Household Income and Subsequent Youth Tobacco Initiation: Minorities’ Diminished Returns

Abstract

Introduction

Household income, a prominent socioeconomic status (SES) indicator, is known to mitigate youth engagement in various health risk behaviors, including tobacco use. Nevertheless, the Minorities’ Diminished Returns theory suggests that this protective effect may be less pronounced for racial and ethnic minorities compared to majority groups. This study aimed to investigate the protective role of high household income against tobacco use among youth and explore potential variations across different racial and ethnic groups.

Methods

Conducted as a longitudinal analysis, this study utilized data from the initial three years of the Adolescent Brain Cognitive Development (ABCD) Study spanning 2016–2022. The cohort consisted of 11,875 American youth aged 9–10 years, tracked over a three-year period. The dependent variable was tobacco initiation, irrespective of the product, while household income served as the independent variable. Covariates included youth age, gender, family education, structure, and employment, with race/ethnicity acting as the moderating variable.

Results

Out of the 8,754 American youth who were non-smokers at baseline, 3.1% (n = 269) initiated tobacco use during the 30-month follow-up, while 96.9% (n = 8,485) remained non-smokers. A family income exceeding $100,000 per year was associated with a lower hazard ratio for tobacco initiation (transitioning to ever-use) over the follow-up period (HR = 0.620, p = 0.022). However, household income of $50–100k exhibited significant interactions with race/ethnicity on tobacco initiation, indicating weaker protective effects for Black (HR for interaction = 7.860, p < 0.001) and Latino (HR for interaction = 3.461, p = 0.001) youth compared to non-Latino White youth.

Conclusions

Within the United States, the racialization and minoritization of youth diminish the protective effects of economic resources, such as high household income, against the transition to tobacco use. Non-Latino White youth, the most socially privileged group, experience greater protection from their elevated household income regarding tobacco initiation compared to Black and Latino youth, who face minoritization and racialization. Policymakers should address not only the SES gap but also the mechanisms contributing to the heightened risk of tobacco use among racialized and minoritized youth from affluent backgrounds.

1. Introduction

Tobacco remains a persistent and significant contributor to preventable diseases in the United States, with approximately half a million Americans succumbing to tobacco-related illnesses each year, and over 16 million individuals experiencing the adverse health effects of tobacco[1]. The economic impact of these illnesses is staggering, costing the US more than $300 billion annually[2]. Regrettably, the burden of tobacco-related health issues is not distributed equally, disproportionately affecting marginalized populations that have low socioeconomic status (SES) and racial/ethnicity minority status[3].

As shown by the Minorities’ Diminished Returns (MDRs), behavioral and health effects of family SES indicators such as household income tend to be weaker in racial/ethnic minority groups compared to their majority counterparts[4]. These persist across various SES resources, outcomes, and study designs[5]. These findings underscore that racial/ethnic disparities are not solely caused by SES gaps but also by differing health gains from SES resources across racial/ethnic groups[6]. Furthermore, some racial/ethnic gaps in behavioral and health outcomes may even increase as SES levels rise, emphasizing the importance of addressing racial/ethnic disparities that sustain across the entire SES spectrum[7].

The MDRs findings shift the focus from merely examining behavioral health disparities in low SES racial/ethnic minorities[8] to encompassing racial/ethnic minorities in middle-class populations as well[9]. This is important because middle-class racial and ethnic minorities are a segment of the US population that is steadily growing. The MDRs framework aligns with Navarro’s proposal of considering race/ethnicity “and” SES, rather than race/ethnicity “or” SES, as the primary contributor to health disparities[10], [11], [12]. Additionally, MDRs framework underscores poor comparability of SES indicators across racial/ethnic groups[13], [14].

The MDR framework has been applied to elucidate racial/ethnic differences in tobacco[15], marijuana[16], and alcohol[17] use among adolescents and adults. Notably, various studies have highlighted differential effects of family SES indicators such as parental educational attainment on the use of substances such as tobacco among different racial/ethnic groups[15], emphasizing the need for an understanding of the nuanced interplay between race/ethnicity and SES as correlates of youth tobacco use.

However, it is crucial to note that the existing literature predominantly relies on cross-sectional data[18], [19], [20], [21], lacking evidence from longitudinal studies[15]. Extensive research has suggested that MDRs also extend to youth across various outcomes, including tobacco use[15]. For instance, parental education has differing impacts on the transition of youth to tobacco use[15], and impulsivity[22] for White and Black youth. Yet, there is a notable scarcity of studies on the contribution of MDRs to tobacco use disparities in pre-youth transitioning to adolescence, necessitating further longitudinal investigations into the protective effects of household income on the first time of tobacco use in pre-youth.

