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. Author manuscript; available in PMC: 2022 Jan 1.
Published in final edited form as: Nurs Res. 2021 Jan;70(5):S31–S42. doi: 10.1097/NNR.0000000000000527

Racial and Economic Adversity Differences in Stress Markers and Immune Function among Urban Adolescents

Jodi L Ford 1, Christopher R Browning 2, Samantha J Boch 3, Darlene A Kertes 4, Jake Tarrence 5, Baldwin M Way 6, Kammi K Schmeer 7
PMCID: PMC8515952  NIHMSID: NIHMS1713202  PMID: 34173379

Abstract

Background:

Exposure to racism and associated adversities, such as poverty, are hypothesized to contribute to racial inequities in health via stress and immune pathways. Furthermore, the effects of adversity may be more salient during sensitive developmental periods. Our study examined racial differences in stress and immune biomarkers during adolescence and the effects of exposure to economic adversity at distinct developmental time periods, and cumulatively in accounting for potential racial differences.

Methods:

Secondary analysis of the Adolescent Health and Development in Context study was conducted. Data were derived from self-administered surveys, interviews, smartphone-based, geographic-explicit, ecological momentary assessment, stress biomarkers (evening salivary cortisol over six nights and hair cortisol), immune biomarkers (salivary shedding of Epstein-Barr virus [EBV] DNA among EBV-positive adolescents). Current socioeconomic status (SES) measures included annual household income and caregiver education. Caregivers also reported experiences of bankruptcy, difficulty paying bills, receipt of food stamps/Supplemental Nutrition Assistance Program/ electronic benefit transfer, and job loss when the child was between birth–5 years, 6–10 years, and 11 years or older. An affirmative response to any item was defined as exposure to economic adversity for that developmental time period (yes/no). A cumulative economic adversity measure was calculated as the sum of exposures across developmental periods (never exposed = 0 to exposed across all time periods = 3). Descriptive and multivariable regression analyses were conducted, accounting for covariates.

Results:

Black/African American adolescents had higher salivary cortisol concentration, higher hair cortisol concentration, and an increased odd of salivary shedding of EBV DNA compared to White adolescents. Racial differences were not attenuated by current SES or economic adversity (developmental period or cumulatively).

Discussion:

Our study provides evidence that stress and immune biomarkers differ by race as early as adolescence and may be one pathway through which racism and associated adversities contribute to racial health inequities. Further research on the contribution of multiple adversities beyond poverty to racial inequities in physiologic stress and health is critical for informing effective prevention and intervention efforts.

Keywords: cortisol, Epstein-Barr virus, immune function, racial differences, racism, stress

Racial inequities in health are pervasive in the U.S. as Black/African Americans are more likely than their White counterparts to suffer from poor birth and pregnancy outcomes, infectious and chronic disease, and premature mortality (National Academies of Sciences, Engineering, and Medicine, 2017). Racism and the associated systematic exposure to adverse social conditions (e.g., poverty, residential and educational segregation, unsafe housing and living environments, violence, etc.) are hypothesized to be the root causes of racial inequities in health that often begin early in life and persist across the life span (Bailey et al., 2017; Goosby et al., 2018; Shonkoff et al., 2021; Trent et al., 2019). Life-course and stress theories posit that the chronic stress associated with racism and adverse exposures negatively affects health through the damage to organs and tissues that occurs due to recurrent and prolonged activation of physiologic stress response systems and subsequent immune dysregulation. Furthermore, the effects of chronic stress may be more salient if exposure to adversity occurs during sensitive developmental periods or life transitions, such as childhood and adolescence (Goosby et al., 2018; Shonkoff et al., 2021).

Prior research supports this line of inquiry as Black/African American youth and adults are more likely than their White counterparts to experience dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis. Specifically, researchers have found Black/African American youth and adults are more likely than White youth and adults to experience blunted salivary cortisol diurnal rhythm and elevated cortisol concentration at bedtime (Deer et al., 2018; DeSantis et al., 2007, 2015), decreased morning salivary cortisol concentration (Martin et al., 2012), increased salivary cortisol reactivity with delayed recovery in response to an experimental social stress test (Tackett et al., 2017), and more recently, elevated hair cortisol concentration (Lehrer et al., 2020; Wosu et al., 2015). While longitudinal studies investigating the effects of HPA dysfunction on long-term health outcomes are limited, a recent meta-analysis found robust prospective and cross-sectional associations between blunting of the salivary diurnal curve and impaired physical (e.g., immune and inflammatory diseases, cancer, body mass index [BMI]/obesity, mortality, etc.) and mental health (e.g., depression; Adam et al., 2017).

Racial differences in immune function, including reactivation of latent herpes viruses—a marker of cell-mediated immune function—have also been found. Specifically, Black/African American youth and adults are more likely than their White counterparts to experience reactivation of Epstein-Barr virus (EBV; Dowd et al., 2014; Ford & Stowe, 2013, 2017) and cytomegalovirus (Dowd & Aiello, 2009) as manifested by higher levels of antiviral immunoglobulin G (IgG) antibodies or increased odds of salivary shedding of EBV DNA among those with prior latent viral infection. One study found Black–White differences among adults for reactivation of the herpes-simplex virus, but not EBV (Stowe et al., 2010). Chronic or repeated latent viral reactivation is of concern as it can lead to prolonged or recurrent inflammation and, depending on the pathogen, increase host susceptibility to other infectious pathogens, cancer, or chronic disease (e.g., cardiovascular disease and autoimmune disorders; Aiello et al., 2010; Ford & Stowe, 2013; Longnecker & Neipel, 2007).

