Families are important. Family background shapes health and economic outcomes throughout life. In our modern society, families are still the central organizing unit for economic support and for providing care for those physically unable to care for themselves. Understanding families, and how individuals and families change with age, has been a central concern behind the design of the Health and Retirement Study.
The HRS provides uniquely detailed data on sharing, or "transfers," of time and help, money, and dwellings across generations within families. These data permit analysts to examine how family needs and obligations affect health and retirement decisions and the well-being of Americans as they age. In the long run, the HRS data will be important for determining the extent to which financial transfers to relatives boost or curtail savings for retirement, the links between parental support to children and future assistance from those children, and the links between help from children and the transfer of assets through bequests.
Family structure has been an important area of interest for researchers examining data gathered through the HRS. Much of this work to date pertains to the role in life that people assume (e.g., whether one is married, has children, or cares for grandchildren), although some studies have dealt with transitions between roles, such as from marriage to widowhood. Other studies have considered links between family structure and living arrangements (e.g., the effects of family structure on the probability of nursing home admission), family and health, and the family and economic realms.
This chapter summarizes some of the research that has used HRS data to study family characteristics and intergenerational transfers. Topics discussed include HRS participants' living situations; the relationships of living arrangements, marriage, and childlessness to health; the impact of multiple life roles on well-being; bequests; and the extent of intergenerational sharing of time, money, and co-residence.
The HRS tells us that people over 50 are not generally dependent on their families. Rather, on average, they provide significant economic help to their children and grandchildren. The HRS tells us that:
In 2002, a large majority of HRS participants (79 percent) lived in a dwelling that they owned. Although the rate of home ownership declined with age (Figure 4-1), more than half of people age 85 and older resided in homes they owned. One in eight HRS participants lived in rental housing. The proportion of people living in nursing homes or assisted living facilities was very low among those ages 55 to 74, rising to 7 percent among the 75 to 84 age group and then more steeply to nearly 20 percent among those age 85 and older.
|Nursing Home/Retirement Community||1.6||3.6||6.8||19.7|
HRS data have been used to probe the links between living arrangements and measures of physical, cognitive, and emotional well-being in late midlife. Married couples living alone or with children have been shown to have the highest levels of functioning, whereas single adults living in "complex" households (e.g., unmarried people living with others) have the lowest levels of functioning. Relative functional deficits for those living in complex households were reduced, but not eliminated, when demographic characteristics and household resources and demands were taken into account (Waite and Hughes 1999; Hughes and Waite 2002).
Figure 4-2 shows proportions of HRS participants with different combinations of living close relatives. In 2002, about 45 percent of participants ages 55 to 64 had a partner, parent or parent-in-law, and at least one child who was living. This percentage dropped sharply in the older age groups. Nearly 70 percent of the youngest participants had both a partner and child(ren) who were living. Among participants age 85 and older, less than one-fifth had both a partner and child(ren). The percentage of people with at least one living child was high and fairly consistent across age groups. Figure 4-2 appears to indicate declining numbers of close living family members as age increases, but it should be noted that the loss of parents and spouses is often numerically compensated by children and grandchildren. Nevertheless, a substantial proportion of single men are childless; as they age, these men may have only their own resources and public programs to rely on for financial and other support.
|Partner, Parent(s) and Child(ren)||44.5||16.8||3.7||2.2|
|Partner and child(ren)||68.5||63.5||46.2||23.4|
|Partner and Parent(s)||46.1||17.4||4.0||2.2|
(Note: Parents include parents-in-law.)
Marital status has clear effects on the mental health of older people. A comparison of married and unmarried HRS participants of all ages found that married women were less likely than their unmarried counterparts to report symptoms of depression, and that the mental health benefits of marriage were even greater for men than for women (Earle et al. 1998).
Turvey et al. (1999) found a strong association between the loss of a spouse and both syndromal depression and depressive symptoms among adults age 70 and older. Controlling for pre-loss depressive symptoms, the researchers found that the rate of syndromal depression among people who were newly bereaved was nearly nine times as high, and the rate of depressive symptoms was nearly four times as high, as the rates for married individuals. Some widows and widowers experienced high levels of depressive symptoms up to 2 years after the loss of their spouses. Neither demographic variables nor variables concerning the nature of the spouse's death predicted the level of bereavement-related depression.
