Multiple Family Member Deaths and Cardiometabolic Health among Black and White Older Adults

Abstract

Although the bereavement literature is voluminous, we know very little about how exposure to multiple family member deaths across the life course shapes health trajectories as people age and whether unequal exposure to bereavement contributes to racial inequities in cardiometabolic health. We use longitudinal data from the Health and Retirement Study (1992–2016) to consider how multiple family member deaths before midlife shape trajectories of cardiometabolic health after age 50 for Black and white adults (n = 22,974). Results show that multiple family member deaths prior to age 50 are associated with more cardiometabolic conditions at age 50 and a faster increase in conditions with advancing age. Moreover, Black adults are significantly disadvantaged by a greater risk of bereavement and more cardiometabolic conditions regardless of bereavement status. The life course trauma of exposure to multiple family member deaths uniquely contributes to the cardiometabolic risk of Black Americans.

Keywords

bereavement cardiometabolic health race racial disadvantage stress

The death of a loved one is a uniquely distressing event, and an extensive literature shows that bereavement increases the risk of poor health (Buckley et al. 2010; Stroebe, Schut, and Stroebe 2007; Umberson 2017). Moreover, prior research suggests that family member deaths experienced earlier in the life course may have long-term consequences for health (e.g., Maier and Lachman 2000; Norton et al. 2009; Shonkoff et al. 2012; Smith and Hanson 2015; Stroebe et al. 2007). However, much of what we know about bereavement ignores a stark racial disparity in the United States, wherein Black Americans are much more likely than white Americans to experience the death of multiple family members over their life span (Umberson et al. 2017). We suggest that exposure to the death of multiple family members before midlife, which unequally burdens Black families, will have adverse consequences for cardiometabolic health in mid to later life. Prior research has not considered the possibility that this specific type of life course trauma—multiple family member deaths—uniquely contributes to the high levels of cardiometabolic risk of Black Americans.

Cardiometabolic conditions such as cardiovascular disease, diabetes, and stroke are several of the leading causes of death in the United States (Kochanek, Xu, and Arias 2020). Moreover, Black adults are more likely than white adults to develop cardiometabolic conditions, to develop these conditions earlier in life, and to experience more severe forms of disease (e.g., Bibbins-Domingo et al. 2009; Mitchell et al. 2019; Williams et al. 2010). For example, incident heart failure before age 50 is substantially more likely for Black adults compared to white adults (Bibbins-Domingo et al. 2009). As such, we analyze longitudinal data from the Health and Retirement Study (HRS; 1992–2016) to consider how experiencing multiple family member deaths across the life course adversely impacts cardiometabolic health. Guided by a stress and life course perspective (Pearlin et al. 2005), we suggest that the death of a family member is a significant life course stressor and that multiple family member deaths represent a unique kind of life course trauma that adds to the cumulative burden of stress over the life course. We primarily focus on how multiple family member deaths prior to midlife may launch a trajectory of declining cardiometabolic health because each death may add to an accumulation of stress and health-harming risk factors over time (Umberson 2017). Although the present study is focused primarily on deaths prior to midlife, we also consider how additional family member deaths after midlife may add to the toll of bereavement and further undermine the cardiometabolic health of aging adults.

We extend past bereavement research in at least two ways. First, we examine how multiple family member deaths shape long-term trajectories of cardiovascular health among aging adults. Although understanding the health consequences of specific family member deaths, such as the death of a spouse or child, is crucial, we emphasize the importance of understanding how multiple family member deaths throughout life take a cumulative toll on health and health trajectories—a process that has not been tested in prior research. The present study, then, applies a stress and life course perspective to test the accumulation of stress and risk factors over time. Findings from the present study can inform future research on racial inequities in health and mortality by pointing to the importance of repeated life course bereavement events. Second, we underscore the racial context of bereavement in the United States, wherein Black adults experience an unequal burden of family deaths (Umberson et al. 2017) and inequities in cardiometabolic health (Bibbins-Domingo et al. 2009; Mitchell et al. 2019; Williams et al. 2010). Whereas recent research documents that unequal exposure to bereavement contributes to racial disadvantage in psychological distress (Umberson and Donnelly 2021), dementia (Cha, Thomas, and Umberson 2021; Liu, Lin, and Umberson 2022; Umberson et al. 2020), and mortality risk (Donnelly et al. 2020; Liu, Umberson, and Xu 2020), we extend prior research by examining the health consequences of racial inequities in exposure to multiple family member deaths across the life course. Therefore, the present study emphasizes that differential exposure to repeated bereavement events across the life course may contribute to racial inequities in cardiometabolic health for aging adults.

Background

Theoretical Background: A Life Course Perspective for Bereavement and Health Inequalities

A stress and life course perspective (Pearlin et al. 2005; Pearlin and Skaff 1996) provides the guiding framework to understand how life course stressors such as the death of family members cascade to affect long-term health outcomes. The death of even one close family member is a stressful event that can erode health and increase risk for premature mortality (Stroebe et al. 2007). For example, prior research finds that the death of a sibling (e.g., Rostila, Saarela, and Kawachi 2012), a child (e.g., Hendrickson 2009), or a spouse (e.g., Dupre, Beck, and Meadows 2009; Shor et al. 2012) at any age undermines health and increases mortality risk. Many of these effects persist long after the death occurred (e.g., Hendrickson 2009; Norton et al. 2009; Rogers et al. 2008; Rostila et al. 2012; Smith et al. 2014; Stroebe et al. 2007), suggesting lasting health consequences of bereavement. When considering the lasting consequences of bereavement, we emphasize two tenets from the stress and life course perspective that guide the present study: The stress process can result in life-long health inequalities, and the timing and sequencing of stressful events in a person’s life matter. Taken together, this framework provides insight into how socially patterned stressors, such as racial inequities in the death of family members, produce lasting disadvantages in health long after the death of family members.