Because Black/African American children and adolescents are more likely than their White peers to experience poverty as a consequence of racism (National Academies of Sciences, Engineering, and Medicine, 2019; Trent et al., 2019), deprivation of material and social resources associated with poverty may be one explanation for the racial differences observed in physiologic stress (Trent et al., 2019). In addition, researchers have found low socioeconomic status (SES) to be directly associated with irregularities in cortisol concentration and latent viral infection (Deer et al., 2018; DeSantis et al., 2015; Dowd et al., 2012). However, these findings are not ubiquitous as some studies found no direct effect of current SES on stress or immune outcomes (DeSantis et al., 2007; Dowd et al., 2014; Ford & Stowe, 2013), and none found current SES explained the racial differences in these outcomes (Deer et al., 2018; DeSantis et al., 2007, 2015; Dowd et al., 2014; Ford & Stowe, 2013). Thus, a better understanding of the potential effect of low SES experienced at distinct phases of development and cumulatively across early life development in explaining the racial differences in physiologic stress and immune function is needed.

The current study builds on this prior research through the examination of the extent to which racial inequities exist across two biomarkers of cortisol activity (salivary and hair cortisol) and one marker of cell-mediated immune function (salivary shedding of EBV DNA among EBV IgG positive adolescents) in a racially and socioeconomically representative sample of urban adolescents. In addition, we examined the extent to which economic adversity at distinct developmental time periods (infancy to early childhood, middle childhood, and preadolescence to adolescence) and cumulatively accounted for potential racial differences. Our two cortisol markers offer unique contributions as salivary cortisol measures momentary HPA axis activity at bedtime. In contrast, the hair cortisol captures cumulative exposure to cortisol over time as each 1 cm of hair growth approximates 1 month of mean cortisol output (Russell et al., 2012). To date, few studies examine multiple stress biomarkers enabling a robust investigation of potential racial differences in physiologic stress.

Methods

Study Design

A secondary analysis was conducted using data from two linked studies: The Adolescent Health and Development in Context study (AHDC), a prospective cohort study, and the Linking Biological and Social Pathways to Adolescent Health and Well-Being study, which collected stress biomarkers among a subsample of youth participating in the AHDC study. The study design and sampling procedures have been described in previous analyses (Browning et al., 2017, 2021; Ford et al., 2019; Ford & Stowe, 2017).

Sampling and Data Collection

The studies were conducted in Columbus, Ohio, and several surrounding suburban municipalities in 2014–2016. Sampling, recruitment, and data collection were performed in collaboration with the Center for Human Resources Research—a survey research center housed within the university with experience conducting prospective cohort studies. Youth in the study area were recruited using a mix of vendor- and school-based address lists. Random households were drawn from the list and mailed a flyer that described the study with instructions to call if they were interested in participating. Trained interviewers also called to determine interest and eligibility (youth aged 11–17 years, at least one primary caregiver, and English speaking). If the household had more than one youth eligible for the study, one focal youth was randomly selected for participation in the AHDC study. The university institutional review board approved both studies, and parental consent and youth assent were obtained prior to data collection.

All data were collected in the home by trained interviewers and included (a) an entrance face-to-face interview and self-administered survey with both the focal youth and their primary caregiver, (b) a 7-day smartphone-based Global Positioning System tracking, Ecological Momentary Assessment (EMA), and nightly salivary collection for cortisol with the youth, and (c) a face-to-face exit interview and biomarker collection with the youth (hair for cortisol and saliva for EBV antibodies and viral DNA) and a self-administered survey with the primary caregiver. The interviewers reviewed and provided written instructions to the youth on the nightly salivary collection, including the need to record the collection date and time and place the specimen in the home freezer immediately after collection. In addition, these instructions were sent to the youth nightly via the EMA. The interviewer collected saliva from the youth at the exit interview for EBV IgG antibody and viral DNA. The saliva collection for cortisol and EBV measures were collected via passive drool using a saliva collection aid. The youth were instructed to avoid eating, drinking, and brushing their teeth 20 min before data collection, and to rinse their mouth with water 10 min beforehand. The interviewer transported all saliva specimens from the home to the survey research center. They were stored at −20°C and then transferred on dry ice to the −80°C freezers at the university laboratory until assay. The interviewer collected the hair sample at the exit interview with instructions to cut approximately 25–75 mg of hair (0.4–1 cm in diameter) from the posterior vertex region of the scalp cutting as close to the scalp as possible with thinning shears. Thinning shears were used to maximize the amount of hair collected at once while minimizing the visibility that the hair was cut. Youth were surveyed during the visit on their hair care practices, such as frequency of washing, chemical treatments (e.g., dyes, perms, straighteners), and hair product use. Hair specimens were stored at room temperature prior to assay.

Measures

Dependent Variables

Salivary cortisol:

Before assay, the saliva samples were thawed completely and then vortexed and centrifuged at 1,500g for 15 min. The saliva was then assayed using the Salimetrics® Cortisol Enzyme Immunoassay Kit (Carlsbad, CA). All samples from each participant were assayed simultaneously, on the same plate, and in duplicate. Inter- and intra-assay coefficients of variation were < 10%. The My Assay® analytic software program using the Salimetrics® protocol was used to calculate the cortisol concentrations in µg/dL. Due to the skewed nature of the salivary cortisol measures, the values were natural log-transformed for statistical analysis.