Another study brought a "couples perspective" to the analysis of depressive symptoms in middle-aged and older adults. Townsend et al. (2001) found that husbands' and wives' depressive symptoms were moderately correlated, with the symptom level of one spouse explaining approximately one-fourth of the variance in the other spouse's level. The study also found that net worth was an independent predictor of depressive symptoms after controlling for income and other factors.
A study using AHEAD data focused further attention on the possible additional negative effects of childlessness on psychological well-being (Zhang and Hayward 2001). Two dimensions of well-being-loneliness and depression-were considered, and the findings identified prominent gender differences. Divorced, widowed, and never-married childless men had significantly higher rates of loneliness compared with women in similar circumstances. Divorced and widowed childless men also had significantly higher rates of depression than their female counterparts. Given that men, who are much more likely to be married than women at older ages, generally show lower rates of depression than women, these findings warrant additional analyses to provide insights into the role of family connections in the mental well-being of men and women.
HRS data have also been used to evaluate the relationship between marital status and major chronic illnesses, functional limitations, and disability. Findings from one study (Pienta et al. 2000) suggest that marriage conveys health advantages across a broad spectrum of chronic disease conditions, functional problems, and disabilities, and that these advantages are widely shared across demographic groups (men and women, Whites and Blacks, and groups defined by duration of marriage). A limitation of this cross-sectional analysis was the inability to assess whether the observed correlation of marriage and good health occurs because marriage itself promotes health, or whether the healthy are more likely to be married (or remarried). With HRS longitudinal data on health and marriage, it will be possible to distinguish between these explanations.
Chapter 3 describes the relationship between current marital status and wealth. Retrospective first-wave data also have documented links between marital histories and economic well-being (Holden and Kuo 1996). In more than one-third of all married-couple households in 1992, at least one spouse had a previous marriage that ended in divorce or widowhood. These respondents who had experienced divorce or widowhood had significantly lower incomes and fewer assets than did couples in first marriages. The researchers found that widows and couples in which the prior marriage of one spouse had ended in widowhood were no better off economically than their divorced peers. Also, women and Blacks in the original 1992 HRS cohort (ages 51 to 61) had spent a higher percentage of their lifetimes outside of marriage than had men and Whites. The study raises important questions about the long-term economic consequences of past marital dissolution.
In a related vein, Angel et al. (2003) used five waves of the HRS to assess the economic consequences of marital disruption for pre-retirement-age women. Prior research has shown that a woman's financial situation in later life is determined by her marital and work history. HRS women who were age 51 or older in 1992 grew up during a period when female employment rates and rates of marital disruption both increased substantially. For HRS women generally, marital disruption results in a substantial loss of both income and assets. The economic consequences are greatest for Black and Hispanic women, who have lower household incomes and fewer assets even when married.
While family connections enhance well-being in many ways, the burden of family roles can also be a strain, especially when one person takes on multiple roles. Several researchers have examined the link between performing multiple family roles and well-being. One study using 1992 data evaluated depressive symptoms associated with the roles of wife, mother, paid worker, and informal caregiver for women (Reid and Hardy 1999). The study also assessed role demands and satisfaction. Although the number of roles was linked with depressive symptoms, the number had no significant effect after controlling for role demand and satisfaction. In other words, role quality, not role occupancy per se, is linked with psychological well-being.
Another study brought a racial perspective to the analysis of multiple-role participation and depressive symptoms (Cochran et al. 1999). Among women ages 55 to 61, Blacks were less likely than White women to be married and employed, and more likely to be grandmothers and caregivers. Older Black women reported significantly more depressive symptoms than did White women, and employment was found to have a more powerful influence on diminishing depressive symptoms for Black women than for White women. The research also suggested that in the absence of a spouse and/or employment, Black women who are caregivers and grandmothers may be more likely to face economic hardship that increases the likelihood of depressive symptoms.
There is considerable controversy about the current and future importance of bequests in our society. Some argue that baby boomers are likely to receive large estates from their parents who have had relatively high lifetime incomes and have benefited from stock market gains. Others argue that the role of bequests in strengthening intergenerational relationships and contributing to future well-being of kin has been overstated.
In order to understand the role of bequests, the HRS acquires two distinct types of information about them. From living respondents, it asks whether they themselves have received bequests, as well as their expectations to receive them in the future and to leave them to their own heirs. Following the death of a respondent, a special interview is conducted with a knowledgeable proxy (often a surviving spouse or child) to obtain information about the last years of life and about the distribution of the estate. Thus, in a longitudinal setting, it becomes possible over time to see how well plans and expectations are carried out after death.