When considering the life-long consequences of stress, the stress process model emphasizes that stress tends to proliferate across the life course (Pearlin et al. 2005; Pearlin and Skaff 1996). In the context of bereavement, experiencing the death of family members can have long-term implications for health if bereavement elicits biosocial responses that act as chains of risk over the life course. Indeed, life course approaches to health tend to emphasize that stress and adversity often lead to repeated insults over time, and this accumulation of risk has significant consequences for health trajectories (e.g., Kuh et al. 2003; Miller, Chen, and Parker 2011; O’Rand and Hamil-Luker 2005; Turner and Lloyd 1995). For instance, the death of a family member may result in health-harming coping behaviors, such as self-medication with drugs and alcohol or overeating (Umberson, 2017). Because many harmful health behaviors tend to emerge early in the life course and then remain stable throughout life (Umberson, Crosnoe, and Reczek 2010), stressors that activate unhealthy behaviors earlier in the life course are likely to have long-term implications for health. Losing a family member may also trigger adverse social responses that erode health over time. The death of close family members, for example, can lead to hypervigilance in relationships, reluctance to form new relationships, and relationship strain (Rogers et al. 2008; Umberson et al. 2014), all of which have detrimental effects for health and mortality (Holt-Lunstad, Smith, and Layton 2010). Over time, these intersecting stress responses likely take a cumulative toll on health outcomes, including cardiometabolic health. Moreover, these stress processes may be reactivated with each additional death of a family member, pointing to the importance of understanding the health consequences of multiple family deaths before midlife. Racial inequities in exposure to bereavement, then, can lead to racial inequities in health through this stress proliferation process.

With respect to life course timing, a stress and life course framework posits that the timing of stressful life events is crucial for understanding the long-term consequences for health outcomes and health inequalities. When significant events occur during sensitive developmental periods in the life course, such as childhood and adolescence, they can have profound effects on health (e.g., Ben-Shlomo and Kuh 2002; Miller et al. 2011; O’Rand and Hamil-Luker 2005). For example, stressful experiences during childhood can result in biosocial disruptions that fundamentally alter trajectories of health over the life course (e.g., Miller et al. 2011; Mitchell et al. 2017; Shonkoff et al. 2012). This is clearly illustrated when considering the death of a parent in childhood and early adulthood. Prior research shows that losing a parent before age 17 results in worse health and well-being in midlife (e.g., Jacobs and Bovasso 2009; Maier and Lachman 2000) and increased mortality risk after age 65, especially for deaths related to cardiovascular disease (Smith et al. 2014). Common explanations for the lasting health consequences of early parental death center around factors such as biological dysregulation (Braveman and Barclay 2009; Shonkoff et al. 2012), the loss of household income (Mitchell et al. 2017), less educational attainment (Patterson, Verdery, and Daw 2020), and increased psychological distress (Maier and Lachman 2000). Notably, Black children are 2 to 3 times more likely than white children to lose a mother or father by age 10 (Umberson et al. 2017), and exposure to loss early in the life course likely contributes to racial inequities in health across the life course. Thus, racial inequities in exposure to bereavement early in life may contribute to cumulative disadvantage in health across the life course.

Together, these stress and life course tenets help us to understand how socially patterned variation in exposure to stress, such as the deaths of family members, creates and sustains racial inequities in health. Indeed, systemic racism fundamentally structures exposure to stress, and the accumulation of stress and adversity over the life course contributes to racial inequities in health (e.g., Boen 2020; Ferraro and Shippee 2009; Gee, Walsemann, and Brondolo 2012; Hatch 2005; O’Rand 2006; Shuey and Willson 2008). This greater burden of stress among Black adults leads to more “wear and tear” on the body, thereby accelerating physiological deterioration in health for Black adults (Geronimus et al. 2006). When considering racial inequities in exposure to the death of a family member, the process of stress proliferation can widen inequities in health that stem from the stratification of stressors (i.e., the death of family members) by race. Moreover, the greater likelihood of Black Americans to experience family member deaths earlier in the life course may have profound influences on health and launch different trajectories of health for Black adults compared to white adults. Overall, the present study situates differential exposure to bereavement, especially repeated bereavement events, as a central component in the production of racial health inequities.

Race, Multiple Family Member Deaths, and Cardiometabolic Health

Due to systemic racism that erodes health (Sternthal, Slopen, and Williams 2011; Williams, Lawrence, and Davis 2019), Black Americans experience higher mortality rates compared to white Americans at almost every age (Kochanek et al. 2020; Rogers et al. 2019). As a result, Black families are much more likely to experience the death of family members than white families, including the death of a parent, sibling, spouse, or child (Umberson et al. 2017). Moreover, Black Americans experience these losses earlier in the life course and are more likely to experience multiple family member deaths. For example, Black adults are over 3 times as likely as white adults to experience two or more family member deaths by age 30, and this disparity persists into later life (Umberson et al. 2017). The present study focuses on how exposure to multiple family member deaths by age 50 is associated with trajectories of cardiometabolic health in mid to later life, with attention to differences for Black adults and for white adults.

