Reaction paper DEP

Material Hardship and Self-Rated Mental Health among Older Black Americans in the National

Survey of American Life Gillian L. Marshall, Roland J. Thorpe Jr., and Sarah L. Szanton

This article examines the association between material hardships and self-rated mental health (SRMH) among older black Americans and determines whether the effect varies by race and ethnicity. Using data from the National Survey of American Life, multiple logistic regression models were specified on a sample of older white Americans (n = 289), African Americans (n = 1,135), and black Caribbean Americans (n = 377). Material hardship was measured as an index of seven items that occurred within the past year. Material hardship (odds ratio = 0.48; 95 percent confidence interval = 0.29–0.79) was associated with SRMH for both groups. None of the interactions were significant. The study concludes that mater- ial hardship may contribute to poorer SRMH among older African Americans and black Caribbean Americans. Future studies should examine these associations by using longitu- dinal designs, which may be better designed to confirm these results.

KEY WORDS: African Americans; black Caribbean Americans; material hardship; mental health

Although federal agencies such as theNational Institutes of Health [NIH], theNational Academy of Medicine [NAM] (formerly the Institute of Medicine), and the Admin- istration on Aging (AoA) have goals of reducing or eliminating mental health disparities across the life course (AoA, 2001; U.S. Department of Health and Human Services [HHS], AoA, 2008), significant racial, ethnic, and economic disparities in mental health persist. This is particularly true among older adults (AoA, 2001). One of the goals set out by NIH and NAM has been to better understand and reduce socioeconomic and racial health disparities.

Earlier work suggests that socioeconomic status (SES), in part, is one mechanism by which health dis- parities exist (Williams & Collins, 1995; Williams, Yu, Jackson, & Anderson, 1997). The impact of SES as a risk factor resulting in poor health outcomes has been well documented (Braveman, Cubbin, Egerter, Wil- liams, & Pamuk, 2010; Farmer & Ferraro, 2005; Lantz, House, Mero, & Williams, 2005). Although the con- tribution of SES is important in that it has been a ma- jor source for understanding health disparities, it still does not fully explain the gap in health that remains or the pathway by which low income affects health (Whitfield, Thorpe, & Szanton, 2011). SES indicators other than education, income, and occupation may

be worth exploring. Some evidence suggests that the differences in the relationship between low SES and poor health outcomes may be attributed to eco- nomic hardships (Kahn & Pearlin, 2006; Krause, 1987; Szanton et al., 2008; Szanton, Thorpe, & Whitfield, 2010; Thorpe, Szanton, Bell, & Whitfield, 2013). Material hardship, for example, complements mea- sures of SES in an attempt to capture hardships ex- perienced related to unfavorable economic situations and vulnerabilities due to limited resources (Beverly, 2001; Mayer, 1997; Mayer & Jencks, 1989; Ouellette, Burstein, Long, & Beecroft, 2004).

With the rapid growth of the older adult popula- tion (AoA, 2001; U.S. Census Bureau, 2004), it is expected that the diversity already in this demo- graphic will become even more obvious as the numbers increase within each subgroup. It is esti- mated that between 2007 and 2030, the number of white Americans 65 years and older will increase by 68 percent, compared with African Americans (184 percent); Latinos (244 percent); American Indians, Eskimos, and Aleuts (126 percent); and Asian and Pacific Islanders (213 percent) (HHS, 2008). This suggests that the number of older adults of color will surpass that of the older white population. There- fore, to avoid obscuring potential differences in health within a racial group, ethnic group affiliation

doi: 10.1093/hsw/hlx008 © 2017 National Association of Social Workers 87

should be considered with a national sample (Jackson, Torres, et al., 2004).

RACE AND ETHNICITY African Americans and black Caribbean Americans have long been assumed to belong to the same racial group (black); in fact, they are ethnically distinct and display considerable heterogeneity when compared with respect to history, culture, life experience, con- text, status dimensions, beliefs, and cultural norms. The term “African American” refers to people who are U.S.-born black people from the African diaspora who self-identify as Negro, black, Afro-American, or African American. Black Caribbean Americans are those who self-identify as people who trace their ethnic heritage to a Caribbean country but who now reside in the United States. The term “black” is often used to describe groups of black people who are either U.S.-born citizens or foreign-born immigrants.