To develop a new method for estimating the magnitude of future bequests, a group of researchers (Smith and Hurd 2002) combined HRS data on current wealth and self-reported probabilities of bequests with actual bequests (from proxy interviews for a sample of HRS participants who died between 1992 and 1998). The researchers were especially interested to learn whether expected bequests differed greatly across cohorts, if bequests were distributed evenly among children, and the extent to which older households spend (or "dissave") in order to finance their own consumption in older age.
The study resulted in three major conclusions. First, the distribution of bequests, like the distribution of wealth, is highly skewed. The typical baby boom child of an older HRS respondent can expect only a modest inheritance, and approximately 20 percent will not receive any bequest from their parents. The median bequest that children of HRS participants in the oldest cohort (born in 1923 or earlier) are likely to receive is about $8,000, while the median bequest that children of HRS participants born between 1942 and 1947 can expect to receive is $19,200.
Second, there is considerable inequality in the estimates of expected bequests. Table 4-1 shows expected bequests from four different parent cohorts according to selected wealth percentiles. Among parents who were born between 1942 and 1947, those in the 10th percentile of wealth do not expect to leave any bequests to their children. Parents in the 25th percentile will leave relatively small bequests of approximately $3,000 per child. Parents in the 90th percentile, however, will leave $187,000 per child, and those in the 95th percentile will bequeath more than twice that amount ($382,000). The distribution of bequests reflects the highly skewed distribution of wealth mentioned in Chapter 3, as well as the tendency of the wealthy to have fewer children than those with lower wealth levels.
|Years of Birth:||-1923||1924-1930||1931-1941||1942-1947|
|Average number of children in family||2.8||3.2||3.3||2.6|
|Average inheritance per child||47,000||45,000||70,000||86,000|
Source: Smith and Hurd 2002
Third, the study found very minor differences in the size of expected bequests for the two oldest parent cohorts (those born in 1930 or earlier), but an increasing magnitude of expected bequests among younger parent cohorts.
Based on proxy interviews about deceased HRS participants, the study also discovered that about 90 percent of financial inheritances are bequeathed to immediate family members. In multiple-child families, four out of five parents give equal inheritances to each child if there is no surviving spouse. Finally, the study found clear evidence that people in HRS households intend to spend a large portion of their savings during older age. On average, households of participants ages 70 to 74 will likely spend more than 60 percent of their current assets, leaving the remainder as bequests.
Intergenerational sharing, or transfers, can be grouped into three main categories: time, money, and co-residence. Figure 4-3 presents the overall pattern of transfers between HRS parents (unmarried versus married) and their children in 2002, that is, whether there are any exchanges and, if so, in which direction they flow. Sizable proportions of HRS parents-about one-third of married and 40 percent of unmarried participants-neither give nor receive time, money or co-residence. Married parents, especially those over age 64, are more likely to give but not receive transfers.
|Neither Give Nor Receive||33.0||42.7||42.1|
|Give and Receive||40.8||31.2||28.0|
|Neither Give Nor Receive||22.6||36.9||49.9|
|Give and Receive||42.2||22.0||14.8|
Note: Data may not sum to 100% due to rounding.
One would expect that disability among HRS participants would correlate with assistance from their children. Figure 4-4 contrasts intergenerational transfers from adult children to their parents who have activity of daily living (ADL) limitations (i.e., disability) with transfers to non-limited parents. In 2002, regardless of ADL limitations, single HRS participants were more likely than married parents to receive help from their children across all transfer dimensions. Parents with ADL limitations were somewhat more likely than non-limited parents to receive money from a child, but this form of transfer was uncommon.
|Time (From children only)||13.8||36.6|
|Time (Children and/or Other)||51.2||54.8|
|Time (From children only)||0.6||3.6|
|Time (Children and/or Other)||2.7||4.7|
Notes: "Other" includes grandchildren, spouse if married, and paid home help. Co-residence may be with a child or another person. ADL limitation refers to problems with one or more activities of daily living.
Transfers of time were much more important to disabled parents. Households in which a parent had an ADL limitation were 10 times more likely than non-limited households to receive help (i.e., time) from their children, and even more so when grandchildren, other relatives, and paid home help were factored in. Roughly 4 in 10 unmarried parents with ADL limitations, compared with 1 in 7 married parents with ADL limitations, received time help from a child. When assistance from others was added to that from children, more than half of unmarried and married people received help in the form of time.
