on baseline trends in coresidence patterns across the adult life course during a period
of rapid social, demographic, and economic change, and addresses our second
1452 J.R. Kahn et al.
question directly: have resources become more important in determining the likeli-
hood of residing in a parent–adult child household? We then address the question of
“who supports whom” by examining the actual resources of each coresiding gener-
ation in order to better determine the direction of the flow of support within house-
holds. We expect that younger adults will be more financially dependent on their
parents and older adults less financially dependent on their adult children in 2010
relative to 1960, but that the trends in the effects of financial resources might have
changed differentially between the generations.
Data and Measures
Our analysis of the determinants of intergenerational living arrangements and the
relative financial position of the generations begins with an analysis of change
between 1960 and 2010 based on U.S. census and ACS data. These data provide
the best view available of long-term change, although with limited measures. The
1960 census is the earliest to provide detailed information on income, education, and
employment on all members of the household, and the 2010 ACS is the most recent
national survey to obtain this information.
Data
We use decennial data from the IPUMS (Ruggles et al. 2010), which provide
nationally representative 1 % samples of households in the U.S. census between
1960 and 2000, and from the ACS (2010). Although both sets of data are subject to
minor levels of undercount (Robinson 1988; U.S. Census Bureau 2001), they are far
more representative than the sample survey data that constitute the basis for much
recent research on parent–child relationships. For all years, we use the self-weighted
subsamples generated for IPUMS users.
Given that our interest focuses on intergenerational coresidence among adult
relatives, our working sample includes only individuals 25 years of age or older,
living in households. This is the internationally recommended population to study for
these questions, primarily because in most cases, these young adults have completed
the nest-leaving process, at least insofar as it is connected with continuing education
(Pew Social and Demographic Trends 2010; United Nations 2005).
To determine coresidential status, we first classify all individuals into gen-
erations according to their relationship to the householder1: (1) grandparents
and grandparents-in-law; (2) parents, parents-in-law, uncles, and aunts; (3)
spouses, siblings, and relatives of similar age (defined here as no more than
15 years older or younger than the householder); (4) children, children-in-law,
nephews, and nieces; (5) grandchildren; and (6) other (including nonrelatives).
Our classification of multiple-generation households is similar to the existing
MULTGEN variable in IPUMS, except that we only include adults aged 25 and
1 The U.S. Census Bureau’s change in 1980 from “head of household” to the less sexist “householder” term
has no effect on our definition of multigenerational households because our determination is based on
comparing the relationships of all household members with the designated householder.
Growing Parental Economic Power in Parent–Adult Child Households 1453
older.2 Hence, all households containing only parents and their children younger than
age 25 in the original sample are here classified as one-generation households.
Next, we build our main dependent variables by assigning a multigenerational
status to each adult in the sample. Those in “one-generation households” were living
alone or with a spouse and/or a child younger than 25, a sibling, another relative who
is no more than 15 years older or younger than themselves, or a nonrelative, but not
with any other related adults aged 25 or older. In households with multiple adult
generations, all individuals are assigned into one of the following categories: “multi-
generation with parents,” if they were living with one or more older related adults
(98 % of whom were parents or parents-in-law) and “multigeneration with adult
child,” if they were living with one or more younger related adults (99 % of whom
were adult children).
We use two separate approaches to assigning multigenerational status: one for
householders and one for all other household members aged 25 or older. For the
multigenerational status of individuals who are not the householder, multigenerational
status is simply based on their relationship to the householder. However, because
householders have relationship codes with every member of the household, we create
a hierarchy of relationships in order to determine the householder’s multigenerational
status. Most cases are coded unambiguously because the householders either did not
live with an older or a younger adult relative (and are therefore coded as living in a
one-generation household), or they lived with a member of only one other generation
(older or younger). In the rare event (less than 1 % of adults) that a householder lived
with both older and younger adult relatives, our hierarchy gives priority to older adults;
hence we coded the householder as living with parents.
Table 1 shows the distribution on household generational status for all U.S. adults
aged 25 and older for each decade between 1960 and 2010. We divide the sample into
three age groups: young adults (aged 25–44), middle-aged adults (aged 45–64), and
older adults (aged 65 and older). For these ages and years, we show the proportions
living in one- versus multigeneration households. Figure 1 summarizes the trends.
Throughout the 50-year period and regardless of age, most adults lived in one-
generation households. Whereas in 1960, 12.4 % of young adults, 16.6 % of middle-
aged adults, and 26.7 % of older adults lived with another adult generation, by 2010,
between 15 % and 20 % of all three groups lived in multigenerational households
(Fig. 1). The steep decline in coresidence for the elderly during the 1960s and 1970s
is noteworthy, as is the steady increase after 1980 for young adults; in fact, however,
all three age groups saw increases after 1980, which is consistent with earlier findings
showing an increase between 1980 and 1990 (Goldscheider et al. 1994).
As one might expect, when we distinguish by whether the individual is living with
an adult child or older parent, the likelihood of living in one or the other type of
multigenerational household differs substantially by age. Table 1 shows that among
those who lived with relatives of a different generation, young adults were much
more likely to live with a parent rather than an adult child (11.5 % vs. 0.5 %
2 Because our focus is on the relative resources of adults (aged 25 or older) living in multigenerational
households, we do not consider other extended household forms (e.g., adult siblings who live together)
even though they may be important in groups such as recent immigrants. For the same reason, we also do
not control for the presence of dependent children, even though they may influence both the need for and
desirability of coresidence.
1454 J.R. Kahn et al.
Table 1 Household generational status of U.S. adults, by age and census year (1960–2010): Adults aged
25 and older
1960 1970 1980 1990 2000 2010
Age 25–44
N 447,351 455,701 591,384 728,269 749,965 658,397
Generational statusa
One generation 87.6 90.1 90.9 88.2 87.6 82.1
Two generations with parent 11.5 9.2 8.6 11.1 11.6 16.9
Two generations with adult child 0.5 0.6 0.3 0.4 0.3 0.3
% 100.0 100.0 100.0 100.0 100.0 100.0
Age 45–64
N 347,134 402,481 432,730 462,314 587,994 826,710
Generational statusa
One generation 83.4 85.8 84.8 81.3 83.7 82.1
Two generations with parent 7.1 6.3 5.0 4.3 4.9 6.1
Two generations with adult child 9.0 7.6 9.9 14.1 11.1 11.2
% 100.0 100.0 100.0 100.0 100.0 100.0
Age 65 and Older
N 147,367 186,408 234,594 307,631 326,961 460,904
Generational statusa
One generation 73.3 80.5 84.5 84.2 81.8 80.8
Two generations with parent 0.9 1.3 1.1 0.8 0.8 0.9
Two generations with adult child 25.2 17.9 14.2 14.6 17.1 18.1
% 100.0 100.0 100.0 100.0 100.0 100.0
a Generational status is determined for each adult based on his or her relationship with other adults in the
same household, regardless of the presence of children younger than age 25. A person is classified as living
in a one generation household if s/he lives alone, with a spouse or a sibling, but not with any adult children
or own parents or parents-in-law. A person is classified as living in a two generations with parent household
if s/he lives with at least one member of an older generation (e.g., a parent, parent-in-law, or grandparent). A
person is classified as living in a two generations with adult child household if s/he lives with at least one
member of a younger adult generation (e.g., an adult child or adult grandchild).
Fig. 1 Trends in intergenerational coresidence by age, 1960–2010
Growing Parental Economic Power in Parent–Adult Child Households 1455
in 1960; 16.9 % vs. 0.3 % in 2010), given that few were old enough to have
an adult child. Older adults were much more likely to live with an adult child
than with a parent (25.2 % vs. 0.9 % in 1960, 18.1 % vs. 0.9 % in 2010)
because few still had a living parent. The middle-aged were more evenly split
between living with parents and adult children at each census. Based on these
general patterns, we restrict our analyses of coresidence with parents to age
groups in which individuals are likely to have living parents (aged 25–44 and
45–64); our analysis of coresidence with adult children is limited to age
groups in which individuals are likely to have adult children (aged 45–64
and 65 and older).
In addition to examining “who coresides,” we also consider “who supports
whom” within intergenerational households by comparing the income received
by the members of each generation within these households. Our ultimate
dependent variable is an indicator of financial dependency reflecting whether
an individual (plus his or her spouse, if married) provides less than 40 % of the
income earned by members of the two generations, combined. If so, that person
(and spouse, if any) is considered to be financially dependent on the other
generation. Without more precise data on the flow of support, we assume that if
one generation provides substantially less than one-half of the household in-
come, then it is likely to be the recipient of support from the other (donor)
generation.3 There may not always be a donor and recipient in multigenera-
tional households, but our goal is to see how the balance of economic resources
within multigenerational households has changed over time.4
To create our measure of income dependency, we limit our focus to indi-
viduals who are living in multigenerational households. We first calculate the
income received (from all sources) by each generation, including the spouse’s
income if either generation is married with a spouse present. This means that
for each individual, we have his or her own/couple income as well as the
income of the other generation in the household. We then sum the incomes
from both generations to produce a measure of “multigenerational income”
within that household. In more than 75 % of cases, multigenerational income
equals total household income; the remaining households have other adults who
receive income.5 Based on total multigenerational income, we determine wheth-
er each generation’s share is less than 40 % of the total, indicating their
dependency on the other generation. Hence, we are attempting to distinguish
income dependency from the myriad other reasons to coreside, including health
conditions and other noneconomic reasons, such as tastes valuing companion-
ship relative to privacy.
3 We selected the 40 % threshold because it was sufficiently below the 50–50 mark and would therefore
indicate an unequal sharing of financial support by the two generations. We explored other thresholds (e.g.,
10 % and 25 %), but there were few differences, either in trends or determinants.
4 Throughout the period from 1960–2010, in only 15 % to 20 % of multigenerational households is financial
support shared relatively equally (i.e., with between 40 % and 60 % of income provided by each generation).
5 In no more than 15 % of multigenerational households do other adults contribute more than 25 % of
household income. However, the income of other earners has no effect on our intergenerational compar-
isons because we focus only on income from the adult children and their parents (and spouses, if any).
1456 J.R. Kahn et al.
Other Measures
Other individual and household characteristics are used as potential correlates of each
adult’s likelihood of living with and depending on adult relatives of a different
generation. These variables are coded in the same way for all adults in all years,
including both members of an intergenerational household pair. Marital status included
four categories: (1) married, spouse present; (2) separated, divorced, or married, spouse
absent; (3) widowed; and (4) never married. Race is coded into three categories: whites,
blacks, and other. Because the 1960 census did not include a question on Hispanic
origin, reflecting the small numbers of Hispanics in the United States at that time (Bean
and Tienda 1987), we do not distinguish Hispanics in this analysis. Each individual’s
nativity is derived from his or her place of birth, and we classify people into native (born
in the United States, excluding outlying areas and territories) and foreign-born. Area of
residence indicates whether the individual’s household was located in a metropolitan
area. Formal education is measured by the highest grade completed at the time of the
census and is grouped as follows: less than high school, high school graduate, some
college, and college graduate or more. Employment status indicates whether the indi-
vidual was currently employed at the time of the census or ACS interview. Total
personal income from all sources is adjusted for inflation to reflect 1999 U.S. dollars,
and is expressed in tens of thousands of dollars. Age is coded as a trichotomy: young
adult (24–44), middle age (45–64), and older adult (65 and older).
