Discrimination Distress and Current Combustible and Non-combustible Tobacco Product Use Among US Youth, 2023

Meman Diaby; Osayande Agbonlahor; Maggie K Richardson; Joy L Hart; Shyanika W Rose; Delvon T Mattingly

doi:10.1093/ntr/ntaf166

. 2025 Aug 5;28(1):97–107. doi: 10.1093/ntr/ntaf166

Discrimination Distress and Current Combustible and Non-combustible Tobacco Product Use Among US Youth, 2023

Meman Diaby ^1,^✉, Osayande Agbonlahor ², Maggie K Richardson ³, Joy L Hart ^4,^5,⁶, Shyanika W Rose ^7,^8,⁹, Delvon T Mattingly ^10,^11,¹²

¹ Center for Health, Engagement, and Transformation, College of Medicine, University of Kentucky, Lexington, KY, USA

² Department of Preventive Medicine, University of Mississippi Medical Center, Jackson, MS, USA

³ Department of Educational, School, & Counseling Psychology, College of Education, University of Kentucky, Lexington, KY, USA

⁴ Department of Communication, College of Arts and Sciences, University of Louisville, Louisville, KY, USA

⁵ Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY, USA

⁶ American Heart Association Tobacco Center for Regulatory Science, Dallas, TX, USA

⁷ Center for Health, Engagement, and Transformation, College of Medicine, University of Kentucky, Lexington, KY, USA

⁸ Department of Behavioral Science, College of Medicine, University of Kentucky, Lexington, KY, USA

⁹ Markey Cancer Center, College of Medicine, University of Kentucky, Lexington, KY, USA

¹⁰ Center for Health, Engagement, and Transformation, College of Medicine, University of Kentucky, Lexington, KY, USA

¹¹ Department of Behavioral Science, College of Medicine, University of Kentucky, Lexington, KY, USA

¹² Markey Cancer Center, College of Medicine, University of Kentucky, Lexington, KY, USA

^✉

Corresponding Author: Meman Diaby, MS, Center for Health, Engagement, and Transformation, College of Medicine, University of Kentucky, Lexington, KY 40536, USA. Telephone: 1 (859) 323-0464; E-mail: Meman.Diaby@uky.edu

Roles

Meman Diaby: MS, Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Writing - original draft, Writing - review & editing

Osayande Agbonlahor: MD, PhD, Conceptualization, Investigation, Validation, Writing - review & editing

Maggie K Richardson: MS, MA, Validation, Writing - review & editing

Joy L Hart: PhD, Conceptualization, Funding acquisition, Validation, Writing - review & editing

Shyanika W Rose: MA, PhD, Funding acquisition, Validation, Writing - review & editing

Delvon T Mattingly: PhD, Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Resources, Software, Supervision, Validation, Writing - review & editing

PMCID: PMC12723236 PMID: 40973143

Abstract

Introduction

Discrimination is the unfair treatment of people based on their identity. Youth who experience discrimination may cope with associated distress by using tobacco products, with amplified health consequences depending on the type of product.

Methods

We used data from the 2023 National Youth Tobacco Survey (n = 22 069) and derived an overall continuous measure from the 15-item Adolescent Discrimination Distress Index, as well as three continuous discrimination distress sub-indices: educational, institutional, and peer (range for each: 0–5). We defined current tobacco use as two outcomes: any past 30-day use of combustible (cigarettes, cigars, hookah, roll-your-own, pipe, bidis) and non-combustible (e-cigarettes, smokeless tobacco, snus, heated tobacco, nicotine pouches, oral nicotine) products. To estimate associations between discrimination measures and tobacco use outcomes, we conducted multivariable logistic regression.

Results

Youth experienced more educational (mean = 0.56) than peer (mean = 0.48) and institutional (mean = 0.38) discrimination distress, and the prevalence of current combustible and non-combustible tobacco use was 3.89% and 9.67%. A single unit increase in overall discrimination distress was associated with increased odds of combustible (AOR: 1.26, 95% CI: 1.08 to 1.47) and non-combustible (AOR: 1.23, 95% CI: 1.09 to 1.39) tobacco use. For subindices, only a single unit increase in institutional discrimination distress was associated with current combustible tobacco use (AOR: 1.30, 95% CI: 1.06 to 1.59).