A natural follow-on issue relates to the effectiveness of assistance that children provide. HRS data from the mid-1990s indicate that the receipt of regular ADL assistance from children significantly reduced the likelihood of a parent having to enter a nursing home (Lo Sasso and Johnson 2002). Disabled individuals age 70 and older were 60 percent less likely to experience nursing home care if they received help from a child in the form of basic personal care all or most of the time, compared with those who did not receive such help.
Disability and care are not static, as the ability to provide care and the need for care change often. Freedman et al. (2004) used data for unmarried participants age 70 and older to examine how care requirements change over time. The study found that both paid and unpaid care hours received by older, unmarried, community-dwelling participants increased during the 1990s. However, trends in care hours differed according to shifts in ADLs versus instrumental activities of daily living (IADLs). Responses to ADL changes were fairly symmetric, in that care hours increased as disability worsened and decreased as people recovered function. With IADLs, both paid and unpaid care hours increased with the number of IADL limitations, but paid hours (and, to a lesser extent, unpaid care hours) did not decrease as IADLs improved.
Another factor in the care equation is the policy and service environment surrounding the provision of long-term care. The Federal-State Medicaid program funds the largest share of formal long-term care services, but individual States determine their own eligibility criteria, payment levels, and other program characteristics. One examination of HRS results suggested that in States with strong commitments to home- and community-based services, older adults who needed help with one or more ADLs were more likely to receive services that allowed them to remain in the community rather than entering nursing homes (Muramatsu et al. 2004). Therefore, the researchers concluded, although family resources and caregiving are still paramount in determining long-term care use, the effect of these resources on nursing home admission depends on the long-term care context of one's State of residence.
Research using HRS data has shown that a child's financial situation affects parents' decisions about whether or not to give money to their children-and how much to give. In 2002, participants were asked if they had given $500 or more to any of their children during the prior two years. More than one-third (36 percent) of participants said they had. The likelihood of giving money to children decreases as the age of parents increases (Figure 4-5); 43 percent of parents ages 55 to 64, compared with 24 percent of parents age 85 and older, provided such financial support.
Note: Age for households with couples is based on the man's age.
The amount parents give to their children varies by the children's financial situations. Analysis of data for participants age 70 and older indicated that parents were more likely to give money to children in lower versus higher income brackets (McGarry and Schoeni 1997). Adult children in the lowest income category were 50 percent more likely to receive a financial transfer from their parents, and on average received $300 more than their siblings who were in the highest income categories. The researchers also found other factors that influenced parents' decisions: parents were more likely to give to younger children than older children; less likely to give money to children who were married, had children of their own, or owned their own homes; and more likely to give to children who lived within 10 miles of their parents or who had less education.
Geographic proximity of older parents to adult children is related to opportunities for intergenerational transfers. In 2002, 11 percent of HRS participants' households included a resident child of the participant, and 51 percent of households had at least one child living within 10 miles. Figure 4-6 shows fairly small differences by age of HRS participant. There is an increase with age in the percent without living children, and a notable decline in the proportion with resident children at ages 65 to 74 compared with ages 55 to 64.
|Within 10 miles||48.4||55.0||53.6||49.8|
|Beyond 10 miles||28.6||30.4||30.4||27.3|
Note: Data may not sum to 100% due to rounding.
Intergenerational transfers and help from children are related because families engage in a web of transfers that encourage reciprocity. Sociologists and economists who have examined this issue hypothesize that past assistance to family members encourages immediate or future repayment of assistance. Henretta et al. (1997) examined this issue among unmarried HRS participants with a need for personal care and more than one child. They found a substantial relationship between financial help from a parent to a particular child and later help from that child to the parent. Among children who received large money gifts from a parent in the past, nearly 50 percent were providing financial help to the parent, compared with slightly more than one-fourth of their siblings who had not received gifts. These findings are consistent with the reciprocity hypothesis.