The coresidence models include all adults aged 25 and older and incorporate these
individuals’ characteristics. The income-dependency models are restricted to adults
who live in multigenerational households, incorporating characteristics of both the
younger and older generations. For both stages of the analysis, we present descriptive
and regression results for only 1960, 1990, and 2010. We include results for all six
census years in the tables in the online appendix (Online Resource 1).
Results
Coresidence Analysis
We present results for the coresidence analysis separately for two overlapping age
groups of younger and older adults corresponding to the results from Table 1: adults
aged 25–64 make up the sample at risk of living with a parent, and adults aged 45 and
older are those at risk of living with an adult child. Sample characteristics for the
coresidence analysis are included in Table 2, which shows the expected large changes
between 1960, 1990, and 2010 in the distributions on many socioeconomic and
demographic characteristics. (The full set of characteristics for the coresidence
sample for the six census years appears online in Table S1).
Turning to the relationships between the covariates and intergenerational coresi-
dence, Table 3 presents bivariate relationships for the likelihood of living in a
multigenerational household, shown separately for those living with parents and adult
children for the years 1960, 1990, and 2010. (The full set of bivariate relationships for
the six census years appears online in Table S2.) Throughout the 50-year period, the
trends show a small increase in the likelihood of living with parents (from 9.6 % in
Growing Parental Economic Power in Parent–Adult Child Households 1457
Table 2 Distributions on covariates by age and census year, (1960, 1990, and 2010): Adults aged 25 and older
Adults Aged 25–64 Adults Aged 45 and Older
1960 1990 2010 1960 1990 2010
N 794,485 1,190,583 1,485,107 494,501 769,945 1,287,614
Economic Characteristics
Education
Less than high school 54.3 15.5 9.9 70.9 29.7 12.9
High school graduate 27.8 33.9 34.5 16.0 35.1 38.9
Some college 9.5 27.6 24.5 7.4 19.3 21.3
College graduate or higher 8.4 23.1 31.1 5.7 16.0 27.0
Employment status
Not currently employed 36.8 25.0 27.8 50.5 54.7 49.1
Currently employed 63.2 75.0 72.2 49.5 45.4 50.9
Income
In 10 K of 1999 dollars 1.9 3.0 3.2 1.6 2.8 3.1
Below the median income 45.7 44.9 46.6 54.8 54.9 51.1
Above the median income 54.3 55.1 53.4 45.2 45.2 48.9
Other Characteristics
Age
25–44 56.3 62.3 48.4 NA NA NA
45–64 43.7 37.7 51.6 70.2 60.9 66.9
65 and older NA NA NA 29.8 39.2 33.1
Sex
Male 48.3 48.5 48.1 47.6 45.2 46.6
Female 51.7 51.5 51.9 52.4 54.8 53.4
Marital statusa
MSP 82.5 70.3 61.2 71.6 67.3 62.2
MSA/separated/divorced 5.9 13.9 17.5 5.5 11.5 18.3
Widowed 4.5 2.7 2.0 16.7 16.7 11.4
Never married 7.1 13.2 19.3 6.2 4.6 8.1
Race
White 90.3 85.6 81.1 91.4 88.4 84.3
Black 8.9 10.6 12.3 8.0 9.0 10.5
Other 0.8 3.8 6.7 0.6 2.6 5.2
Nativity
Native-born 92.9 89.3 81.4 86.7 90.3 84.9
Foreign-born 7.2 10.7 18.6 13.3 9.7 15.2
Area of residence
Nonmetropolitan/not identifiable 40.3 23.7 22.3 42.4 26.4 25.1
Metropolitan area 59.7 76.3 77.7 57.7 73.6 74.9
a MSP = married, spouse present. MSA = married, spouse absent.
1458 J.R. Kahn et al.
1960 to 11.3 % in 2010) and an even smaller decline in the likelihood of living with
adult children (from 13.8 % in 1960 to 13.4 % in 2010). The percentages at the top of
Table 3 show that for both types of coresidence, however, the trend was not
monotonic. For young adults, there were declining levels of coresidence between
1960 and 1990, followed by a particularly large bump up in coresidence with parents
between 1990 and 2010. For older adults, there was a slight increase in the likelihood
of coresidence between 1960 and 1990 (from 13.8 % to 14.3 %) followed by a slight
decline between 1990 and 2010 (from 14.3 % to 13.4 %).
These totals mask considerably larger changes over time for specific sociodemo-
graphic subgroups, as well as different patterns for upward and downward coresi-
dence. There were dramatic declines in the proportion of never-married adults who
live with a parent (from 47.7 % in 1960 to 31.4 % in 2010), suggesting that the small
increases observed for all younger adults reflect the increase in the proportions never
married, and declines for those aged 65 and older and for widows who live with adult
children (from 25.2 % to 18.0 %, and from 35.5 % to 26.6 %, respectively), although
in each case, even lower levels appeared during the intermediate period.
We also see particularly strong increases over time, however, in coresidence with parents
among more vulnerable subgroups. Those who are nonwhite, have low education, are not
employed, or have lower than the median personal income were more likely to live with a
parent in 2010 than in 1960. Moreover, both the race and education gradients in
coresidence with a parent grew steeper by 2010, implying that disadvantage has played
an increasing role in the residential choices of young adults. Finally, we see an interesting
reversal in the effects of employment and income on coresidence with parents: in 1960,
individuals with more resources (e.g., a job or higher income) were more likely than those
with fewer resources to live with parents (perhaps because they could afford to offer
support to their parents if they were in need). However, by 2010, individuals with fewer
resources were more likely to live with parents (perhaps because they needed the support
and their parents could now provide it). Consistent with this interpretation, we see, in
contrast, a weakening of the negative gradients for income and employment on the
likelihood of living with adult children. This suggests that over time, older adults’ own
economic needs may be playing a less important role in their coresidence decisions, and
their children’s economic needs may be playing a larger role.
The bivariate results suggest, in addition to the curvilinear patterns over time, a
fundamental shift in the processes leading to intergenerational coresidence for youn-
ger and older adults. Whereas socioeconomic disadvantage is playing a bigger role in
the residential choices of young adults in the year 2010 than in 1960, it has become
less central to the story for older adults.
Multivariate Analysis of the Changing Determinants of Coresidence
To assess the net impact of these factors, we now turn to the multivariate logistic
regression results. Table 4 presents odds ratios from logistic regressions that predict the
likelihood of living either with a parent (columns 1–3) or an adult child (columns 7–9) for
Growing Parental Economic Power in Parent–Adult Child Households 1459
Table 3 Bivariate relationships of coresidential status with covariates, by age and census year (1960, 1990,
and 2010), for adults aged 25 and older: Likelihood of multigenerational coresidence
% Adults Aged 25–64 Living
With a Parent
% Adults Aged 45 and Older Living
With an Adult Child
1960 1990 2010 1960 1990 2010
N 794,485 1,190,503 1,485,082 494,501 769,902 1,287,602
% 9.6 8.5 11.3 13.8 14.3 13.4
Economic Characteristics
Education
Less than high school 9.0 9.6 13.3 16.5 18.8 25.0
High school graduate 10.8 9.7 14.0 8.3 14.4 14.3
Some college 9.8 8.3 11.3 7.3 11.6 11.4
College graduate or higher 9.7 6.4 7.8 5.2 9.0 8.3
Employment status
Not currently employed 7.9 10.0 15.3 19.6 15.2 16.4
Currently employed 10.6 8.1 9.8 8.0 13.2 10.6
Income
Below the median income 8.7 11.1 15.9 18.5 16.5 16.7
Above the median income 10.3 6.4 7.3 8.2 11.7 10.1
Other Characteristics
Age
25–44 11.5 11.1 16.9 NA NA NA
45–64 7.1 4.3 6.1 9.0 14.1 11.2
65 and older NA NA NA 25.2 14.6 18.0
Sex
Male 10.1 9.9 12.9 10.4 11.8 10.5
Female 9.1 7.2 9.9 16.9 16.4 16.0
Marital statusa
MSP 5.7 2.6 4.2 9.8 13.2 11.9
MSA/separated/divorced 20.6 13.8 14.5 16.1 14.9 14.1
Widowed 7.4 5.0 6.8 35.5 21.5 26.6
Never married 47.7 35.4 31.4 0.3 3.6 4.9
Race
White 9.5 7.6 10.2 13.5 13.0 12.1
Black 10.8 14.5 15.9 17.2 24.2 18.7
Other 13.2 13.0 16.4 21.5 26.4 25.2
Nativity
Native-born 9.9 8.3 11.2 12.3 13.5 11.4
Foreign-born 6.2 10.1 11.8 23.6 22.0 25.0
Area of residence
Nonmetropolitan area/not identifiable 9.3 7.0 10.0 13.0 11.0 10.5
Metropolitan area 9.8 9.0 11.7 14.5 15.5 14.4
a MSP = married, spouse present. MSA = married, spouse absent.
1460 J.R. Kahn et al.
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Growing Parental Economic Power in Parent–Adult Child Households 1461
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1462 J.R. Kahn et al.
three time periods: 1960, 1990, and 2010. Odds ratios for all census years between 1960
and 2010 are included in Table S3 in Online Resource 1. (Given our very large sample
sizes, virtually all coefficients reach statistical significance.) Because our focus is on
changes over time in the determinants of intergenerational coresidence, we test for year
interactions with all covariates in pooled models comparing 1960 with 1990, 1990 with
2010, and 1960 with 2010 (interaction models not shown), and we report the significance
levels of these interactions in columns 4–6 and 10–12 of Table 4. The effects of almost all
covariates changed significantly over time, often monotonically.
Our story about the changing needs of older and younger generations can be seen most
clearly in the effects of employment and income. In 1960, net of other factors, employed
younger adults were 18 % more likely than the unemployed to live with parents
(OR = 1.18), presumably because they were better able to provide them with support;
and employed older adults were only 72 % as likely as the unemployed to live with adult
children, presumably because they were less likely to need support. By 2010, however,
employed younger adults were only 79 % as likely to live with parents as the unemployed
(suggesting they did not need their now well-off parents’ support as much as their
unemployed peers), and employed older adults were 98 % as likely to live with their
adult children. The significant weakening of the negative effect of parents’ employment
probably reflects both the strengthened economic position of all parents (regardless of
employment status) and the growing vulnerability of the younger generation. A similar
pattern can be observed for the effects of income between 1960 and 2010.
In summary, our findings provide a clear picture of the changing determinants of
intergenerational living over the past half-century. Whereas in 1960, the neediness of
the older generation played a large role in coresidence decisions, by 2010, these
decisions were clearly driven more by the economic needs of the younger generation.
The effects of income became more important for the younger generation but became
less important for older parents. Reinforcing this interpretation, the effect of being
employed changed sign: it changed from positively predicting coresidence with a
parent in 1960, implying that financially stable young adults were providing residen-
tial support to their parents, to negatively affecting coresidence, reinforcing the
portrait of an increasingly needy younger generation. The weakening of the negative
effect of employment for the older generation clarifies this portrayal as their own
financial needs played a smaller role in coresidence decisions.
Our other findings also highlight important changes during this period. Although men
were more likely than women to live with their parents in all census years, and women
were more likely than men to live with their adult children, the gender gaps grew larger
over time. Thus, by 2010, younger women were significantly less likely than men to live
with parents compared with 1960, and older women became significantly more likely
than men to live with adult children in 2010 than in 1960. These gender patterns are likely
to be linked to the delays in marriage (especially if it is unmarried men who are more
likely to live with parents than unmarried women), wage stagnation (which affected men
more than women), and increases in marital disruption (especially if previously married
mothers are more likely than previously married fathers to live with adult children). In
spite of the changes in marital status, the differences in coresidence patterns by marital
status have moderated over time: never-married adults are still more likely than others to
live with parents, but the gap between the never- and the ever-married has narrowed.
