Racism May Interrupt Age-related Brain Growth of African American Children in the United States

Research Article

J Pediatr & Child Health Care. 2021; 6(3): 1047.

Racism May Interrupt Age-related Brain Growth of African American Children in the United States

Assari S1,2,3* and Mincy R4,5,6

1Marginalization-Related Diminished Returns (MDRs) Research Center, Charles R Drew University of Medicine and Science, Los Angeles, CA, USA

2Department of Family Medicine, Charles R Drew University of Medicine and Science, Los Angeles, CA, USA

3Department of Urban Public Health+, Charles R Drew University of Medicine and Science, Los Angeles, CA, USA

4Center for Research on Fathers, Children and Family Well-Being, Columbia University, New York, USA

5Columbia Population Research Center (CPRC), Columbia University, New York, USA

6Columbia University School of Social Work, Columbia University, New York, USA

*Corresponding author: Shervin Assari, Marginalization-Related Diminished Returns (MDRs) Research Center, Department of Family Medicine, Department of Urban Public Health+, Charles R Drew University of Medicine and Science, Los Angeles, CA, USA

Received: September 23, 2021; Accepted: November 02, 2021; Published: November 09, 2021


Background: Considerable research has documented age-related growth in brain size as a marker of normal brain development. This is particularly important because brain volume has a significant role in overall cognitive performance. However, less research is done on whether age-related changes in the global brain volume differ across diverse racial and ethnic groups. We hypothesized that age-related growth in brain size would be disrupted in African American children who are historically affected by racism.

Purpose: Considering race as a proxy of racism rather than genetics, this study tested racial and ethnic differences in the effects of age on global brain volume using structural brain imaging data. Built on a sociological, rather than a biological theory, we built our study on Marginalization-related Diminished Returns (MDRs) framework, which argues that under racism, resources and assets are less effective for social groups that are historically racialized, discriminated against, marginalized, and segregated. Considering age as an asset/resource that increases the global brain volume, we expected weaker effects of age on overall brain size of African American and Hispanic children, than White and non-Hispanic children, again as a result of racism.

Methods: We borrowed the structural Magnetic Resonance Imaging (sMRI) data from the Children Brain Cognitive Development (ABCD) study, which included 9,311 9-10 year old children. The independent variable was the child’s age treated as a continuous measure (in months). The primary outcome was global brain volume. Sex, parental employment, parental education, household income, and parental marital status were the covariates. Race and ethnicity, as proxies of racism, were the moderators. To analyze the data, we used linear regression models.

Results: Age was positively associated with the global brain size in children. In line with the MDRs, the positive association between age and global brain volume was weaker for African American than White children, while family structure, sex, and family socioeconomic status was controlled.

Conclusions: Under racism, age has unequal effects on global brain size of diverse racial groups. In line with the MDRs, we observe diminished agerelated growth of the brain for African American children, which documents detrimental effects of racism. For White children who are not affected by racism, age makes a large difference regarding global brain volume. Age-related growth of global brain size is diminished in African American children, whose daily lives are shaped by racism. School and residential segregation may have a role in reducing the effect of age on children’s brain growth in African American families. The results should not be interpreted as inferiority of one group but social processes that hinder normal development of a historically oppressed group.

Keywords: Age; Global brain volume; Brain development; Structural MRI; MRI; Social determinants; Racism


Marginalization-related Diminished Returns (MDRs) [1-3] refer to weaker effects of protective factors, resources, and assets on the development, behaviors, and health of all marginalized social groups. In his 20-year review of Fundamental Cause theory, Clouston and Link refer to these MDRs as indicators of structural racism in the United States (US) [4]. More recently, these MDRs are shown to be a mechanism that explains how racism influences brain development [5-11]. Such effects may explain transgenerational transition of inequalities as a result of racism [5-11]. These MDRs also explain why health inequalities can be also seen in high socioeconomic position (SEP) families [5-11].