Although African Americans and black Caribbean Americans share commonalities such as phenotype, vulnerability to discrimination, and a history of enslavement by white people, black Caribbean Americans also share similarities with Europeans in their experience of migration and maintaining ties with their country of origin (Rogers, 2006).

These distinct differences have been largely ig- nored (Bryant, 2003; Lincoln, Chatters, Taylor, & Jackson, 2007; Lyons, 1997; Thorpe et al., 2013; Whitfield, Allaire, Belue, & Edwards, 2008; Williams et al., 2007). In spite of the growing numbers of both older African Americans and older black Caribbean Americans in the United States, the empirical research regarding the similarities and dif- ferences in mental health status between these groups is lacking (Williams et al., 2007). Therefore, it is worth considering that these factors may have a bearing on how members of each group perceive material hardship and rate their mental health status.

Prior work in this area has demonstrated that eco- nomic measures are an important predictor of men- tal well-being and strongly associated with mental health outcomes (Alley & Kahn, 2012; Lee & Brown, 2007; Savoy et al., 2014). Yet few studies have used a national sample of older black Americans to investigate the effects of material hardship on self- rated mental health (SRMH) among all older black Americans (African Americans and black Caribbean Americans). Despite the growing interest in the

mental well-being of adults in late life, little is known about how material hardship affects well- being. Furthermore, it is not known whether differ- ences in ethnicity within race can serve as a potential explanation for why there is variation in SRMH.

Using a nationally representative sample of older white Americans, African Americans, and black Caribbean Americans, this study examines the association between material hardship and SRMH status, while controlling for key covariates such as age, income, marital status, and education and de- termines whether this relationship varies by ethnic group. We hypothesize that after adjusting for cov- ariates, material hardship will be positively asso- ciated with SRMH and that this relationship will vary by ethnic group.

METHOD Study Sample Data for these analyses were obtained from the National Survey of American Life: Coping with Strain in the 21st Century (NSAL). This is a cross- sectional survey study of inter- and intragroup racial and ethnic differences with respect to mental disorders, psychological strain, help seeking, and the use of informal and formal health services (Jackson, Neighbors, Nesse, Trierweiler, & Torres, 2004). Face-to-face interviews were conducted with a total of 6,082 adults in the United States, age 18 years and older, consisting of 3,750 African Americans, 1,621 black Americans of Caribbean descent, and 892 non-Hispanic white Americans.

This is a nationally representative, probability complex sample for which primary data were col- lected from 2001 through 2003 (Jackson, Neigh- bors, et al., 2004) by the University of Michigan’s Institute for Social Research Survey Center, which is part of the National Institute of Mental Health Collaborative Psychiatric Epidemiology Surveys initiative. People ineligible for the study were those institutionalized in prison or jail, psychiatric facil- ities, nursing homes, and other long-term medical or dependent care facilities. Also excluded were those who had been homeless or were in the military.

The analytic sample for this study was composed of 1,801 men and women age 50 years and older who self-identified as African American (n = 1,135), black Caribbean American (n = 377), or white American (n = 289).

88 Health & Social Work Volume 42, Number 2 May 2017

Measures Dependent Variable. SRMH was assessed using a single item in which participants were asked, “How would you rate your overall mental health?” at the present time. There were five possible response op- tions: 1 = poor, 2 = fair, 3 = good, 4 = very good, and 5 = excellent. This variable was dichotomized into two categories: 0 = fair/poor and 1 = good/ very good/excellent mental health.

Independent Variables. Material hardship con- sisted of a seven-item scale asking, “In the past 12 months was there a time when you (1) didn’t meet basic expenses; (2) didn’t pay full rent or mortgage; (3) were evicted for non-payment; (4) didn’t pay full gas, electric, or oil; (5) had gas or oil discon- nected; (6) had telephone disconnected; (7) couldn’t afford leisure activities.” Responses were either no (0) or yes (1). All responses were summed for a total composite score; higher scores reflected greater material hardship. This approach is similar to that of previous investigators (Hughes, Kiecolt, & Keith, 2014).

Covariates. Covariates included age (50 to 94 years, as a continuous measure), gender (0 = male; 1 = female), race and ethnicity (African Americans, black Caribbean Americans, and white Americans as the reference group), education (<12 years, 12 years, >12 years), and annual household income (<$10,000; $10,000–$19,999; $20,000–$39,999; $40,000–$59,999; ≥$60,000).