Similarly, whereas previously married adults are still more likely than married adults to
Growing Parental Economic Power in Parent–Adult Child Households 1463
live with adult children, again the gaps have narrowed, probably reflecting the wider
options available for older widowed and divorced adults to live on their own.
There was a shift in race patterns of coresidence. In 1960, blacks were 14 % less
likely than whites to live with parents (OR = 0.86), but in 2010, they were only 5 %
less likely to do so (OR = 0.95). This change could reflect the greater distance
between many blacks and their parents in 1960 compared with whites because of
the Great Migration north between the two World Wars (Tolnay 1997), but by 2010,
race differences in proximity between generations were likely to have declined.
Nevertheless, the lower level of coresidence with parents among younger black adults
compared with whites is something of a puzzle, given that studies based on surveys
normally found greater parental coresidence among young black adults (e.g.,
Goldscheider and DaVanzo 1989).
Coresidence patterns by nativity have shifted as well, probably reflecting historical
immigration patterns. Whereas in 1960, foreign-born adults were only 64 % as likely as
the native-born to live with parents (OR = 0.64), by 2010, they were 6 % more likely to
do so (OR = 1.06). And between 1960 and 2010, foreign-born adults became even more
likely than the native-born to live with adult children (OR = 1.68 in 1960, and OR = 1.93
in 2010). This could be due to the shifting composition of the younger foreign-born
population, with many more recent immigrants in 2010 than in 1960, who may have
immigrated as children and still live near their parents. Immigrants became more likely
to live with their parents and also more likely to live with their adult children. Again, it is
not clear how much of this reflects their own needs versus those of their relatives.
Finally, there were interesting shifts in metropolitan/nonmetropolitan patterns:
whereas in 1960, metropolitan-area residents were equally likely as nonmetropolitan-
area residents (OR = 0.99, nonsignificant) to live with parents, by 2010, adults in
metropolitan areas were significantly more likely to live with parents (OR = 1.17).
This may reflect the higher cost of living in metropolitan areas. From the older adults’
perspective, metropolitan-area residents became increasingly likely over time to live
with adult children compared with nonmetropolitan-area residents (OR = 1.17 in 1960,
and OR = 1.36 in 2010).
Overall, then, our results suggest substantial changes in intergenerational coresi-
dence patterns in recent decades, which indicate that there have been shifts in the
patterns of need that produce multigenerational households. Not all are totally
unidirectional, but none of the few curvilinear series of coefficients evident either
in Table 4 or in Table S3 in Online Resource 1 seem either substantive or interpret-
able. Hence, we focus on the overall pattern of change, which seems to support an
argument that whereas in 1960, coresidence decisions primarily reflected the needs of
older rather than younger adults, by 2010, it was clear that the financial needs of the
younger generation became more important. Indeed, the results suggest a pattern of
growing neediness among younger adults along with their increasing dependency on
older relatives for support.
The results from the coresidence analysis in Table 4 suggest that the younger
generation has grown needier over time, forcing the older generation to continue in
the provider role later in life. The evidence based on shifting economic determinants
of coresidence, however, is suggestive at best. To examine these relationships explic-
itly, we now look at the relative incomes of coresiding generations to draw inferences
about the flow of support across generations within households.
1464 J.R. Kahn et al.
Analysis of Financial Dependency Within Coresidential Households
Our analysis of financial dependency is restricted to the subsample of adults who
were living in coresidential households. Characteristics of both coresiding genera-
tions in these households are presented for 1960, 1990, and 2010 in Table 5,
separately for adults aged 25–64 who were living with a parent, and adults aged 45
or older who were living with an adult child. (Distributions for all census years
between 1960 and 2010 are presented in Table S4 in Online Resource 1.) Although it
is based only on adults who live in intergenerational households, the results in Table 5
show many of the same trends as Table 2 (e.g., rising education, declining marriage
among young adults). Moreover, the pattern of growing neediness of the younger
generation suggested by our earlier analysis is clearly confirmed by our direct
estimates of financial dependency within multigenerational households.
Table 6 shows bivariate relationships between the covariates and the likelihood of
contributing less than 40 % of multigenerational income (income dependency), for
1960, 1990, and 2010 (results for all census years are presented in Table S5 in Online
Resource 1). Trends in income dependency are plotted in Fig. 2 which shows that
over time, despite fluctuations, income dependency increased sharply for those who
lived with a parent (from 19.2 % in 1960 to 47.7 % in 2010) and declined sharply for
those who lived with an adult child (from 54.4 % in 1960 to 26 % in 2010). In other
words, older parents shifted from having lower incomes than their coresident adult
children in 1960 to being the financial providers in 2010. Unlike the trends in
coresidence, which varied substantially by subgroup, the trends in intergenerational
dependency were pervasive, and the gradients by social and economic status persisted
over time. As one might expect among coresiding adults, the more vulnerable
subgroups (e.g., the youngest and oldest adults, the unmarried, the less-educated,
and the unemployed) were much more likely to be financially dependent on the other
generation in all years.
Table 7 presents odds ratios from logistic regressions for 1960, 1990, and 2010,
predicting whether an individual (plus his or her spouse, if married) contributes less
than 40 % of the total income received by both coresiding generations, implying
financial dependency on the other generation. The models of financial dependency
are presented separately from the adult child’s and parent’s perspectives (in columns
1–3 and 7–9, respectively), although all models include characteristics of both
generations. Results from year-interaction tests for each covariate are presented in
columns 4–6 and 10–12. Results for all census years from 1960 to 2010 are in
Table S6 in Online Resource 1.
The regression results show that the flows of resources within multigenerational
households reflect the characteristics of both generations in the household. The effect
of socioeconomic resources such as education and employment on financial depen-
dency is especially strong. For both parents and adult children in multigenerational
households, having a higher education protects each generation from dependency on
the other, and this effect has grown stronger over time. Controlling for the education
of the parent or child with whom one lives, one’s own lower education is an
increasingly important predictor of financial dependency, suggesting that individ-
uals with fewer educational resources were at a greater relative disadvantage in
2010 than in 1960. Individuals living with a highly educated parent or child were
Growing Parental Economic Power in Parent–Adult Child Households 1465
Table 5 Distributions on covariates, by age and census year (1960, 1990, and 2010): Coresident adults of
different generations
Adults Aged 25–64
Living With a Parent
Adults Aged 45 and Older
Living With an Adult Child
1960 1990 2010 1960 1990 2010
N 76,303 100,542 148,593 68,400 110,130 160,512
Economic Characteristics
Child’s education
Less than high school 50.7 17.8 11.0 49.9 16.1 9.9
High school graduate 31.2 39.1 42.5 29.9 38.7 42.1
Some college 9.7 26.2 23.7 10.4 27.0 24.1
College graduate or higher 8.4 16.9 22.8 9.9 18.3 23.8
Parent’s education
Less than high school 86.0 44.9 25.1 84.4 39.8 22.5
High school graduate 8.5 31.7 41.5 9.6 35.3 42.4
Some college 3.6 14.0 17.2 3.9 15.2 18.1
College graduate or higher 2.0 9.4 16.2 2.1 9.8 17.1
Employment status
Both unemployed 22.2 20.1 24.5 14.6 18.1 23.0
Child unemployed, parent employed 7.9 9.2 12.2 6.5 9.0 13.1
Child employed, parent unemployed 49.3 40.4 39.1 56.8 40.7 36.6
Both employed 20.6 30.1 24.2 22.2 32.2 27.3
Other Characteristics
Child’s age
25–44 67.7 80.1 69.2 71.6 84.3 73.4
45–64 32.3 19.9 30.8 28.4 15.8 26.6
Parent’s age
45–64 35.7 50.9 47.4 45.8 59.1 54.2
65 and older 64.3 49.1 52.6 54.2 40.9 45.8
Child’s sex
Male 50.9 56.0 54.1 66.0 61.9 57.9
Female 49.1 44.0 45.9 34.1 38.2 42.1
Parent’s sex
Male 42.1 47.7 37.5 35.9 37.4 37.2
Female 57.9 52.3 62.5 64.1 62.6 62.8
Race
White 88.8 78.1 74.6 89.2 81.4 77.1
Black 10.0 16.1 14.9 9.9 13.8 13.3
Other 1.1 5.8 10.5 1.0 4.8 9.6
Child’s marital status
Unmarried 51.4 78.3 74.4 70.2 88.4 85.4
Married 48.6 21.7 25.6 29.8 11.6 14.6
Parent’s marital status
Unmarried 70.0 56.9 59.6 49.4 37.9 41.5
Married 30.0 43.1 40.4 50.6 62.1 58.6
1466 J.R. Kahn et al.
significantly more likely than others to be financially dependent, even controlling
for their own education.
Over time, employment continues to be highly protective against financial
dependency for both adult children and parents, especially when the other gener-
ation is unemployed. Not surprisingly, unemployed adult children living with
employed parents and unemployed parents living with employed adult children
were increasingly more likely to be financially dependent than those living in
households where neither generation was employed (the reference category). These
effects are noticeably stronger in 2010 than in previous years, and they are
consistent with the bivariate relationships in Table 6, which shows that in 2010,
almost 90 % of unemployed adult children were economically dependent on their
employed parents, compared with only 50 % of unemployed parents living with
employed adult children. Interestingly, in 2010, in the case in which both gen-
erations were unemployed, 58 % of adult children are economically dependent on
their aging parents; this compares with only 17 % of parents who were econom-
ically dependent on their adult children.
There were also interesting changes in the effects of the other covariates less
closely tied to resources. We see a weakening of the relative financial position of
young adults in 1990 and 2010 as they became more likely than middle-aged adult
children to be financially dependent on their parents, compared with 1960, when they
were less likely than the middle-aged to be dependent; similarly, we see that over
time, parents became even less likely to be financially dependent on their young adult
rather than middle-aged children. The financial position of elderly parents also
strengthened such that by 2010, they were no longer so much more vulnerable to
financial dependency than middle-aged parents: in 1960, they were almost twice as
likely as middle-aged parents to be dependent on their adult children, whereas in
2010, they were only 7 % more likely.
Also, in contrast to our results for coresidence, the analysis of financial dependen-
cy shows a decline in the significance of gender, at least among adult children.