Conclusion

Overall discrimination distress was associated with current use of combustible and non-combustible tobacco products; however, only institutional discrimination distress was associated with combustible product use. These findings highlight the importance of considering discriminatory contexts as they relate to potential youth tobacco use as a distress-coping mechanism.

Implications

This study adds to the growing evidence that discrimination distress, particularly in institutional contexts, is associated with youth combustible tobacco use. By highlighting the unique role of institutional discrimination in tobacco use, our findings emphasize the need for targeted interventions to address discriminatory environments in these settings. These results underscore the importance of integrating anti-discrimination policies and support systems into tobacco prevention efforts to reduce maladaptive behaviors among youth. This research also suggests examining how differing discrimination contexts may shape nicotine use behavior, potentially revealing insights helpful in tailoring prevention strategies.

Introduction

Tobacco use is a public health concern due to its addictive properties, extensive physical health risks, and associated economic burden of tobacco-related disease and healthcare costs.¹ The 2023 National Youth Tobacco Survey (NYTS) found that 22.2% (approximately 6.21 million) of US middle and high school students had ever used a tobacco product.² Meanwhile, 10.0% (about 2.80 million students) reported using tobacco products currently.² Although recent declines in youth tobacco consumption have been observed,³^,⁴ concerns persist regarding the potential long-term health risks for youth who initiate and continue to use tobacco products.⁵^,⁶

Understanding factors influencing youth tobacco use, especially among marginalized groups, is essential. These groups often face unique challenges and stressors, such as interpersonal and systemic discrimination, potentially associated with socioeconomic disparities and limited access to resources, that may exacerbate their vulnerability to tobacco use.⁷ Among these challenges, experiences with racial and ethnic discrimination can contribute to stress, depression, and anxiety, and potentially lead to coping with tobacco use.⁷^,⁸ Psychological distress due to these discriminatory experiences may further amplify these effects, creating a feedback loop of heightened vulnerability.⁹

Adolescence is a formative period where experiences of discrimination can profoundly affect psychological well-being and developmental outcomes.^10–13 Certain populations, particularly racial and ethnic minority youth, are more likely to be exposed to discrimination and the associated distress.¹⁴ Studies have shown that exposure to racial and ethnic discrimination during this critical period is associated with increased risk of mental health issues such as anxiety, depression, lower self-esteem, and poorer academic performance.^10–13 These experiences can contribute to long-term disparities in social, educational, and health outcomes, shaping trajectories into adulthood.¹⁰^,¹² While many studies have focused on adverse outcomes associated with experiences of discrimination, perceptions about discrimination also matter for these outcomes to manifest. For example, among women high in optimism, perceived racial discrimination can be linked with health-promoting behaviors.¹⁵ Moreover, previous studies have shown that various kinds of perceived racial discrimination are associated with high tobacco consumption among adults¹⁶^,¹⁷ and youth.^18–20 For instance, a study analyzing data from the 2021 Adolescent Behaviors and Experiences Survey found that perceived racism and discrimination at school were associated with increased current tobacco product, marijuana, alcohol, and prescription opioid use among US high school students.¹⁸ However, most studies on discrimination in tobacco use have either focused on a single product or prioritized traditional products such as cigarettes, cigars, hookah, e-cigarettes, or smokeless tobacco and have often relied on non-nationally representative samples.¹⁷^,²¹^,²² It is essential to understand the impact of discrimination on the use of emerging non-combustible tobacco products, such as nicotine pouches, which are growing in popularity among youth.³^,²³ According to Jamal et al.’s analysis of NYTS 2024 data, nicotine pouches were the second most commonly used tobacco product, with 890 000 students reporting current use in 2024.³