Racial/ethnic minority youth, particularly Latino youth, emerge as a high-risk group for smoking in the U.S.[23], [24]. This heightened risk is influenced by factors such as differing perceptions of tobacco product dangers, increased experimentation with tobacco, lower perceived harm of conventional and electronic cigarettes, increased exposure to tobacco ads, and exposure to high-risk peers. Moreover, Latino and Black youth exhibit a potential telescoping effect of tobacco use, defined as the faster transition from experimental use and initiation to problem use that leads to undesired outcomes such as chronic diseases even when the smoking onset is late[25], [26], [27].

To address tobacco-related health disparities[28], [29], [30], [31], we have decided to conduct a study on MDRs, which is likely to generate a more comprehensive understanding of the intricate interplay between ethnicity and SES indicators, such as household income on youth tobacco initiation. Our longitudinal study of tobacco-naïve youth is hoped to uncover the nuanced dynamics that are evolving and contributing to racial/ethnic SES disparities, particularly among youth. The derived knowledge may inform targeted interventions and policy initiatives.

2. Methods

Adolescent Brain Cognitive Development (ABCD) Study[32], [33], [34], [35] is a longitudinal study of youth in the US. Participants were followed from baseline (time 0), and subsequent data from follow-ups each six months (month 6, month 12, month 16, month 24, and month 30). Recruitment took place between 2016 and 2018, involving participants and their parents/guardians from twenty-one research sites across 19 cities in 15 states.

The ABCD study included a cohort of 11,876 9–10-year-old pre-youth who were enrolled in the ABCD Study. The sampling strategy that was employed in the ABCD included a stratified probability approach based on eligible schools to match the sociodemographic profile of the American Community Survey (ACS)[36]. Our analysis utilized data from ABCD Data Release 4.0 (DOI: 10.15154/1523041, October 2021; data collected through February 15, 2021), covering the full year two cohort and half of the year four cohort.

The study received approval from a centralized institutional review board (IRB) at the University of California, San Diego. Detailed exclusion criteria for Baseline enrollment are available in the Supplement. Informed consent from parents/guardians and assent from youth were obtained at each session.

Each annual visit involved 1–2 sessions where the youth and one parent/guardian underwent a comprehensive assessment covering biological and behavioral domains. This included evaluations related to substance use[37]. Interviews were initially conducted in person, transitioning to virtual methods or telephone calls during the COVID-19 pandemic. Questionnaires were administered through iPads using REDCap[38], ensuring consistency across sites[39]. Youth were interviewed separately from parents, maintaining privacy during both in-person and virtual visits. Mid-year phone follow-ups included a condensed battery, focusing on the past six-month substance use[37]. While ABCD included biological markers[40], mental and physical health[41], peer, family, culture, and environment[42], genetics[43], neurocognitive functioning[44], and magnetic resonance brain imaging[45], such data were not included here.

Confidentiality was emphasized to participants before the substance use module administration, where youth indicated awareness of and experimentation with a list of substances (applicable to baseline and 24-month evaluation only). Follow-up questionnaires were administered if youth endorsed experimental use.

Our statistical analysis considered the following demographic and socioeconomic factors: baseline age (nine or ten years), sex assigned at birth (male or female), household size (number of individuals in the household), self-identified race and ethnicity (White, Black, Latino), parent/guardian highest levels of educational attainment (1–22 based on years of schooling), parents present in the household (one vs. two), parental employment (unemployed vs employed parents) and annual household annual income of the family (less than 50k, 50–100k, and 100k+) [41].

Annual assessments involved the iSay Sipping Inventory[46] for recent or first experimentation with nicotine products[37]. Follow-up questions on circumstances surrounding first use were administered at one-time point, however, such information was not included in our analysis.

At Baseline (Y0), youth reported lifetime use of tobacco products with a web-based Timeline Follow-Back (TLFB)[47] interview for substances used in the past six months (only for baseline evaluation at time 0) or since the last study session (for measures at months six, twelve, eighteen, twenty-four, and thirty months). The analysis covered various substances, and Mid-Year phone follow-ups contributed to a comprehensive past-year tobacco use for each yearly follow-up.

