Abstract

Greater educational attainment is generally associated with healthier and longer lives. However, important heterogeneity in who benefits from educational attainment, how much, and why remains underexplored. In particular, in the United States, the physical health returns to educational attainment are not as large for minoritized racial and ethnic groups compared with individuals racialized as White. Yet, our current understanding of ethnoracial differences in educational health disparities is limited by an almost exclusive focus on the quantity of education attained without sufficient attention to heterogeneity within educational attainment categories, such as different institution types among college graduates. Using biomarker data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), we test whether the physical health of college graduates in early adulthood (aged 24–32) varies by institution type and for White, Black, and Hispanic adults. In considering the role of the college context, we conceptualize postsecondary institutions as horizontally stratified and racialized institutional spaces with different implications for the health of their graduates. Finally, we quantify the role of differential attendance at and returns to postsecondary institution type in shaping ethnoracialized health disparities among college graduates in early adulthood.

Introduction

Only 14% of U.S. adults had completed four or more years of college in 1975, compared with 33% by 2015 (U.S. Census Bureau 2019). During this period, access to higher education increased for White as well as Black and Hispanic Americans (Grodsky 2007): from 20% to 34% for White adults, from 10% to 21% for Black adults, and from 7% to 14% for Hispanic adults (U.S. Census Bureau 2015). Alongside this dramatic expansion, educational attainment became an increasingly salient dimension of stratification, with widening educational gradients across various life outcomes, including health (Crimmins and Zhang 2019; Sasson and Hayward 2019). For example, adults with a college degree can expect to live more than 10 years longer than their peers without a high school diploma (Hummer and Hernandez 2013). As educational attainment has expanded, it has become increasingly important for health and longevity.

Yet, not everyone benefits equally from educational attainment, particularly in terms of health. Whereas the relationship between educational attainment and health is robust for White adults, educational gradients across a variety of measures of health are shallower or even nonexistent among Black and Hispanic adults (Beltrán-Sánchez et al. 2016; Crimmins et al. 2007; Hummer and Hernandez 2013; Hunt et al. 2003; Kimbro et al. 2008; Sasson 2016; Turra and Goldman 2007; Vable et al. 2018). The ability of racial and ethnic minorities to translate socioeconomic resources into health-promoting resources is a key component of social mobility and stratification (Pearson 2008), a process blocked by a legacy of structural and institutional racism (Flippen 2004; Massey 2007; Reardon and Bischoff 2011; Torres and Massey 2012). Although educational attainment is viewed as the primary mechanism for upward mobility in the United States, the country's history of racial exclusion and segregation in education undergirds contemporary patterns of higher education attendance and attainment (Harper et al. 2009; Roebuck and Murty 1993; Span 2015). Furthermore, educational access alone is insufficient to eliminate health disparities if equal attainment has differential returns by ethnoracial group (Bell et al. 2020; O'Brien et al. 2020) or if upward mobility comes at a physical health cost for ethnoracialized minorities (Chen et al. 2015; Gaydosh et al. 2018; Pearson 2008).

Just as U.S. postsecondary enrollment has grown, so too has the number of degree-granting postsecondary institutions, from 3,231 in 1980 to 4,627 in 2014 (Snyder et al. 2019). Postsecondary institutions vary tremendously in their quality and composition. Greater differentiation within postsecondary educational contexts creates inequality within the educational attainment level of college completion, helping to maintain stratification systems (Espenshade and Radford 2009; Jennings et al. 2015). Inequalities are maintained through horizontal stratification, wherein institutional resources (e.g., endowments and expenditures) and quality (e.g., rank and selectivity) increasingly shape the returns to education (Charles and Bradley 2002; Gerber and Cheung 2008). Most research on educational disparities in health, however, has focused on the highest degree completed and health at older ages, without attention to sources of heterogeneity within the college completion category that may determine the health returns to education across the life course (for exceptions, see Montez et al. 2018; Walsemann et al. 2018). In this article, we investigate heterogeneity in the attainment category of college graduation by interrogating the role of institutional characteristics.

Widely varied college characteristics not only influence the returns to college completion but also shape the individual experience of the attainment process during college in ways that differ by ethnoracial group, making college completion more or less stressful and thereby physiologically taxing or beneficial (Allen et al. 2019; Wickrama et al. 2016). Yet, little research has examined how characteristics of institutions of higher education, such as selectivity and resources, influence health in general (for exceptions, see Fletcher and Frisvold 2011, 2014; Ross and Mirowsky 1999) and differentially by ethnoracial group, partly because of limited prospective information on educational context and individual health outcomes.

In this article, we use longitudinal and biomarker data from the nationally representative National Longitudinal Study of Adolescent to Adult Health (Add Health) to examine heterogeneity in the physical health of White, Black, and Hispanic college graduates in early adulthood (ages 24–32). Using a new supplementary dataset merged with Add Health (Gaydosh et al. 2019a, 2019b), we examine the role of college characteristics in shaping racialized health disparities among college graduates. With biomarker data, we can examine underlying health risks that may otherwise be unobservable in this young adult population (Harris and Schorpp 2018). Using biomarkers to measure health risks in young adulthood is a key contribution to the literature on ethnoracial and educational stratification in health because poor underlying physiological functioning might not yet manifest in symptomatic health conditions at this life course stage (Harris and Schorpp 2018).

Drawing on a conceptualization of postsecondary institutions as horizontally stratified and racialized organizations, we answer three research questions. First, how do college characteristics influence the physical health of college graduates in young adulthood? Second, does graduation from different types of institutions differentially confer health benefits for White, Black, and Hispanic adults? Finally, how do the distribution and effect of institution type contribute to ethnoracial disparities in health? To our knowledge, this is the first study to describe the role of college context in the biomarker-measured physical health of college graduates and to assess how these processes differ among non-Hispanic White, non-Hispanic Black, and Hispanic young adults. With detailed prospective data on childhood context, we control for observed factors influencing selection into college completion using a host of individual, family, and secondary school characteristics. We also test for moderation by ethnoracial group. We then decompose Black–White and Hispanic–White disparities in health, estimating the contribution of differential attendance and differential returns to institution type. This research recontextualizes the value of college completion for health and its role in ethnoracial health disparities.