Statistical Analysis Descriptive statistics included percentages and p values for categorical variables and mean and standard variations for continuous variables for the total sample and by material hardship. Logis- tic regression models were used to determine the associations between SRMH and material hard- ship and other covariates. Interaction terms were created for material hardship × ethnic group to determine whether material hardship varies by ethnic group. We reported results as odds ratios with 95 percent confidence intervals (CIs). NSAL data are weighted by using sampling weights adjust- ing for disproportionate sampling, nonresponse, and population representation across various sociode- mographic characteristics across the United States (Heeringa et al., 2004, 2006). Results with p values less than .05 were considered statistically significant. We used Stata (Version 11) to conduct statistical procedures (StataCorp, 2009).

RESULTS Table 1 presents demographic information about the characteristics of the total NSAL sample (N = 1,801) by material hardship. The mean age among those with material hardship and those without was 60 years (SD = 9.5) and 64 years (SD = 9.4), respect- ively. Compared with 19 percent of white Amer- icans, 29 percent of African Americans and 26 percent of black Caribbean Americans were likely to experience material hardship. We found that a lower proportion of those who were married or partnered reported material hardship. With regard to SES indi- cators, 32 percent of those with less than 12 years of education were likely to experience material hard- ship. Across all income levels, only a small percent- age measured having material hardship. Among those without material hardship, 80 percent reported experiencing good to excellent health; 35 percent of those with material hardship reported poor to fair health status.

Table 2 presents the association between material hardship and SRMH. Specifically, model 1 tested for the direct effect between material hardship and SRMH. People who experienced material hardship had 48 percent higher odds of reporting fair or poor mental health than those without material hardship (95 percent CI = 0.29, 0.79). When we exam- ined the association between material hardship and SRMH controlling for race (model 2), we found that those who did report material hardship had 49 percent higher odds of reporting poor mental health compared with those who did not have material hardship (95 percent CI = 0.031, 0.77). Model 3 examined the association between material hardship and SRMH by controlling for all demographics fac- tors. We found that people with material hardship (95 percent CI = 0.39, 0.79) had 56 percent greater odds of reporting poor or fair mental health. For model 4, we added one interaction term to test whether material hardship varied by ethic group (African American × material hardship; black Carib- bean Americans × material hardship). When the interaction term was added to the model, we found that material hardship lost its significance. In add- ition, the interaction in model 4 was not significant.

DISCUSSION By using data from a nationally representative sam- ple of older African American and black Caribbean Americans, we examined the relationship between material hardship and SRMH. Results indicate that

89Marshall, Thorpe, and Szanton / Material Hardship and Self-Rated Mental Health

those who experienced material hardship were more likely to report fair or poor mental health. Our study differs from previous work in that it examined within-group differences among older black Amer- icans. In addition, the current study extended the lit- erature by examining material hardship and its association to SRMH in late life.

Older African Americans and black Caribbean Americans who had material hardship had higher odds of reporting fair or poor mental health. As sta- ted earlier, material hardship measures comple- ment measures of SES by measuring specific concrete bills (for example, gas, light, power) in an attempt to capture hardship related to unfavorable economic situations and vulnerabilities due to lim- ited resources (Szanton et al., 2008). These are actionable by policy that may provide additional information regarding an older person’s economic well-being.

This finding is novel in that it contributes to the literature on hardship related to material hardship and SRMH as few studies, if any, have. This is especially significant because the study used this measure with a national sample of older African Americans and black Caribbean Americans. These findings suggest that material hardship directly in- fluences black adults’ reports of their mental health status in later life. Studies using other measures of economic hardship have found similar results (Lin- coln & Chae, 2010; Szanton et al., 2010).