Whereas in 1960, adult daughters were 23 % more likely than adult sons to be
financially dependent on their parents, the gap dropped to 10 % in 1990 and reversed
direction by 2010, at which time sons were 5 % more likely than daughters to be
Table 5 (continued)
Adults Aged 25–64
Living With a Parent
Adults Aged 45 and Older
Living With an Adult Child
1960 1990 2010 1960 1990 2010
Nativity
Both foreign-born 4.0 10.5 17.2 3.7 8.7 14.9
Child native-born, parent foreign-born 20.6 5.5 9.2 19.1 5.3 9.5
Parent native-born, child either 75.5 84.0 73.6 77.2 86.0 75.6
Area of residence
Nonmetropolitan area 39.0 24.1 22.8 39.6 24.8 23.9
Metropolitan area 61.0 75.9 77.2 60.4 75.2 76.1
Growing Parental Economic Power in Parent–Adult Child Households 1467
Table 6 Bivariate relationships of dependency status with covariates, by age and census year (1960, 1990,
and 2010), for individuals living with a parent or an adult child: Likelihood of dependency (% contributing
less than 40 % of multigenerational income)
Likelihood of Dependency
Among Adults Aged 25–64 Living
With a Parent
Among Adults Ages 45 and Older
Living With an Adult Child
1960 1990 2010 1960 1990 2010
N 76,303 100,542 148,593 68,400 110,130 160,512
% 19.2 43.7 47.7 53.4 27.0 26.0
Economic Characteristics
Child’s education
Less than high school 21.1 45.3 50.5 54.7 27.7 24.1
High school graduate 16.4 43.6 50.3 52.4 25.9 23.0
Some college 20.1 44.4 48.0 49.2 26.4 25.4
College graduate or higher 17.7 41.5 41.2 54.1 29.7 32.5
Parent’s education
Less than high school 18.2 34.1 32.5 55.4 37.4 40.5
High school graduate 20.9 43.7 45.7 45.9 24.1 25.9
Some college 27.0 56.7 58.5 41.9 16.6 17.5
College graduate or higher 43.1 70.4 64.7 30.2 11.4 16.0
Employment status
Both unemployed 22.0 48.4 58.3 32.7 20.9 16.8
Child unemployed, parent employed 58.6 82.1 87.4 9.7 5.1 3.6
Child employed, parent unemployed 5.3 20.2 20.6 73.5 46.6 50.1
Both employed 34.4 60.6 60.6 28.2 11.7 12.1
Other Characteristics
Child’s age
25–44 23.2 49.9 55.6 45.0 21.4 19.6
45–64 10.9 18.7 29.8 74.7 56.7 43.6
Parent’s age
45–64 30.4 57.5 60.6 34.4 16.1 15.9
65 and older 13.0 29.5 36.1 69.5 42.8 37.9
Child’s sex
Male 18.3 45.6 50.7 60.4 29.0 25.7
Female 20.2 41.4 44.1 39.9 23.8 26.3
Parent’s sex
Male 34.7 63.0 64.4 40.0 17.2 18.6
Female 8.0 26.2 37.6 60.9 32.9 30.3
Race
White 18.3 43.9 49.0 54.2 25.7 23.6
Black 26.7 47.7 51.1 46.2 28.1 26.2
Other 22.4 30.1 33.3 52.9 45.8 45.1
Child’s marital status
Unmarried 34.2 54.0 60.4 39.7 20.4 18.1
Married 3.4 6.8 10.9 85.8 77.3 72.1
1468 J.R. Kahn et al.
financially dependent. Based on the bivariate trends in Table 6, it appears that sons
saw a greater increase in dependency over time than did daughters. Mothers, how-
ever, remained more financially dependent on adult children compared with fathers
(OR = 1.07 in 1960, and OR = 1.09 in 2010). Nevertheless, the gender of the child
mattered less to a parent’s financial dependency in 2010 than in 1960: whereas in
1960, a parent was 75 % as likely to be financially dependent on a daughter as on a
son, by 2010, the odds were even (OR = 1.0). Thus, for the younger generation,
gender has come to play a smaller role in the flow of resources within intergenera-
tional households.
Race differences have also narrowed over time such that black adult children are
no longer more likely than white adult children to be dependent on their coresidential
parents (OR = 1.21 in 1960 vs. OR = 0.93 in 2010). However, during the same
period, black parents became even more likely than white parents to be financially
dependent on their adult children (OR = 0.95 in 1960 vs. OR = 1.27 in 2010). These
Table 6 (continued)
Likelihood of Dependency
Among Adults Aged 25–64 Living
With a Parent
Among Adults Ages 45 and Older
Living With an Adult Child
1960 1990 2010 1960 1990 2010
Parent’s marital status
Unmarried 9.3 26.0 32.9 78.3 51.2 44.9
Married 42.3 67.2 69.4 29.2 12.2 12.6
Nativity
Both foreign-born 9.7 25.5 24.2 69.1 49.6 52.1
Child native-born, parent foreign-born 14.2 34.4 46.8 63.5 35.3 27.7
Parent native-born, child either 21.1 46.7 53.3 50.2 24.2 20.6
Area of residence
Nonmetropolitan area 22.4 44.8 51.2 50.3 25.3 21.1
Metropolitan area 17.2 43.4 46.6 55.4 27.6 27.5
Fig. 2 Trends in income dependency within intergenerational households by age, 1960–2010
Growing Parental Economic Power in Parent–Adult Child Households 1469
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Growing Parental Economic Power in Parent–Adult Child Households 1471
patterns suggest that younger whites are no longer as advantaged over younger blacks
as in the past, and also that the gains we have observed for older adults are less
characteristic of blacks and other races (likely Hispanics) than for whites.
Our results also highlight the importance of marriage for both generations. When
either adult children or parents are married, they are significantly less likely to be
financially dependent on the other generation, regardless of the latter’s marital status.
And conversely, when the other generation is married, this raises the likelihood of
financial dependency, regardless of one’s own marital status. In addition, we find that
immigrant families have become even more likely than native families to support
their adult children into adulthood, with especially strong intergenerational support in
families with foreign-born parents and native-born children. And finally, we find that
the odds of being financially dependent on parents were higher in nonmetropolitan
areas in 1960 and in metropolitan areas in 2010. These patterns probably reflect the
rapidly rising cost of living in metropolitan areas as well as the movement of young
adults from rural areas to metropolitan areas during this time period. Nonetheless, by
1990 and again in 2010, there was no difference in the likelihood of financial
dependency on adult children between parents from metropolitan areas and those
from nonmetropolitan areas.
Discussion
In this article, we examine the changing nature of intergenerational coresidence and
financial support in the United States over the past half-century—a period of rapid
social, economic, and demographic changes. Unlike previous studies that have focused
primarily on only one age group, such as young single adults or elderly widows, we
focus on the residential choices of both younger and older adults in order to understand
how the needs of different generations influence their joint living arrangements. And
unlike previous studies, we examine change over a recent, five-decade period by using
U.S. census and ACS data from 1960 through 2010. We examine changes over time in
the determinants of living with either an older or a younger generation from the
perspective of younger adults (aged 25–64) and older adults (aged 45 and older), as
well as the determinants of financial dependency within parent–adult child households,
in each case assessing how these determinants have changed over the period.
We find that the patterns of intergenerational coresidence and resource flows
within coresidential households have changed in dramatic ways, paralleling the
general trends toward the greater economic security of older adults and the
increasing financial strain experienced by younger adults. Consistent with our
first hypothesis, we found that younger adults have become increasingly needy
over time, as reflected in their likelihood of intergenerational coresidence. Our
results suggest that the needs of the older generation played a much larger role in
coresidence decisions in 1960 than in 2010, when these decisions were clearly
driven more by the economic needs of the younger generation. Further, consistent
with our second hypothesis, economic resources played a more important role in
the decisions of young adults to coreside in 2010 than was the case in 1960.
However, this was not the case for the older generation, for whom the effects of
their own resources on the coresidence decision declined.
1472 J.R. Kahn et al.
These countervailing patterns highlight the importance of considering the financial
well-being of both generations. The strengthening effect of income insecurity on the
likelihood that young adults coreside with their parents is likely to be the result of the
decline in impoverished elderly parents living with their relatively affluent children,
rather than any increase in “tastes” for privacy. Similarly, the declining effect of
resources on the likelihood that older parents coreside with their adult children is
likely to reflect that their relatively impoverished adult children have come to live
with them rather than any decline in “tastes” for privacy. Our direct measures of
individual-level income provide a more robust test of the changing impact of income
on coresidence than was possible in the studies by Costa (1999), which used state
average Old Age Assistance benefit levels, and McGarry and Schoeni (2000), which
used an imputed average Social Security benefit.
Our analysis of the determinants of being financially dependent in parent–adult
child households shows that young adults have clearly become the more financially
dependent generation compared with their parents. Although the determinants of
financial dependency have not changed over time nearly as much as the determinants
of coresidence, our results suggest increasing challenges for young adults, especially
those with fewer economic resources. In addition to finding that younger adults are
increasingly disadvantaged relative to older age groups, we also find that education
played a larger role in financial dependency in 2010 than in 1960, further disadvan-
taging the least educated.
Whereas nonemployment and nonmarriage remain strongly associated with de-
pendency for both adult children and older parents, we find that gender became less
predictive of dependency, in spite of the growing gender gap in coresidence: by 2010,
young men were much more likely to coreside than young women, and older women
became increasingly likely to live with adult children compared with older men.
Daughters are no longer so much more likely than sons to be financially dependent on
their parents. Surely, the increases over time in women’s employment and wages
along with the relative stagnation of men’s wages have combined to reduce the
gender gap in dependency. Although mothers remain more likely than fathers to be
financially dependent on their adult children, they are now equally likely to depend
on daughters as sons.
Finally, our findings regarding race suggest a mixed pattern with a narrowing of
the race gap in financial dependency at younger ages (whereby young blacks are no
longer more likely to be dependent than young whites) but a disturbingly larger race
gap at older ages. Whereas in 1960, black parents were no more likely than white
parents to be financially dependent on their coresidential adult children, by 2010, the
race gap for parental dependency had increased: black parents in 2010 were 27 %
more likely than whites to be financially dependent on their children. These changes
parallel those in the analysis of coresidence.
Our findings with regard to gender, marital status, and race deserve additional
research in analyses that are possible when using IPUMS. Does the changing gender
pattern of coresidence reflect increases in female unmarried parenthood? Do the
changes in effects for race reflect the changes in race/ethnic/nativity composition
that occurred over the 50-year period covered by our analysis? Do the same patterns
characterize households with combined incomes below the poverty line the same way
as more financially well-off households?
Growing Parental Economic Power in Parent–Adult Child Households 1473
These questions are becoming particularly critical as the United States struggles
with the prolonged economic strains caused by the Great Recession. Our results for
the period 2000–2010 showed a particularly large increase (by almost 50 %) in young
adults’ coresidence with parents, which may reflect the increases in youth unemploy-
ment or housing foreclosures (Kochhar et al. 2011; Wiemers 2012). Middle-aged
adults were not exempt from these trends as they too saw an increase of almost 25 %
in the proportion living with parents; in contrast, elders aged 65 and older saw an
increase of only 5 % in the proportion living with adult children. So although there
clearly has not yet been a reversal of fortunes at older ages—the current elderly are
even more likely to be providing coresidence and financial support to their children
than in the past—the result for middle-aged adults may presage substantial change by
2020. Given that their behavior more closely resembled that of younger adults than
the oldest adults, by the time the middle-aged have become elderly—with lower
savings than earlier cohorts, a lower likelihood of receiving a generous private
pension, and perhaps substantial cuts in the value of social (and health) security—a
reversal does not seem totally implausible in the near future.
Thus, coresidence (and the support that it typically provides) clearly continues to
be an important resource for families. It can increase financial well-being not just for
those unable to live independently—such as the traditional categories of children, the
disabled, and those with substantial caregiving demands—but also for struggling
adults. Much more needs to be learned about the ways in which families do or do not
provide such support. As our results indicate, the IPUMS is an extraordinary resource
with which to address such questions.