In the present study, we focus on cardiometabolic conditions as a crucial outcome because racial inequities in cardiometabolic conditions are extensive and well documented and widen as older adults age (Cheng et al. 2019; Mitchell et al. 2019; Virani et al. 2020). Black adults tend to develop these diseases earlier in life, experience greater disease severity, and have poorer survival outcomes compared to white adults (e.g., Bibbins-Domingo et al. 2009; Williams et al. 2010). Moreover, mortality rates for diabetes and heart disease are twice as high and 25% higher, respectively, for Black adults compared to white adults (National Center for Health Statistics 2021). Because scholars hypothesize that unequal exposure to stress across the life course contributes to racial inequalities in numerous health outcomes (e.g., Boen 2020; Gee et al. 2012; Goosby, Cheadle, and Mitchell 2018; Sternthal et al. 2011), including metabolic dysregulation (Boen 2020) and cardiometabolic conditions (Sternthal et al. 2011), we consider lifetime exposure to family member deaths as a significant stressor that is likely to have cumulative effects on the cardiometabolic health of aging Black and white adults.

Emerging research documents how race differences in exposure to specific types of bereavement add to existing racial inequities in health. For example, Black parents are much more likely than white parents to lose a child during their lifetime, and this unequal exposure to a traumatic life course stressor contributes to racial disadvantage in psychological distress (Umberson and Donnelly 2021), dementia (Umberson et al. 2020), and mortality risk (Donnelly et al. 2020) among aging parents. Compared to white adults, Black adults are also more likely to experience the death of a parent, to be widowed, and to experience a sibling death (Umberson et al. 2017). Recent research shows that these disparities contribute to the higher rates of dementia (Cha et al. 2021; Liu et al. 2022) and mortality (Liu et al. 2020) among aging Black adults.

Perhaps because even one family member death is consequential, we know much less about how exposure to multiple family deaths shapes health outcomes for Black adults and for white adults. One study found that compared to white adults, Black adults were more likely to experience two or more family member deaths prior to age 50, and this cumulative exposure to family deaths undermined subjective life expectancy—a predictor of future health and mortality—in later life (Donnelly, Umberson, and Pudrovska 2020). Another recent study found that cumulative losses by midlife were associated with a biological marker of cardiovascular risk in women, especially among Black women (Lewis et al. 2021). However, these studies did not examine how multiple family member deaths prior to midlife shaped long-term trajectories of health among aging adults and whether patterns differed by race.

Although the present study is primarily focused on the lasting consequences of bereavement prior to midlife, exposure to additional deaths in mid and later life are likely to take a further toll on health. For example, prior research documents the heightened risk of adverse health outcomes and mortality following the death of a sibling (Cha et al. 2021) or spouse (e.g., Liu et al. 2020; Shor et al. 2012) in later life. We suggest that experiencing the death of family members after midlife adds to a lifetime burden of bereavement, with adverse consequences for the health of aging adults. Notably, Black adults experience more family deaths throughout life (Umberson et al. 2017) and are therefore at greater risk of experiencing repeated effects of bereavement on health before midlife and in later life.

Because responses to stress may differ by race, health trajectories following bereavement may be different for Black and white adults. For example, Black older adults are more likely than white adults to use religion and spirituality to cope with stress (Taylor et al. 2007), and this may buffer some of the adverse consequences of bereavement. Moreover, prior research finds that Black older adults experience a greater stress burden than white adults but are less likely to appraise certain chronic stressors as upsetting (Brown, Mitchell, and Ailshire 2020). On the other hand, the environmental affordances model demonstrates that coping mechanisms that may alleviate the mental health consequences of stress (e.g., smoking, alcohol use) may contribute to disadvantages in health and mortality for Black adults (Mezuk et al. 2013). Taken together, prior research suggests that pathways linking stressful events to health may differ for Black and white older adults, necessitating an examination of whether associations between multiple family member deaths and health trajectories differ by race. Therefore, we test the following specific hypotheses:

Hypothesis 1: Experiencing multiple family member deaths prior to midlife will be associated with more cardiometabolic conditions in mid to later life.

Hypothesis 2: Additional family member deaths after midlife will further add to disadvantage in cardiometabolic health for aging adults.

Hypothesis 3: Associations between multiple family member deaths and cardiometabolic health will be similar for Black adults and for white adults, but the greater exposure to bereavement among Black adults may add to racial inequities in cardiometabolic health.

Data and Methods

Data and Sample

In the present study, we relied on data from Waves 1 through 13 of the Health and Retirement Study (1992– 2016). The HRS is a nationally representative, ongoing study of adults aged 51 years and older in the United States. The HRS began interviewing in 1992 with a cohort of respondents born in 1931 through 1941 (age 51–61 in 1992), and follow-up interviews have been conducted every two years. The HRS adds a new cohort of adults ages 51 to 56 every six years. In addition, the HRS oversampled Black and Hispanic adults to facilitate the analysis of racial groups. More information about the characteristics of HRS can be found in Sonnega and colleagues (2014).