Hair cortisol:

Hair was prepared for assay at the Ohio State University College of Nursing Stress Science Lab using an adapted protocol (Meyer et al., 2014) as described in prior research (Ford et al., 2019). Prior to the assay, the hair sample (1 cm to 3 cm) was washed with high-performance liquid chromatography (HPLC) grade isopropanol and dried over 1 to 3 days. The hair was then minced in a microcentrifuge tube before being grounded into powder using a Retsch® 400 Mill for approximately 5 min. A total of 1.1 ml of HPLC grade methanol was added to the ground sample and incubated for 18–24 hr at room temperature with constant agitation. The tubes were then centrifuged at 5,000g for 5 min at room temperature to pellet the powdered hair. The entire amount (~1 ml) of supernatant was transferred to a clean microcentrifuge tube, and the methanol was removed by evaporation using a stream of air for 6–8 hr at room temperature. The cortisol extract was immediately reconstituted in 100ul of Salimetrics® immunoassay cortisol analysis diluent buffer. Hair samples were assayed in duplicate using the Salimetrics® high sensitivity enzyme immunoassay cortisol kit. Inter- and intra-assay coefficients of variation were < 10%. The My Assay® analytic software program using the Salimetrics® protocol was used to calculate the cortisol concentrations in µg/dL. Hair cortisol concentration was converted to pg/mg using the formula provided by Meyer et al. (2014). Due to the skewed nature of the hair cortisol measures, the values were natural log-transformed for statistical analysis.

Salivary Shedding of EBV DNA:

A primary objective of this study was to examine the potential for EBV reactivation through salivary shedding of EBV DNA; thus, the sample for this analysis included only those youth who were EBV viral capsid antigen (VCA) IgG positive (had evidence of past primary EBV infection) determined through an adapted enzyme-linked immunosorbent assay (ELISA) method using saliva (Stowe et al., 2014). In preparative pilot work, we found a 0.92 correlation coefficient between serum and salivary EBV IgG antibodies in which an antibody titer greater than 0.02 was suggestive of prior EBV infection. Thus, youth with a salivary EBV VCA IgG antibody level greater than 0.02 were considered EBV positive (Ford & Stowe, 2017; Stowe et al., 2014).

Salivary shedding of EBV DNA was measured dichotomously due to the skewed nature of the distribution (36% of the youth had no evidence of salivary shedding); thus, youth who had 10 or more copies (10 copies was the lower bound detectable level) of EBV DNA in their saliva (yes = 1) were compared to youth who were below the detectable level. The EBV DNA viral load assessment was accomplished using polymerase chain reaction (PCR) methodology at Microgen laboratories (Mehta et al., 2013; Stowe et al., 2007). DNA was isolated from saliva using the QiaAmp blood kit (Qiagen, Valencia, CA). EBV copy numbers were measured in samples using real-time PCR with PCR primers that amplify a portion of the BALF5 gene. Real-time fluorescence measurements were taken over 40 cycles using an Mx3005P real-time PCR instrument, and unknowns were compared to a standard curve (serially diluted plasmids containing single copy viral genes). Copy numbers were then calculated automatically using the StrateGene® software (Bellingham, WA).

Independent Variables of Interest

Race.

Dichotomous measures based on self-report included non-Hispanic Black/African American and non-Hispanic White (reference) adolescents.

Current SES.

Caregiver reported measures of current SES included annual household income (categorical measure: $0 to $30,000, $30,001 to $60,000, and $60,001 and greater [reference]) and educational attainment (less than high school, high school degree, some college, bachelor’s degree, and graduate or professional degree [reference]).

Economic Adversity.

Caregivers were queried on youth exposure (yes/no) to the following four economic adversities during the subsequent time periods: birth–5 years (infancy to early childhood), 6–10 years (middle childhood), and 11 years and greater (preadolescence to adolescence): experienced bankruptcy, had difficulty paying bills, received food stamps/ Supplemental Nutrition Assistance Program (SNAP)/electronic benefit transfer (EBT), and a parent lost their job. Youth exposed to any one of the four items were defined as having been exposed to economic adversity for that developmental time period (yes/no for each period). A cumulative economic adversity measure was calculated using a sum score of exposure across the developmental periods (never exposed = 0 to exposed across all time periods = 3).

Covariates

Additional measures in the analysis included the following: sex: youth self-identification as male or female (reference); age (continuous measure 11 to 17 years); caregiver married (yes vs. no); season of data collection (fall, winter, spring vs. summer [reference]); household size (caregiver reported number of people living in the household), weight status (objective height and weight collected and calculated according to the Centers for Disease Control and Prevention child and adolescent BMI guidelines with overweight and obese categories compared to the reference underweight/normal weight; Kuczmarski et al., 2002)); and pubertal development (youth self-reported sex-specific scales adapted from Petersen et al., 1988; Ford & Stowe, 2017; Petersen et al., 1988) in which youth were asked about their perceptions of pubertal development (both sexes were asked about growth spurt in height, growth of pubic hair, and skin changes; males were asked about voice change and facial hair and females were asked about breast growth and menstruation onset). Response options for each item ranged from 1 (no development) to 4 (development complete). To create the composite, the item scores were summed and averaged for those who had complete data on all five items; those missing a response to any item were set to missing on the scale. For the hair cortisol analysis, additional covariates included hair length in centimeters, hair chemically treated (yes = 1), and daily hair washing (yes = 1). For the salivary cortisol analysis, additional covariates include day-level measures of time since waking in hours and waking time.