Acknowledgements This research was supported in part by funds provided to the Maryland Population
Research Center from the Eunice Kennedy Shriver National Center for Child Health and Human Devel-
opment Grant R24-HD041041. The authors gratefully acknowledge the helpful comments from the
anonymous reviewers. They also acknowledge the unpublished work by Goldscheider et al. (1994), which
formed the conceptual basis for this article. Previous versions of this article were presented at the 2011
annual meeting of the Population Association of America, Washington, DC, and 2011 annual meeting of
the Social Science History Association, Boston, MA.
References
Alwin, D. F., Converse, P. E., & Martin, S. S. (1985). Living arrangements and social integration. Journal
of Marriage and the Family, 47, 319–334.
Bean, F., & Tienda, M. (1987). The Hispanic population of the United States. New York: Russell Sage.
Burch, T., & Mathews, B. (1987). Household formation in developed societies. Population and Develop-
ment Review, 13, 495–512.
Choi, N. G. (2003). Coresidence between unmarried aging parents and their adult children: Who moved in
with whom and why? Research on Aging, 25, 384–404.
Cohen, P. N., & Casper, L. M. (2002). In whose home? Multigenerational families in the United States,
1998–2000. Sociological Perspectives, 45, 1–20.
Costa, D. (1999). “A House of Her Own”: Old age assistance and the living arrangements of older
nonmarried women. Journal of Public Economics, 72, 30–39.
Easterlin, R. (1978). What will 1984 be like? Socioeconomic implications of recent twists in age structure.
Demography, 15, 397–432.
Furstenberg, F. F., Jr., Kennedy, S., McLoyd, V. C., Rumbaut, R. G., & Settersten, R. A., Jr. (2004).
Growing up is harder to do. Contexts, 3(Summer), 33–41.
Glick, J., & Van Hook, J. (2002). Parents’ coresidence with adult children: Can immigration explain racial
and ethnic variation? Journal of Marriage and Family, 64, 240–253.
1474 J.R. Kahn et al.
Goldscheider, F., Biddlecom, A., & McNally, J. (1994, August). Dependency, privacy, and power in intergen-
erational households: Changes in the living arrangements of the elderly in the U.S., 1940–90. Paper
presented at the 1994 annual meeting of the America Sociological Association, Los Angeles, CA.
Goldscheider, F., & DaVanzo, J. (1989). Pathways to independent living in early adulthood: Marriage,
semiautonomy, and premarital residential independence. Demography, 26, 597–614.
Goldscheider, F., & Goldscheider, C. (1987). Moving out and marriage: What do young adults expect?
American Sociological Review, 52, 278–285.
Gustman, A. L., Steinmeier, T. L., & Tabatabai, N. (2010). What the stock market decline means for the
financial security and retirement choices of the near-retirement population. Journal of Economic
Perspectives, 24, 161–182.
Kobrin, F. (1976). The fall in household size and the rise of the primary individual in the United States.
Demography, 13, 127–138.
Kochhar, R., Fry, R., & Taylor, P. (2011). Wealth gaps rise to record highs between whites, blacks, Hispanics
(Pew Research Center, Social and Demographic Trends). Washington, DC: Pew Research Center.
Kotlikoff, L., & Morris, J. (1990). Why don’t the elderly live with their children? A new look. In D. Wise
(Ed.), Issues in the economics of aging (pp. 149–169). Chicago, IL: University of Chicago Press.
Krivo, L. J., & Mutchler, J. E. (1989). Elderly persons living alone: The effect of community context on
living arrangements. Journal of Gerontology, 44, S54–S62.
Levy, F. (1999). The new dollars and dreams. New York: Russell Sage Foundation.
Lopata, H. (1973). Widowhood in an American city. Cambridge, MA: Schenkman.
McGarry, K., & Schoeni, R. (2000). Social Security, economic growth and the rise in elderly widows’
independence in the twentieth century. Demography, 37, 221–236.
Mutchler, J. E., & Burr, J. (2003). Living arrangements among older persons. Research on Aging, 25, 531–558.
O’Rand, A. M., Ebel, D., & Isaacs, K. (2009). Private pensions in international perspective. In P. Uhlenberg
(Ed.), International handbook of population aging (pp. 429–443). Rueil-Malmaison, France: Springer
Science + Business B.V.
Pampel, F. (1983). Changes in the propensity to live alone: Evidence from consecutive cross-sectional
surveys, 1960–1976. Demography, 20, 433–447.
Pew Social and Demographic Trends. (2010). The return of the multi-generational family household
(Report). Washington, DC: Pew Research Center. Retrieved from http://pewsocialtrends.org/2010/03/
18/the-return-of-the-multi-generational-family-household
Preston, S. (1984). Children and the elderly: Divergent paths for America’s dependents. Demography, 21, 435–457.
Robinson, J. G. (1988, April). Perspectives on the completeness of coverage of population of the United
States decennial censuses. Paper presented at the annual meeting of the Population Association of
America, New Orleans, LA.
Ruggles, S. (2007). The decline of intergenerational coresidence in the United States, 1850 to 2000.
American Sociological Review, 72, 964–989.
Ruggles, S. J., Alexander, T., Genadek, K., Goeken, R., Schroeder, M. B., & Sobek, M. (2010). Integrated public use
microdata series: Version 5.0 [machine-readable database]. Minneapolis: University of Minnesota.
Santi, L. (1990). Household headship among unmarried persons in the United States, 1970–1985. Demog-
raphy, 27, 219–232.
Schmertmann, C., Boyd, M., Serow, W., & White, D. (2000). Elder-child coresidence in the United States.
Research on Aging, 22, 23–42.
Schoeni, R. (1997). Reassessing the decline in parent–child old-age coresidence during the twentieth
century. Demography, 35, 307–313.
Speare, A., & Avery, R. (1993). Who helps whom in older parent–child families? Journal of Gerontology:
Social Sciences, 48, S64–S73.
Tolnay, S. (1997). The Great Migration and changes in the northern black family, 1940 to 1990. Social
Forces, 75, 1213–1238.
United Nations. (2005). Living arrangements of older persons around the world. New York: United
Nations, Population Division, Department of Economic and Social Affairs.
U.S. Census Bureau. (2001). Preliminary estimates show improvement in Census 2000 coverage. Retrieved
from http://www.census.gov/newsroom/releases/archives/census_2000/cb01cn03.html
Ward, R., Logan, J., & Spitze, G. (1992). The influence of parent and child needs on coresidence in middle
and later life. Journal of Marriage and the Family, 54, 209–221.
White, L. (1994). Coresidence and leaving home: Young adults and their parents. Annual Review of
Sociology, 20, 81–102.
Wiemers, E. (2012, May). The effect of unemployment on household composition and doubling up. Paper
presented at the annual meetings of the Population Association of America, San Francisco, CA.
Growing Parental Economic Power in Parent–Adult Child Households 1475
http://pewsocialtrends.org/2010/03/18/the-return-of-the-multi-generational-family-household
http://pewsocialtrends.org/2010/03/18/the-return-of-the-multi-generational-family-household
http://www.census.gov/newsroom/releases/archives/census_2000/cb01cn03.html
Reproduced with permission of the copyright owner. Further reproduction prohibited without
permission.
- c.13524_2013_Article_196
Growing…
Abstract
Introduction
Background
Data and Measures
Data
Other Measures
Results
Coresidence Analysis
Multivariate Analysis of the Changing Determinants of Coresidence
Analysis of Financial Dependency Within Coresidential Households
Discussion
References
Terrence F. Cahill, EdD, FACHE, and Mona Sedrak, PhD, PA • 3
F
e
a
t
u
r
e
Terrence F. cahill, edd, Fache, and Mona Sedrak,
Phd, Pa
Su m m a r y • over the past several years, leaders in healthcare have noticed
an increase in generational tension among employees, most often focused on
the attitudes and behaviors of the arriving millennials (generation Y). While
these employee relations issues were a nuisance, they rarely rose to the level
of a priority demanding leadership intervention. Some leaders, in fact, hoped
that the issues would resolve themselves as these young employees settled in
and learned that they had to demonstrate new behaviors to be successful in the
workplace. Most organizations adopted this wait-and-see attitude.
not so today. as the boomer generation has begun its exodus from the
workplace, organizations are increasingly looking at the millennials as not a
problem but a solution to the workplace manpower transition that is under
way. our problem is that we don’t yet know how best to lead such a diverse,
multigenerational workforce.
this article examines the generational topic and provides advice concern-
ing a variety of changes that leaders may implement to advance their organiza-
tion’s ability to attract and to retain the millennials.
Leading a Multigenerational Workforce:
Strategies for Attracting and Retaining
Millennials
Terrence F. Cahill, EdD, FACHE, is chair and associate professor in the department of graduate
programs in health sciences in the School of Health and Medical Sciences at Seton Hall Uni-
versity in South Orange, New Jersey. Mona Sedrak, PhD, PA, is associate dean of the division
of health sciences in the School of Health and Medical Sciences at Seton Hall University.
Frontiers_29_1Fall.indd 3 8/15/12 4:13 PM
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4 • f r o n t i e r s o f h e a l t h s e r v i c e s m a n a g e m e n t 2 9 : 1
senior healthcare leaders. for example,
if you are one of those older leaders, did
you ever get a trophy for just showing up
to play or to participate in an activity as a
child? our millennial employees did. is it
any wonder that they arrive at our work-
places with high expectations for positive
feedback? early life experiences contribute
to generational differences that are deeply
imprinted in individuals’ beliefs, values,
preferences, and behaviors and are not
easily changed.
During the last decade, consulting
organizations, professional and industry
associations, and the academic com-
munity published reports that drew our
attention to the issue of generations in
the workplace. the Society for Human
resource Management published Gen-
erational Differences: Survey Report (Burke
2004), in which they presented the
results of a survey that explored what
human resource professionals observed
as advantages and disadvantages of an
intergenerational workforce. Deloitte
Development llc published Decoding
Generational Differences (Smith 2008), a
report of several years of research on the
topic. Pew research produced Millenni-
als: A Portrait of Generation Next (taylor
and Keeter 2010) to compare the values,
attitudes, and behaviors of millennials
with those of older adults. integrated
Healthcare Strategies (2007), in col-
laboration with the american Society for
Healthcare Human resources adminis-
tration of the american Hospital associ-
ation (aHa), published The Multigenera-
tional Workplace: Strategies and Solutions
for Healthcare Employers to report on
emerging trends on the topic.
While these and similar publications
provide excellent information on the
increasingly important topic of leading
Introduction
in Good to Great (2001), collins reports
that leaders who take their companies from
good to great first pay attention to who is on
their bus, who is working in their organiza-
tion. Have you noticed that the people on
your bus are changing? We are referring to
the retirement of the baby boomer genera-
tion while increasing numbers of millen-
nials (generation Y)—those in their twen-
ties—are arriving in the workplace.
for the past several years, we have been
studying generational issues in the health-
care workplace. What we
have found is that while
leaders are aware that the
boomers are approaching
retirement and may have
been advised of tensions
among employees result-
ing from generational
differences, most leaders
have made generational
issues a low priority.
this is understandable given the
many pressing demands on leaders of
healthcare organizations during the past
decade. However, we also found that this
lack of attention to generational ten-
sions was deliberate in some cases. We
heard senior healthcare leaders express
the opinion that these tensions would
naturally resolve themselves as millen-
nials matured and realized that they had
to change their behaviors if they wanted
to be successful in their jobs. “after all,”
those leaders argued, “weren’t we like that
too? and we learned.”
Unfortunately, the evidence so far does
not support this wait-and-see approach
concerning generational tensions. the
millennial employees grew up with very
different family, school, and environ-
mental influences compared with today’s
Today’s workplace requires
a new human relations
guide referred to as the
platinum rule—“Do unto
others as they prefer to be
treated.”