Transfers flow not only to and from HRS participants and their children and grandchildren, but also in many cases, from the participants to their own parents. Table 4-2 presents the pattern of such transfers from HRS participants under the age of 80. In 2002, nearly 7 in 10 HRS participants under age 65 with living parents gave no assistance in the form of money or help with care or chores to their parents. Fifteen percent of HRS participants under age 65 helped their parents with chores only, and about 11 percent made monetary transfers (either only money or money in conjunction with other forms of assistance). HRS participants age 65 and older were slightly less likely than younger participants to provide most forms of assistance to their parents, and three-fourths of the older participants provided no assistance to their very old parents.
|Hours of care only||1.5||1.9|
|Chore hours only||14.6||12.0|
|Care and chores||3.8||3.1|
|Money and care||0.5||0.9|
|Money and chores||2.9||1.9|
|Money, care and chores||1.7||1.4|
The family traditionally has been the leading source of care for its older members, but as fertility rates decline and more women participate in the formal labor market, we might anticipate greater tension between workforce demands and parental care needs. Analyses of HRS data from the mid-1990s suggest that devoting time to informal care of older parents may indeed be incompatible with having a full-time job during midlife (Johnson and Lo Sasso 2000, 2001). The studies found that women who provided an average of 2 or more hours per week of parental help (with either ADLs or IADLs) worked 43 percent fewer hours than women overall. For men providing similar care, the reduction in hours of paid work was about 28 percent. Women ages 53 to 63 who helped their parents with personal care reduced their hours of paid work by about 70 percent. These findings suggest the need for further research to look at family responsibilities as a major obstacle to encouraging workers to delay retirement, as well as the need to develop accurate estimates of the financial costs incurred by families who provide informal care.
Medical and workforce costs associated with certain diseases were discussed in Chapters 1 and 2. HRS data may also be used to generate national estimates of the costs of informal caregiving (by family and friends) to people with chronic health conditions. Figure 4-7 shows one set of estimates for five different conditions, four of which cost at least $6 billion annually and one of which-dementia-costs $18 billion annually in informal caregiving.
Source: Langa and colleagues, various reports 2000-2004.
Looking at people age 70 and older in the 1990s, researchers found that those with mild dementia received 8.5 more hours of care per week and those with severe dementia received 41.5 more hours of care per week than that received by elders with normal cognitive function (Langa et al. 2001). To estimate the yearly costs of caring for older family members with dementia, the researchers adjusted the number of hours of reported care to account for chronic health conditions other than dementia (and for other factors). They then multiplied the results by the 1998 national average wage for a home health aide of $8.20 per hour, and estimated that the yearly cost for dementia at the national level was $18 billion for informal caregiving alone, in addition to direct and indirect costs of dementia in the United States. This finding underscores the importance of including valid estimates of unpaid caregiver time when evaluating future clinical and policy interventions aimed at reducing the impact of dementia on individuals, families, and society.
The main alternative to informal family-based care is paid care either in the home or in a nursing home. Long-term care insurance can help cover such costs, but it is purchased by relatively few older adults. One question that arises is whether or not the expectation of care from children is a factor reducing the demand for long-term care insurance. One study using HRS data found that expectations about future caregiver availability in the form of family and friends had no significant effect on ownership of long-term care insurance (Mellor 2001).
Descriptive studies from several datasets have indicated the growing importance of the grandparent-grandchild care relationship. However, few surveys are large enough to explore this relationship in any detail. Early HRS results showed that roughly two-thirds of participants had grandchildren, and that 40 percent of these grandparents provided 100 or more hours of grandchild care per year. Women were about 2.5 times more likely than men to provide grandchild care, and single grandmothers provided the most help (about 20 hours per week on average).Hughes et al. (2004) used six waves of HRS data to examine different types of grandparent caregiving and changes in caregiver health. The researchers distinguished between grandparents who provided care to grandchildren who did not live with them and those whose grandchildren lived with them. They determined that grandparents who provided a considerable amount of care to non-resident grandchildren did so because of desire and resources, while grandparents who co-resided with grandchildren often did so because some family crisis had made this a necessity. The study found that co-residence with grandparents is relatively uncommon. In 1998, for example, only 5 percent of HRS participants lived with grandchildren, mostly in three-generation households.
HRS data consistently show that grandparents who provide little if any direct care to their grandchildren are in better health than those who do provide care, especially compared with those who live with their grandchildren. This relationship holds true for both self-rated health and number of depressive symptoms (Figure 4-8). However, few changes in health were found over time among the different groups. The researchers conclude that differences in the physical or emotional health of grandparent caregivers are a function of the underlying characteristics that lead them to provide care, rather than negative health effects due to providing care.
|Self-Rated Health||No. of Depressive Symptoms|
|Living with Child & Grandchild||2.96||1.98|
|Living with Grandchild Only||2.84||2.14|
Notes: Self-rated health is assessed on a 5-point scale ranging from excellent (5) to poor (0). Data refer to persons who made the transition to a type of care between 1998 and 2000 and/or between 2000 and 2002.
Source: Hughes et al. 2004.