Analytic Samples

The sample size for each outcome varied slightly due to timing of collection and methodological challenges (e.g., insufficient hair length, refusals, and outlier results). The analytic sample across all outcomes included only youth who self-identified as non-Hispanic Black/African American or non-Hispanic White and excluded youth on corticosteroids due to their effect on cortisol and immune response. The final analytic sample sizes were: (a) salivary cortisol n = 2,648 salivary cortisol samples nested within 494 adolescents (5.4 samples on average per participant, range 1–6); (b) Hair cortisol n = 453 adolescents; and (c) EBV reactivation n = 426 adolescents who were EBV positive (79% of the eligible sample).

Analytic Strategy

Univariate analysis was conducted to describe the characteristics of the total sample for each outcome—salivary cortisol, hair cortisol, and salivary shedding of EBV DNA. Racial differences in current SES and economic adversity were described, and statistical significance was tested via chi-square and bivariate linear regression. In addition, multivariable logistic regression was conducted to examine racial differences in salivary shedding of EBV DNA, multivariable linear regression to examine racial differences in hair cortisol concentration, and multilevel linear regression analysis to examine racial differences in salivary cortisol concentration. Four models were analyzed for racial differences in each outcome: without covariates (Model 1); with current SES and covariates (Model 2); with current SES, economic adversity by developmental period (birth–5 years, 6–10 years, and 11 years and greater), and covariates (Model 3); and with current SES, cumulative economic adversity, and covariates (Model 4). Additionally, we conducted post hoc sensitivity analysis to examine separate relationships for current household income and caregiver level of education and each of the three outcomes; the findings of the post hoc analysis were consistent with those presented in Model 2 for all three outcomes in which current household income and caregiver level of education are modeled simultaneously. Finally, missing responses to the independent variables were examined, and multiple imputations of independent variables using 25 imputations were conducted for all regression analyses. The puberty measure had the highest proportion of missing data (21%–23% across the three outcomes), with most due to unknown responses. Analysis was conducted using SAS® 9.4 (Cary, NC) for the hair cortisol and salivary shedding of EBV DNA outcomes using Proc MI for the multiple imputation and R was used for the salivary cortisol outcomes with multiple imputation via chained equations using the Multivariate Imputation by Chained Equations (MICE) package (25 multiple imputations used for all analyses; van Buuren & Groothuis-Oudshoorn, 2011).

Results

The descriptive characteristics for the total sample of adolescents for all three outcomes are presented in Table 1. The mean logged cortisol level for saliva was 0.12 µg/dL, and for hair, it was 0.98 pg/mg. Nearly 64% of the adolescents were shedding EBV DNA in the saliva, suggestive of EBV reactivation. Across the outcomes, approximately 35%–38% of the youth self-identified as Black/African American. Current SES was fairly consistent across the outcomes with 3%–5% of the primary caregivers having less than a high school degree, 13%–14% with a high school degree, 29%–30% with some college, 27%–29% with a bachelor’s degree, and 21%–24% with a graduate or professional degree. Furthermore, across outcomes, the annual household income was less than $30,000 a year for 26%–28% of the adolescents, between $30,001-$60,000 for approximately 20% of the adolescents, and $60,001 and higher for 44%–46% of the adolescents. Across all the outcomes, approximately a third of the adolescents experienced economic adversity from birth to age 5 years (36%–40%), 6–10 years (33%–37%), and 11 years and higher (28%–33%) with a slightly higher proportion prior to age 5 years. For cumulative economic adversity, 40%–47% of the youth across outcomes never experienced economic adversity, approximately 19% experienced it at one developmental time period, 12%–15% experienced it at two time periods, and 18%–19% experienced economic adversity across all three time periods. Across the outcomes, 48%–51% of the adolescents were male, the average age was 14 years, approximately 60% of the primary caregivers were married, the average household size was about four, and the average pubertal development was 3 (range 1–4). Approximately 2% of the adolescents were underweight, 56%–60% were normal weight, 15%–18% were overweight, and 18%–19% were obese. Season of collection had some variation across outcomes due to timing of collection. Table 1 includes descriptive characteristics for additional covariates specific to the cortisol collections.

Table 1.