Background

Diminishing Health Returns to Education by Race and Ethnicity

Although educational attainment is robustly associated with general health, this relationship is well-known to be heterogeneous by race and ethnicity. Specifically, the physical health and life expectancy gains to education are smaller for minoritized groups than for non-Hispanic Whites (Goldman et al. 2006; Hummer and Hernandez 2013; Noppert et al. 2021; Sasson 2016). Diminishing returns describes a general pattern of fewer benefits associated with greater resources among Black Americans relative to their White peers, originally regarding income returns to educational attainment (Bowles and Gintis 1976; Farley 1984; Williams and Collins 1995). The diminishing returns hypothesis with respect to racialized health disparities describes a pattern in which the health difference between Black and White individuals is greatest at high levels of socioeconomic status (SES) (Farmer and Ferraro 2005). Deeply entrenched racism in the United States means that attained status among marginalized ethnoracial groups is more difficult to obtain and less rewarded (Mangino 2010; Pearson 2008), leading to diminished returns to health. Research has found strong evidence of diminishing returns of SES, including education, to health by race and ethnicity for Black and Hispanic adults (Boen 2016; Boen et al. 2020; Brown et al. 2016; Ciciurkaite 2021; Esposito 2019; Farmer and Ferraro 2005).

Most explanations for these patterns tend to emphasize individual behavior or psychological characteristics—namely, how status attainment for Black Americans is difficult and stressful (Jackson et al. 2010; James et al. 1983; Jetten et al. 2008). Although individual factors, such as behavior, coping, and resilience, help us to understand the mechanisms behind disparities in population health, contextual factors, such as neighborhood economic opportunity and state educational investment, structure individual experiences and influence health outcomes (Chetty and Hendren 2018; Gaydosh and McLanahan 2021; Hargrove et al. 2022; Montez et al. 2017; Montez et al. 2019; Zajacova and Lawrence 2018).

Limited research has examined the role of college characteristics in promoting or constraining the health benefits of educational attainment and contributing to racial and ethnic disparities in life course health. In a predominantly White postsecondary setting, Cheadle et al. (2020) found that racism-related experiences increase negative emotion and a real-time biophysical measure of physiological stress among Black and Latinx students, supporting the biological plausibility of a pathway from institutional context to physical health. Our research contributes to this literature by investigating the role of institutional characteristics in the physical health of college graduates.

Our study takes a different approach to understanding the diminishing returns to educational attainment among Black and Hispanic adults by concentrating on heterogeneity among college graduates only. This decision is influenced both by the need for better understanding differences within this educational attainment category and by data limitations that preclude our ability to examine individuals with only some college education. We investigate the role of institution type in shaping the cardiometabolic health of college graduates overall and by race and ethnicity. Previous research overwhelmingly relied on self-reported health measures and tended to focus exclusively on Black–White health disparities. This study improves on this research by considering objective measures of physical health using biomarkers among Black, White, and Hispanic young adults.

Horizontal Stratification in Postsecondary Education

The expansion of postsecondary education was accompanied by greater differentiation in institutional characteristics, creating stratification within educational attainment categories and maintaining stratification systems (Conwell and Quadlin 2021; Espenshade and Radford 2009; Jennings et al. 2015; Quadlin and Conwell 2021). Yet, we know very little about how the characteristics of postsecondary educational institutions shape health outcomes (Hummer and Hernandez 2013). Horizontal stratification refers to increasing differentiation within attainment categories (Gerber and Cheung 2008). As educational opportunities expand and attainment levels increase, differentiation within educational attainment categories intensifies (Lucas 2001). Thus, the education level attained is no longer the sole influence on well-being outcomes; variation within that level also matters (Gerber and Cheung 2008).

Well-resourced institutions provide students with greater financial and educational support during their educational careers, which might make the experience of college completion less stressful and therefore less physiologically taxing (Evans et al. 2011). College quality might also influence the amount of knowledge obtained through college completion—resources that individuals can then deploy to promote their health and self-advocate in healthcare settings (Becker 1993; Link and Phelan 1995). Finally, college characteristics influence labor market outcomes and other socioeconomic returns to college completion (Anelli 2020; Brand and Halaby 2006; Chetty et al. 2017; Dale and Krueger 2002; Gerber and Cheung 2008; Hout 2012), and these resources lie on the pathway from greater education to better health. Most research on postsecondary institutional characteristics has concentrated on labor market outcomes. Four notable exceptions examined the influence of college quality on health outcomes and found generally protective effects, but these studies either did not consider differences by race or ethnicity or produced mixed findings (Fletcher and Frisvold 2011, 2014; Ross and Mirowsky 1999; Wang and Conwell 2022).

The literature on horizontal stratification within postsecondary education and differential returns to college quality suggests that students with access to privileged institutions accumulate advantages in ways that are constrained at institutions with lower status and resources. We posit that institutions at the top of the educational hierarchy, with greater resources and status, provide greater benefits to students during and after college. Therefore, the health benefits associated with college completion will be largest among those attending traditionally privileged, predominantly White, wealthy institutions.