Notably, while perceived racial and ethnic discrimination is widely linked to tobacco consumption in the United States, it is also critical to examine whether distress attributable to perceived racial and ethnic discrimination influences the consumption and patterns of use of emerging tobacco products across diverse youth populations.³^,¹⁸^,²³^,²⁴ Understanding these associations is also essential for addressing the broader implications of perceived racial and ethnic discrimination and developing targeted interventions to mitigate its deleterious effects.²⁴ This study examines the associations of perceived racial and ethnic discrimination distress (hereafter “discrimination distress”) on current use of non-combustible and combustible tobacco products among youth. We hypothesize that youth experiencing higher levels of perceived discrimination distress are more likely to use tobacco products and that this relationship persists even after accounting for sociodemographic factors.

Methods

Data and Participants

This study used data from the 2023 National Youth Tobacco Survey (NYTS), conducted by the US Food and Drug Administration and the Centers for Disease Control and Prevention. The NYTS is a nationally representative, cross-sectional, school-based, self-administered web survey of middle and high school students across the United States. NYTS employed a stratified, three-stage cluster sampling technique to achieve a representative sample of US middle and high school students.²⁵ In 2023, NYTS included 22 069 students from 179 schools, achieving an overall response rate of 30.5%, with a school response rate of 33.6% and a student response rate of 70.9%.²⁵ This study was deemed exempt from review by the University of Kentucky institutional review board, given use of publicly available, deidentified data, and followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.²⁶

In our analysis, principal variables included age, gender, academic grades, sexual orientation, race and ethnicity, secondhand smoking/vaping exposure, multilingual status, any past 30-day use of combustible products (cigarettes, cigars, hookah, roll-your-own, pipe, bidis), any past 30-day use of non-combustible products (e-cigarettes, smokeless tobacco, snus, heated tobacco, nicotine pouches, oral nicotine), and discrimination indicators. To address missing data concerns, we employed multiple imputation using the “mice” package in R. Predictive mean matching and logistic regression were used to impute values, tailored to the specific types of variables involved.²⁷ This approach generated five imputed datasets (m = 5), preserving the dataset’s structure and essential demographic and behavioral patterns while addressing missingness.²⁸ Parameter estimates and significance levels reported in this study were combined across these datasets.²⁹

Supplementary Table S1 displays the distributions of participant characteristics prior to multiple imputation. Approximately one-fourth of participants (25.60%) had missing observations in one or more of these variables before the imputation process.

Measures

Discrimination Distress

In the 2023 NYTS, participants were asked if they had ever experienced any of 15 distinct discriminatory situations (yes/no) because of their race and ethnicity. These situations were (1) being discouraged from joining an advanced-level class, (2) receiving a lower grade than deserved, (3) being wrongfully disciplined, (4) being discouraged from joining a club, (5) being excluded from peer activities, (6) being held to higher expectations compared to peers, (7) being held to lower expectations compared to peers, (8) having assumptions made about their English proficiency, (9) being hassled by police, (10) being hassled by store staff, (11) being called racially insulting names, (12) receiving poor service in public establishments, (13) having people assume they were not smart, (14) being treated with fear by others, and (15) being threatened.³⁰ For each situation to which they responded “yes,” participants were then asked, “How much did this experience upset you?” with response options ranging from 1 (Not at all) to 5 (Extremely). From these responses, we created a continuous distress index ranging from 0 to 5 by averaging the scales, where 0 indicated that participants did not experience these situations and 5 indicated they were extremely upset by these situations. The weighted distribution of each individual discrimination measure is displayed in Supplementary Table S2.