The HRS covers a range of topics, including the history of respondents’ family bereavement experiences, demographic characteristics, and cardiometabolic symptoms, making the data set ideal for the purpose of this study. For the present study, we focused on non-Hispanic Black and non-Hispanic white respondents, excluding Hispanic respondents and respondents who identified as another race-ethnicity. We excluded Hispanic respondents because most Hispanic adults in the HRS are foreign-born, and their exposure to bereavement prior to age 50 likely depends on the mortality conditions of the country of origin—a possibility that we cannot account for in the present study. We also lacked the appropriate sample size necessary to consider life course exposure to family member deaths separately for foreign-born and U.S.-born Hispanic respondents. We further excluded respondents who were under age 50 or who were in the AHEAD cohort (Asset and Health Dynamics Among the Oldest Old; n = 201)—a cohort of adults over age 70 first interviewed in 1993.

Because we consider specific indicators of family bereavement after age 50 (described in the following), we necessarily excluded never-married adults and adults who never had children. We discuss the limitations of this approach in the following. Finally, we dropped respondents who had missing values on cardiometabolic symptoms at any wave (n = 174), family death before age 50 (n = 38), age (n = 1), health insurance (n = 780), and marital status at baseline (n = 3), yielding an analytic sample of 22,974 respondents. Because less than 1% of covariates had missing values, we used listwise deletion (complete case analysis) for missing data. As a sensitivity test, we used multiple imputation to replace missing data on covariates and results were similar (online Appendix A).

Measures

Respondents were asked, “Has a doctor ever told you that you have (had a) [condition]?” To assess cardiometabolic conditions, we considered (1) high blood pressure or hypertension; (2) diabetes or high blood sugar; (3) heart attack, coronary heart disease, angina, congestive heart failure, or other heart problems; and (4) stroke or transient ischemic attack. We used a measure of the total number of cardiometabolic conditions ever diagnosed, ranging from 0 to 4. We used this index because it holistically captures health status (Aneshensel 2005) compared to a single indicator of disease. Moreover, binary measures of single disease items may lead to insufficient statistical power because of low levels of cell coverage in population studies without explicit oversampling on these conditions (Ferraro and Wilmoth 2000). Previous research suggests that respondents’ self-reports of chronic conditions are consistent with physician evaluations of disease (e.g., Skinner et al. 2005).

We created a history of family bereavement file to track the family deaths that occurred over the life course. To understand exposure to multiple family member deaths prior to age 50, we used retrospective reports to consider whether respondents experienced the death of a mother, father, spouse, or child before age 50. In each wave, respondents report whether their mother and father are alive and, if not, what year the parent died. Respondents who lost their mother before age 50 were coded as 1, whereas respondents with a living mother and respondents who experienced their mother’s death after age 50 were coded as 0. We followed a similar process to create an indicator of father’s death prior to age 50. To document spousal bereavement, the HRS asks respondents about the start and end date of marriages that have ended in divorce or widowhood. We again created an indicator of spousal death before age 50 to identify respondents who lost a spouse before age 50 relative to those who lost a spouse after 50 or who were never widowed. The HRS also asks respondents if they have experienced the death of a child and, if so, the year their child died. An indicator of child death before age 50 identified respondents who lost a child before age 50. By harnessing retro-spective reports of bereavement, we documented exposure to family deaths that occurred before respondents entered the HRS study. We summed these four indicators to calculate the total number of losses prior to age 50 (range = 0–4). Because few respondents experienced all four family deaths, we top-coded this measure at two or more deaths.

We also considered family deaths after age 50, including the death of a parent, spouse, sibling, or child after age 50. We created indicators of parent, spousal, and child bereavement after age 50 following the approach described previously. For sibling deaths, respondents reported the total number of living siblings in each wave. We constructed an indicator of sibling death if the number of living siblings decreased between waves.

Race is central to the present study, and we created a measure of non-Hispanic Black and non-Hispanic white (reference) based on self-reports of race and ethnicity. All models accounted for several sociodemographic covariates that may be associated with bereavement and cardiometabolic health, including age (in years), gender (1 = female), educational attainment (less than high school [reference category], high school diploma, some college, and college degree or higher), marital status (1 = unmarried [divorced, widowed]), and whether respondents were born in the South (1 = yes). We also accounted for time-varying household income, measured in dollars, which included all forms of income from the year prior to the interview. We logged household income to reduce the skewness of the distribution and transformed it into 2010 dollars using the Consumer Price Index. To account for potential birth cohort effects, we controlled for approximate birth cohorts: HRS original cohort (born 1931–1941), War Baby cohort (born 1942–1947), Early Baby Boomers (born 1948–1953), and Mid and Late Baby Boomers (born 1954–1965). We controlled for whether respondents had health insurance (1 = no health insurance) to partially account for measurement error in the evaluation of cardiometabolic conditions among respondents with limited access to care. Finally, indicators of censoring (missing and deaths) during the observation period were included in all models to adjust for differential rates of attrition, consistent with previous research (Brown 2018; Lin et al. 2019).

Analytic Approach

We modeled random coefficient growth curves in a mixed model (i.e., hierarchical linear model) framework to estimate differences in health trajectories by experiences of family bereavement. We assessed individual change with age, where repeated observations (Level 1) are nested within respondents (Level 2). Respondents were observed until they died or until the last interview in 2016. Growth curve models estimate individual trajectories shaped by person-specific intercepts (initial values) and slopes (rate of changes across age). The models show intraindividual changes in health as a function of age. We compared the nested likelihood ratio tests of several types of health trajectories (e.g., linear, quadratic, or cubic models), and the test results suggested that a linear growth curve with random intercepts and random linear age slopes provided the best model fit. We added sets of independent variables to the model to examine the extent to which they accounted for observed differences in health intercepts and slopes. Age was centered at age 50 to facilitate model interpretation.

