State-level structural racism and adolescent mental health in the United States

Abstract

We explored state-level indicators of structural racism on internalizing symptoms of depressive affect among US adolescents. We merged 16 indicators of state-level structural racism with 2015-19 Monitoring the Future surveys (n = 41 258) examining associations with loneliness, self-esteem, self-derogation, and depressive symptoms using regression analyses. Students racialized as Black in states with bans on food stamp eligibility and temporary assistance for drug felony conviction had 1.37 times the odds of high depressive symptoms (95% confidence interval [CI], 1.01-1.89) compared to students in states without bans. In contrast, students racialized as White living in states with more severe disenfranchisement of people convicted of felonies had lower odds of high self-derogation (odds ratio [OR], 0.89; 95% CI, 0.78-1.02) and high depressive symptoms (OR, 0.83; 95% CI, 0.70-0.99) compared to states with less severe disenfranchisement. These findings demonstrate the need to address the legacy of structural racism at the state level to reduce mental distress for US youth.

This article is part of a Special Collection on Mental Health.

Introduction

Mental health problems, including mood disorders and other internalizing symptoms, among United States (US) adolescents have rapidly increased in recent years,^1,2 with greater concentrations among adolescent cisgender girls.³ Consequences of mental health problems in youth, including rates of suicide, are concomitantly increasing,^4,5 especially among youth racialized as Black.⁶ These racial disparities have long been attached to biobehavioral antecedents like psychiatric disorders and mental health care, and less to systemic inequity.⁷ There is strong literature that suggests adverse structural inequity influences the environment in which youth are nested that contribute to poor mental health and suicide risk.^8,9 Yet there is still a dearth of public health literature that explores structural racism on these outcomes.

Structural racism, one of the most pervasive and persistent forms of systemic inequity,¹⁰ refers to the ways multiple institutions collaborate to produce disproportionate structural violence and limited access to resources for minoritized groups.^11,12 The United States has a longstanding relationship with structural racism, as it was embedded into the fabric of the constitution through passages like Article 1 Section 2 that declared that non-free persons, like those racialized as Black that were enslaved at the time, were counted as three-fifths of a free person (ie, a US citizen). This US policy both justified restricting the rights of people racialized as Black while allowing their bodies to be counted toward a census that increased the congressional representation of slave-holding states¹²—reinforcing the power of these states over further policy decision-making.

Other US policies targeted the daily lives of racialized and minoritized groups with most policies dictated by states. The most widespread were late 19th century Jim Crow laws that created and maintained “separate but equal” neighborhoods whereby people racialized as Black lived separate from people racialized as White.¹³ Residential segregation was reinforced by corporate practices like redlining that restricted access to home loans and insurance.^14,15 Residential segregation influenced educational attainment by limiting resources allocated to schools in areas where most people were racialized as Black.¹⁵ Residential segregation and differential political power between groups racialized as Black and White were reinforced by policing practices and state-sanctioned lynchings of people racialized as Black,^16,17 where perpetrators racialized as White rarely faced criminal consequences.^18‑20 State voting laws restricted the access of people racialized as Black, producing a largely White voting body and legislature.²¹ Vagrancy laws allowed for the arrest of “criminals” largely racialized as Black, enrolling them in prison, free labor programs (ie, chain gang) comparable to slavery and legally stripping them of voting rights.^22,23 Lack of voting rights, or voter suppression, continues to be a potent example of state-level structural racism visible through felony disenfranchisement policies,^24,25 where approximately 5.3 million US citizens, or 1 in 45 adults, are ineligible to vote due to felony convictions.²⁶ Though appearing as “race-neutral” policies, people racialized as Black are disproportionately affected with the rate of disenfranchisement 7 times higher than other groups.²⁶ As a result, political power, public agency, and social change have been systemically weakened.^25‑27

Despite intent, the 1968 Fair Housing Act did little to end residential segregation, the remnants of which can be seen today.¹⁴ Other Jim Crow–related practices endure like school segregation²⁸ and the killing of people racialized as Black for being perceived to be in the wrong neighborhood (eg, Ahmaud Arbery, Trayvon Martin), comfortably at home (eg, Breonna Taylor, Atatiana Jefferson), or disproportionately through death row convictions.²⁹ These and other forms of structural racism influence homeownership,³⁰ college aspiration,^31,32 and civic engagement,³³ the latter of which (with other social needs) is no longer available to persons convicted of felony crimes (eg, food stamps). These outcomes further influence reverberating experiences like poverty and the morbidity of communities racialized as Black.^34,35