Based on prior work by Fisher et al.,³⁰ we divided this distress measure into three subscales reflecting different contexts of discrimination distress: (1) institutional (including being held to lower expectations, being hassled by police, being hassled by store staff, receiving poor service, being assumed not smart, being treated with fear), (2) educational (including being discouraged from advanced-level classes, being wrongfully disciplined, receiving a lower grade, being held to higher expectations), and (3) peer (including being discouraged from joining clubs, being excluded from activities, assumptions about English proficiency, being called racial names, being threatened) distress.³⁰ These categorizations were identified using a three-factor principal components analysis, which distinguished institutional, educational, and peer discrimination as distinct but interrelated dimensions of discrimination distress, reflecting systemic structures rather than isolated individual actions.³⁰ The subscales were defined by grouping the individual items corresponding to each context of discrimination distress and calculating the average score for each subscale. As a result, the subscale scores ranged from 0 to 5, with a score of 0 indicating no reported experiences of discrimination, and higher scores indicating greater levels of distress.

Furthermore, we created binary versions of the three discrimination distress subscales, as well as the overall discrimination index, by classifying participants based on whether they reported any experience of discrimination-related events (yes/no).

Current Tobacco Use

Participants were asked if they used the following tobacco products in the past 30 days: cigarettes, cigars, hookah, roll-your-own, pipe, bidis, e-cigarettes, smokeless tobacco, snus, heated tobacco, nicotine pouches, and oral nicotine. The weighted distribution of each tobacco product use outcome is displayed in Supplementary Table S3.

From their responses, we defined two variables, current combustible tobacco use as any use of combustible products (cigarettes, cigars, hookah, roll-your-own, pipe, bidis) and non-combustible tobacco use as any use of non-combustible products (e-cigarettes, smokeless tobacco, snus, heated tobacco, nicotine pouches, oral nicotine) within the past 30 days.

Covariates

The following sociodemographic characteristics were included: (1) age (9–12, 13–15, ≥16 years), (2) race and ethnicity (Hispanic; non-Hispanic [NH] White, NH Black, NH multiracial, some other NH race including NH Asian, American Indian/Alaska Native, or Native Hawaiian/Other Pacific Islander), (3) gender (male, female, non-binary, or something else, other responses including “Not sure/Questioning” and “Decline to answer”), (4) sexual orientation (heterosexual, lesbian, gay, or bisexual [LGB] or something else, other responses including “Not Sure/Questioning,” “Don’t know,” and “Decline to answer”), (5) past-year academic performance (A’s, B’s, C/D/F’s, none/unspecified), (6) past-week smoking or vaping secondhand exposure (yes/no), and (7) multilingual status (yes/no).

Statistical Analysis

We estimated the weighted distribution of sociodemographic characteristics, current tobacco use, and discrimination distress. Next, we calculated the prevalence of each sociodemographic characteristic and discrimination distress level by current combustible and non-combustible tobacco use and assessed associations using Wald test p-values to evaluate the distribution of each sociodemographic characteristic across tobacco product use categories.

We then conducted both bivariate and multivariable logistic regression analyses. Specifically, we ran two multivariable logistic regression models, adjusting for age, race/ethnicity, gender, sexual orientation, past-year academic performance, past-week smoking or vaping secondhand exposure, and multilingual status, to estimate adjusted associations between overall discrimination distress and current tobacco use, as well as between the three sub-indices of discrimination distress and current tobacco use. A significance level of p < .05 was set. Additionally, we conducted two sensitivity analyses to assess the impact of overall discrimination distress and the three-discrimination distress sub-indices on current use of each individual tobacco product by running both bivariate and multivariable logistic regression analyses.

We imported the imputed datasets from R and performed all analyses in STATA version 18.0, using the “mi estimate, svy:” command to account for the NYTS study design, adjust for non-response and selection probabilities, and appropriately handle multiple imputed datasets to ensure valid parameter estimates and standard errors reflecting the uncertainty introduced by missing data.³¹

Results

Distribution of Participant Characteristics

Table 1 presents the weighted prevalence of sociodemographic characteristics, current tobacco use, and experiences of discrimination among the sample. Regarding age, the largest proportion of participants was aged 13–15 (45.27%) years, followed by those aged 16 and older (37.38%) and 9–12 (17.35%). For race and ethnicity, participants who identified as NH White represented the highest proportion of the overall sample (46.00%), whereas NH multiracial (4.18%) and another NH race (7.29%) represented the lowest proportions. In terms of gender, male participants (45.80%) were the highest proportion, followed by female (43.05%), other responses (6.30%), and nonbinary or something else (4.85%).