For current analyses, tobacco use variables were defined as follows: Tobacco use experimentation as low-level tobacco use (e.g., puffing). Tobacco initiation as reporting >1 puff of nicotine. Tobacco use onset as the time of reported tobacco use other than experimentation [48].

SPSS (v27.0)[49] was employed for analyses using ABCD Data Release 4.0 (DOI: 10.15154/1523041, October 2021). Descriptive statistics were computed overall and by race/ethnic group. Racial/ethnic differences in study variables were examined through Chi-square and ANOVA tests. A series of Cox regression modes were used to explore associations between income and time to event (from baseline to dichotomized tobacco initiation/onset (time zero to 30 months). Missing data were minimal, and participants with missing data on income or tobacco initiation were excluded from our Cox regression models[50]. Adjusted Hazard Ratios (AHRs), their 95% confidence intervals (95% CI), and p values were derived for interpretation.

3. Results

As shown in Table 1, 5664 (64.7%), 1279 (14.6%), and 1811 (20.7%) were White, Black, and Latino, respectively. Black and Latino youth were from families with lower education, employment, and income than White youth, and Black youth had lower odds of living in two-parent households compared to White or Latino youth.

Table 1.

Descriptive Data Overall and By Race/Ethnicity.

	All		White		Black		Latino
	n	%	n	%	n	%	N	%
Age
Nine	4510	51.7	2898	51.3	643	50.5	969	53.7
Ten	4215	48.3	2750	48.7	630	49.5	835	46.3
Sex
Female	4173	47.7	2668	47.1	641	50.1	864	47.7
Male	4581	52.3	2996	52.9	638	49.9	947	52.3
Two parents in the household
No	2116	24.2	806	14.2	788	61.6	522	28.8
Yes	6638	75.8	4858	85.8	491	38.4	1289	71.2
Parents Employed
No	2465	28.2	1512	26.7	389	30.4	564	31.1
Yes	6289	71.8	4152	73.3	890	69.6	1247	68.9
Family Income
Less than 50 K	2379	27.2	694	12.3	836	65.4	849	46.9
50–100 K	2555	29.2	1723	30.4	283	22.1	549	30.3
100 K+	3820	43.6	3247	57.3	160	12.5	413	22.8
Tobacco Use
No	8485	96.9	5502	97.1	1242	97.1	1741	96.1
Yes	269	3.1	162	2.9	37	2.9	70	3.9
Race
White	5664	64.7
Black	1279	14.6
Latino	1811	20.7
Empty Cell	Mean	SD	Mean	SD	Mean	SD	Mean	SD
Time (Follow Up in Months)	33.8772	6.50844	5.7334	.92405	5.3597	1.40938	5.5759	1.23671
HH size	4.7161	1.51547	4.7316	1.39494	4.6098	1.83322	4.7402	1.63617

Overall, 3.1% (n = 269) of youth transitioned to tobacco use, which was composed of 162White (2.9%), 37 Black (2.9%), and 70(3.9%) Latino youth.

Overall, 3.1% (n = 269) of youth transitioned to tobacco use, which was composed of 162White (2.9%), 37 Black (2.9%), and 70(3.9%) Latino youth.

As shown in Table 2, a family income exceeding $100,000 per year was associated with a lower hazard ratio for tobacco initiation (transitioning to ever-use) over the follow-up period (HR = 0.620, p = 0.022). However, household income of $50–100k exhibited significant interactions with race/ethnicity on tobacco initiation, indicating weaker protective effects for Black (HR for interaction = 7.860, p < 0.001) and Latino (HR for interaction = 3.461, p = 0.001) youth compared to non-Latino White youth.

Table 2.

Summary of Cox Regressions in the Pooled Sample.