We incorporated respondents who participated in the study at least once, including respondents who dropped out, during the observation period to minimize prospective selection biases because conventional approaches that exclude respondents with incomplete data generate biased estimates of differences in health trajectories (Raudenbush and Bryk 2002). In addition, we adjusted for racial differences in mortality and dropout attrition by including indicators of deaths and missing waves in all multivariate models. Because of the complex sample design, all analyses accounted for geographical stratification and clustering and computed robust standard errors. We applied respondent-level weights to the descriptive results in Table 1 to adjust for the unequal probability of selection and nonresponse. For the growth curve models, we applied normalized wave-specific weights to Level 1 and baseline sample weights to Level 2 (Heeringa, West, and Berglund 2017).

Table 1.

Descriptive Statistics at Baseline Interview (HRS; n = 22,974).

	Total		Non-Hispanic Black		Non-Hispanic White
	Mean	SD	Mean	SD	Mean	SD
Number of cardiometabolic conditions	.64	.01	.96	.02	.58	.01
Age	53.87	.02	53.86	.05	53.88	.03
Female	.48		.53		.47
Non-Hispanic Black	.14		1.00		.00
Household income	6.60	.02	5.58	.04	6.77	.03
Educational attainment
Less than high school	.11		.22		.09
High school diploma	.33		.31		.33
Some college	.27		.29		.27
College+	.29		.18		.31
Cohort
HRS (born 1931–1941)	.26		.21		.27
War Babies (born 1942–1947)	.16		.14		.16
Early Baby Boomer (born 1948–1953)	.18		.17		.18
Mid/Late Baby Boomer (born 1954–1965)	.39		.47		.38
No health insurance	.12		.19		.10
Unmarried	.29		.51		.26
Born in South	.32		.61		.27
Dropout at a given follow-up^a	.20		.19		.20
Family deaths before age 50
0 death	.29		.25		.30
1 death	.43		.41		.43
2+ deaths	.28		.34		.27
Specific family deaths before age 50^a
Mother death	.37		.44		.36
Father death	.63		.69		.62
Spouse death	.04		.07		.03
Child death	.08		.13		.07
Family deaths after age 50^a
Any parent death after age 50	.47		.41		.48
Any child death after age 50	.15		.17		.15
Any spouse death after age 50	.10		.103		.098
Any sibling death after age 50	.17		.21		.16
N individuals	22,974		5,940		17,034
N person-years	144,924		29,918		115,006

Note: All the estimates between non-Hispanic white and non-Hispanic Black are statistically different at p < .001 except for some college. HRS = Health and Retirement Study.

The reported percentages of dropout and percentage of family deaths after midlife were calculated based on person-period files (N = 144,924), reflecting the percentage across subsequent survey waves.

Results

Descriptive Results

Table 1 presents descriptive results for the analytic sample and separately for Black and white respondents. Non-Hispanic Black respondents reported almost twice as many cardiometabolic conditions, on average, compared to non-Hispanic white respondents. Experiencing the death of family members is a common event for respondents in the analytic sample. For example, 71% of adults experienced at least one family member death (i.e., mother, father, spouse, or child) prior to age 50. Moreover, 15% of adults experienced the death of a child after 50, 10% of adults were widowed after 50, and 17% of adults experienced the death of a sibling after age 50. Table 1 also shows racial disparities in exposure to family member deaths. For example, compared to white respondents, Black respondents were less likely to experience no family member deaths before age 50 and more likely to experience two or more family member deaths before age 50. Turning to specific family member deaths prior to age 50, Table 1 shows that the death of a parent was common, and Black adults were more likely than white adults to experience the death of a mother or father. Although spousal or child deaths before age 50 were less common, Black adults were about twice as likely as white adults to experience these bereavement events. Black adults were also more likely than white adults to experience the death of a child, spouse, or sibling after age 50.

Family Member Deaths and Cardiometabolic Health

Table 2 presents results from random coefficient growth models predicting trajectories of cardiometabolic conditions. Model 1 shows that compared to adults who experienced one family member death prior to age 50, respondents who experienced two or more family member deaths prior to age 50 report more cardiometabolic conditions at age 50 (b = .052; p < .05), net of covariates. The difference in cardiometabolic conditions at age 50 between adults who experienced one family member death and zero family member deaths prior to age 50 is not statistically significant, indicating that multiple deaths are more salient for cardiometabolic conditions. Model 1 also shows that family member deaths are associated with the rate of change in cardiometabolic conditions (i.e., the slope) after age 50. Indeed, experiencing two or more family member deaths prior to age 50 is associated with a faster increase in cardiometabolic conditions with advancing age (b = .004; p < .05). Overall, Model 1 of Table 2 indicates that multiple family member deaths prior to age 50 are associated with more cardiometabolic conditions at age 50 and a faster increase in conditions with advancing age. This supports Hypothesis 1 that family member deaths before age 50 shape trajectories of cardiometabolic health in mid to later life.

Table 2.

Random Coefficient Growth Curve Results of Cardiometabolic Conditions Regressed on Exposure to Multiple Family Member Deaths (HRS; n = 22,974).