Table 1.

Weighted Prevalence of Sociodemographic, Current Tobacco Use, and Discrimination Characteristics (n = 22 069)

	Percentage	95% CI
Covariates, n (%)
Age in years
9–12	17.35%	13.33% to 21.37%
13–15	45.27%	40.01% to 50.53%
≥16	37.38%	31.81% to 42.94%
Race and ethnicity
Hispanic	28.69%	25.14% to 32.24%
Non-Hispanic White	46.00%	41.74% to 50.26%
Non-Hispanic Black	13.84%	11.53% to 16.16%
Non-Hispanic multiracial	4.18%	3.47% to 4.89%
Another non-Hispanic race^a	7.29%	5.77% to 8.81%
Gender
Male	45.80%	43.76% to 47.84%
Female	43.05%	40.94% to 45.15%
Nonbinary or something else	4.85%	3.97% to 5.72%
Other^b	6.30%	5.52% to 7.09%
Sexual orientation
Heterosexual	62.61%	60.41% to 64.81%
LGB or something else	16.87%	15.41% to 18.34%
Uncertain^c	20.51%	18.89% to 22.14%
Student grades
A’s	42.74%	39.81% to 45.66%
B’s	29.95%	28.66% to 31.23%
C/D/F’s	18.88%	16.52% to 21.23%
None/unspecified	8.44%	7.25% to 9.62%
Secondhand smoking/vaping exposure (yes)	36.48%	34.45% to 38.51%
Multilingual status (yes)	34.56%	30.90% to 38.21%
Current tobacco product use, n (%)
Combustible products (yes)^d	3.89%	3.19% to 4.59%
Non-combustible products (yes)^e	9.67%	8.58% to 10.77%
Discrimination distress (binary), n (%)
Any discrimination (yes)	56.21%	53.69% to 58.73%
Any educational discrimination (yes)	41.11%	39.00% to 43.22%
Any institutional discrimination (yes)	35.15%	32.79% to 37.50%
Any peer discrimination (yes)	40.48%	37.76% to 43.20%
Discrimination distress (continuous)	Mean
Overall discrimination (range: 0–5)	0.48	0.44 to 0.51
Educational discrimination (range: 0–5)	0.56	0.53 to 0.60
Institutional discrimination (range: 0–5)	0.38	0.35 to 0.42
Peer discrimination (range: 0–5)	0.48	0.44 to 0.52

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Another non-Hispanic race includes respondents who identified as non-Hispanic Asian, American Indian/Alaska Native, or Native Hawaiian/Other Pacific Islander.

Other includes people who responded: “Not Sure/Questioning and Decline to answer.”

Uncertain includes people who responded: “Not Sure/Questioning, Don’t know, and Decline to answer.”

Combustible includes the following products: cigarettes, cigars, hookah, roll-your-own, pipe, and bidis.

Non-combustible includes the following products: e-cigarettes, smokeless tobacco, snus, heated tobacco, nicotine pouches, and oral nicotine.

For sexual orientation, those identifying as heterosexual had the highest proportion of the overall sample (62.61%) compared to those identifying as LGB or something else (16.87%) and those uncertain (20.51%). In terms of academic performance, participants reporting A grades represented the highest proportion of the sample (42.74%), followed by those with B grades (29.95%), C/D/F grades (18.88%), and those with unspecified or no reported grades (8.44%).

A total of 36.48% of participants reported secondhand exposure to smoking or vaping, and 34.56% reported being multilingual. Experiences of discrimination were also prevalent, with 56.21% reporting any type of discrimination, 41.11% reporting educational discrimination, 35.15% reporting institutional discrimination, and 40.48% reporting peer discrimination.

Current use of combustible tobacco products was reported by 3.89% of participants. More participants (9.67%) reported current use of non-combustible tobacco products.