Frontiers_29_1Fall.indd 4 8/15/12 4:13 PM
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Clearance Center at www.copyright.com.
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f
e
a
t
u
r
e
munication patterns, hospitals need to
orient young workers to the expectation
of patients and staff from the traditional,
baby boomer, and X generations, as
well as differences in expectation by
gender, race, and ethnicity.
these prescriptions call for a twofold
response to problems related to genera-
tional issues. first, programmatic changes
related to generational issues are needed.
in this article we discuss changes that are
recommended by generation for benefits,
work structure, training, and commu-
nication, with particular attention to the
millennials. Second, the aHa recommen-
dations accentuate the need for healthcare
leaders who know how to lead a multigen-
erational workforce.
Unfortunately, because we are all new to
these challenges, we are all still in a learn-
ing process. for example, the golden rule,
“Do unto others as you would have them do
unto you,” has been a guiding principle in
human relations throughout the twentieth
century. However, when generational dif-
ferences are considered, the rule no longer
works. take the issue of feedback. research
says that millennials demand constant
feedback and interpret silence as negative.
in contrast, older employees prefer to just
do their jobs and are content to receive
little feedback. What happens when either
the millennial or the older employee is
the manager and applies the golden rule?
employee relations become tense. today’s
workplace requires a new human relations
guide referred to as the platinum rule—“Do
unto others as they prefer to be treated”
(alessandra 1994).
to address these individual and rela-
tionship issues, we discuss a variety of
actions that organizations are taking to
sensitize their employees to generational
multigenerational organizations, the aHa
issued a call to action of much greater
urgency with its report Workforce 2015:
Strategy Trumps Shortages (2010). accord-
ing to the report, generational issues were
no longer merely an employee relations
matter. rather, the retirement of the baby
boomer generation from the workplace
is becoming a real threat to the ability of
healthcare organizations to ensure ad-
equate staff, and the arrival of the mil-
lennials is our primary hope. across the
United States, 10,000 baby boomers are
retiring daily, and this pattern is predicted
to continue for the next several years
(Meister and Willyerd 2010). the employ-
ment forecast for this period is that these
retirements will result in over 15 million
job openings, but only 12 million new
individuals (i.e., millennials, immigrants)
will be available to fill those jobs. as a
result of this dire forecast, the aHa (2010)
recommends the following:
• In identifying, developing, and appoint-
ing managers, hospitals need to give
increased attention to the employee’s
understanding of, appreciation for, and
effectiveness working with the multiple
workforce generations.
• To accommodate the preferences of the
multiple workforce generations, hospi-
tals need to replace traditional human
resources policies that were applied
uniformly to all workers with policies
and programs that include flexibility
and choices.
• Hospitals need to work with employees
approaching retirement age to iden-
tify attractive options regarding roles,
schedules, and benefits for continuing
to work full- or part-time.
• Given the generational differences in
dress, cosmetics, body art, and com-
Terrence F. Cahill, EdD, FACHE, and Mona Sedrak, PhD, PA • 5
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6 • f r o n t i e r s o f h e a l t h s e r v i c e s m a n a g e m e n t 2 9 : 1
growing up at the same time and being
exposed to similar stimuli, a group of
children tend to develop similar world-
views, beliefs, attitudes, values, and
behaviors. However, while acknowledg-
ing this process as the basis for viewing
generational similarities, stereotyping
and failure to recognize individual dif-
ferences are obvious dangers. genera-
tional theory acknowledges heterogene-
ity within groups by identifying cuspers,
individuals who are born near the end
of one generation or the beginning of
the next generation. these cuspers often
have characteristics associated with both
generations (Mcarthur 2009). With the
cautionary note concerning the risk of
stereotyping in mind, there is much we
can learn by understanding characteris-
tics associated with each of the four gen-
erations represented in our workplace.
The Generations
americans are living longer and work-
ing longer than at any other time in our
nation’s history. as a result, four distinct
generations are currently in the workplace
(exhibit 1). each of these generations
brings its own set of values, beliefs, life
experiences, and attitudes.
Traditionalists: Loyalists
traditionalists grew up in difficult times,
experiencing both the Depression and
World War ii. to survive, they saved for a
rainy day. in battle, they followed orders.
and in times of challenge, they main-
tained an immense faith in and loyalty to
their institutions. While a small number
of traditionalists remain employed, in hos-
pitals this population is more often found
in our volunteer services and, of course, in
our hospital beds—our Medicare patients.
differences. We begin by discussing the
concept of generational theory and identi-
fying the generations and their workplace
characteristics.
What Makes a Generation?
Most of us first encounter the concept
of generational differences in our early
family experiences. remember when a
holiday celebration was approaching and
all the thoughtfulness that went into ac-
commodating different family members’
needs, wants, and values? What will we
serve? When will we eat? Who will sit
where at the table? What
will we wear? consider-
able effort was made to
appreciate individual
differences to avoid indi-
vidual disappointments
and unnecessary tensions
and make it an enjoyable
event for all. While this is
a simple metaphor, it cap-
tures the type of sensitivity and proactive
planning that is necessary to become a
successful leader of a multigenerational
workforce. leaders who understand the
concept of generation and how it contrib-
utes to individual values, preferences,
and habits will be better prepared to rec-
ognize and address the needs of today’s
workforce.
a generation is “the average span of
time from the birth of parents to that
of their offspring” (Merriam-Webster
2011). in general, this is approximately
20 to 22 years. children are born into a
particular era, and they are influenced
not only by the values and attitudes of
their family, friends, and communities,
such as schools, but also by significant
world events, social trends, and environ-
mental factors occurring at that time.
At what point do we stop
viewing the millennials as
joining our organizations
and accept the reality
that our organizations
have become their
organizations?
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themselves. resourceful and independent,
Xers adopted a “show me the money,” short-
term orientation. Highly educated, they
favor pay-for-performance over tenure as the
basis for rewards.
Millennial Generation: “Trophy Kids”
the newest generation to enter the work-
place, the millennials, is the largest age co-
hort. in addition to being called millenni-
als, they are also referred to as generation
Y, nexters, and trophy kids. in 2010 they
represented only 27 percent of the work-
force, but with the escalating retirements
of boomers and the continuing influx of
millennials, they are predicted to represent
48 percent of the workforce in 2014 (Meis-
ter and Willyerd 2010). this projected
change raises the question: at what point
do we stop viewing the millennials as join-
ing our organizations and accept the reality
that our organizations have become their
organizations?
the millennials have been a sheltered
group since their births; think of the
countless minivans with “baby on board”
signs. their parents are very protective,
particularly of their children’s self-image.
they have provided continual reminders
to their millennial children that they are
“special.” for example, to prevent their
children’s disappointment, parents made
Baby Boomers: Me Generation
Baby boomers grew up in a thriving, post-
war economy characterized by optimism
and a can-do attitude. they inherited their
parents’ hard work ethic and are known
for their long work hours and willingness
to sacrifice personal and family matters
for their careers. Yet, the boomers were
also very much into themselves, leading
to their other name: the me generation.
through the 1960s boomers aspired to fix
society’s ills through various movements
(e.g., the peace movement, civil rights,
feminism). Boomers are a competitive
generation, as their large numbers re-
quired that they strategize and struggle to
succeed in their careers. Boomers favor
relationships, loyalty, and teamwork in
their approach to success.
Generation X: Skeptics
gen Xers grew up as the first latch-key gen-
eration because their boomer parents were
out working. they grew up in a time of in-
creasing unsettledness in society character-
ized by high divorce rates, an unstable econ-
omy, and high crime rates. Xers watched as
organizations downsized, merged, and went
out of business, often resulting in hardships
for their parents and families. as a result
of those experiences, Xers grew skeptical
of institutions and learned to rely more on
Terrence F. Cahill, EdD, FACHE, and Mona Sedrak, PhD, PA • 7
Exhibit 1 The Generations
Traditionalist Baby Boomer Gen X Millennial
Date of birth Before 1945 1946–1964 1965–1978 1979–2002
Age 67 and older 48–66 34–47 10–33
Current cohort size 27 million 76 million 60 million 88 million
Generation
Used with permission. © American Hospital Association. Workforce 2015: Strategy Trumps Shortage, 2010. Accessible at
http://www.aha.org/advocacy-issues/workforce/workforce2015.shtml
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8 • f r o n t i e r s o f h e a l t h s e r v i c e s m a n a g e m e n t 2 9 : 1
they also want work–life balance. to the
dismay of their supervisors, they will consis-
tently choose personal obligations over work
responsibilities. a related characteristic is
their internal clock. Millennials operate in a
24/7 virtual world that has almost unlimited
access to information.
While historically the
distinction between work time and non–
work time has been clear, millennials are
less oriented to the scheduled work hours
and more to the work itself. as long as the
work gets done, why does it matter where or
when it gets done? for healthcare organiza-
tions that have traditionally been oriented
to the acute care model, this millennial
characteristic is a challenge. However, it
may become a significant asset as healthcare
becomes less institution based and more
community/wellness oriented.
Millennials have never known a time
without sophisticated technology. as such,
they are the most tech-savvy generation.
Having trouble with a technology issue?
give it to a millennial and he or she will
figure it out. While older generations use
technology as a tool to accomplish a task,
millennials view technology as a way of
life, a part of who they are. as healthcare
pursues the adoption of more technology,
organizations will benefit from having
millennials on their bus.
a related issue is that technology has
brought with it the expectation for instant
solutions. accustomed to microwaves,
internet, text messaging, and cell phones,
millennials are impatient with delays. if
we asked you how long you were prepared
to wait for a response to an application for
a job, what would you say? Whatever you
answered, that is too long for a millennial.
organizations targeting the recruitment of
millennials have figured out ways to provide
not only the instant e-mail acknowledgment
of the application but also a call-back within
24 hours and a decision within days.
sure that everyone involved in recreational
sports received a trophy for just showing
up, regardless of achievement. Millennials
have been continually praised throughout
their developmental years, and as a result
organizations are finding their demands
for feedback surprising and frustrating. if
millennials do not receive feedback, they
interpret it as an indication that they did
something wrong. With their parents hov-
ering so closely overhead to protect them,
the term helicopter parents was coined to
describe how they swoop
in whenever their children
are threatened. teachers
all the way up to college
and even graduate school
report parents of millenni-
als scheduling meetings to
discuss why their child did
not get a better grade.
Millennials have grown
up working in teams. their schooling gets
the credit for instilling good teamwork skills,
as most school assignments were done
collaboratively. in today’s healthcare environ-
ment, very little can be accomplished alone.
therefore, the millennials’ teamwork and
collaboration skills should be considered
valuable contributions to our healthcare
organizations.
Millennials pursue a very busy sched-
ule, having juggled multiple activities
from very young ages. in learning how to
navigate these matters, millennials de-
velop very good multitasking skills. How-
ever, some have questioned whether this
routine leads the millennials to be satis-
fied with superficial skills. additionally, as
a result of their busy schedules, they grow
accustomed to having very little downtime,
with the result that when they are not
busy, they get bored very quickly.
While the millennials are known for
working hard to achieve their objectives,
While historically the
distinction between work
time and non–work time
has been clear, millennials
are less oriented to the
scheduled work hours and
more to the work itself.
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bility. for healthcare organizations this
should be a good thing, as we are a mis-
sion-driven industry.