Racialization in Postsecondary Institutions

The horizontally differentiated college hierarchy is maintained on the premise of meritocracy: college admission is ostensibly based on academic merit, and the institutions with the highest quality and status confer the greatest rewards and are the most selective (Grodsky 2007; Karen 2002; Roksa et al. 2007; for nuanced discussion of merit in selective institution admissions, see also Bowen and Bok 1998). Yet, this meritocracy myth conceals the reality of postsecondary institutions as racialized organizations and elite institutions, in particular, as sites that preserve White privilege (Karabel 2005; Karabel and Astin 1975; Ray 2019; Yosso et al. 2004). The postsecondary hierarchy thereby legitimizes the unequal distribution of resources and helps maintain and reproduce racial and ethnic inequality (Domina et al. 2017; Ispa-Landa and Conwell 2015; Ray 2019).

Historical exclusion and contemporary underrepresentation contribute to the maintenance of universities, particularly elite universities, as predominantly White institutions and what scholars have referred to as White Spaces (Anderson 2011, 2015; Harper and Hurtado 2007). This term does not refer exclusively to places where individuals racialized as White are the numerical majority and minoritized individuals have been historically excluded; it also extends to places where organizational and cultural logics are rooted in Whiteness (Anderson 2022; Cabrera et al. 2016; Ray 2019). It is unsurprising, then, that White students often report higher levels of belonging and inclusivity on campus than Black and Hispanic students (Cabrera et al. 2016; Hurtado and Carter 1997; Johnson 2012; Johnson et al. 2007). In institutions where Black and Hispanic students have been historically excluded, negative interpersonal social interactions, status threats, and social exclusion are common (Aries and Seider 2005; Jack 2016; Lee 2016; Yosso et al. 2009). Hispanic and Black students face interpersonal microaggressions in elite postsecondary universities (Johnson and Joseph-Salisbury 2018; Solórzano et al. 2002; Solórzano et al. 2000; Yosso et al. 2009). Interpersonal race-related stressors lead to elevated biological stress (Cheadle et al. 2020), which can accumulate and contribute to physiological dysregulation (Goosby et al. 2018; McEwen 1998).

Further, beyond the educational context, racism and discrimination continue as college-educated Black and Hispanic adults transition from college to the workplace and their adult residential locations. In occupational settings where Black workers are a very small minority, racial discrimination and exclusion are commonly reported (Stainback et al. 2018), and feelings of hypervisibility lead to sustained vigilance (Hudson et al. 2020). Such settings offer fewer resources for support and mentorship (Wingfield and Chavez 2020), which might also lead to greater job stress. Black college graduates are also more likely to live among White neighbors relative to their same-race counterparts without a degree, but they still have poorer residential contexts even relative to low-SES White adults, highlighting the precarity of upward residential mobility for highly educated Black adults (Landry and Marsh 2011; Pattillo 2005; South and Crowder 1997, 1998).

Little research has examined how characteristics of higher education institutions influence health in general, and differentially by race and ethnicity, partly because of limited prospective information on educational context and individual health outcomes. Some previous research suggests that Black student attendance at predominantly White institutions is associated with worse mental health (Barry et al. 2017), a pattern consistent with research on secondary school racial composition (Goosby and Walsemann 2012; Walsemann et al. 2011). Drawing on this research and the framework outlined earlier, we posit that the college experience will be more stressful and less health-promoting for minoritized students attending institutions at the top of the status hierarchy. We hypothesize that the health of Black and Hispanic college graduates will be worse among those attending traditionally privileged, predominantly White, wealthy institutions compared with same-race graduates from other types of institutions.

Data and Methods

We use data from Add Health, an ongoing longitudinal study of the social, behavioral, and biological linkages in developmental and health trajectories from early adolescence into adulthood (Harris 2010; Harris et al. 2019). The data are representative of American adolescents in grades 7–12 in 1994–1995. The initial sample included 20,745 individuals aged 12–20; they were followed over time across five interview waves. At Wave IV in 2008–2009, respondents were aged 24–32 (n = 15,701; 80.3% response rate). These data are particularly well-suited to address our research questions because they include detailed precollege characteristics at multiple levels of measurement and biomarker measures of health risk in young adulthood. Furthermore, the Add Health sample contains an oversample of Black and Hispanic individuals, enabling an examination of ethnoracial heterogeneity in the association between college characteristics and physical health.

We limit our analytic sample to respondents who participated in the Wave I and Wave IV in-home interviews, had valid sampling weights, completed a four-year college degree, and identified as White, Black, or Hispanic (n = 4,135). We combine race and ethnicity into the ethnoracial groups White, Black, and Hispanic, excluding groups for whom the sample size is insufficient to support group-stratified analysis (Hummer 2023; Martinez et al. 2023; Williams 2012).

College completion is an age-appropriate measure of educational attainment, given that most respondents (84%) are no longer enrolled in school in young adulthood (24–32). Further, half of those still enrolled already completed a college degree (in 1998–2008), including individuals who completed a postbaccalaureate degree; for 75% of the sample, a bachelor's degree is the highest degree obtained. Results are robust to the exclusion of individuals with an advanced degree and to controlling for advanced degree completion (Table A1, online appendix). We include them in the analysis to retain the largest sample size available. From this sample, we exclude those without complete data on the indicators of cardiometabolic risk, our adulthood health outcome (n = 3,261; Table 1). For participants missing information on the covariates of interest (including adolescent, high school, and college characteristics), we use principal component analysis to impute the missing values. In brief, we first use leave-one-out, fivefold cross-validation to determine the appropriate number of dimensions for the principal component analysis; two dimensions produced the smallest mean square error of prediction. We then use the observed data to estimate variability patterns across characteristics and impute values for missing observations based on the first two estimated principal components.