	Model 1	Model 2	Model 3
Intercept
Family deaths ages 0–50 (reference = 1 death)
0 death	−.028(.021)	−.028(.021)	−.032(.022)
2+ deaths	.052* (.021)	.047* (.021)	.039⁺ (.023)
Family deaths age 50+
Parent death		−.004(.016)	−.004(.016)
Child death		.086(.064)	.086(.064)
Spouse death		.000(.036)	.000(.036)
Sibling death		.033(.027)	.033(.027)
Age (centered at 50)	.066* (.003)	.064* (.004)	.064* (.004)
Female	−.073* (.017)	−.072* (.017)	−.072* (.017)
Household income	−.005⁺ (.002)	−.004⁺ (.002)	−.004⁺ (.002)
Educational attainment (reference = less than high school)
High school diploma	−.049(.032)	−.050(.032)	−.050(.032)
Some college	−.057⁺ (.034)	−.058⁺ (.034)	−.058⁺ (.034)
College degree	−.172* (.034)	−.173* (.034)	−.173* (.034)
Cohort (reference = HRS)
War Babies	.311* (.023)	.308* (.023)	.308* (.023)
Early Baby Boomer	.396* (.023)	.394* (.023)	.394* (.023)
Mid/Late Baby Boomer	.470* (.025)	.464* (.025)	.463* (.025)
No health insurance	−.010(.020)	−.010(.020)	−.010(.020)
Unmarried (reference = married)	.082* (.021)	.082* (.021)	.082* (.021)
Born in South	.089* (.019)	.089* (.019)	.090* (.019)
Dropout at a given follow-up	.006(.031)	.008(.031)	.008(.031)
Non-Hispanic Black	.247* (.027)	.247* (.027)	.220* (.036)
Linear slope (age)
Family deaths ages 0–50 (reference = 1 death)
0 death	−.002(.002)	−.002(.002)	−.003(.002)
2+ deaths	.004* (.002)	.005** (.002)	.005** (.002)
Family deaths age 50+
Parent death		.002(.001)	.002(.001)
Child death		−.003(.003)	−.003(.003)
Spouse death		.000(.002)	.000(.002)
Sibling death		−.001(.002)	−.001(.002)
Female	−.008* (.002)	−.009* (.002)	−.009* (.002)
Household income	.000(.000)	.000(.000)	.000(.000)
Educational attainment (reference = less than high school)
High school diploma	−.005* (.003)	−.005⁺ (.003)	−.005⁺ (.003)
Some college	−.008** (.003)	−.008** (.003)	−.008** (.003)
College degree	−.015* (.003)	−.015* (.003)	−.015* (.003)
Cohort (reference = HRS)
War Babies	−.006* (.002)	−.006* (.002)	−.006* (.002)
Early Baby Boomer	−.014* (.002)	−.014* (.002)	−.014* (.002)
Mid/Late Baby Boomer	−.022* (.003)	−.021* (.003)	−.021* (.003)
No health insurance	−.002(.002)	−.002(.002)	−.002(.002)
Unmarried (reference = married)	.001(.002)	.001(.002)	.001(.002)
Born in South	.003⁺ (.002)	.003⁺ (.002)	.003⁺ (.002)
Dropout at a given follow-up	−.000(.002)	−.000(.002)	−.000(.002)
Non-Hispanic Black	.007** (.002)	.007** (.002)	.008* (.003)
Interaction—Intercept
Family deaths ages 0–50 (reference = 1 death)
0 death × Black			.029(.064)
2+ deaths × Black			.059(.058)
Interaction—Slope
Family deaths age 0–50 (reference = 1 death)
0 death × Black			.001(.006)
2+ deaths × Black			−.003(.005)
Random effects
Level 1 residual	.112* (.002)	.112* (.002)	.112* (.002)
Level 2 age	.003* (.000)	.003* (.000)	.003* (.000)
Level 2 intercept	.613* (.013)	.613* (.013)	.613* (.013)
N (person-years)	144,924

Note: Robust standard errors are in parentheses. HRS = Health and Retirement Study.

p < .10, *p < .05, **p < .01.

We further consider whether and how exposure to family member deaths after age 50 adds to adverse cardiometabolic health experiences in mid and later life. Model 2 of Table 2 shows that family member deaths after age 50 are not associated with more cardiometabolic conditions in mid and later life, net of covariates and earlier life exposure to family deaths. The coefficients for child death (b = .086) and, to a lesser extent, spousal death (b = .033) are relatively large but not statistically significant. Overall, results do not support Hypothesis 2 that additional family member deaths after age 50 will be associated with cardiometabolic health trajectories for older adults.

We also examine whether associations between multiple family member deaths and cardiometabolic health differ by race. Model 3 adds an interaction term for multiple family member deaths before age 50 with race for the intercept and the slope of trajectories of cardiometabolic conditions. None of the interaction terms are statistically significant, suggesting similar associations between bereavement and cardiometabolic health for Black adults and for white adults. Notably, the interaction term for two or more deaths prior to age 50 is positive and relatively large (b = .059), providing suggestive evidence that the disparity in cardiometabolic conditions at age 50 by family bereavement prior to age 50 may be slightly larger for Black adults than for white adults. Findings provide support for Hypothesis 3 such that health trajectories appear similar for Black adults and white adults, but the greater exposure to bereavement among Black adults may add to racial inequities in cardiometabolic health.