Despite the long-lasting effects of structural racism via state-level policies, minimal research examines its policy-level impact on the mental health of youth racialized as Black in the present. Such impact may produce unique deleterious effects based on gender. For cisgender girls racialized as Black, the intersection of structural factors creates power dynamics and societal expectations that may serve as risk factors for depressive symptomatology and self-esteem.^36,37 For cisgender males racialized as Black, the societal privileges of being cisgender male do not always translate into mental health benefits as cisgender boys racialized as Black experience internalized structural oppression that produces poor self-esteem and self-derogation,³⁸ though there is a dearth on this literature too.³⁹

This study examines state-level indicators of structural racism—across the domains of civics, criminal justice, and neighborhood factors^40,41—and its association with internalizing symptoms of depressive affect among US high school seniors racialized as Black and White in nationally representative samples surveyed from 2015-19. This novel approach engages budding research on how to capture aggregate and historical structural racism and uses psychometric approaches to examine aggregate and individual downstream area-level indicators of structural racism on adolescents racialized as Black—testing the specificity of associations in comparison with adolescents racialized as White. Given depressive symptom increases are more concentrated among cisgender female youth, we test whether state-level structural racism interacts with the self-reported cisgender category.

Methods

Sample

Respondents are students from Monitoring the Future (MTF) cross-sectional surveys of approximately 400 US private and public high schools selected each year using a multistage random sampling design.⁴² Selected schools are invited to participate for two years and replaced by geographically proximate schools if they decline. For this study, 72% of US states were represented in 2015, 2016, and 2019, 70% in 2017, and 74% in 2018. Questionnaires are self-administered and responses are confidential. The current study focuses on 12th grade students participating from 2015-19 who received forms that included questions about internalizing symptoms (n = 41 258).

Measures

Internalizing symptoms of loneliness, self-esteem, self-derogation, and depressive symptoms were assessed using questionnaire items that asked students how much they agree/disagree with each statement (See Appendix 1). Positive statements were inversely coded similar to other studies. A summary score was created for each mental health outcome with scores ranging from 4 to 20. Internal consistency over 2015-19 ranged from 0.81 to 0.83 for loneliness, 0.84 to 0.85 self-esteem, 0.87 to 0.88 self-derogation, and 0.77 to 0.81 depressive symptoms. Due to distributional skewness, we dichotomized the scores at the 75th percentile for loneliness, self-derogation, and depressive symptoms, and 25th percentile for self-esteem, as done in other studies.⁴³

Structural racism

We evaluated 16 downstream indicators of racial inequity using previous approaches to measuring structural racism that include domains like civics, education, income, criminal justice, health, and segregation.^{12,40,41,44‑53} For items that captured the presence of specific structural racism policies (ie, Jim Crow laws 1865-1965, pre-clearance for election changes 2013, severity of felon disenfranchisement 2019, ban on food stamp eligibility for drug felony conviction 1996, and ban on temporary assistance 1996), we dichotomized the items as “no laws” and “any law.” For other items, we used a Black-White ratio dichotomized at the median to indicate “lower” (<median) and “higher” (> = median) state-level structural racism. These items included 2015-19 Black-White differences in persons incarcerated, maternal mortality, residential segregation, persons lynched 1882-1968, and Black-White differences in percentage of voter registration, voters, people living below the poverty line, living in owner-occupied housing units, elected officials, and high school and bachelor’s degree graduates. Data for all structural racism indicators were drawn from publicly available data sets (Supplemental Table 1 lists each item and source).

Covariates

Analyses assessing the effect of structural racism on mental health were adjusted for using cisgender categories of “female” and “male.” We did not include other individual-level covariates given that structural racism is a determinant of individual-level constructs like schooling and socioeconomic status and thus are on the causal pathway of interest. We included population density from the US Census Historical Population Density Data as an area-level covariate.