Visible and invisible social identities that cause discrimination, different treatment, and decreased access to the opportunity structures are believed to generate MDRs. MDRs are shown for race [12,13], place [22], ethnicity [14-16], nativity [17,18], and sexual orientation [19-21]. That is, African American [12,13], Hispanic [14- 16], Native American [23], Asian American [24], immigrant [17,18], LGBT [19-21], and even marginalized White [22] people show weaker than expected effects of resources such as socioeconomic position (SEP) [17,18], coping [25], and age [26], on generating outcomes. Observation of MDRs in all marginalized groups including Whites suggests that they are shaped by social forces rather than biological traits [1,2]. Although studies find MDRs for all marginalized groups, they are strongest in African Americans who have had a unique history of slavery and racism in the US [1,2].

As a result of MDRs, racial and ethnic minority children and youth show poorer health, behavioral, and developmental outcomes, despite having access to social, economic, personality, and psychological resources and assets [27-31]. For example, high SEP Hispanic and African American children remain at risk of anxiety [32], depression [33], poor school performance [12,13], as well as high-risk behaviors, [31] such as aggression [31] and substance use [34, 35]. Diminished effects of economic resources for racial and ethnic minority groups of children are robust [36-40]. Similarly, high SEP Hispanic and African American children report higher risk of impulsivity, aggression, anxiety, depression, poor health, poor school performance, and attention-deficit/hyperactivity disorder (ADHD) [14,29,40,41].

While SEP has a protective effect on brain development, and high SEP backgrounds are protective against school drop-out [42], depression [43], suicide [44,45], antisocial behaviors [46], aggression [47], and use of legal [48,49] and illegal substances [50], Hispanic and African American children with high SEP remain at risk of almost all of these domains [14,29,40,41]. This is partly because protective factors, such as SEP [51] are diminished for Hispanic and African American children. Therefore, despite having the resources, Hispanic and African American children do not show optimal brain development that is expected given their resources.

While low access to resources and assets is partially responsible for the worse than expected health status of Hispanics and African Americans, lower access to resources and assets does not explain all the White-African American and White-Hispanic gaps in developmental and health outcomes. Another cause of such gaps is MDRs, which denote weaker effects of available resources and assets for African Americans and Hispanics than non-Hispanic Whites [36,37,39,52- 56], protective of high SEP on various behavioral outcomes are attributed to the effects of high family SEP. These MDRs may exist for multiple aspects of brain structures [57] and functions, such as global brain volume [58]. Although there is an extensive body of research on weaker effects of family SEP for racial and ethnic minority groups, we are unaware of previous studies of racial/ethnic differences in the size of the effects of age on a wide range of health, economic, and behavioral outcomes.

Research has established how race(ism) alters the effects of high SEP on children’s brain development [59-63]. Due to racism, high SEP African Americans remain at risk of depression, impulsivity, novelty/ fun seeking, poor emotion regulation, and poor inhibitory control. These can be, in theory, due to a delay in the brain development of Black children because of environmental stressors in Black families’ lives across all SEP spectrums. In this view, the environment’s negative effect is so large that it interferes with the effect of age on the brain in a similar way that it diminishes the impact of SEP on brain development of the racialized group [59-63].

Multiple studies have shown an association between SEP and larger global brain volume [58]. Noble and colleagues documented a positive association between family SEP and MRI-assessed global brain volume in children [51], independent of race(sim) and genetic markers [51]. Interestingly, Waldstein and colleagues argued that African American race might be associated with an increased sensitivity to SEP influences on brain health [58]. However, our research shows the opposite [1,2,31]. Our results suggest that racism reduces the significance of individual-level factors, because their influences are bound by the unfair aspects of racism in society [64- 67].


Conceptualizing race as a proxy of racism, this study explored racial and ethnic differences in age-related changes in the global brain volume of 9-10 year old children. We expected racial and ethnic variation in the magnitude of the effect of age on global brain volume to be in line with the MDRs phenomenon [1,2,31]. More specifically, we expected diminished age-related changes, as documented by weaker associations between age and global brain volume for African American and Hispanic than White and non-Hispanic children. In a small study, Waldstein showed similar results for the effects of SEP on global brain volume [58].