Empty Cell	B	SE	Exp(B)	Lower 95.0% CI for Exp(B)	Upper 95.0% CI for Exp(B)	P Value
Model 1
Race/Ethnicity						.063
White	Ref
Black	−.487	.218	.614	.401	.941	.025
Latino	−.028	.164	.973	.705	1.342	.867
Sex (Male)	−.031	.124	.970	.761	1.235	.803
Household Size	.021	.041	1.021	.942	1.107	.612
Age (9–10) Years	.816	.132	2.262	1.748	2.928	<.001
Two Parents in the Household (Married Or Partnered)	−.508	.160	.602	.440	.824	.002
Highest Parental Education (1–21) Years	−.084	.026	.919	.873	.967	<.001
Neighborhood Household Income_(/50000)	.166	.160	1.180	.863	1.614	.299
Household Annual Income						.027
Less than 50 K	Ref
50–100 K	−.076	.175	.927	.657	1.307	.664
100 K+	−.478	.208	.620	.413	.932	.022
Model 2
Race/Ethnicity						<.001
White	Ref
Black	−1.143	.286	.319	.182	.558	<.001
Latino	−.596	.243	.551	.343	.887	.014
Sex (Male)	−.032	.124	.968	.760	1.233	.793
Household Size	.016	.041	1.016	.938	1.101	.693
Age (9–10) Years	.815	.132	2.258	1.745	2.923	<.001
Two Parents in the Household (Married Or Partnered)	−.492	.159	.611	.448	.834	.002
Highest Parental Education (1–21) Years	−.095	.026	.909	.863	.957	<.001
Neighborhood Household Income_(/50000)	.091	.157	1.095	.804	1.490	.564
Household Annual Income						<.001
Less than 50 K
50–100 K	−.425	.212	.654	.431	.992	.046
100 K+	−.941	.228	.390	.250	.610	<.001
Race/Ethnicity × Household Income						<.001
50–100 K × Black	.831	.467	2.295	.919	5.734	.075
100 K+ × Black	2.062	.487	7.861	3.025	20.431	<.001
50–100 K × Latino	.633	.347	1.883	.954	3.715	.068
100 K+ × Latino	1.242	.381	3.461	1.639	7.308	.001

Table 3 summarizes Cox Regressions in each race/ethnic group. Only in White youth (HR =.436, 95% CI =.263 –.724, p =.001), an income more than 100 k was protective against subsequent tobacco use. This effect was non-significant for Black or Latino youth.

Table 3 summarizes Cox Regressions in each race/ethnic group. Only in White youth (HR =.436, 95% CI =.263–.724, p =.001), an income more than 100 k was protective against subsequent tobacco use. This effect was non-significant for Black or Latino youth.

Table 3.

Summary of Cox Regressions in each race/ethnic group.

Empty Cell	B	SE	Exp(B)	Lower 95.0% CI for Exp(B)	Upper 95.0% CI for Exp(B)	P Value
White
Sex (Male)	−.147	.158	.863	.634	1.177	.352
Household Size	−.036	.058	.964	.860	1.081	.534
Age (9–10) Years	.826	.169	2.283	1.640	3.179	<.001
Two Parents in the Household (Married Or Partnered)	−.442	.217	.643	.420	.984	.042
Highest Parental Education (1–21) Years	−.140	.039	.869	.805	.939	<.001
Neighborhood Household Income_(/50000)	.017	.219	1.017	.662	1.564	.937
Household Annual Income						.004
Less than 50 K	Ref.
50–100 K	−.361	.227	.697	.447	1.088	.112
100 K+	−.829	.259	.436	.263	.724	.001
Black						.
Sex (Male)	.531	.353	1.700	.850	3.399	.133
Household Size	.029	.098	1.030	.849	1.248	.767
Age (9–10) Years	.360	.350	1.434	.722	2.846	.303
Two Parents in the Household (Married Or Partnered)	−.563	.434	.569	.243	1.332	.194
Highest Parental Education (1–21) Years	−.006	.084	.994	.842	1.172	.940
Neighborhood Household Income_(/50000)	.263	.379	1.301	.619	2.735	.488
Household Annual Income						.404
Less than 50 K	Ref.
50–100 K	.219	.475	1.244	.490	3.159	.646
100 K+	.807	.609	2.242	.680	7.391	.185
Latino						.
Sex (Male)	−.009	.244	.991	.615	1.598	.971
Household Size	.117	.074	1.125	.973	1.300	.112
Age (9–10) Years	1.050	.267	2.858	1.695	4.820	<.001
Two Parents in the Household (Married Or Partnered)	−.581	.279	.560	.324	.968	.038
Highest Parental Education (1–21) Years	−.074	.040	.929	.858	1.005	.066
Neighborhood Household Income_(/50000)	.093	.268	1.097	.649	1.856	.729
Household Annual Income						.782
Less than 50 K	Ref.
50–100 K	.182	.311	1.200	.652	2.209	.558
100 K+	.247	.393	1.280	.593	2.763	.529

4. Discussion

The present study yielded two noteworthy findings. Firstly, in the overall sample, household income of more than 100k emerged as a protective factor against tobacco use initiation among tobacco-naïve youth. Secondly, the protective influence of high household income against the subsequent transition to tobacco use was attenuated for Black and Latino youth compared to their non-Latino and White counterparts.