Current Tobacco Product Use by Covariate Characteristics and Discrimination Distress

Table 2 presents current tobacco product use by sociodemographic characteristics and situation of discrimination distress. For the continuous discrimination distress indices, mean scores were higher among participants currently using both combustible (0.79) and non-combustible (0.68) tobacco products. This trend was also reflected in the subindices.

Table 2.

Weighted Prevalence of Sociodemographic Characteristics and Discrimination Distress by Current Combustible and Non-combustible Tobacco Product Use (n = 22 069)

	Combustible tobacco use^a			Non-combustible tobacco use^b
	No	Yes	p ^c	No	Yes	p ^c
	Percentage (95% CI)	Percentage (95% CI)		Percentage (95% CI)	Percentage (95% CI)
Covariates
Age in years			.001			<.001
9–12	17.62% (13.51% to 21.74%)	10.67% (5.70% to 15.65%)		18.33% (14.05% to 22.61%)	8.21% (5.94% to 10.48%)
13–15	45.35% (40.13% to 50.57%)	43.36% (32.92% to 53.80%)		45.79% (40.62% to 50.97%)	40.39% (32.50% to 48.28%)
≥16	37.03% (31.50% to 42.56%)	45.97% (36.56% to 55.37%)		35.88% (30.31% to 41.45%)	51.40% (43.34% to 59.46%)
Gender			.006			<.001
Male	45.99% (43.85% to 48.14%)	41.13% (35.37% to 46.90%)		46.77% (44.51% to 49.03%)	36.81% (31.83% to 41.79%)
Female	43.38% (41.31% to 45.45%)	34.71% (27.02% to 42.41%)		42.72% (40.52% to 44.92%)	46.11% (40.13% to 52.09%)
Non-binary or something else	4.45% (3.61% to 5.30%)	14.57% (8.01% to 21.14%)		4.26% (3.43% to 5.08%)	10.34% (6.43% to 14.25%)
Other^d	6.17% (5.39% to 6.95%)	9.58% (5.29% to 13.88%)		6.26% (5.42% to 7.09%)	6.74% (4.69% to 8.79%)
Race and ethnicity			.014			.006
Hispanic	28.40% (24.90% to 31.90%)	35.88% (29.13% to 42.64%)		28.20% (24.84% to 31.56%)	33.24% (27.19% to 39.29%)
Non-Hispanic White	46.42% (42.22% to 50.61%)	35.71% (27.09% to 44.33%)		46.18% (41.91% to 50.44%)	44.34% (36.93% to 51.75%)
Non-Hispanic Black	13.66% (11.39% to 15.92%)	18.39% (10.48% to 26.29%)		14.11% (11.70% to 16.53%)	11.33% (8.20% to 14.45%)
Non-Hispanic multiracial	4.18% (3.44% to 4.91%)	4.25% (2.27% to 6.23%)		4.06% (3.32% to 4.80%)	5.31% (3.50% to 7.13%)
Another non-Hispanic race^e	7.35% (5.91% to 8.80%)	5.78% (2.29% to 10.42%)		7.45% (5.96% to 8.94%)	5.78% (0.82% to 10.74%)
Sexual orientation			<.001			.001
Heterosexual	63.17% (60.87% to 65.47%)	48.72% (41.82% to 55.62%)		63.25% (60.95% to 65.55%)	56.67% (50.97% to 62.37%)
LGB or something else	16.26% (14.71% to 17.82%)	32.06% (24.22% to 39.90%)		15.90% (14.34% to 17.46%)	25.98% (20.44% to 31.52%)
Uncertain^f	20.57% (18.89% to 22.24%)	19.22% (13.44% to 25.01%)		20.85% (19.25% to 22.45%)	17.35% (13.42% to 21.28%)
Student grades			<.001			<.001
A’s	43.55% (40.59% to 46.52%)	22.57% (14.71% to 30.43%)		44.14% (41.02% to 47.25%)	29.67% (24.82% to 34.52%)