With this general understanding of the
four generations, we next identify work-
place characteristics associated with each
generation.
Generational Workplace
Characteristics
in viewing workplace characteristics (ex-
hibit 2), a generational lens reveals a new
level of diversity in the workforce.
By itself, each of these generational
characteristics is neither positive nor nega-
tive. However, when the preferences of
each generation are considered in relation
to the preferences of other generations,
sources of tension become evident.
Millennials see themselves as custom-
ers, even in their employment relationship.
they grew up in a customer-centric world
in which retail organizations, recognizing
that millennials commanded significant
purchasing power, catered to them. as mil-
lennials enter the workforce they continue
to expect that their organizations want them
there and that their leaders are interested
in their ideas. When we present to millen-
nial audiences, we hear that this expectation
results in the biggest culture shock as they
enter the workforce. often, millennials re-
port that no one listens to them. this leads
us to our last millennial characteristic.
Millennials want to do meaningful
work. they are attracted to mission-driven
organizations and organizations that are
committed to corporate social responsi-
Terrence F. Cahill, EdD, FACHE, and Mona Sedrak, PhD, PA • 9
Exhibit 2 The Generational Workforce Characteristics
Used with permission. © American Hospital Association. Workforce 2015: Strategy Trumps Shortage, 2010. Accessible at
http://www.aha.org/advocacy-issues/workforce/workforce2015.shtml
Traditionalist Baby Boomer Gen X Millennial
Respectful of authority Values individuality Self-reliant Image conscious
Values duty and sacrifice Driven by goals for success Highly educated Need for feedback and
reinforcement
Values accountability Work ethic = hours worked and
monetary rewards
Questioning Values instant gratification
Values practical experience Believes in teamwork Most loyal employees Idealist
Work ethic = timeliness and
productivity
Emphasizes relationship
building
Wants open communication Team-oriented
Strong interpersonal skills Expects loyalty from coworkers Respects production over
tenure
Wants open communication
Promotions and recognition
come with job tenure
Career = identity Values control of his or her
time
Searches for others who will help
him or her achieve his or her goals
Values academic credentials Wants work-life balance Invests loyalty in a person, not
in an organization
Wants job that is personal
fulfillment
Accepts limited resources Risk averse Searches for ways to shed stress
in his or her life
Loyal to employer; expects
loyalty in return
Racial and ethnic identification
less important
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10 • f r o n t i e r s o f h e a l t h s e r v i c e s m a n a g e m e n t 2 9 : 1
to lead in a multigenerational environment,
the more successful we and our organiza-
tion will become. Second, failure to learn
how to lead a multigenerational workforce
will result in career derailment for aspiring
leaders. the aHa (2010) report foreshad-
ows this fact. third, for organizations, the
payoff for addressing generational issues is
improved organizational effectiveness. We
need all employees to be energized and cre-
ative in doing their work. Particularly as we
continue to squeeze costs out of the system,
we cannot afford clash points that distract
our attention and drain additional resources.
Generational Clash Points
the values and perspectives of each gen-
eration often conflict with the values and
perspectives of other generations, result-
ing in multiple clash points. in exhibit 3
we summarize generational characteristics
identified by many researchers as contrib-
uting to clash points.
recognizing and addressing generational
clash points in the workplace will benefit
organizations in several ways. first and
foremost, the multigenerational workplace
is not going away. this is not an “it too will
pass” phenomenon. the faster we learn how
Exhibit 3 Generational Clash Points in the Workplace
Clash Point Traditionalist Baby Boomer Gen X Millennial
Outlook Practical Optimistic Skeptical Hopeful
Work definition
Work ethic Committed Ambitious Balanced Determined
Work/career goal What will I leave
behind?
Accomplishing
bigger things
Building my
skill set
So many interest-
ing things to do
Organizations Believe in them Change them Doubt them Judge them
View of authority Deferential Love/hate Uninterested Civil
Reward system Doing good work Tangibles; corner
office, title
Independence Meaningful work
Feedback No news is good
news
Occasionally is
fine
Regular feed-
back, please
Constant feed-
back or else
Changing jobs Bad Only to move
ahead
A must Routine
expectation
Learning “I learned it the
hard way; you can
too.”
“Train ’em too
much and they
will leave.”
Motivates me
to stay
I expect it
A place you go Anytime, anyplace
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organizational culture that recognizes
and addresses generational differences.
Developing Emotional Intelligence
leaders and employees need to be emo-
tionally intelligent (goleman 2006) in
respect to generational diversity issues.
emotional intelligence entails understand-
ing one’s own generational personality
and biases, as well as learning about dif-
ferences among other employees that are
based on generational issues. the desired
outcome is an appreciation that, due to
generational differences, there are few
one-size-fits-all solutions for addressing
employee issues. We are living in the age
of the platinum rule and must treat others
as they wish to be treated.
organizations that are leading the way
in building strong, effective multigen-
erational workforces invest in a variety of
educational activities. intergenerational
workshops that introduce employees to
different generational preferences are
common. Mutual understanding is fos-
tered in an attempt to reduce misunder-
standing and miscommunication. Because
different generations prefer different
teaching styles and formats, these pro-
grams include a creative mix of tactics. for
example, baby boomers are used to having
PowerPoint slides, but millennials prefer
a more interactive approach to learning.
therefore, using a variety of educational
formats is common in generationally
sensitive organizations. to accommodate
the millennials’ 24/7 virtual orientation, e-
learning courses are being developed that
employees may take at a time and location
of their choice. Speaker series is another
alternative for providing groups with ac-
cess to generational information. Which-
ever educational formats are utilized to
address this topic, employees and leaders
Leading a Multigenerational
Workforce
We repeat collins’s (2001) question,
“Who is on the bus?” the starting point
in developing your organization’s mul-
tigenerational workforce is for you to
understand your current workforce in
respect to their generations. conduct an
audit and analyze the results to deter-
mine the generational composition of
your workforce. explore whether there is
a higher attrition rate for particular gen-
erations. identify generational tensions
in particular areas of the organization
or concerning particular issues. this
information provides several benefits.
first, it allows you to determine if you
have greater staffing risks in certain
departments due to approaching retire-
ments. Second, with your understanding
of each generation’s needs, you can bet-
ter craft a workforce plan that addresses
employees’ needs. third, you can use
this generational information to iden-
tify beneficial organizational changes in
areas such as benefits planning, continu-
ing education programs, and employee
relations planning.
in addition to this baseline audit,
we agree with and expand upon the
twofold strategy recommended by the
aHa (2010) report. first, to success-
fully lead a multigenerational workforce,
healthcare organizations need to adopt
organizational policies, procedures, and
structures that fit the needs and interests
of their generationally diverse employ-
ees. Second, we need to develop not
only leaders but also employees who are
generationally sensitive and competent
in their business exchanges. While both
are necessary, we suggest that organiza-
tions begin with the latter action, as this
contributes to establishing an inclusive
Terrence F. Cahill, EdD, FACHE, and Mona Sedrak, PhD, PA • 11
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12 • f r o n t i e r s o f h e a l t h s e r v i c e s m a n a g e m e n t 2 9 : 1
A key retention strategy is
to provide the opportunity
for lateral moves within
your organization when
a millennial is anxious for
new learning.
body art such as tattoos and piercings are
much more prevalent among millennials
than they are with older employees. While
organizations historically “just said no” to
drastically changing dress code standards,
more organizations are now willing to
negotiate dress code rules to arrive at a
solution that works for both the hospital’s
patients and its employees.
another benefit that is particularly
popular with millennials is the opportu-
nity for work release to engage in commu-
nity volunteer activity. Millennials expect
their work to be meaningful, and they are
attracted to employers who want to make
a difference in the world (i.e., corporate
social responsibility). Some organizations
offer employees the opportunity for paid
leave to volunteer in a community project.
in addition to benefits, organizations
are negotiating work structures to accom-
modate employees’ needs and interests,
and for the millennials this often has to do
with work–life balance issues. What nurs-
ing departments have done for years to
accommodate employees’ diverse schedul-
ing needs is now expanding across health-
care organizations. Job sharing, flexible or
remote work arrangements, special term
appointments, even seasonal months-off
programs are examples of the willingness
of organizations to customize their em-
ployees’ employment arrangements.
for millennials, this customization
also applies to career development. While
millennials are anxious to advance their
careers and eager to learn new things,
the population shift that is occurring
due to the boomers’ retirements means
organizations need to prepare millenni-
als to assume supervisory responsibility
earlier in their careers than was the case
with previous generations. Mentoring
programs (reverse, two-way, clinical),
must learn about their generational biases,
others’ preferences, and how to address
generational clash points.
Implementing Programmatic Changes
to engage employees of different genera-
tions, organizations are adopting human
resources (Hr) policies and programs that
offer flexibility and choices. for example,
while cafeteria-style benefits programs
have historically provided choices, organi-
zations are now packaging their benefits
in ways that are attractive to employees
with varying life stage
needs or interests. Scripps
Health has adopted this
life stage benefits approach
with offerings such as
training, mentoring, and
career advancement op-
portunities that are popu-
lar among millennials and
gen Xers. an assortment of work–life and
wellness programs is offered in response
to the interests of different generations.
flexible work schedules, job sharing, and
telecommuting arrangements respond to
work–life balance interests, a subject that
is particularly attractive to millennials but
also increasingly popular across the gen-
erations (aarP 2007).
caregiver benefits for elder and family
care issues are another example of orga-
nizations responding to their employees’
generational needs. While boomer and
gen X employees are dealing with the chal-
lenge of caring for their parents or grand-
parents, millennials and gen Xers run
into child care issues that distract them
from their work responsibilities. also, the
never-ending dress code issue takes on
new generational overtones as the mil-
lennials arrive in the workplace with very
informal dress code practices. in addition,
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promotional, move. therefore, a key reten-
tion strategy is to provide the opportunity
for lateral moves within your organiza-
tion when a millennial is anxious for new
learning. also, millennials are attracted
to fast-moving, technology-based envi-
ronments. remember, they grew up on
technology that produced instant results,
and they were multitaskers from an early
age. as revolutionary changes concerning
the introduction of new technologies occur
in the healthcare industry, we should be
very attractive in the eyes of millennials.