The overarching finding concerning the protective effects of household income aligns with established knowledge on social patterning, social determinants[51], fundamental causes[52], [53], [54], and social gradients[55] in health and health behaviors. Extensive theoretical and empirical research in the U.S.[52], [53], [54], Europe[55], and globally[51] has consistently documented that high household income is a key protective resource against various risk behaviors among youth. As shown by the literature, high household income not only guards against tobacco use but also shields against its risk factors such as depression, anxiety, and school dropout.

Our findings for Black and Latino youth resonate with prior research indicating that high household income and other SES indicators, such as educational attainment, marital status, and employment, have weaker protective effects on the health and behaviors of Black and Latino youth and adults. As such, highly educated Black and Latino youth and adults with high SES remain at a disproportionately higher risk of health problems[4]. As a result of MDRs, youth and adults from high SES background may remain at risk of substance use[15]—a risk level not anticipated given their family SES. This observation may contribute to understanding why Black and Latino youth and adults remain susceptible to chronic respiratory and cardiovascular disease.

Thus, while household income serves as a protective factor against youth tobacco use initiation, this protection appears unequal, with Blacks and Latinos experiencing weaker safeguarding compared to the non-Latino and White populations. A paper using PATH data [15] showed the same pattern for parental education of Latino populations. These two studies exemplify how race/ethnicity, as a marginalizing social identity, diminishes the protective effects of household economic resources as a fundamental SES resource against subsequent tobacco use for racial and ethnic minority groups.

There are also other studies that show neurocognitive mechanisms for such effects[56]. An analysis of 15-year-old youth in the Fragile Families and Child Well-being Study (FFCWS) showed that while high SES, such as household income and parental education, provide better protection against poor emotion regulation and impulse control of adolescents, these effects are weaker for Black and Latino youth[22]. These suggest that Minorities’ Diminished Returns (MDRs) are a systematic mechanism for transgenerational transmission of health inequalities in the US. Interventions should be implemented across different SES levels to address these disparities effectively. Other ABCD papers showed that SES effects on the youth brain are weaker for Black and Latino youth[57], [58].

Multiple socioeconomic mechanisms may explain the high tobacco risk of high SES Black and Latino youth and adults. First, regardless of their SES, Black and Latino communities may be targeted by aggressive tobacco marketing strategies[59]. Studies have shown high tobacco ad exposure of high SES Black and Latino people[59]. Another mechanism is that high SES Black and Latino people remain in at-risk neighborhoods[60]. Stress remains high in the lives of Black and Latino youth from high SES families[61]. Depression may also remain high in high SES Black youth[62]. Other explanation is that high SES Black and Latino youth and adults have less knowledge regarding tobacco harm. Finally, the presence of more peers[63] and family members[64] engaging in substance use and attending schools with higher social-environmental risks[63] further compounds the risk of tobacco use among high SES Black and Latino youth.

Racial and ethnic residential segregation may contribute to some of these MDRs, impacting the availability of cigarettes and fostering advertising and sales in communities of color[59]. The affordability of tobacco use in Latino and low-income communities is influenced by strategies such as the sale of single cigarettes. Greater education does not necessarily translate into the ability to purchase homes in neighborhoods with regulated tobacco sales and advertising.

Tobacco products are heavily promoted in Black and Latino communities, with tobacco companies employing branding, financial contributions, targeted advertising, and other marketing strategies to appeal to this population[65]. Predatory marketing practices may play a role in generating MDRs in tobacco use for racial and ethnic minority youth, imposing additional risks through the reduction of SES effects. High SES Black and Latino youth may be exposed to a dense concentration of tobacco retailers and advertisements. Implementing more restrictive tobacco marketing regulations, such as banning additional point-of-sale advertisements, flavoring, coupons, and discounts in predominantly ethnic minority areas, could be particularly beneficial to Black and Latino populations. However, these hypotheses warrant further research to deepen our understanding of the complex interplay between marketing practices, ethnicity, and SES disparities in tobacco use.