Descriptive Characteristics of the Adolescents for Each Sample by Outcome

Salivary Cortisol
Sample
N=494		 Hair Cortisol
Sample
N=453		 Salivary EBV
Sample
N=426
n % n % n %
Youth race
 Black/African American 174 35.2 158 34.9 162 38.0
 White 320 64.8 295 65.1 264 62.0
Caregiver education
  Less than high school 20 4.0 15 3.3 18 4.2
 High school degree 69 14.0 62 13.7 63 14.8
 Some college 149 30.2 132 29.1 130 30.5
 Bachelor’s degree 142 28.7 135 29.8 119 27.9
 Graduate/prof degree 109 22.1 109 23.2 93 21.8
 Missing 5 1.0 4 0.9 3 0.7
Household income
 $0-$30,000 141 28.5 119 26.3 122 28.6
 $30,001-$60,000 101 20.5 92 20.3 85 19.9
 $60,001 and higher 219 44.3 210 46.3 191 44.9
 Missing 33 6.7 32 7.1 28 6.6
Economic adversity developmental period
 0–5 years
  Yes 185 37.5 164 36.2 170 39.9
  No 296 59.9 279 61.6 241 56.6
  Missing 13 2.6 10 2.2 15 3.5
 6–10 years
  Yes 176 35.6 153 33.8 159 37.3
  No 306 61.9 288 63.6 249 58.5
  Missing 12 2.4 12 2.6 18 4.2
 11 years and more
  Yes 159 32.2 131 28.9 133 31.2
  No 324 65.6 310 68.4 276 64.8
  Missing 11 2.2 12 2.6 17 4.0
Economic adversity cumulative
 Never 220 44.5 213 47.0 172 40.4
 1 time period 97 19.6 87 19.2 84 19.7
 2 time periods 62 12.6 55 12.2 64 15.0
 3 time periods 97 19.6 82 18.1 80 18.8
 Missing 18 3.6 16 3.5 26 6.1
Youth sex
 Male 237 48.0 232 51.2 219 51.4
 Female 257 52.0 221 48.8 207 48.6
Caregiver married
 Yes 303 61.3 282 62.2 259 60.8
 No 188 38.1 167 36.9 159 37.3
 Missing 3 0.6 4 .9 8 1.9
Youth weight status
 Underweight 10 2.0 11 2.4 10 2.4
 Normal weight 299 60.5 269 59.4 241 56.6
 Overweight 74 15.0 73 16.1 79 18.5
 Obese 96 19.4 90 19.9 78 18.3
 Missing 15 3.0 10 2.2 18 4.2
Season of collection
 Winter 132 26.7 120 26.5 144 33.8
 Spring 147 29.8 141 31.1 36 8.5
 Summer 104 21.0 98 21.6 116 27.2
 Fall 111 22.5 94 20.8 130 30.5
Chemical use in hair
 Yes 76 16.8
 No 370 81.7
 Missing 7 1.5
Washes hair daily
 Yes 178 39.3
 No 257 56.7
 Missing 18 4.0
Salivary shedding of EBV DNA
 Yes 272 63.9
 No 154 36.2
n Mean (SD) n Mean (SD) n Mean (SD)
Logged salivary cortisol1 2648 0.12 (0.15) 453 0.98 (1.1) -- --
Time since waking 2540 13.5 (2.5) -- -- -- --
Waking time 2540 7.8 (1.8) -- -- -- --
Age (range 11–17) 494 14.6 (1.8) 453 14.6 (1.8) 426 14.4 (1.8)
Household size 491 4.6 (1.6) 453 4.58 (1.6) 426 4.63 (1.6)
Pubertal development (range 1–4) 386 3.05 (0.71) 356 3.04 (0.7) 326 3.02 (0.7)
Logged hair cortisol1 453 0.98 (1.1)
Hair length in cm 448 2.98 (1.1)
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Note. EBV= Epstein Barr virus

1

Salivary cortisol expressed as µg/dL and hair cortisol as pg/mg

Table 2 presents the descriptive statistics for current SES and economic adversity by developmental period and cumulatively stratified by race. Across all outcomes, Black/African American adolescents were significantly more likely to experience low SES and economic adversity than White adolescents. For example (across outcomes), 7%–8% of Black/African American adolescents had a primary caregiver with less than a high school degree compared to less than 2% of White adolescents; approximately 50% of Black/African American adolescents lived in households with an annual income less than $30,000 compared to 12%–16% of White adolescents; 48%–52% of Black/African American adolescents experienced economic adversity between birth and age 5 compared to 28%–32% of White adolescents, 44%–46% of Black/African American adolescents experienced economic adversity between 6 to 10 years of age compared to 27%–32% of White adolescents, and 41%–43% of Black/African American adolescents experienced economic adversity at 11 years of age and older compared to 22%–26% of White adolescents; and approximately 30% of Black/African American adolescents experienced economic adversity across all three developmental periods compared to 11%–13% of White adolescents.

Table 2.

Bivariate Results of Racial Differences in Current SES and Economic Adversity for Each Sample, By Outcome

Salivary Cortisol
Sample		 Hair Cortisol
Sample		 Salivary EBV
Sample
Black/AA
n=174		 White
n=320		 Black/AA
n=158		 White
n=295		 Black/AA
n=162		 White
n=264
SES Characteristics n % n % n % n % n % n %
Caregiver education1.2,3
 Less than high school 14 8.1 6 1.9 11 7.0 4 1.4 13 8.0 5 1.9
 High school degree 34 19.5 35 10.9 34 21.5 28 9.5 41 25.3 22 8.3
 Some college 84 48.3 65 20.3 76 48.1 56 19.0 66 40.7 64 24.2
 Bachelor degree 30 17.2 112 35.0 25 15.8 110 37.3 29 17.9 90 34.1
 Graduate/prof degree 12 6.9 97 30.3 12 7.6 93 31.5 13 8.0 80 30.3
 Missing 0 0 5 1.6 0 0 4 1.3 0 0 3 1.1
Household income1.2,3
 $0-$30,000 90 51.7 51 15.9 82 51.9 37 12.5 82 50.6 40 15.2
 $30,001-$60,000 54 31.0 47 14.7 49 31.0 43 14.6 46 28.4 39 14.8
 $60,001 and higher 19 11.0 200 62.5 20 12.7 190 64.4 21 13.0 170 64.3
 Missing 11 6.3 22 6.9 7 4.4 25 8.5 13 8.0 15 5.7
Economic adversity Developmental period
 0–5 years1.2,3
  Yes 85 48.9 100 31.3 79 50.0 85 28.8 85 52.5 85 32.2
  No 78 44.8 218 68.1 70 44.3 209 70.9 65 40.1 176 66.7
  Missing 11 6.3 2 0.6 9 5.7 1 0.3 12 7.4 3 1.1
 6–10 years1.2,3
  Yes 79 45.4 97 30.3 71 44.9 82 27.8 75 46.3 84 31.8
  No 83 47.7 223 69.7 76 48.1 212 71.9 70 43.2 179 67.8
  Missing 12 6.9 0 0 11 7.0 1 0.3 17 10.5 1 0.4
 11 years and more1.2,3
  Yes 75 43.1 84 26.3 65 41.1 66 22.4 67 41.4 66 25.0
  No 88 50.6 236 73.7 82 51.9 228 77.3 79 48.8 197 74.6
  Missing 11 6.3 0 0 11 7.0 1 0.3 16 9.8 1 0.4
Economic adversity: Cumulative1.2,3
 Never 54 31.0 166 51.9 49 31.0 164 55.6 41 25.3 131 49.6
 1 time period 28 16.1 69 21.6 26 16.5 61 20.7 26 16.0 58 22.0
 2 time periods 22 12.7 40 12.5 20 12.7 35 11.9 22 13.6 42 15.9
 3 time periods 54 31.0 43 13.4 48 30.4 34 11.5 50 30.9 30 11.4
 Missing 16 9.2 2 0.6 15 9.5 1 0.3 23 14.2 3 1.1
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Note. SES= socioeconomic status