Data analysis

Factor analyses

Due to the novelty of using psychometric approaches to capture a latent structure of state-level structural racism (n = 50), we performed an exploratory factor analysis (EFA) with a maximum likelihood oblique rotation that allowed the 16 indicators to freely load onto factors (> = 0.40) using the “lavaan” R package.^54,55 To determine factorability, we used Kaiser-Meyer-Olkin Measure of Sampling Adequacy test (KMO > 0.5) and Barlett’s test (P < .05). To examine adequate fit of the EFA model, we used the “psych” R package to conduct a confirmatory factor analysis (CFA) with a diagonally weighted least squares estimator using the following fit indices in concert: comparative fit index (CFI > = 0.95), Tucker–Lewis index (TLI > 0.90), standardized root mean square residual (SRMR < 0.08), and root mean square error of approximation (RMSEA < 0.06).⁵⁶

Regression analysis

State-level structural racism factor scores and individual indicators were linked to MTF data based on the US state in which the school was located, using the federal information processing standards codes as an anchor variable. Sample weights provided by MTF were used in all estimates. Logistic regression analyses assessed the association between each factor/indicator and mental health indices dichotomized due to skewness. We performed separate models for students racialized as Black and those racialized as White and adjusted by cisgender category and population density. Models were then assessed for multiplicative interaction between structural racism indicator and cisgender category.

Results

Sample characteristics

Our analytic sample focused on respondents who identified as being racialized as Black or White, and who received forms that included questions regarding internalizing symptoms (n = 41 258). Among these, students racialized as Black were 19% (n = 7701) and students racialized as White were 81% (n = 33 557). Roughly 32% (n = 2075) of all students—32% of students racialized as Black and 33% of students racialized as White—reported high loneliness. For reports of low self-esteem, there was 24% (n = 3150) in all students, 22% Black, and 25% White; 30% high self-derogation (n = 3817) in all students, 31% Black, and 30% White; and 28% high depressive symptoms (n = 3124) in all students, 32% Black, and 27% White.

Aggregate state-level structural racism

The EFA yielded 3 factors across 13 indicators with the remaining 3 loading below 0.4 (Table 1). Factor 1 included Black-White differences in owner-occupied units, elected officials, jail population, maternal mortality rate, voter registration, voting, and below the poverty line, as well as having Jim Crow laws and pre-clearance for election. Factor 2 included Black-White differences in high school diplomas, bachelor degrees, and cross-loading items voter registration and below the poverty line. Factor 3 included bans on food stamp eligibility and temporary assistance for drug felony conviction. Bartlett’s test (387.86, P < .05) was significant in indicating equal variances, but the KMO test (0.39) suggested a factor analysis was not useful for these data. The CFA for the 3-factor model obtained adequate fit (CFI = 0.982, TLI = 0.974, SRMR = 0.082, RMSEA = 0.187).

Table 1.

EFA and CFA factor loadings for structural racism indicators (K = 16).

Indicators	N	% of states with high structural racism	Mean (SD)	EFA factor loadings				CFA factor loadings
				1	2	3	Communalities	1	2	3
Occupied owner units	50	50.0%	81.6 (157.4)	0.87	0.01	−0.05	0.76	0.85
Elected officials	50	50.0%	25.0 (31.9)	0.80	−0.03	0.03	0.65	0.93
Jail population	45	51.1%	3.9 (4.9)	−0.79	0.32	0.04	0.44	−1.03
Maternal mortality rate	26	50.0%	0.2 (0.2)	0.60	−0.23	0.04	0.44	0.78
Voter registration	35	48.6%	1.1 (0.2)	0.60	0.40	0.22	0.56
Voting	35	45.7%	1.2 (0.2)	0.59	0.08	0.35	0.50
Jim Crow laws	50	20.0%	dichotomous	−0.42	−0.34	0.21	0.30		−0.45
Below the poverty line	47	51.1%	0.5 (0.1)	0.40	0.56	−0.15	0.44		0.37
Pre-clearance for election changes	50	82.0%	dichotomous	0.39	−0.03	−0.19	0.18
Segregation	50	50.0%	0.6 (0.2)	−0.28	−0.26	0.18	0.16
Lynching	50	50.0%	3.9 (8.2)	−0.22	0.02	0.17	0.07
Bachelor’s degree	50	48.0%	1.5 (0.3)	−0.21	0.90	0.07	0.88		0.97
Ban on temporary assistance	50	50.0%	dichotomous	0.08	0.02	0.68	0.48			0.78
Severity of felon disenfranchisement	50	22.0%	dichotomous	−0.07	−0.07	0.05	0.01
Ban on food stamp eligibility for drug felony conviction	49	42.9%	dichotomous	−0.02	−0.03	0.90	0.81			1.19
High school graduation	50	52.0%	1.1 (0.1)	0.00	0.61	−0.24	0.43		0.98