The results are important given the very long term of substance use of youth in their development[66]. As a public health priority, countries try to prevent youth substance use initiation[67]. In a recent analysis of Swedish registry, the hazard ratio for substance use among individuals experiencing poverty compared with those never lived in poverty was 1.40. The study showed that 25% of this association in females, and 13% of this association in males can be explained by adolescent psychiatric disorders [68]. Another analysis of Swedish registry introduced five trajectories of childhood/adolescence poverty: (1) never poor, (2) moving out of poverty in childhood) (3) moving into poverty in adolescence; (4) moving out of poverty in adolescence; and (5) always poor. All other trajectory groups had higher risks for drug use problems than ‘never poor’ group [69].

The findings of this study hold important policy and public health implications, shedding light on factors influencing susceptibility to tobacco use and contributing to the development of tobacco-related disparities. These insights can guide the formulation and implementation of public policies aimed at addressing these disparities, including more stringent national and local marketing regulations[70]. The literature indicates a positive reception of tobacco control regulations among Americans, with these measures not perceived as infringing on personal autonomy[70]. This favorable sentiment provides a conducive environment for the implementation of policies designed to combat tobacco-related health disparities. There is a pressing need for comprehensive national and local policies explicitly targeting Minorities’ Diminished Returns (MDR)-related disparities in tobacco use and associated health conditions. Future research should delve into the roles played by factors such as discounts, coupons, flavoring, and the density of tobacco retailers in shaping MDR-related disparities in tobacco use[71]. Additionally, understanding the impact of tobacco control policies and regulations in mitigating MDR-related tobacco disparities is crucial. An essential focus should be on investigating how marketing strategies specifically target Black and Latino communities across SES levels[72]. To address racial and ethnic disparities in tobacco use, it is imperative to curb predatory tobacco marketing practices in racial and ethnic minority areas. The reduction of MDR-related inequalities needs to be recognized as a central element within tobacco prevention strategies, particularly for middle-class racial and ethnic minorities. Leveraging these study findings to inform and advocate for targeted policies and programs is crucial in the ongoing efforts to minimize tobacco-related health disparities that affect Black and Latino youth across SES levels. This includes not only addressing tobacco marketing practices but also developing strategies that acknowledge and counteract the diminished returns of household income that is experienced by racial and ethnic minorities in the context of tobacco use and beyond.

This study is subject to a few methodological limitations. Notably, the sample size exhibited imbalances across racial and ethnic groups. We also had a low percentage that transitioned to tobacco use. As such, we decided not to conduct racial and ethnic-specific models to prevent disparate statistical power across groups. Some potential confounders such as geographic location (zip code) which could serve as a pseudo variable for access to tobacco products in one’s community were not included. Another confounder which was not included is mental and physical health since youth having more mental health issues are more likely to use tobacco as well as more likely to be from a lower socioeconomic environment. Additionally, crucial socioeconomic indicators such as wealth were not included in the study, potentially impacting the comprehensiveness of our analysis. The absence of parental smoking data introduces the possibility of unmeasured confounding. The study lacked information on parental substance use. Factors such as state and local policies, school context, and peer behaviors that are all relevant to youth smoking were not explicitly considered. Moreover, our study did not account for variations in tobacco products that may correlate differently with SES and tobacco control policies. Despite these limitations, the study boasts notable strengths, including a large sample size, robust methodology, and a longitudinal design. While the results are not generalizable to the US, our findings are in line with a past study using a nationally representative sample[15]. The longitudinal approach allowed for modeling the incidence of youth tobacco use transitions, offering a nuanced perspective on time to initiate tobacco beyond the cross-sectional prevalence of tobacco use. In addition, this is one of few longitudinal studies on 9–10 year old children who are tobacco naive at baseline and are followed for initiation of substances over time.

5. Conclusion

Within the United States, minority youth face a relative disadvantage compared to their non-Latino White counterparts in reaping tobacco use prevention benefits from household income. Although elevated household income is associated with reduced tobacco use among adolescents, this trend is more pronounced in the most privileged, namely non-Latino White youth, as opposed to their Black and Latino counterparts. Consequently, there is an anticipated higher-than-expected risk of tobacco use in Black and Latino youth from high-SES families. This underscores the presence of tobacco-related health disparities that extend beyond the scope of SES factors, necessitating further exploration into structural elements contributing to the diminished protective effects of household income on tobacco use among middle-class Black and Latino youth. Research efforts should delve into these structural factors to gain a comprehensive understanding of the nuanced dynamics influencing tobacco-related health outcomes in this demographic.