However, change comes slowly, particu-
larly in certain departments and positions,
and the enthusiasm and energy that a mil-
lennial brings to our organizations can be
quickly drained if management does not
nurture it.
as we recognize the challenge of gen-
erational differences, managers will need
to address these new issues. learning how
to manage a multigenerational workforce
is minimally, if at all, addressed in current
educational programs. therefore, managers
need on-the-job training and self-learning
to be able to recognize and respond to the
different needs and interests of today’s
multigenerational workforce. Perhaps the
most basic issue concerns communica-
tion. communication is often taken for
granted if the other individual looks like
you and talks like you. However, different
generations use language differently. they
may look like you, talk like you, and sound
like you, but their meaning can be very dif-
ferent. as managers, we need to appreciate
how individuals use the english language
differently and facilitate conversations that
build collaborative engagement and action
to achieve our organizational objectives.
think of the word work. Work means dif-
ferent things to different people. addi-
tionally, millennials frequently use a very
internships, rotational training, and other
fast-track-to-management programs are
examples of actions that organizations are
taking to prepare millennials for career
advancement.
in addition to these selective career
advancement programs, organizations
are responding to millennials’ general
need for social support as they transition
from school to workplace by providing
social networking forums. Young pro-
fessional networks, regional millennial
councils, emerging leaders organiza-
tions, and cross-generational councils are
examples of forums that provide young
employees with the opportunity not only
to collectively support each other but
also to engage in fun activities, which
is another millennial expectation. in-
novation groups are another idea that
some organizations have introduced to
engage millennials in meaningful work
that capitalizes on their new energy and
their entrepreneurial spirit. a caution-
ary note, however, is that millennials
expect that organizations are interested
in their ideas, so if you invite millennials
to speak, be sure to listen to them or risk
increasing millennial turnover.
turnover is already a concern with
the millennial generation. in fact, a new
term was created to describe this prob-
lem: retention deficit disorder (Johnson
and lopes 2008). While it is too early to
identify definitively what might lead mil-
lennials to remain at an organization, the
organizational actions noted above are
expected to contribute to better results. ad-
ditionally, millennials like to continually
learn. if they find another organization
that offers them a better learning experi-
ence, they are likely to leave your organiza-
tion. interestingly, when these departures
occur, they are typically a lateral, not a
Terrence F. Cahill, EdD, FACHE, and Mona Sedrak, PhD, PA • 13
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14 • f r o n t i e r s o f h e a l t h s e r v i c e s m a n a g e m e n t 2 9 : 1
Managers’ performance
management assessments
should include evaluation
of their talent management
skills, and appropriate
rewards or consequences
should be provided.
yet to arrive at a clear understanding of
what it takes to be a successful leader in
this new environment. We believe that
due to generational differences, no single
answer or approach will be successful,
and we accept that this makes the job of
managers more complex and challenging.
While we have provided many examples
of tactics that organizations are utilizing
to address generational challenges, par-
ticularly as related to millennials, there
is no doubt that we have much to learn
concerning this matter. We have focused
on generational differences as the basis for
learning how to be successful leaders of a
multigenerational workforce. others argue
that a better approach is to understand
what we have in common, such as the
need for respect and success (Deal 2007).
We suspect that a combination of both
lines of thinking will ultimately help us to
better understand this subject.
in closing, we note that healthcare or-
ganizations have adopted patient-centered
care as the only way that care should be
delivered. to support this philosophy, a
complementary philosophy is necessary:
an employee-centered framework. While
this is not a new concept (remember the
upside-down pyramid?), we offer a new
lens, generational differences, as a means
for noticing and addressing information
that may help us become more employee
centered and better leaders of a multigen-
erational workforce.
References
aarP. 2007. Leading a Multigenerational
Workforce. Washington, Dc: aarP.
alessandra, t. 1994. “the Platinum rule.”
Leadership Excellence 11 (5): 12.
american Hospital association’s 2009
long-range Policy committee. 2010.
Workforce 2015: Strategy Trumps Shortages.
chicago: american Hospital association.
informal communication style, and this
can irritate others, resulting in employee
tensions. Managers who are sensitive to
this issue can help employees understand
others’ communication styles and negoti-
ate reasonable solutions to avoid tensions.
in the process, managers help employees
achieve a common understanding of the
communication rules of the department or
organization.
as noted earlier, the generations have
different preferences concerning the
frequency and style of feedback. Manag-
ers who understand these
preferences will be more
effective in engaging and
guiding their employees
in the accomplishment
of their organization’s
objectives.
While sensitivity to em-
ployees’ needs is not a new
concept, we believe it fair
to say that historically this
was regarded as a soft objective and was
too often passed over in favor of attending
to more bottom-line results. However, in
the current workforce transition, inatten-
tion to millennials’ turnover represents a
real threat to organizations. the predicted
workforce shortages are considerably more
threatening than the ones we have experi-
enced in the past. for organizations to suc-
ceed, managers must be accountable for
maintaining and developing their employ-
ees. Managers’ performance management
assessments should include evaluation of
their talent management skills, and ap-
propriate rewards or consequences should
be provided.
Conclusions
We are living through the transition to a
multigenerational workforce, and we have
Frontiers_29_1Fall.indd 14 8/15/12 4:13 PM
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Clearance Center at www.copyright.com.
For reprints, please contact HAP1@ache.org.
f
e
a
t
u
r
e
Mcarthur, J. 2009. “gen Y Working Model.”
Intheblack 79 (10): 52.
Meister, J. c., and K. Willyerd. 2010. The
2020 Workplace: How Innovative Compa-
nies Attract, Develop, and Keep Tomorrow’s
Employees Today. new York: Harper
collins.
Merriam-Webster inc. 2011. Merriam-Web-
ster’s Collegiate Dictionary, 11th edition.
Springfield, Ma: Merriam-Webster inc.
Smith, S. 2008. Decoding Generational
Differences: Fact, Fiction . . . or Should We
Just Get Back to Work? new York: Deloitte
Development llc.
taylor, P., and S. Keeter. 2010. Millennials: A
Portrait of Generation Next. Washington,
Dc: Pew research center.
Burke, M. e. 2004. Generational Differences:
Survey Report. alexandria, va: Society for
Human resource Management.
collins, J. 2001. Good to Great. new York:
Harper Business.
Deal, J. J. 2007. Retiring the Generation Gap.
San francisco: Jossey-Bass.
goleman, D. 2006. Emotional Intelligence.
new York: Bantam Dell.
integrated Healthcare Strategies. 2007. The
Multigenerational Workplace: Strategies
and Solutions for Healthcare Employers.
Minneapolis, Mn: integrated Healthcare
Strategies.
Johnson, J., and J. lopes. 2008. “the
intergenerational Workforce, revisited.”
Organization Development Journal 26 (1):
31–36.
Terrence F. Cahill, EdD, FACHE, and Mona Sedrak, PhD, PA • 15
Frontiers_29_1Fall.indd 15 8/15/12 4:13 PM
Photocopying or distributing this PDF
is prohibited without the permission of Health
Administration Press, Chicago, Illinois.
For permission, please contact the Copyright
Clearance Center at www.copyright.com.
For reprints, please contact HAP1@ache.org.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
V O L . 1 0 2 ■ N O . 1 ■ 2 0 1 0 J F C S 7 3
Nearly 3,000 adults were surveyed on aspects of
everyday life with comparisons among four age
subgroups (18–29, 30–49, 50–64, 65+ years) as to
expectations of the three younger groups and the
actual experiences of the older group. The
younger groups expect that the negative bench-
marks of aging (i.e., memory loss, inability to
drive, struggles with loneliness, illness) will be
part of their later lives more frequently than is the
reality as reported by the actual experiences of the
older group. For example, 57% of the younger
group (n � 1,631) expected memory loss while
only 25% of those 65+ reported actual memory
loss (n � 1,332)—this was the largest gap. As to
the benefits of aging, the largest gaps between
expectations were for doing volunteer work (80%
expected to do it, 52% were actually doing it),
travel (77% expected to do more traveling while
52% were), and having a second career (expected
by 39% while being experienced by 14%). The
older group identified spending more time with
family and grandchildren as the best benefit.
To counter the challenge that the older group
does not represent those who are in care settings
or who cannot participate in a 20-minute survey,
adult children were asked about the current situa-
tions of their parents. This was to provide a pro-
file of the oldest group—it was not to match
responses of adult children to those of their par-
ents. For those 65–74, the perceptions of this age
cohort and of adult children were not significantly
different—8% in each group indicated help was
needed in handling their affairs. The percentages
increased as did the gap between the age cohorts
and the reporting of adult children with the 75–84
and 85+ age groups.
The major trends examined included percep-
tions of old age, daily lives of older Americans,
family and friends, intergenerational relations
within families (time and other intergenerational
exchanges), and work and retirement. Each of
these topics gives important perspectives on the
adult population and suggests that some of the
commonly held perspectives may be myths. FCS
professionals should review this report whether to
understand the characteristics of the age groups
worked with or to explore dynamics within one’s
own family and workplace.
Explorations of social trends are frequently
reported by the Pew Research Center (http://
pewsocialtrends.org) after surveying a wide spec-
trum of the population and examining databases.
In 2009, they issued more than 20 trend reports,
many that addressed trends on topics highly
relevant to FCS such as family, employment, the
generations, and economic impact. Reports in
2010 have looked at the Millennial Generation
in relation to confidence, connectedness, change,
and the new economics of marriage. Two recent
reports are included here.
I
N
B
R
I
E
F
The Return of the Multi-Generational Family
Household (March 2010)
This report uses data from the previous one as
well as from the U.S. Census Bureau American
Community Surveys (2006, 2007, and 2008).
Compared to 1980 when 28 million or 12% of the
population was living in multi-generational family
households, in 2008, 49 million or 16% of the
population are in multi-generational households.
This is a reversal of a trend that had peaked in
1940 when 25% of Americans were in such
households. Multi-generational family households
are those with two or more generations of adults
and also the “skipped generations”—grandparents
and grand children (who may be adults) without
the parental generation.
Growing Old in America: Expectations vs.
Reality (June 2009)
JFCS-102-1-15-InBrief_100020.qxp 4/30/10 1:05 PM Page 73
With the current focus on health care policy, the
local picture may get less attention. The Robert
Wood Johnson Foundation and the University of
Wisconsin Population Health Institute have col-
laborated to evaluate health status by county in a
project to “mobilize action toward community
health” www.countyhealthrankings.org/). What is
the rank of your county, as to health outcomes
and health factors, in your state? Higher ranks
indicate the healthiest counties.
Health outcomes are measures of length of life
(premature deaths before age 75) and quality of
life (overall health, physical and mental health,
and birth outcomes). Health factors include meas-
ures in four areas. Health behaviors include diet
and exercise, tobacco use, alcohol use, and unsafe
sex (30% of the score). Quality and access to
health care are the factor of clinical care (20% of
the score). The social and economic factors
include education, employment income, family
and social support, and community safety (40%).
The fourth factor is the physical environment
including environmental quality and the built
environment (10%).
This website includes tables and graphics of
each state providing visuals for easy comparisons.
In addition, there is a library of nearly 80 pro-
grams and policies that work locally. These vary
from limiting access to non-nutritious foods in
school to expansion of child development pro-
grams to pedestrian/bicycle plans.
To illustrate two counties AAFCS can identify
with—AAFCS headquarters is in Fairfax County
Virginia, the county ranks 1st of 132 counties for
health outcomes and 7th of 132 for health factors in
Virginia. With the upcoming AAFCS Conference
and Expo in Cleveland, OH, we find that Cuya-
hoga County ranks 77th of 88 for health outcomes
and 47th of 88 for health factors. An observation:
counties with large cities seem to rank lower than
areas of lesser population density as in Colorado,
the County of Denver (also the city) ranked 47th on
outcomes and 50th on factors of 56 counties (data
were not available for 8 other counties).
What explains changes in the trend? Growing
numbers of immigrants (primarily Latin Ameri-
cans and Asians), increasing median age at first
marriage (5 years older than in 1970), and more
recently high unemployment and foreclosure
rates. One of 5 adults in the age groups 25–34
(more men than women) and 65 and older (more
women than men) live in multi-generational family
households. At the same time, there are more sin-
gle person households (10.3% in 2008) with 27%
of those 65 and over living in single person house-
holds (this peaked at 29% in 1990).
This report suggests the importance of consid-
ering the variety of family household types that we
have in society and work with on a daily basis.
With multi-generational and one person house-
holds accounting for 1 in 4 households, there are
also two generations—parent(s) and children,
married and cohabiting couples, and unrelated
person households.
County Health Rankings
7 4 V O L . 1 0 2 ■ N O . 1 ■ 2 0 1 0 J F C S
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