Figure 1 shows the predicted number of cardiometabolic conditions by multiple family member deaths prior to age 50 separately for Black adults and for white adults based on estimates from Table 2, Model 3. We emphasize three key findings from this figure. First, Figure 1 shows that adults who experienced family member deaths prior to age 50 report more cardiometabolic conditions at every age, especially adults who experienced the deaths of two or more family members. Second, this disparity in cardiometabolic conditions by bereavement increases with advancing age. Third, Figure 1 shows that Black respondents experience more cardiometabolic conditions at every age regardless of life course history of bereavement. Thus, Figure 1 shows the additive effects of bereavement and race such that Black adults with two or more family member deaths prior to age 50 experience the highest number of cardiometabolic conditions.

Figure 1.

Trajectories of Cardiometabolic Conditions for Black and White Adults by Exposure to Family Member Deaths Prior to Age 50 (HRS; n = 22,974).

Discussion

The death of even one family member is a stressful life course event with lasting consequences for health. However, we know very little about how exposure to multiple family member deaths prior to midlife shapes long-term trajectories of health in mid to later life. Indeed, prior research has devoted minimal attention to the impact of multiple bereavement experiences on health in the general population. Although a growing body of research documents racial inequities in exposure to bereavement (e.g., Cooper and Williams 2020; Umberson et al. 2017), prior research does not test how differential exposure to multiple family member deaths contributes to high levels of cardiometabolic risk for Black Americans. In the present study, we examine how exposure to multiple family member deaths across the life course undermines cardiometabolic health in mid to later life, with additional attention to Black Americans who are at greater risk for multiple deaths. We highlight three key themes from the findings.

First, the deaths of family members before midlife have lasting consequences for cardiometabolic health after age 50 for both white and Black Americans. The stress process model emphasizes that stress proliferates across the life course (Pearlin et al. 2005; Pearlin and Skaff 1996), and bereavement likely elicits biosocial responses that act as chains of risk over the life course. Indeed, multiple bereavement events likely lead to repeated insults over time, such as reduced economic resources, heightened psychological distress, increased relationship strain, and engagement in health-harming behaviors, with cumulative effects for health. This framework reflects a process of cumulative disadvantage wherein bereavement events, especially when repeated throughout the life course, take a cumulative toll on health and contribute to or exacerbate inequities in health. Although we hypothesize stress and disadvantage as likely mechanisms linking bereavement to long-term health outcomes, future research should aim to disentangle the extent to which early adversity leads to increased risk of bereavement and early bereavement increases the risk of lifetime stress and disadvantage.

Findings in the present study also point to the importance of the timing of stressful events, given that significant events during sensitive developmental periods can have profound effects on health (e.g., Ben-Shlomo and Kuh 2002; Miller et al. 2011; O’Rand and Hamil-Luker 2005). For example, experiencing the death of a parent in childhood or adolescence is associated with worse health and well-being in midlife (e.g., Jacobs and Bovasso 2009; Maier and Lachman 2000) and increased mortality risk after age 65 (Smith et al. 2014). Our findings align with a recent study on the effect of multiple family deaths before midlife on a biological marker of cardiovascular risk in women (Lewis et al. 2021), and we build on this work in three primary ways. First, the present study included men and women, demonstrating the robust effects of multiple bereavement events for the health of older adults. Second, we harness 24 years of longitudinal data to show that multiple family deaths contribute to a faster increase in cardiometabolic conditions after age 50. Third, we consider how additional family member deaths after age 50 are associated with cardiometabolic health to capture life course exposure to bereavement (discussed in detail in the following).

The second theme concerns the racial context of bereavement in the United States. In line with prior research on the greater burden of bereavement in Black families (Umberson et al. 2017), we find that Black Americans are more likely than white Americans to experience multiple family member deaths before age 50 as well as additional family member deaths after age 50. That is, we document a greater cumulative burden of bereavement across the life course for Black Americans. Because unequal exposure to stress contributes to racial inequalities in metabolic dysregulation (Boen 2020) and cardiometabolic conditions (Sternthal et al. 2011), we suggest that bereavement is a significant life course stressor and differences in lifetime exposure to family member deaths may contribute to racial inequalities in cardiometabolic health. Older Black Americans experience a double disadvantage: They are more likely to experience the death of multiple family members and are more likely to experience cardiometabolic conditions regardless of bereavement history.

Our results are consistent with research pointing to systemic racism as the driver of differential exposure to stress and adversity, which contributes to racial inequities in health (e.g., Boen 2020; Ferraro and Shippee 2009; Gee et al. 2012; Hatch 2005; O’Rand 2006; Shuey and Willson 2008). That is, systemic racism shortens the lives of Black Americans and subsequently leads to a greater exposure to bereavement—a significant form of stress—in Black families. The exposure to multiple family member deaths across the life course, in turn, further erodes the health of Black Americans. Notably, recent murders of Black Americans by police and white vigilantes have sparked public discourse, media attention, and protests drawing attention to systemic racism as a root cause of premature mortality among Black Americans. Because police killings of unarmed Black Americans can have spillover effects on the mental health of Black citizens in the same state (Bor et al. 2018), these highly publicized deaths could lead to vicarious stress and collective bereavement among Black adults. Although we are unable to examine this possibility in the present study, we note that future research should consider the health effects of community-level bereavement exposures. Indeed, recent research documents a spike in depression and anxiety among Black Americans, but not white Americans, after the murder of George Floyd (Thomeer, Moody, and Yahirun 2022). Although findings in the present study show the adverse consequences of lifetime bereavement for Black and white adults, our inability to account for collective bereavement events may result in underestimation of bereavement effects and conceal race differences in linkages between bereavement and health. Overall, we point to racial inequities in life course exposure to bereavement as a consequence of systemic racism that has lasting implications for health.