1

p < .001 for racial differences in current SES and economic adversity for salivary cortisol sample

2

p < .001 for racial differences in current SES and economic adversity for hair cortisol sample

3

p < .001 for racial differences in current SES and economic adversity for salivary EBV sample

Table 3 presents the results for the multilevel linear regression analysis of racial differences in evening salivary cortisol concentration. Across Models 1–4, Black/African American adolescents had higher salivary cortisol concentration in comparison to White adolescents and the size of the effect was not attenuated by the SES measures: in the baseline model (Model 1) controlling only for daily measures of time since waking and wake-up time (b = 0.18, SE = 0.01, p = .002); in Model 2 accounting for current SES and covariates (b = 0.25, SE = 0.08, p = .001); in Model 3 accounting for current SES, developmental period economic adversity and covariates (b = 0.25, SE = 0.08, p = .001); and in Model 4 accounting for current SES, cumulative economic adversity and covariates (b = 0.25, SE = 0.08, p = .001). Adolescents who had a primary caregiver with less than a high school degree had lower salivary cortisol concentration than those with a graduate or professional degree (Models 2–4). Results for the covariates are available upon request.

Table 3.

Multilevel Linear Regression Results of the Racial Differences in Logged Salivary Cortisol among Adolescents, N=2248 salivary samples nested within 464 adolescents

Model 1 Model 2 Model 3 Model 4
b (SE) b (SE) b SE) b (SE)
Youth race
 Black/African American 0.18 (.006)** 0.25 (0.08)** 0.25 (0.08)** 0.25 (0.08)**
 White (ref)
Caregiver education
 Less than high school −0.38 (0.16)* −0.36 (0.16)* −0.37 (0.16)*
 High school degree −0.01 (0.09) 0.00 (0.09) −0.01 (0.10)
 Some college −0.13 (0.09) −0.12 (0.09) −0.013 (0.09)
 Bachelor’s degree −0.05 (0.07) −0.05 (0.07) −0.04 (0.07)
 Graduate/professional degree (ref)
Household income
 $0-$30,000 0.06 (0.09) 0.06 (0.10) 0.07 (0.10)
 $30,001-$60,000 0.04 (0.08) 0.04 (0.08) 0.05 (0.08)
 $60,001 + (ref)
Economic adversity developmental period
 0–5 years −0.004 (0.07)
 6–10 years −0.08 (0.08)
 11 years and more 0.05 (0.07)
Economic adversity Cumulative −0.01 (0.03)
Constant −2.53 (0.03)*** −3.10 (0.26)*** −3.05 (0.26)*** −3.09 (0.26)***
lns1_1_1 constant 0.29 (0.03)*** 0.27 (0.03)*** 0.27 (0.02)*** 0.27 (0.02)***
lnsig_e constant 0.34 (0.02)*** 0.34 (0.02)*** 0.34 (0.02)*** 0.34 (0.02)***
Open in a new tab

Note. Controlling for sex, age, caregiver marital status, season of collection, weight status, pubertal development, household size, time since waking and waking time.

*

p < .05

**

p < .01

***

p < .001

~

p < .10

Table 4 presents the results for the linear regression analysis of racial differences in hair cortisol concentration. Across all Models 1–4, Black/African American adolescents had higher hair cortisol concentration in comparison to White adolescents and the size of the effect was not attenuated by the SES measures: in the baseline model without covariates, (b = 0.48, SE = 0.02, p < .001); in Model 2 accounting for current SES and covariates (b = 0.41, SE = 0.14, p = .003); in Model 3 accounting for current SES, economic adversity by developmental period and covariates (b = 0.42, SE = 0.14, p = .003); and in Model 4 accounting for current SES, cumulative economic adversity and covariates (b = 0.41, SE = 0.14, p = .001). Marginally significant direct associations were found for SES and hair cortisol concentration in which adolescents who had a caregiver with a high school education or more had marginally higher hair cortisol concentration than those with a graduate or professional degree (Models 2–4 p = .06). In comparison, adolescents who experienced economic adversity between birth and 5 years of age had marginally lower hair cortisol concentration than those who did not experience this adversity (Model 3 p = .06). Results for the covariates are available upon request.

Table 4.