B’s	30.05% (28.72% to 31.39%)	27.29% (19.50% to 35.09%)		30.08% (28.57% to 31.59%)	28.69% (23.48% to 33.90%)
C/D/F’s	18.25% (15.94% to 20.56%)	34.41% (27.09% to 41.73%)		17.72% (15.37% to 20.07%)	29.68% (25.54% to 33.83%)
None/unspecified	8.14% (6.93% to 9.35%)	15.73% (10.12% to 21.34%)		8.06% (6.79% to 9.33%)	11.95% (8.45% to 15.45%)
Secondhand smoking/vaping exposure			<.001			<.001
Yes	34.93% (32.91% to 36.94%)	74.92% (67.26% to 82.57%)		33.06% (30.97% to 35.14%)	68.45% (62.44% to 74.46%)
No	65.07% (63.06% to 67.09%)	25.08% (17.43% to 32.74%)		66.94% (64.86% to 69.03%)	31.55% (25.54% to 37.56%)
Multilingual status			.058			.77
Yes	34.28% (30.59% to 37.97%)	41.40% (33.67% to 49.14%)		34.64% (30.99% to 38.29%)	33.76% (26.94% to 40.57%)
No	65.72% (62.03% to 69.41%)	58.59% (50.86% to 66.33%)		65.36% (61.71% to 69.01%)	66.24% (59.43% to 73.06%)
Discrimination distress (binary), n (%)
Any discrimination (yes)	55.67% (53.18% to 58.16%)	69.59% (62.29% to 76.90%)	<.001	55.18% (52.73% to 57.62%)	65.88% (60.61% to 71.15%)	<.001
Any discrimination (no)	44.33% (41.84% to 46.82%)	30.41% (23.10% to 37.71%)		44.82% (42.38% to 47.27%)	34.12% (28.85% to 39.39%)
Any educational discrimination (yes)	40.64% (38.58% to 42.70%)	52.89% (44.16% to 62.61%)	.007	40.09% (38.07% to 42.12%)	50.63% (44.71% to 56.56%)	<.001
Any educational discrimination (no)	59.36% (57.30% to 61.42%)	47.11% (38.39% to 55.84%)		59.91% (57.88% to 61.93%)	49.37% (43.44% to 55.29%)
Any institutional discrimination (yes)	34.50% (32.18% to 36.82%)	51.07% (43.24% to 58.91%)	<.001	33.95% (31.92% to 36.28%)	46.30% (39.99% to 52.62%)	<.001
Any institutional discrimination (no)	65.50% (63.18% to 67.82%)	48.93% (41.09% to 56.76%)		66.05% (63.72% to 68.38%)	53.70% (47.38% to 60.01%)
Any peer discrimination (yes)	39.90% (37.22% to 42.84%)	54.84% (46.88% to 62.79%)	<.001	39.32% (36.68% to 41.95%)	51.35% (45.22% to 57.49%)	<.001
Any peer discrimination (no)	60.01% (57.42% to 62.78%)	45.16% (37.21% to 53.12%)		60.68% (58.05% to 63.32%)	48.65% (42.51% to 54.78%)
Discrimination distress (continuous)	Mean (95% CI)	Mean (95% CI)	p ^g	Mean (95% CI)	Mean (95% CI)	p ^g
Overall discrimination (range: 0–5)	0.46 (0.43 to 0.50)	0.79 (0.64 to 0.93)	<.001	0.45 (0.42 to 0.49)	0.68 (0.59 to 0.77)	<.001
Educational discrimination (range: 0–5)	0.55 (0.52 to 0.59)	0.84 (0.67 to 1.01)	.002	0.54 (0.51 to 0.58)	0.75 (0.65 to 0.85)	<.001
Institutional discrimination (range: 0–5)	0.37 (0.34 to 0.40)	0.73 (0.59 to 0.87)	<.001	0.36 (0.33 to 0.39)	0.61 (0.52 to 0.71)	<.001
Peer discrimination (range: 0–5)	0.47 (0.43 to 0.51)	0.78 (0.63 to 0.93)	<.001	0.46 (0.42 to 0.50)	0.68 (0.57 to 0.79)	<.001

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Combustible includes the following products: cigarettes, cigars, hookah, roll-your-own, pipe, and bidis.