We observed that students racialized as Black in states with higher structural racism via factor 3 (bans on food stamp eligibility and temporary assistance) had 1.37 times the odds of high depressive symptoms (95% CI, 1.01-1.89) compared to students in states with lower structural racism (Table 2). Across factors, we observed wide confidence intervals though some associations were evident in directionality. We observed odds in the hypothesized direction for factor 3 with other internalizing symptoms where students racialized as Black in states with higher structural racism experienced increased odds of loneliness (OR, 1.48; 95% CI, 0.87-2.52) compared to students racialized as Black in states with lower structural racism. In general, associations were of less magnitude in students racialized as White and suggested a protective association in states with higher structural racism (Table 3).

Table 2.

Multivariable logistic regression assessing the relationship between individual structural racism indicators and mental health outcomes among students racialized as Black, adjusting for cisgender category and population density, 2015-19.^a

Indicators	Loneliness	Self-esteem	Self-derogation	Depressive symptoms
Factor 1	1.02 (0.68, 1.51)	0.96 (0.76, 1.21)	1.01 (0.83, 1.23)	0.86 (0.65, 1.15)
Factor 2	1.08 (0.73, 1.61)	0.94 (0.75, 1.18)	1.01 (0.82, 1.22)	0.96 (0.72, 1.27)
Factor 3	1.48 (0.87, 2.52)	1.27 (0.98, 1.67)	1.10 (0.88, 1.38)	1.37 (1.01, 1.89)*
Owner-occupied units	0.65 (0.27, 1.54)	1.25 (0.77, 2.04)	1.10 (0.75, 1.62)	1.32 (0.80, 2.18)
Elected officials	0.70 (0.42, 1.16)	0.98 (0.64, 1.49)	0.82 (0.61, 1.12)	0.93 (0.57, 1.53)
Jail population	1.53 (0.93, 2.54)	0.84 (0.60, 1.17)	1.06 (0.78, 1.43)	1.02 (0.65, 1.61)
Maternal mortality	0.84 (0.59, 1.20)	0.95 (0.75, 1.21)	0.88 (0.72, 1.08)	1.18 (0.87, 1.61)
Voter registration	1.02 (0.68, 1.54)	1.06 (0.82, 1.36)	1.07 (0.88, 1.29)	1.00 (0.74, 1.35)
Voting	0.80 (0.55, 1.18)	1.05 (0.81, 1.36)	0.98 (0.77, 1.24)	1.01 (0.72, 1.41)
Jim Crow laws	1.35 (0.93, 1.96)	1.06 (0.84, 1.32)	1.02 (0.84, 1.25)	1.01 (0.77, 1.32)
Below the poverty line	0.88 (0.60, 1.28)	1.17 (0.94, 1.46)	0.96 (0.80, 1.16)	1.21 (0.91, 1.62)
Pre-clearance for election changes	0.66 (0.43, 1.02)	1.08 (0.85, 1.38)	0.95 (0.77, 1.18)	0.95 (0.70, 1.28)
Segregation	1.17 (0.75, 1.84)	0.96 (0.75, 1.23)	1.10 (0.90, 1.34)	1.08 (0.80, 1.47)
Lynching	1.11 (0.76, 1.62)	0.93 (0.74, 1.16)	1.03 (0.85, 1.25)	1.16 (0.88, 1.53)
Bachelor’s degree	0.99 (0.68, 1.45)	1.03 (0.82, 1.29)	0.94 (0.78, 1.14)	1.26 (0.96, 1.65)
Ban on food stamp eligibility for drug felony conviction	1.01 (0.69, 1.48)	0.96 (0.77, 1.20)	1.05 (0.87, 1.27)	1.07 (0.81, 1.42)
Ban on temporary assistance	0.95 (0.65,1.38)	0.97 (0.78, 1.21)	1.03 (0.85, 1.24)	1.03 (0.77, 1.37)
Severity of felon disenfranchisement	1.19 (0.72, 1.96)	0.99 (0.74, 1.35)	0.98 (0.78, 1.24)	0.90 (0.63, 1.29)
High school graduation	0.98 (0.68, 1.42)	1.07 (0.86, 1.34)	0.99 (0.82, 1.21)	1.17 (0.90, 1.54)