These findings should be interpreted with caution as this study has limitations. First, this was a cross- sectional study, which limits our ability to make in- ferences about the causal direction of the relation- ships. In addition, longitudinal studies that examine the impact of material hardship and change in SRMH are needed. Second, this study examined only two English-speaking black ethnic groups:

Table 1: Demographic Characteristics of Older Adults 50 and over, by Material Hardship

Characteristic

Material Hardship

p Total

(N = 1,801) With Material Hardship

(n = 520) Without Material Hardship

(n = 1,381)

Age (years): mean (SD) 62.9 (9.5) 60.3 (9.5) 63.7 (9.4) <.001 Race and ethnicity African American 59.7 28.7 71.3 .004 Black Caribbean 19.8 25.5 74.5 .653 White 20.5 18.6 81.4 .004

Gender .23 Male 47.1 21.2 78.8 Female 52.9 24.8 75.2

Marital status <.001 Single/divorced/ widowed

47.4 28.0 72.0

Married/partnered 52.6 17.2 82.8 Education level .003 Less than 12 years 28.1 32.4 67.6 12 years (ref) 33.4 21.9 78.1 More than 12 years 38.5 17.4 82.6

Income <.001 $200–$9,999 12.1 42.5 57.5 $10,000–$19,999 22.8 29.0 71.0 $20,000–$39,999 27.1 22.8 77.2 $40,000–$59,999 14.4 19.0 81.0 $60,000+ 23.6 10.4 89.6

Self-rated mental health status

.002

Poor/fair 11.9 35.0 65.0 Good/very good/

excellent 88.1 20.5 79.5

Notes: All values are percentages, unless otherwise indicated; ref = reference category.

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African American and black Caribbean Americans. Black Caribbean Americans consist of people from several islands that are diverse in culture, language, and experience. The island-specific subgroups were too small to provide stable estimates; hence, one limitation is that the Caribbean American sample was examined as if it represented one homoge- neous group. A third potential limitation might be the use of a single-item measure of SRMH as a dependent variable. The single-item assessment of SRMH has received some attention to date in its association with psychological symptoms and mental disorders (Kim et al., 2010). However, in spite of the reported validity of the SRMH vari- able, some have argued that the degree to which SRMH may be used as a proxy for other mea- sures of mental health is unclear (Fleishman & Zuvekas, 2007). Perhaps a more robust measure of mental health might have more variability and therefore be better able to detect any changes. Despite these limitations, however, the findings are

important in that they showed that material hardship plays a significant role in the lives of older African Americans and black Caribbean Americans who rated their mental health status as being either fair or poor. This study is one of the first to investigate the association between material hardship and SRMH in a national sample of older African Americans and black Caribbean Americans in the United States.

This study also extends the aging and mental health literature by examining the differences and similarities in the association of hardship and depres- sive symptoms among older African Americans and black Caribbean Americans.

SOCIAL WORK PRACTICE IMPLICATIONS The aim of this study was to assess the association between material hardship and SRMH status and determine whether this relationship varied by ethnic group. Our results are consistent with those of simi- lar studies examining the relationship of hardship

Table 2: Logistic Regression for Self-Rated Mental Health, by Material Hardship, Demographic Characteristics, and Interaction Terms

Variable

Model 1 Model 2 Model 3 Model 4

OR 95% CI OR 95% CI OR 95% CI OR 95% CI

Material hardship 0.48** 0.29, 0.79 0.49** 0.31, 0.77 0.56** 0.39, 0.79 0.73 0.38, 1.40 Race and ethnicity White (ref) African American 0.87 0.52, 1.45 0.91 0.60, 1.38 1.07 0.64, 1.78 Black Caribbean 0.67 0.28, 1.60 0.54 0.24, 1.23 0.59 0.22, 1.60

Age: mean (SD) 0.99 0.97, 1.02 0.99 0.97, 1.02 Gender Male (ref) Female 0.76 0.41, 1.39 0.77 0.42, 1.41

Marital status Single/widowed/divorced (ref) Married/partnered 1.32 0.68, 2.57 1.32 0.68, 2.57

Education 12 years (ref) Less than 12 years 0.56* 0.31, 1.01 0.56 0.31, 1.00 More than 12 years 0.59 0.26, 1.31 0.59 0.26, 1.32

Income $200–$9,999 (ref) $10,000–$19,999 1.40 0.26, 1.31 1.40 0.89, 2.20 $20,000–$39,999 1.81** 0.89, 2.19 1.84** 1.07, 3.15 $40,000–$59,999 3.24** 1.23, 8.56 3.27** 1.23, 8.68 $60,000+ 5.84*** 2.71, 12.57 6.01*** 2.79, 12.93

Ethnicity × material hardship African American 0.62 0.26, 1.45 Black Caribbean 0.79 0.20, 2.94

Notes: CI = confidence interval; ref = reference category. *p < .05. **p < .01. ***p < .001.