Linear Regression Results of the Racial Differences in Hair Cortisol in Adolescents, N=453

Model 1 Model 2 Model 3 Model 4
b SE b SE b SE b SE
Youth race
 Black/AA 0.48 (0.02)*** 0.41 (0.14)** 0.42 (0.14)** 0.41 (0.14)**
 White (ref)
Caregiver education
 < high school 0.21 (0.33) 0.21 (0.33) 0.18 (0.33)
 High school degree 0.38 (0.19)~ 0.36 (0.20)~ 0.37 (0.20)~
 Some college 0.15 (0.17) 0.13 (0.17) 0.14 (0.17)
 Bachelor degree 0.21 (0.14) 0.22 (0.14) 0.21 (0.14)
 Grad/prof degree (ref)
Household income
 $0-$30,000 −0.10 (0.17) −0.10 (0.18) −0.07 (0.18)
 $30,001-$60,000 −0.02 (0.16) −0.02 (0.16) −0.01 (0.16)
 $60,001 + (ref)
Economic adversity developmental period
 0–5 years −0.25 (0.13)~
 6–10 years 0.22 (0.15)
 11 years and more 0.02 (0.14)
Economic adversity cumulative −0.002 (0.05)
Constant 0.81 (0.01)*** 0.80 (0.48) 0.76 (0.49) 0.80 (0.49)
Open in a new tab

Note. Controlling for sex, age, caregiver marital status, season of collection, weight status, pubertal development, household size, hair length, frequency of hair washing and chemical use in hair.

*

p < .05

**

p < .01

***

p < .001

~

p < .10

Table 5 presents the results for the logistic regression analysis of racial differences in salivary shedding of EBV DNA. Across all Models 1–4, Black/African American adolescents had an increased odds of salivary shedding of EBV DNA compared to White adolescents and the size of the effect was not attenuated by the SES measures: in the baseline model without covariates, (OR = 1.91, 95% CI [1.04, 3.53], p = .038); in Model 2 accounting for current SES and covariates (OR = 1.94, 95% CI [1.05, 3.57], p = .034); in Model 3 accounting for current SES, developmental period economic adversity and covariates (OR = 1.91, 95% CI [1.03, 3.54], p = .039); and in Model 4 accounting for current SES, cumulative economic adversity and covariates (OR = 1.91, 95% CI [1.04, 3.52], p =.038). Significant direct associations between SES and salivary shedding of EBV DNA were found as adolescents who had a caregiver with some college had lower odds of salivary shedding of EBV DNA than those with a graduate or professional degree (Models 2–4), while adolescents who experienced economic adversity between birth and 5 years of age had higher odds of salivary shedding of EBV DNA than those who did not experience this adversity (Model 3). Results for the covariates are available upon request.

Table 5.

Logistic Regression Results of the Racial Differences in Salivary Shedding of EBV DNA among Adolescents, N=426

Model 1 Model 2 Model 3 Model 4
OR 95% CI OR 95% CI OR 95% CI OR 95% CI
Youth race
 Black/African American 1.91 (1.04,3.53) 1.94 (1.05, 3.57) 1.91 (1.03, 3.54) 1.91 (1.04, 3.52)
 White (ref)
Caregiver education
 Less than high school 1.98 (0.21, 18.40) 1.80 (0.19, 17.0) 1.74 (0.20, 15.1)
 High school degree 0.52 (0.20, 1.30) 0.48 (0.19,1.24) 0.50 (0.20, 1.26)
 Some college 0.33 (0.15, 0.73) 0.32 (0.15,0.72) 0.32 (0.14, 0.71)
 Bachelor’s degree 0.56 (0.29, 1.08) 0.54 (0.28, 1.04) 0.56 (0.29, 1.07)
 Graduate/prof degree (ref)
Household income
 $0-$30,000 1.56 (0.69, 3.51) 1.59 (0.67, 3.78) 1.53 (0.66, 3.56)
 $30,001-$60,000 0.73 (0.35,1.52) 0.73 (0.34,1.57) 0.71 (0.33, 1.51)
 $60,001 + (ref)
Economic adversity developmental period
 0–5 years 1.91 (1.04, 3.50)
 6–10 years 0.72 (0.35, 1.48)
 11 years and more 0.89 (0.45,1.77)
Economic adversity cumulative 1.10 (0.87, 1.39)
Constant 0.83 (0.09, 7.69) 0.89 (0.10, 8.16) 0.76 (0.08, 7.39) 0.83 (0.09, 7.69)
Open in a new tab

Note. Controlling for sex, age, caregiver marital status, season of collection, weight status, pubertal development, and household size

Discussion

Significant racial differences in cortisol and immune biomarkers were found in our study. Black/African American youth had higher salivary and hair cortisol concentration and increased odds of salivary shedding of EBV DNA compared to their White peers. Our findings are consistent with prior research documenting racial inequities in physiologic stress and immune function (DeSantis et al., 2007, 2015; Dowd et al., 2014; Ford & Stowe, 2013; Lehrer et al., 2020; Tackett et al., 2017; Wosu et al., 2015) and provide novel contributions of robust Black–White differences across multiple stress biomarkers among the adolescents in this study. Notably, extant research documents how dysregulation of the HPA axis and the immune response are associated with numerous poor health outcomes (Adam et al., 2017; Longnecker & Neipel, 2007). Thus, our study adds to the evidence that elevated stress and immune biomarkers differ by race as early as adolescence and may be one pathway through which racism and associated adversities contribute to the Black–White health inequities observed in the U.S.