^aWhen reading results for below the poverty line, jail population, and maternal mortality, more persons racialized as Black signifies more structural racism. When reading all other indicators, more persons racialized as White signifies more structural racism.

^*Indication of statistical significance.

Table 3.

Multivariable logistic regression assessing the relationship between individual structural racism indicators and mental health outcomes among students racialized as white, adjusting for cisgender category and population density, 2015-19.^a

Indicators	Loneliness	Self-esteem	Self-derogation	Depressive symptoms
Factor 1	1.02 (0.86, 1.21)	1.03 (0.91, 1.17)	1.01 (0.88, 1.16)	1.12 (0.96, 1.30)
Factor 2	1.10 (0.93, 1.31)	0.99 (0.88, 1.14)	1.06 (0.92, 1.23)	1.13 (0.96, 1.33)
Factor 3	1.08 (0.91, 1.28)	1.08 (0.95, 1.22)	1.05 (0.91, 1.20)	1.13 (0.97, 1.32)
Occupied owner units	0.84 (0.69, 1.01)	0.99 (0.89, 1.12)	1.02 (0.91, 1.13)	0.99 (0.86, 1.16)
Elected officials	0.90 (0.74, 1.10)	1.03 (0.92, 1.16)	1.04 (0.93, 1.16)	1.04 (0.90, 1.20)
Jail population	0.98 (0.81, 1.18)	0.97 (0.86, 1.09)	0.95 (0.84, 1.06)	0.95 (0.82, 1.10)
Maternal mortality	1.03 (0.86, 1.23)	1.01 (0.88, 1.16)	1.07 (0.92, 1.25)	1.02 (0.86, 1.21)
Voter registration	1.01 (0.85, 1.18)	1.01 (0.90, 1.13)	0.99 (0.89, 1.12)	0.99 (0.86, 1.14)
Voting	0.99 (0.84, 1.16)	0.98 (0.87, 1.10)	0.98 (0.87, 1.10)	1.04 (0.90, 1.20)
Jim Crow laws	1.14 (0.97, 1.35)	1.01 (0.88, 1.15)	0.95 (0.83, 1.08)	0.98 (0.83, 1.14)
Below the poverty line	1.01 (0.87, 1.18)	1.05 (0.94, 1.17)	1.05 (0.94, 1.17)	1.05 (0.92, 1.19)
Pre-clearance for election changes	1.16 (0.96, 1.40)	1.05 (0.89, 1.23)	1.07 (0.91, 1.25)	1.14 (0.94, 1.38)
Segregation	0.98 (0.84, 1.14)	1.06 (0.95, 1.18)	1.06 (0.95, 1.19)	1.06 (0.93, 1.21)
Lynching	0.97 (0.84, 1.13)	0.98 (0.87, 1.12)	0.92 (0.81, 1.03)	0.97 (0.84, 1.12)
Bachelor’s degree	0.92 (0.77, 1.08)	0.97 (0.87, 1.09)	0.99 (0.88, 1.12)	0.94 (0.81, 1.07)
Ban on food stamp eligibility for drug felony conviction	1.06 (0.90, 1.25)	0.97 (0.87, 1.09)	1.08 (0.96, 1.22)	1.04 (0.90, 1.19)
Ban on temporary assistance	1.03 (0.88, 1.20)	0.99 (0.89, 1.11)	1.04 (0.93, 1.16)	1.02 (0.90, 1.17)
Severity of felon disenfranchisement	0.88 (0.70, 1.10)	0.96 (0.82, 1.12)	0.89 (0.78, 1.02)	0.83 (0.70, 0.99)*
High school graduation	0.89 (0.76, 1.04)	0.96 (0.86, 1.08)	0.94 (0.84, 1.05)	0.90 (0.78, 1.02)

^aWhen reading results for Below the poverty line, jail population, and maternal mortality, more persons racialized as Black signifies more structural racism. When reading all other indicators, more persons racialized as White signifies more structural racism.