Measures

Physical Health

We measure the physical health of Add Health respondents in young adulthood using cardiometabolic risk, a count of the number of high-risk values across eight biomarkers measured at Wave IV: C-reactive protein, hypertension/blood pressure, waist circumference, glycosylated hemoglobin, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and obesity (see Table 1). The selected biomarkers represent function across inflammatory, cardiovascular, and metabolic systems and are implicated in the stress response system, which is appropriate for the hypothesized relationship between college context and physical health (Deighton et al. 2018; Harris and McDade 2018; McEwen 2012). We use this measure because cardiometabolic risk is an objective measure of physical health that captures variation in health risks across these eight biomarkers before evidence of disease is manifest and is highly predictive of future chronic disease among young adults (Harris and Schorpp 2018). Objective measures of physical health represent underlying biological processes related to disease onset that are more closely aligned with environmental exposures than subjective health measures, such as those used in prior research; subjective health measures are limited because they may confound mental and emotional aspects of well-being (Gruenewald et al. 2006; Navarro et al. 2012; Qian et al. 2024; Weir 2018). Further, having been born at the onset of the obesity epidemic in the late 1970s and early 1980s, the Add Health cohort has experienced higher levels and greater variation in cardiovascular and metabolic health risks than prior young adult cohorts in the United States (Harris et al. 2019; Harris et al. 2021).

We define a high-risk threshold for each biomarker according to National Cholesterol Education Program Expert Panel guidelines and sum across the set of markers, consistent with previous research using Add Health data (Bohr et al. 2016; Gaydosh et al. 2018). Summing the number of risk indicators across the eight markers creates a cardiometabolic risk score of 0 to 8, with an average of 2.52 (Table 1).1 Note that when we examine each marker individually, the results are substantively similar and are not driven by any particular marker.

Adolescent Characteristics

A strength of the data is the availability of prospectively measured reports of individual and family characteristics that describe the precollege context and influence selection into different postsecondary institution types. This feature allows us to assess the role of adolescent context in selection processes across multiple relevant domains (Ferraro et al. 2015). In models that control for adolescent characteristics, we include grade point average, Peabody Picture Vocabulary Test score, difficulties completing homework and paying attention in school, belief in working hard to get what you want, and both the desire to attend and the expectation of attending college. We also include measures of adolescent health and health behaviors, including body mass index, self-reported health, depressive symptoms, smoking, binge drinking, and physical activity. We measure the adolescent family environment using the highest parental educational attainment, family welfare receipt, and family structure from the parent questionnaire and the Wave I in-home survey. Finally, we include a measure of neighborhood disadvantage at Wave I: a summary score for the census tract of residence including the proportion of female-headed households, households in poverty or receiving public assistance, unemployed adults, and adults with less than a high school education (Belsky et al. 2019).

School Characteristics and Types

We include secondary and postsecondary school characteristics that are parallel and capture resources, quality, and student composition (Table A2, online appendix). Measures for secondary school are from various sources, including the school administrator questionnaire implemented at Wave I and the Adolescent Health and Academic Achievement (AHAA) study conducted at Wave III. The AHAA merged data from the Common Core of Data, the Private School Survey, the Office for Civil Rights, and the School District Demographics System at the National Center for Education Statistics (NCES) to the schools and school districts where participants attended school at Wave I (Muller 2005; Muller et al. 2007). We examine nine measures of secondary school context to assess resources, quality, and student composition that might influence health and selection processes of postsecondary schools. We measure secondary school resources using the student–teacher ratio and per capita expenditures in the district. To measure school quality, we use the graduation rate, the percentage of 12th graders who proceed to postsecondary schooling, the percentage of students testing at grade level, and the average percentage of students who pass their grade level. The percentage of students ineligible for free and reduced-price lunch, the percentage of White students, and the percentage of students from families earning more than $150,000 per year are measures of student demographic composition.

At Wave IV, respondents reported the postsecondary institution from which they received their (most recent) bachelor's degree and the year they received the degree. Using the Integrated Postsecondary Education Data System from the NCES, we compile a dataset linking individuals to the characteristics specific to their college and the year they graduated (Gaydosh et al. 2019a). We also merge data from Opportunity Insights (Chetty et al. 2017), which are appropriate for Add Health respondents’ college context because these data include children born in 1980–1982 (Add Health mean year is 1979) and attending college at ages 19–22 in the early 2000s (Add Health mean year of graduation is 2003) (Gaydosh et al. 2019b). We examine nine measures of college context to assess the role of resources, quality, and student composition—domains similar to those used for secondary school characteristics. We capture resources using measures of endowment and instructional expenditures per student in 2000 dollars. To measure institutional quality, we use the six-year graduation rate, the average SAT score, the application rejection rate, and the college-specific intergenerational income mobility rate. Using linked tax records of parents and children, Chetty et al. (2017) calculated the intergenerational income mobility rate of the college as the percentage of students with parents in the bottom quartile of the income distribution who reached the top quartile of the income distribution by their early 30s. Finally, we measure the sociodemographic composition of the student body using the percentages of students not receiving financial aid, who are non-Hispanic White, and who are from families in the top 1% of the income distribution.

Our goal is to characterize general institutional contexts that might influence health using the specific individual institutional characteristics we described. We use k-means clustering to identify institution types using the individual measures of school characteristics. We combine all characteristics to fit three clusters of secondary school types and four clusters of postsecondary school types. The resulting clusters are the best-fitting number of clusters that also retain a sufficient sample size in each cluster to permit analyses stratified by ethnoracial group (Figures A1 and A2, online appendix). Note that we conducted clustering in the pooled sample to capture general stratification patterns in educational settings; however, results are substantively similar when we cluster institution types within ethnoracial groups. We label the three secondary school types as low, average, and high according to general patterns in resources and quality (Figure A3, online appendix). On the basis of the postsecondary school distributions, we identify four institution types: low status, average, advantaged, and elite (Figure A4, online appendix).