91Marshall, Thorpe, and Szanton / Material Hardship and Self-Rated Mental Health

and poor mental health outcomes in older African Americans (Savoy et al., 2014; Szanton et al., 2010). However, few studies to date have examined material hardship within-group differences specifically.

Frequently neglected in the literature is a discus- sion regarding hardships in later life. Older adults, often vulnerable and underserved, may also have increasing needs and experience hardships as they age, potentially leading to poor mental health out- comes in late life (Lee & Brown, 2007; Szanton et al., 2008). With the growth in the older adult population and increased life expectancy, older adults will need to manage their financial resources over a longer or extended period of time (Hill, Kellard, Middleton, Cox, & Pound, 2007). Older adult clients face hardships, such as possessing lim- ited financial resources or lacking knowledge about finances; this may be why they come into contact with social workers for assistance. Social workers are often faced with the task of helping their clients address stressful life situations. Stress related to hardships in the form of debt is one such stressful life situation that has been often over- looked in social work practice, especially among the older adult population.

The National Association of Social Workers (2015) has identified enhancing the capacity of people to address their own needs as one of social work’s top priorities. One such need is assistance with financial matters. Although social workers have the opportunity to help individuals and families with their financial problems in a variety of practice settings (Sherraden, Laux, & Kaufman, 2007), a cursory review of social work curricula suggests that the skills to do so are not being taught. Social work graduates are rarely provided with the expertise and formal training on how to help individuals and fam- ilies manage household finances and financial decision making (Despard & Chowa, 2013; Frey et al., 2015; Gillen & Loeffler, 2012; Sherraden et al., 2007).

Although social workers are not given this formal training, many are already doing work in household finance areas and have some of the necessary skills and knowledge on financial matters to practice well. However, many other social work professionals are not prepared to assist families with financial concerns and are at a disadvantage when working with clients, especially those who borrow from fringe economy enterprises (payday lenders, pawn shops, rent-to- own shops) (Karger, 2015). Despite this challenge,

working in this area provides an opportunity for social workers to intervene to help clients better address their financial circumstances. Social workers interested in improving clients’ financial well-being have used intervention methods such as financial counseling or financial education as potential prac- tice approaches (Despard & Chowa, 2013).

Newer fields of study, such as financial capabil- ity, have emerged to address the specific financial needs of the clients social workers serve. Financial capability incorporates aspects of financial literacy and financial stability. A recent pre- and poststudy conducted by Frey et al. (2015) examined the knowl- edge, attitudes, and behaviors of social workers before taking a financial capability training program and then assessed them again after the training. Frey et al. found that although many clients who sought out social work services had financial problems, social workers reported not having any formal training in this area. Posttest assessments revealed that social workers increased their financial knowledge and behaviors.

Another emerging field of study specific to the older population is financial gerontology—a multidis- ciplinary approach drawing from various disci- plines, such as biology, psychology, sociology, and demography, and using a life span framework to advance understanding of lifelong wealth span is- sues and aspirations of older adults and their fam- ilies (American Institute of Financial Gerontology, 2007). Evidence from practitioners using interven- tions such as financial capability and gerontology, financial counseling, or financial education is prom- ising, but additional research and evaluations of these models are needed. HSW

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Williams, D. R., Haile, R., Gonzalez, H. M., Neighbors, H., Baser, R., & Jackson, J. (2007). The mental health of black Caribbean immigrants: Results from the National Survey of American Life. American Journal of Public Health, 97, 52–59.

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Gillian L. Marshall, PhD, MSW, is assistant professor, Department of Social Work, University of Washington, 1900

Commerce Box 358425, Tacoma, WA; e-mail: [email protected]. Roland J. Thorpe Jr., PhD, is associate professor, John Hopkins Bloomberg School of Public Health, and Sarah L. Szanton, PhD, is associate professor, School of Nursing, Johns Hopkins University, Baltimore.

Original manuscript received December 10, 2015 Final revision received March 18, 2016 Editorial decision May 18, 2016 Accepted May 19, 2016 Advance Access Publication March 4, 2017

94 Health & Social Work Volume 42, Number 2 May 2017

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