^*Indication of statistical significance.

Individual indicators of state-level structural racism

While confidence intervals were wide, potential associations emerged whereby students racialized as Black residing in states that historically had Jim Crow laws had 1.35 times the odds of loneliness (95% CI, 0.93-1.96) than students in non-Jim Crow states. Similarly, students racialized as Black in states with greater Black-White differences in the jail population had 1.53 (95% CI, 0.93-2.54) times the odds of loneliness compared with students with less Black-White difference in the jail population. Further, students racialized as Black in states with greater Black-White differences in occupied owner units had 1.25 (95% CI, 0.77-2.04) times the odds of low self-esteem compared to counterparts. Students racialized as Black living in states with greater Black-White differences in bachelor’s degree, maternal mortality, and below the poverty line had 1.26 (95% CI, 0.96-1.65), 1.18 (95% CI, 0.87-1.61), and 1.21 (95% CI, 0.91-1.62), respectively, the odds of having depressive symptoms compared to those exposed to lower levels of these structural racism indicators—though these odds were not statistically different from one.

For students racialized as White, there were statistically significantly lower odds of self-derogation (OR, 0.89; 95% CI, 0.78-1.02) and depressive symptoms (OR, 0.83; 95% CI, 0.70-0.99) in states with more severe disenfranchisement compared to students in states without. This indicator of structural racism also indicated that students racialized as White had lower odds of loneliness (OR, 0.88; 95% CI, 0.70-1.10) than their counterparts. Again, the general magnitude of associations was lower (no odds ratio was above 1.17) than for students racialized as Black, suggesting protective associations.

Interaction of aggregate and individual indicators of state-level structural racism with cisgender category

For students racialized as Black, the association between structural racism and mental health outcome, in general, did not significantly vary by cisgender category (Supplementary Table 2). However, in states with greater Black-White differences in lynching, the association with self-derogation significantly varied by cisgender category (B = −0.45, P = 0.03). To further understand the nature of this interaction, we assessed the relationship between lynching and self-derogation stratified by cisgender category. Students racialized as Black and classified as cisgender female in states with greater Black-White differences in lynching had 0.86 (95% CI, 0.68-1.07) times the odds of self-derogation compared to states with lower Black-White differences in lynching. Conversely, students racialized as Black and classified as cisgender male in states with greater Black-White differences in lynching had 1.28 (95% CI, 0.99-1.67) times the odds of self-derogation compared to states with lower Black-White differences in lynching.

Among students racialized as White, significant interactions emerged in all outcome domains (Supplementary Table 3). The association between segregation and self-derogation significantly varied by cisgender category (B = −0.19, P = 0.03). Compared to students racialized as White in states with lower segregation, cisgender females in states with higher segregation had 0.99 (95% CI, 0.89-1.12) times the odds of self-derogation, whereas as cisgender males had 1.13 (95% CI, 1.00-1.28) times the odds. Similarly, the relationship between lynching with low self-esteem (B = −0.17, P = 0.05), self-derogation (B = −0.21, P = 0.02), and depressive symptoms (B = −0.26, P = 0.03) varied by cisgender category. The associations between voting and low self-esteem (B = −0.25, P = 0.01); severity of felon disenfranchisement with loneliness (B = −0.36, P = 0.03), self-derogation (B = −0.26, P = 0.05), and depressive symptoms (B = −0.40, P = 0.004); ban on food stamp eligibility for drug felony conviction with low self-esteem (B = −0.26, P = 0.01), self-derogation (B = −0.27, P = 0.01), and depressive symptoms (B = −0.28, P = 0.02); ban on temporary assistance with low self-esteem (B = −0.20, P = 0.02) and depressive symptoms (B = −0.28, P = 0.01)—all varied by cisgender category. Compared to states with no ban, cisgender females in states with bans on temporary assistance had 0.89 (95% CI, 0.77-1.04) times the odds of depressive symptoms, whereas cisgender males had 1.13 (95% CI, 0.96-1.34) times the odds.