Third, additional family member deaths after age 50 did not add to cardiometabolic conditions in the present study when accounting for sociodemographic covariates and earlier life exposure to bereavement. This finding does not align with prior research on the consequences of exposure to the death of a sibling or spouse in later life for dementia (Cha et al. 2021) and mortality (Liu et al. 2020) among older adults. However, some of the prior research on later-life bereavement does not consider exposure to additional family member deaths earlier in life (e.g., Liu et al. 2020), which may provide an incomplete picture of the health consequences of bereavement. We note, however, that a few coefficients for later-life bereavement (e.g., child death) are relatively large, and null findings may be due to limitations of the data and sample size. We interpret these results with caution and urge future research to continue to examine the health consequences of lifetime exposure to family member deaths. Nevertheless, the present study points to the importance of early life exposure to bereavement for cardiometabolic health in mid and later life.

Limitations of the present study should be noted. First, because the HRS focuses on adults over age 50, we cannot observe adults who died or were too sick to participate before age 50. Because bereavement is associated with worse health and greater mortality risk (e.g., Buckley et al. 2010; Stroebe et al. 2007; Umberson 2017), adults in the HRS who experienced the death of (multiple) family members may be more select. As such, results may be conservative estimates of the consequences of multiple family member deaths before midlife. Second, the present study relies on a measure of diagnosed cardiometabolic conditions, which necessitates access to medical care. We include a measure of health insurance coverage to partly account for this bias, but future research could examine biomarker data to assess indicators of health that do not require diagnosis. Third, because we examine specific family member deaths after age 50, we necessarily exclude respondents who never married or never had children. Thus, findings from the present study may not be generalizable to all adults. Moreover, Black adults in the sample were more likely than white adults not to have married, and this differential exclusion from the analytic sample could lead to an underestimation of racial inequities in exposure to cumulative and specific family member deaths. Finally, due to data limitations in the HRS, we cannot examine whether results are sensitive to the cause of death, whether the death was expected, and whether caregiving was required before death. Because these factors tend to shape bereavement experiences (Hendrickson 2009; Stroebe et al. 2007), we may miss variation in the health consequences of multiple family member deaths.

The present study provides evidence that repeated bereavement events across the life course unequally burden Black Americans, lead to the accumulation of disadvantage across the life course, and have lasting consequences for cardiometabolic health. We add to an emerging body of research on racial inequities in bereavement and the implications for inequities in health and well-being. Moreover, the COVID-19 pandemic has highlighted racial disparities in exposure to the death of family members (e.g., Cooper and Williams 2020; Garcia et al. 2021; Kidman et al. 2021), drawing attention to the deadly consequences of systemic racism. Our findings point to the need to identify (multiply) bereaved adults, to work to ameliorate the long-term consequences of bereavement, and to aim to reduce racial disparities in family member death in the first place. Eliminating the unequal burden of bereavement in Black communities is likely a key avenue to reduce racial inequities in health.

Supplemental Material

sj-docx-1-hsb-10.1177_00221465221114485 – Supplemental material for Multiple Family Member Deaths and Cardiometabolic Health among Black and White Older Adults

Supplemental material, sj-docx-1-hsb-10.1177_00221465221114485 for Multiple Family Member Deaths and Cardiometabolic Health among Black and White Older Adults by Rachel Donnelly, Hyungmin Cha and Debra Umberson in Journal of Health and Social Behavior

Footnotes

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported, in part, by the National Institutes of Health (R01AG054624 and R01 AG054624-01A1S), by Grant P30AG066614 awarded to the Center on Aging and Population Sciences at The University of Texas at Austin by the National Institute on Aging, and by Grant P2CHD042849 awarded to the Population Research Center at The University of Texas at Austin by the Eunice Kennedy Shriver National Institute of Child Health and Human Development.

ORCID iDs

Rachel Donnelly

Hyungmin Cha

Debra Umberson

Supplemental Material

Appendix A is available in the online version of the article.

Author Biographies

Rachel Donnelly is assistant professor of sociology at Vanderbilt University. Her research focuses on health and health inequities across the life course, with an emphasis on how work and family relationships contribute to disparate health outcomes. In recent research supported by the National Institutes of Health, she examines how individual-level stressors and state-level policies jointly contribute to mental health disparities.

Hyungmin (Min) Cha is a doctoral candidate at the Department of Sociology at the University of Texas at Austin. His research lies at the intersections of medical sociology, aging and life course, and family. In his recent research, he assesses how differential exposure to deaths of family members by race contributes to racial disparities in dementia in the United States.

Debra Umberson is professor of sociology and director of the Center on Aging & Population Sciences at the University of Texas-Austin. Her research focuses on social factors that influence population health over the life course. With support from the National Institute on Aging, she is collecting longitudinal data from gay, lesbian, and straight couples to assess how spouses influence each other’s health from mid to later life. She also examines racial/ethnic differences in exposure to the death of family members and the implications for health and mortality risk.

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