In addition, we found economic adversity experienced between birth and 5 years of age was significantly associated with salivary shedding of EBV DNA and marginally associated with lower hair cortisol; these findings are consistent with prior research (Bunea et al., 2017; Ehlert, 2013; Finegood et al., 2017; Kalmakis et al., 2015; Khoury et al., 2019; Simmons et al., 2016). It is important to note that both high and low cortisol concentrations have been found to be associated with activation of the immune response and poor health (Steudte-Schmiedgen et al., 2016). Low cortisol concentration is thought to be the result of glucocorticoid resistance or abnormalities in the HPA negative feedback loop due to chronic stress, which may explain in part the lower salivary cortisol concentration found among adolescents who had a caregiver with less than a high school education (vs. graduate/professional degree) and the lower hair cortisol concentration (marginally significant) found among adolescents exposed to economic adversity earlier in life. While racism is also a chronic stressor, Black/African Americans experience the deleterious effects of racism daily, which may account for the racial differences in higher cortisol concentrations observed in our study and extant research. Future research of the dynamics of physiological stress over time is greatly needed to understand better the effects of social adversity on racial inequities in stress and health across the life span.

Consistent with prior research (DeSantis et al., 2007; Dowd et al., 2014; Ford & Stowe, 2013), neither current SES nor life course economic adversity (developmental period or cumulative exposure) attenuated the racial differences in salivary and hair cortisol or salivary shedding of EBV DNA among the adolescents in our study despite the vast racial differences they experience in economic adversity. Explanations for the inequities are most likely multifactorial as Black/African American youth also have increased exposure to multiple types of other adversities compared to White youth. For example, in addition to poverty, Black/African American youth are more likely than White youth to be exposed to violence in their residential neighborhood (Census tract) and routine activity locations (activity space; Browning et al., 2017); live in areas with fewer social, educational, economic and health-related resources (using the Child Opportunity Index; Acevedo-Garcia et al., 2020); experience parental death, parental incarceration, parental divorce/separation, and racial discrimination; and witness domestic violence as well as witness or be a victim of neighborhood violence (Maguire-Jack et al., 2020). Moreover, they also are more likely to experience these adverse exposures at much earlier ages (Maguire-Jack et al., 2020), which may contribute to a more significant cumulative burden over time, as well as the potential for more harmful effects due to exposure during a sensitive developmental period (Shonkoff et al., 2021). These increased exposures stem from centuries of structural racism and discriminatory practices historically embedded in our housing, education, health, and correctional systems with significant negative and inequitable health and social consequences for communities, families, and people of color (Bailey et al., 2017; Goosby et al., 2018; Shonkoff et al., 2021; Trent et al., 2019). Research investigating the contribution of these multiple adversities at distinct developmental time periods and across the life span to racial inequities in physiologic stress and health is critical for informing effective prevention and intervention efforts.

Several study limitations warrant further discussion. First, our study is cross-sectional in design, and we measure physiologic stress and immune function at one time point during adolescence, precluding causal inference. Second, our study focused on the direct relationships between race and physiologic stress and immune function. However, there may be heterogeneity in this relationship by other sociodemographic factors (e.g., age, sex, sexual orientation, gender identity, etc.); thus, further research on the effects of these intersections on physiologic stress and immune function is needed. Last, we collected salivary cortisol only at bedtime due to methodological challenges of collecting saliva samples at multiple time points daily over the weeklong data collection period (e.g., school attendance, storage, cost, etc.). While the single time point of collection precluded our examination of the diurnal curve, prior studies have found blunting of the diurnal curve with higher nighttime cortisol levels among low-income and Black/African American samples (Cohen et al., 2006).

Despite these limitations, our study provides novel contributions to examining racial inequities in physiologic stress and immune function in adolescence. Future research is needed to identify individual, social, and structural factors that may prevent and/or buffer stress to develop effective multilevel interventions. To date, interventions have focused primarily on individual resilience. While they may be effective for coping with stress at the individual level, we must address the underlying factors contributing to racial inequities in stress and health—structural racism and its associated adversities—to improve the health and well-being of Black/African Americans and all people of color. Evidence from a review of interventions targeting adverse childhood experiences found professionally led, multicomponent interventions that included parenting education, mental health counseling, social service referral, and/or social support improved child behavioral/mental health well-being and the parent−child relationship (Marie-Mitchell & Kostolansky, 2019). However, the interventions were targeted primarily to families with children 5 years of age or less. Though this is a period of development where intervention is critical to improving lifelong health and well-being, interventions targeting older children, adolescents, and adults across the life course are also needed. Furthermore, structural interventions and financial investment at the local, state, and national levels targeting racism and the associated adversities are critical for preventing racial inequities in stress and health across the life span, ultimately improving all Americans’ health and well-being.

Acknowledgement:

Research reported in this publication was supported by the National Institute of Nursing Research of the National Institutes of Health under Award Number R01NR019008, the National Institute on Drug Abuse of the National Institutes of Health under Award Numbers R21DA034960, R01DA032371, and R01DA042080, the Eunice Kennedy Shriver National Institute on Child of the National Institutes of Health under Award Number P2CHD058484, and the WT Grant Foundation. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the WT Grant Foundation.

Footnotes

The authors have no conflicts of interest to report.

Ethical Conduct of Research: The studies were approved by the Ohio State University Institutional Review Board.

Clinical Trial Registration: Not applicable.

Contributor Information

Jodi L. Ford, The Ohio State University College of Nursing, Columbus, OH.

Christopher R. Browning, The Ohio State University Department of Sociology, Columbus, OH.

Samantha J. Boch, University of Cincinnati College of Nursing, Cincinnati, OH.

Darlene A. Kertes, University of Florida Department of Psychology, Gainesville, FL.

Jake Tarrence, The Ohio State University Department of Sociology, Columbus, OH.

Baldwin M. Way, The Ohio State University Department of Psychology, Columbus, OH.

Kammi K. Schmeer, The Ohio State University Department of Sociology, Columbus, OH.

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