Discussion

This study examined the impact of state-level structural racism occurring throughout history on internalizing symptoms among a sample of 12th graders racialized as Black and White between 2015-19. Suggestive findings emerged that students racialized as Black in the US may have worse mental health when residing in states with historical legacies of Jim Crow laws and other indicators of structural racism such as greater Black-White differences in jail population, occupied owner units, bachelor’s degree, below the poverty line, and maternal mortality. These indicators of structural racism also suggest that associations vary by cisgender category. Although the prevalence of internalizing symptoms is highest among cisgender girls,³ generally, associations between structural racism indicators and internalizing symptoms among students racialized as Black are higher among cisgender boys, indicating that structural racism may have a greater impact on boys’ mental health.

Suggestive evidence emerged that there may be lower levels of mental health problems among students racialized as White in states with greater differences in education, jail population, and registered voters. These findings potentially reflect how structural racism benefits students with racial privilege, as a key component of structural racism is that it unfairly disadvantages racialized and minoritized groups and unfairly advantages those racialized as White.⁴⁷ Therefore, the trends in mental health benefits—less self-derogation and depressive symptoms—that we observe in students racialized as White are expected. Indeed, we observed that adolescents racialized as White living in states with higher levels of structural racism, most notably in terms of felon disenfranchisement, had better mental health than students racialized as White living in states with lower levels of structural racism. Students racialized as Black in those same states experienced worse mental health problems when structural racism was higher. These results are consistent with several other studies on structural racism,⁵⁷ noting that harms to minoritized groups are evidenced through benefits to majoritized groups enriched by wielding and maintaining differential power structures.⁵⁸

However, our results were not uniform in mental health benefits to adolescents racialized as White. For cisgender male youth racialized as White, associations emerged for deleterious mental health consequences of living in states with high structural racism consistent with literature that suggests white supremacy plays a deleterious role in the health of people racialized as White too.⁵⁹ The benefits of white supremacy is even more nuanced as some adolescents may experience the weight of structural racism as people racialized as Middle Eastern or LatinX, yet systematically forced to select “White” as their racialized group.⁶⁰ In such cases, their health outcomes may differ from the majoritized group. Our findings suggest structural racism, as a form of white supremacy, has widespread effects on the wellbeing of students racialized as White and Black that may intersect with other forms of structural inequity to shape distinct gendered outcomes.⁶¹ Specifically, cisgender male youth racialized as Black may face a unique blend of racism- and gender-related stressors like societal and cultural norms and expectations and lack of psychosocial support and space to express diverse emotions that intersect and contribute to mental health challenges.⁶² Further research should explore how unique exposures to structural intersectionality influence outcomes in marginalized groups without reliance on counterfactuals that may have different exposures.

An additional contribution of this analysis was that we analyzed a factor structure of structural racism using 16 indicators. Our findings support conceptual frameworks that posit that structural racism exerts pernicious influence in the aggregate. Most indicators loaded onto factor 1, though a few items loaded in the opposite direction as others, which likely contributed to the lower odds observed in depressive symptoms. The integration of these indicators supports further use of multi-indicator measures to examine aggregate structural racism. However, these findings complicate discourse around the use of separate domains (eg, housing, civics, etc.) of structural racism, as factor 1 demonstrates that owner-occupied units, commonly associated with both housing and wealth accumulation, loaded with elected officials (civics), maternal mortality rate (health), and below the poverty line (income). Though the argument could be made that because education indicators and both bans for drug felony conviction loaded onto other factors, there are different historical patterns that are meaningful to capture. Structural racism via bans on food stamp eligibility for drug felony conviction and temporary assistance was associated with a 37% increase in depressive symptoms for students racialized as Black, suggesting 48% and 10% increased odds of high loneliness and self-derogation, respectively. Conversely, students racialized as White had 11% and 17% lower odds of high self-derogation and high depressive symptoms, respectively, in states with more severe felony disenfranchisement. Thus, both aggregate and individual indicators may be helpful in teasing apart the unique role of structural racism on the mental health of adolescents.