Analytic Strategy

We first estimate disparities by race and ethnicity in cardiometabolic risk by four-year college degree in the full Add Health Wave IV sample (see Figure 1). We then restrict subsequent analyses to respondents who completed at least a four-year bachelor's degree and present descriptive statistics by ethnoracial group (see Table 1). Next, we use Poisson regression to examine the association between college type and cardiometabolic health in early adulthood first in the full sample of college graduates (pooling data for White, Black, and Hispanic respondents) while controlling for ethnoracial group, biological sex, and Wave IV age. We control for whether the respondent was U.S.-born; results are robust to the exclusion of foreign-born respondents, and future research should consider the intersection of nativity, race, and ethnicity in shaping college graduates’ health. We begin by estimating results for models adjusted only for these key demographic variables, given that our primary aim is to describe the overall total association between college characteristics and cardiometabolic health. We then include adolescent precollege characteristics in the model to adjust for observed measures that influence selection into postsecondary institutions and predict health.

We investigate heterogeneity in the relationship between postsecondary institution type and cardiometabolic risk (1) by testing interaction terms in the pooled models and (2) by testing fully interactive models stratified by ethnoracial group. The stratified approach allows us to investigate heterogeneity among college graduates within ethnoracial groups and test for differential associations with institution type. A stratified analysis allows for distinct patterns in the association of all predictors, as is appropriate for the racialized U.S. education system, where the social construction of race undergirds the maintenance of White advantage (Sewell 2016; Williams 2019).

Although our analysis focuses on identifying variation in health by postsecondary institutional type, it is important to account for the nonrandom and racialized process of selection into institution types. We address selection in three ways. First, we include prospectively measured controls in our fully adjusted models for adolescent academic performance in secondary school and adolescent academic aspirations, adolescent health and health behaviors, family SES, and secondary school type based on several school characteristics. Second, in supplementary analyses, we estimate treatment effects of postsecondary institution type using inverse probability-weighted regression adjustment. This counterfactual approach considers selection into different postsecondary institution types as a function of observed adolescent academic performance and aspirations, adolescent health and health behaviors, family socioeconomic background, and secondary school characteristics (Table A3, online appendix). Third, we adjust for unobserved secondary school factors by exploiting the school-based design of Add Health and including secondary school fixed effects (Table A4). Results of the inverse probability-weighted regression adjustment and models with secondary school fixed effects are substantively similar to those of the main analysis.

Finally, we employ multivariate decomposition (Powers et al. 2011) to estimate how much of the observed group differences in cardiometabolic health among college graduates are due to differences in precollege selection factors and postsecondary institution type. Specifically, we are interested in the contribution of group differences in the distribution of graduation from different institution types and the effect of institution types on Black–White and Hispanic–White disparities in cardiometabolic risk. We employ the mvdcmp command in Stata 17, which provides an aggregate and detailed decomposition for all included covariates and tests of statistical significance. The observed Black–White and Hispanic–White difference in average cardiometabolic risk is additively decomposed into the proportion attributable to compositional differences between groups (i.e., differences in the types of colleges attended) and the proportion attributable to differential effects between groups (i.e., differences in the health benefit of the college types attended). We estimate cardiometabolic risk (CMR) as a function of a combination of a vector of predictors X (including institution type) and regression coefficients β:
CMR=F(Xβ),
where F(Xβ)=eXβ. The mean difference in CMR between groups (here, we use Black (A) and White (B) respondents) can be decomposed as follows:
CMRA¯CMRB¯ =  F(XAβA)¯F(XBβB)¯                                = F(XAβA)¯F(XBβA)¯E + F(XBβA)¯-F(XBβB)¯C                                =  k=1KEk+ k=1KCk,

where E refers to the group differences attributable to differences in characteristics between groups, and C refers to the part attributable to differences in the coefficients. In this equation, White respondents are the reference group, and Black respondents are the comparison group; a similar equation applies to White versus Hispanic respondents. The aggregate decomposition components E and C are further decomposed to estimate the contribution of each predictor or group of predictors in the model, a sum of weighted sums of the unique contributions Ek and Ck. All regression and decomposition analyses use weights to adjust for the sampling strategy of Add Health.

Results

Ethnoracial and Educational Disparities in Cardiometabolic Risk

Figure 1 presents predicted cardiometabolic risk for White, Black, and Hispanic adults without versus with a four-year college degree. This analysis controls for age, sex, nativity, and urban residence and allows the association between college completion and cardiometabolic risk to vary by ethnoracial group through interaction terms. We present these descriptive results for three reasons. First, we replicate well-established racial gradients in health, wherein individuals who are racialized as White experience lower cardiometabolic risk, on average, relative to individuals who are racialized as Black. This White health advantage is also evident, albeit smaller, relative to individuals who identify as Hispanic. Second, we document the expected relationship between educational attainment and health, particularly among White and Hispanic adults, wherein college completion is associated with lower cardiometabolic risk. Third, we aim to replicate two important patterns in health disparities research: (1) the relationship between college completion and health is weaker for Black individuals; and (2) ethnoracial disparities in health, particularly between White and Black adults, are largest among those with high educational attainment.

Among college graduates, overall levels of cardiometabolic risk are high, with an average of 2.52 high-risk markers, despite their average age of 28 (Table 1). White college graduates have the lowest levels of cardiometabolic risk (2.42), followed by Hispanic college graduates (2.76); Black college graduates have the highest levels (3.16). The cardiometabolic risk difference between White and Hispanic graduates is marginally significant (p = .07), whereas the difference between White and Black graduates is statistically significant (p < .001).

Differences in College Characteristics by Race and Ethnicity

Table 1 presents the distribution of college characteristics for White, Black, and Hispanic college graduates. Compared with White college graduates, Black college graduates attended postsecondary schools with lower endowments and expenditures, lower graduation rates, lower average SAT scores, fewer students from families in the top 1% of the income distribution, fewer students receiving no financial aid, and fewer White students. However, Black college graduates attended postsecondary schools with slightly higher income mobility rates and higher rejection rates than White graduates. In general, Hispanic graduates attended postsecondary schools much more similar to those of White graduates, except that Hispanic graduates attended postsecondary schools with lower endowments, higher mobility, higher rejection rates, fewer students receiving no financial aid, and fewer White students.