Design and settings

This cross-sectional study was a secondary analysis of the ABCD study data [68-72]. Our analysis used data from wave 1 of the ABCD study, a national brain imaging study of children [68,73]. The ABCD study includes a large, diverse national sample [68-72].

Participants and sampling

In the ABCD study, pre-youth participants were recruited from multiple cities across different states. The ABCD sample primarily relied on the recruitment of pre-youth from US school systems. Schools were selected based on their race, ethnicity, sex, SEP, and urbanicity data. More details of ABCD sampling are published elsewhere [74]. The ABCD sample included 9,311 non-twin Hispanic, non-Hispanic African American, and White 9-10 year old children.

Study variables

Dependent variable: The primary outcome was global brain volume, measured by structural MRI. Prior studies showed that global brain volume was associated with age, stress, SES, and nutrition [75- 77].

Independent variable: Age, the main predictor, was a continuous variable ranging from 9.01 to 10.99 years. Parents reported the age of the children.

Moderators: Race, the moderator, was a self-identified variable coded 1 for African American and 0 for White (reference). Ethnicity, a confounder, was coded 1 for Hispanic and 0 for non-Hispanic.

Confounders: Sex was 1 for boys and 0 for girls. Parental family structure was 1 for married/partner and 0 for other. Parental education was a continuous measure ranging from 1 to 21. Family economic hardship was measured by the following seven items: “In the past 12 months, has there been a time when you and your immediate family experienced any of the following”: 1) “Needed food but could not afford to buy it or could not afford to go out to get it?”; 2) “Were without telephone service because you could not afford it?”; 3) “Did not pay the full amount of the rent or mortgage because you could not afford it?”; 4) “Were evicted from your home for not paying the rent or mortgage?”; 5) “Had services turned off by the gas or electric company, or the oil company would not deliver oil because payments were not made?”; 6) “Had someone who needed to see a doctor or go to the hospital but did not go because you could not afford it?”; and 7) “Had someone who needed a dentist but could not go because you could not afford it?” Responses to each item were either 0 or 1. We calculated a mean score, a continuous measure with a potential range between 0 and 1, where a higher score showed lower economic hardship [78-84]. Parental employment was 0 for unemployed and 1 for employed parents. Family income was a 1–10 interval measure, where a higher score indicated a higher income. The total combined family income in the past 12 months was asked. Responses were 1 = less than $5000; 2 = $5000; 3 = $12,000; 4 = $16,000; 5 = $25,000; 6 = $35,000; 7 = $50,000; 8 = $75,000; 9 = $100,000; and 10 = $200,000.

Data analysis

We used Statistical Package for the Social Sciences (SPSS) for data analysis. We reported n (%) and mean [standard deviations (SDs) for our univariate analysi, Spearman correlations for our bivariate analyses and four linear regression models for our multivariable analysis. In each regression model the outcome variable was global brain volume and the main predictor (independent) variable was age. Each model all controlled for confounders, such as sex, parental marital status, parental employment, parental education, family income, and family economic hardship. We used a pooled sample for the first two models. No interaction term appears in Model 1. In Model 2, we include two interaction terms age X race and age x ethnicity, with non-Hispanic White as the omitted category. We estimated the next two models using separate samples for Whites (Model 3) and African Americans (Model 4). We reported the regression coefficients (b), standard errors (SE), and p-values. We considered a coefficient to be statistically significant if the p-value was less than or of equal to 0.05. Before performing our linear regression models, we explored the distribution of the dependent variable, and a normal distribution confirmed appropriateness of using linear regression for data analysis. We also confirmed that the error terms were normally distributed.

Ethical aspect

Our analysis was exempt from a full review. The ABCD study protocol, however, was approved by the University of California, San Diego (UCSD) Institutional Review Board (IRB) [73].



The sample included 9,311 9-10 year old children. Table 1 presents the descriptive statistics of the pooled sample.