Limitations

There were a few challenges with obtaining construct validity for the aggregate measure. A few indicators shared much of its variance across factors, making it difficult to determine which factor the indicator aligned closely with. Additionally, when items freely loaded using the EFA, some of the direction of items contradicted hypothesized pathways. These challenges illustrate the restricted utility of statistical frameworks in reflecting the dynamic and historical relationships among indicators of structural racism. This is particularly meaningful when examining state-level structural racism, which is historically significant to capture, but will always suffer from a small sample size. Additionally, we dichotomized symptom scales due to data skewness, but acknowledge that dichotomization loses information and that high vs low symptom designation may not reflect the underlying dimensional nature of internalizing symptoms among youth. Because we did not compare racialized groups with different relationships to structural racism to each other, we may have limited the observable magnitude of association by conducting within racialized group comparisons.

Finally, given biological differences among students were not assessed, we considered the survey question “what is your sex?” to reflect gender roles in society. Since only binary categories male and female were available in the MTF data set for the study years included, this study did not capture the intersection of structural racism and being nonbinary or transgender. Additionally, our analytic strategy captured multiplicative and not additive interactions between structural racism and cisgender category. Diverse gender data are important as future directions as recent literature suggests that the intersection of structural experiences influence low self-esteem for sexual and gender minority adolescents from racialized and minoritized groups⁶³ and increase odds of depressive symptoms and suicidality for transgender adolescents racialized as Black and LatinX in comparison to cisgender peers.⁶⁴ Hence, an intersectional examination of historic structural oppression on adolescents across gender is vital.⁶⁵ Future research should explicitly examine how specific policies have influenced the mental health of youth overtime, in addition to refining psychometric scale-building for structural racism. Future research might also explore the role of white supremacy on mental health for adolescents racialized as White.

Conclusion

As mental health problems among adolescents continue to deteriorate in the United States, a broader assessment of the structural factors underlying mental health is increasingly necessary. Early life experiences become physiologically embedded in ways that directly influence adult health and indirectly shift the trajectory of exposures experienced later in life.⁴¹ Despite such risk, the current medicalized system of mental health treatment is insufficient to meet the demand of adolescent psychiatric distress. We find that state-level structural racism is harmful for the mental health of adolescents racialized as Black, as well as those racialized as White. These findings build upon evidence that youth racialized as Black are disproportionately exposed to violence in legal systems that cause mental health conditions.^36,37 As such, primary prevention efforts for poor adolescent mental health—reducing distress before it occurs—must be centered on identifying and removing historical structural racism in US states, as well as addressing structural racism’s legacy over time.

Prevention of depression and other internalizing symptoms optimally occurs throughout the life course and can be successfully implemented through community-based initiatives focused on structural and social determinants like nutrition and housing, social and familial network cohesion, sense of purpose and belonging, safety, and trauma.⁶⁶ State-level reform efforts focused on laws, legal criteria, and system procedures that disadvantage youth racialized as Black should be used to reduce systemic bias that results in disproportionate US legal system contact of youth racialized as Black with the too often such contact results in decreased political power through felony disenfranchisement.^25,26,67,68 Further, processes where the healthcare needs of a community can be ignored based on political and/or majoritized group leadership should not be allowed to influence access to resources and health outcomes.^69,70 Ultimately, the deep-rooted presence of structural racism in US policies threatens the mental health of youth racialized as Black and White. To effectively address psychiatric distress from a public health perspective, it is crucial to focus on structural racism while considering the interconnectedness of other structural factors as they shape governance, policies, and practices that lead to differential risk and mental health outcomes.¹¹

Acknowledgments

We would like to thank the participants of the Monitoring the Future Study.

Supplementary material

Supplementary material is available at American Journal of Epidemiology online.

Funding

National Institute of Drug Abuse R01DA048853-03S1.

Conflict of interest

The authors do not have conflicts to disclose.

Data availability

These data are publicly available; Monitoring the Future data can be accessed through the University of Michigan (https://www.icpsr.umich.edu/web/pages/NAHDAP/index.html); structural racism variables are all from publicly available sources and can be provided for research purposes upon request.