We present additional descriptive statistics on precollege selection factors by ethnoracial group further disaggregated by postsecondary institution type (Table 2). Overall, we find stronger evidence of positive selection into higher quality postsecondary educational institutions according to White and Hispanic students’ precollege characteristics such that adolescents with higher academic achievement, college plans, higher family SES, and attendance at higher quality high schools are more likely to attend higher quality colleges. Selection is weaker among Black adolescents, operating mainly through precollege academic achievement, college plans, and parental education.

Institution Type and Cardiometabolic Health

In the pooled sample, graduation from advantaged and elite postsecondary institutions is significantly associated with lower cardiometabolic risk compared with graduation from low-status postsecondary institutions (Table 3) when we control for only basic demographic covariates (Model 1). The associations for advantaged and elite postsecondary institutions are negative relative to low-status institutions. The associations between institution type and cardiometabolic risk are no longer statistically significant (although they remain negative) after we adjust for individual and secondary school characteristics that influence selection into institution type (Model 2). Our findings suggest that much of the health benefit of graduating from better institutions is driven by individuals’ precollege characteristics. Among college graduates, Black and Hispanic adults’ cardiometabolic risks are significantly higher than those of White adults (Model 1). The magnitudes of these differences are reduced when we control for precollege selection factors and are no longer statistically significant, although Black graduates’ cardiometabolic risk differs marginally from that of their White peers (p = .07). In other words, Black–White disparities in cardiometabolic risk among college graduates remain even after we adjust for precollege selection characteristics and postsecondary institution type. Thus, selection into postsecondary institutions does not explain the Black–White gap in health returns to college completion.

We investigate heterogeneity in the association between postsecondary institution type and cardiometabolic risk first by introducing interaction terms between institution type and ethnoracial group (Model 3). This analysis reveals important differences in the direction of the associations. For White graduates, postsecondary institutional quality is negatively associated with cardiometabolic risk. Relative to graduation from a low-status postsecondary institution, graduation from an average institution is not significantly different, although the direction of the coefficient suggests a reduction in cardiometabolic risk. However, degree completion from an advantaged postsecondary institution is associated with a reduction (0.16) in cardiometabolic risk compared with graduation from low-status institutions. Similarly, graduation from elite institutions is associated with a reduction in cardiometabolic risk (0.12) compared with graduation from low-status institutions. The coefficients for advantaged and elite postsecondary institutions are not significantly different. The pattern among White graduates mirrors the general educational gradient in health: greater educational attainment is associated with better health, and a higher quality education offers additional health benefits. Similar to results for the pooled sample, the association is no longer statistically significant when we adjust for adolescent characteristics, suggesting that the benefit of institution type might result from selection into advantaged institutions. The pattern of association between institution type and cardiometabolic risk does not differ significantly between White graduates and Hispanic graduates (Model 3). This finding also holds for the fully adjusted models (Model 4).

For Black college graduates, the associations for average and advantaged institution types are not significantly different relative to White graduates (Table 3, Model 3). However, degree completion from an elite institution is significantly associated with increased cardiometabolic risk (0.25) relative to degree completion from a low-status institution. This association remains statistically significant and has the same magnitude after we adjust for precollege selection characteristics (Model 4). Moreover, even after we control for institution type and allow the effect of institution type to vary by ethnoracial group, Black college graduates experience significantly higher cardiometabolic risk than White college graduates (0.25 unadjusted, 0.11 adjusted).

Next, we estimate models stratified by ethnoracial group and use the four postsecondary institution types to predict cardiometabolic score (Table 4). Importantly, this approach permits differences in the meaning of measures and relationship patterns across groups and acknowledges that selection into higher education is not race-neutral (as demonstrated in Table 2). Here, again, we find consistent reductions in cardiometabolic risk with increasing postsecondary institution quality among White graduates, particularly for advantaged and elite institutions relative to low-status institutions (Model 1). The pattern is similar, albeit not statistically significant, for Hispanic graduates (Model 5). The significant association of institution type for White graduates is largely accounted for by precollege selection factors (Model 2). In contrast, no significant association of institution type with cardiometabolic risk for Black graduates is evident when we do not adjust for precollege selection factors (Model 3), but the significant importance of institution type is apparent after we account for precollege selection (Model 4). Specifically, relative to graduating from low-status institutions, graduating from average postsecondary institutions is associated with lower cardiometabolic risk and graduation from elite postsecondary institutions is associated with higher cardiometabolic risk among Black graduates. This association is more pronounced after we control for precollege selection factors, wherein Black graduates of elite institutions have lower SES and attend lower quality secondary schools compared with their peers who graduate from lower quality postsecondary institutions. Figure 2 displays the magnitude of these associations in terms of predicted cardiometabolic risk adjusted for precollege selection factors.

Decomposition of Racial and Ethnic Disparities in Cardiometabolic Health

Finally, we decompose ethnoracial differences in cardiometabolic risk among college graduates. We are primarily interested in the contribution of postsecondary institution type (as captured in the independent variables) and graduates’ responses to these institution types (as captured in coefficient values). We contrast the contribution of postsecondary institution type to that of precollege selection factors organized into groups of variables: demographics, adolescent academics, adolescent health, adolescent SES, and secondary school type.

We first examine the difference in cardiometabolic risk between Black and White college graduates, both unadjusted and adjusted for adolescent characteristics (Table 5). The average difference between Black and White adult cardiometabolic risk is 0.743. More than half (58%) the cardiometabolic risk difference between Black and White college graduates is attributed to differences due to endowments; less than half (42%) is attributed to differences due to coefficients, with much of that contribution accounted for by differences in intercepts. Focusing first on the contribution of postsecondary institution type, we find that equalizing the distribution of college types attended by Black graduates to that experienced by White graduates would increase the Black–White cardiometabolic risk disparity by nearly 4%. Moreover, if Black graduates experienced the same health returns to institution type as White graduates, the cardiometabolic risk gap would also increase by more than 14%. However, these aggregate contributions of institutions ignore differences by type, particularly average and elite institutions. As a reminder, in race-stratified models adjusted for precollege selection factors (Table 4), Black graduates experienced a benefit of average institution graduation and a cost of elite institution graduation (relative to low-status institutions), whereas White graduates did not see significant differences in cardiometabolic risk by institution type. The gap in cardiometabolic risk would decrease meagerly, by 0.4%, if Black graduates attended average institutions at the same rate as White graduates but would increase by 16% if Black graduates had the same returns to average institution graduation as their White peers. If Black graduates attended elite institutions at the same rate as White graduates, the gap in cardiometabolic risk would increase by roughly 4.5%. However, if Black graduates had the same returns to elite institution attendance as their White peers, the Black–White gap in cardiometabolic risk would decrease by 5%. The protective association of graduation from average institutions is greater for Black graduates than for White graduates, but the protective association of graduation from elite institutions is smaller for Black graduates than for White graduates.

Considering precollege selection factors, secondary school type does not contribute significantly to the Black–White disparity in cardiometabolic risk, in contrast to the role of postsecondary institutions. However, differences in endowments of adolescent academics (14%) and health (41%) account for the largest statistically significant share of the Black–White cardiometabolic risk difference. If Black graduates had the same distribution of adolescent academics and health as White graduates, the gap would be reduced by 55%, or 0.4 points of cardiometabolic risk. Differences in the effect of adolescent SES account for the largest significant share of the Black–White difference in cardiometabolic risk. If Black graduates enjoyed the same benefit of adolescent SES for adult cardiometabolic risk, the disparity would be reduced by 37%. The decomposition results regarding the contribution of precollege selection factors underscore the extent to which White graduates are disproportionately advantaged relative to their Black graduate peers even before college graduation. The results also point to how the differential benefit of such selection factors contributes to adult health disparities observed more than a decade later.

In contrast to our decomposition results for Black–White disparities, we find no significant contributions of postsecondary institution type or precollege selection factors to the observed Hispanic–White disparity in cardiometabolic risk (Table 6). The average difference between Hispanic and White adult cardiometabolic risk is smaller (0.338). Approximately 39% of the difference in cardiometabolic risk between Hispanic and White college graduates is attributable to differences due to endowments. Most of the difference (61%) is attributable to differences due to coefficients, with much of that contribution accounted for by differences in intercepts. Differences in the distribution of postsecondary institution types attended and differences in the effect of those institution types do not contribute significantly to the observed Hispanic–White disparity in adult cardiometabolic risk.

Robustness

Our substantive results do not change under different specifications and analytic strategies. In addition to adjusting for observed precollege selection factors, we interrogate the possibility of confounding or selection using inverse probability-weighted regression adjustment and secondary school fixed effects (Tables A3 and A4, online appendix). The significant health protective association of graduation from an average college (relative to graduation from a low-status institution) for Black graduates remains, as does the significant increase in cardiometabolic risk associated with elite college graduation for Black graduates. The associations between postsecondary institution type and adult cardiometabolic risk among Black college graduates are not accounted for by unobserved time-invariant characteristics of the secondary schools attended and remain even when we compare individuals coming from the same secondary schools.

Discussion

In this article, we addressed three questions regarding differences in the physical health of White, Black, and Hispanic college graduates. Using nationally representative longitudinal data with biomarker measurement of physical health from Add Health, we used new data on college characteristics to examine how postsecondary institution types shape college graduates’ physical health and whether this relationship differs by ethnoracial group. In general, more selective institutions with greater resources, higher quality, and more advantaged students are protective of health. However, this general pattern is almost completely accounted for by selection into different institution types. Moreover, this general pattern masks underlying heterogeneity by ethnoracial group. In particular, Black college graduates who attended elite institutions have worse health; this effect is not accounted for by observed characteristics that influence selection into institution type. Finally, differences in the college type attended and the effect of college type on health account for a modest but statistically significant amount of Black–White differences in adult cardiometabolic risk among college graduates, but they are not significantly implicated in Hispanic–White differences in cardiometabolic risk.

Our findings provide the first estimates based on biomarker measures of health risk to examine the effect of postsecondary institution type on the health of college graduates. The general patterns we document reflect a process of horizontal stratification: the benefits associated with college completion, especially for White graduates, are the greatest at institutions at the top of the educational hierarchy. We also find support for ethnoracialized differences in the health of college graduates according to institution type. Figure A5 (online appendix) presents predicted cardiometabolic risk by institution type for White, Black, and Hispanic adults and adds results for individuals without a college degree for reference. The physical health benefits associated with college completion among White graduates are largely robust across institution types, supporting the conceptualization of higher education institutions as racialized organizations that are sites for the reproduction and maintenance of racial inequality (Ray 2019). White college graduates reap health benefits of educational attainment regardless of institutional type, quality, and characteristics. The pattern is similar for Hispanic graduates, although low sample sizes for Hispanic graduates of advantaged and elite institutions limit the statistical power. In contrast, Black college graduates’ health is highly contingent on the institution type attended. Black graduates of traditionally privileged, wealthy institutions are predicted to have similar cardiometabolic risk to their peers without a college degree. Relational processes of discrimination, stress, and vigilance are certainly operating (Hudson et al. 2020; Jack 2015, 2016), but we cannot test this mechanism directly. In supplementary analyses, we explored the potential mechanisms of advanced degree completion, occupational prestige, adult neighborhood context, and adult mental health. None of these measures have a statistically significant main effect on cardiometabolic health, and the associations of interest with institution type are unchanged (Tables A1 and A5, online appendix). Future work should consider college graduates’ subsequent adult environments as potential mediators of the role of institutional context. The interrelationship between mental and physical health is another fruitful area for future investigation. Nevertheless, our findings are consistent with previous research establishing the connection between chronic stress and biomarkers of health risk (Goosby et al. 2018; Hänsel et al. 2009; Harris and Schorpp 2018; Pearlin et al. 2005). Our findings are particularly notable given that the physiological effects are observed several years after the college experience.

Our findings regarding the role of precollege characteristics in accounting for the health benefit of college quality among Whites warrant greater attention. The importance of adolescent characteristics in shaping White college graduates’ educational and health trajectories demonstrates the power and persistence of family social status in preserving White privilege in social stratification processes (Chetty et al. 2018; Fiel 2020; Oh and Kim 2019; Song et al. 2020; Zhou 2019). In contrast, adolescent characteristics influencing selection into institution type do not explain the health cost associated with elite college graduation among Black graduates. This finding contributes new insight into why racial disparities in the health benefits of education are greatest at high SES levels: Black graduates are more likely to attend lower quality schools, and those who attend elite institutions might incur a health penalty. We want to emphasize that this finding does not mean that Black college-goers should avoid elite institutions, but instead that historically White and privileged spaces have an opportunity to create environments that support Black students’ success and realization of the full benefits of college education.

Our results are consistent with other paradoxical findings of growing racial disparities with increasing SES. Upward mobility for Black adults necessitates the navigation of racial boundaries in school, work, and neighborhood settings that are predominantly White (Higginbotham 2001; Hudson et al. 2020). In such settings, upwardly mobile Black adults report higher levels of racial discrimination than peers who remain at lower levels of SES (Assari and Lankarani 2018; Hudson et al. 2012; Wingfield and Chavez 2020). When navigating such spaces, Black adults cope by constructing “public identities” that foreground their high SES in hopes of avoiding or lessening exposure to racial discrimination (Lacy 2004, 2007), and they shoulder the burden of performing “equity work” to promote diversity in White-dominated workplaces while trying to disprove stereotypes themselves (Evans and Moore 2015; Wingfield and Chavez 2020). These additional roles and demands for upwardly Black adults require them to expend considerable emotional, physical, and psychological energy to fit into predominantly White educational, work, and public settings, harming their overall well-being (Hicken et al. 2018; Wingfield 2019). The impact on their mental health remains a puzzle, but Hudson and colleagues (2016) noted the greater prevalence of underdiagnosis of depression among Black adults.

The research presented here provides a descriptive foundation for future investigations of the importance of educational context. Although we can measure compositional and resource characteristics with the data we use, it remains unclear what particular aspects of these institutions or these characteristics promote or constrain the health benefit of college completion, particularly for Black graduates. Furthermore, despite the clear pattern of findings for White and Black young adults, the evidence is much more mixed for Hispanic young adults. These mixed findings are consistent with previous work documenting considerable heterogeneity by nativity and country of origin (Beltrán-Sánchez et al. 2016; Goldman et al. 2006; Kimbro et al. 2008). Given sample size limitations, we analyze all Hispanic graduates together. Future research should prioritize considering within-group heterogeneity among Hispanic graduates as well as Black graduates (Hamilton and Hummer 2011).

The analysis is limited to the available data. We focus here on college graduates because of incomplete data on institutions for those with some college education. Yet, compelling evidence suggests that those who complete some college suffer a health penalty (Zajacova et al. 2012), and this educational attainment category is the most predominant among contemporary American adults. Also limiting is that although we know the characteristics of the institutions attended, we know nothing about the experience of respondents while they were enrolled in college. Examining Black graduates of HBCUs would be important in illuminating the mechanisms we propose; unfortunately, our data include only 190 such graduates in the sample. In an ancillary race-stratified analysis including HBCUs as their own institution type, graduation from such an institution had a positive but not statistically significant coefficient relative to graduation from average institutions. Future research in this area would be fruitful.

Finally, our study examines cardiometabolic risk in early adulthood, a composite measure of health risk. Although biomarker measurements enable the investigation of underlying risks before diseases manifest, determining whether such risks will ultimately translate into morbidity and mortality will require that we follow these individuals throughout adulthood. Perhaps upwardly mobile individuals accumulate additional advantages as they progress through their socioeconomic trajectories and subsequently translate this advantage into better health. Future work must document health disparities across the life course to better understand how elevated health risk in early adulthood influences health and aging trajectories.

This study contributes to our understanding of how health disparities unfold across the life course. Health inequalities are important in their own right and in their role in perpetuating the intergenerational transmission of SES. Our findings demonstrate the role of postsecondary institutions in maintaining racialized systems of stratification. Understanding these inequalities is critical for addressing future economic inequality and improving population health.

Acknowledgments

We are grateful to Taylor Hargrove, Alexis Dennis, and Jordan Conwell for their comments on this article. This research was supported by a 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 (NICHD). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Partial support for this research was provided by grants from the NICHD (R21 HD095448, P2C HD050924, P01 HD31921) and the National Institute on Aging Network on Life Course and Health Dynamics and Disparities (R24 AG045061). This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grant P01HD31921 from the NICHD, with cooperative funding from 23 other federal agencies and foundations. Information about how to obtain the Add Health data files is available on the Add Health website (http://www.cpc.unc.edu/addhealth).

Note

1

For detailed Add Health data collection procedures and biomarker validation, see Hussey et al. (2015) and Nguyen et al. (2011).

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