Non-combustible includes the following products: e-cigarettes, smokeless tobacco, snus, heated tobacco, nicotine pouches, and oral nicotine.

Wald test p-value assessing the association between the distribution of each sociodemographic characteristic and tobacco products.

Other includes people who responded: “Not Sure/Questioning and Decline to answer.”

Another non-Hispanic race includes respondents who identified as non-Hispanic Asian, American Indian/Alaska Native, or Native Hawaiian/Other Pacific Islander.

Uncertain includes people who responded: “Not Sure/Questioning, Don’t know, and Decline to answer.”

P-value calculated using bivariate linear regression to test for differences in means between groups.

Among age groups, participants aged 16 and older showed the highest proportion of current combustible (45.97%) and non-combustible (51.40%) tobacco product use. In contrast, participants aged 9–12 had the lowest proportion of current combustible (10.67%) and non-combustible (8.21%) tobacco product use.

Gender differences in tobacco use were also observed. Males had the highest proportion of current combustible tobacco product use (41.13%), whereas females reported the highest proportion of current non-combustible tobacco use (46.11%).

Participants identifying as heterosexual had the highest rates of current use for both combustible (48.72%) and non-combustible (56.67%) tobacco products compared to other groups. Similarly, participants with C/D/F grades (combustible = 34.41%; non-combustible = 29.68%), those exposed to secondhand smoking or vaping (combustible = 74.92%; non-combustible = 68.45%), and those reporting any form of discrimination (combustible = 69.59%; non-combustible = 65.88%) showed higher proportions of current tobacco use for both product types.

Associations Between Discrimination Distress and Current Tobacco Use

Table 3 presents the adjusted associations between sociodemographic characteristics, overall discrimination distress, and current tobacco use by product type. Discrimination distress was associated with 26% higher odds of current combustible tobacco use (95% CI: 1.08 to 1.47) and 23% higher odds of current non-combustible tobacco use (95% CI: 1.09 to 1.39). Participants aged 13–15 (vs. 9–12) had nearly twofold higher odds of current non-combustible tobacco use (adjusted odds ratio [AOR]: 1.98; 95% CI: 1.55 to 2.53). Those aged 16 and older (vs. 9–12) had approximately twofold higher odds of current combustible (AOR: 2.10; 95% CI: 1.26 to 3.51) and threefold higher odds of current non-combustible (AOR: 3.30; 95% CI: 2.40 to 4.53) tobacco use, respectively.

Table 3.

Bivariate and Multivariable Associations Between Overall Discrimination Distress and Current Combustible and Non-combustible Tobacco Use (n = 22 069)

	Combustible^a		Non-combustible^b
	Unadjusted, OR (95% CI)^c	Adjusted, AOR (95% CI)^d	Unadjusted, OR (95% CI)^c	Adjusted, AOR (95% CI)^d
Overall discrimination distress (continuous)	1.55 (1.34 to 1.78)	1.26 (1.08 to 1.47)	1.42 (1.28 to 1.57)	1.23 (1.09 to 1.39)
Covariates
Age in years (ref: 9–12)
13–15	1.59 (0.85 to 2.94)	1.55 (0.84 to 2.89)	1.97 (1.56 to 2.48)	1.98 (1.55 to 2.53)
≥16	2.06 (1.25 to 3.38)	2.10 (1.26 to 3.51)	3.20 (2.37 to 4.32)	3.30 (2.40 to 4.53)
Gender (ref: male)
Female	0.89 (0.67 to 1.19)	0.85 (0.63 to 1.16)	1.37 (1.06 to 1.78)	1.40 (1.05 to 1.88)
Non-binary or something else	3.66 (2.08 to 6.43)	1.89 (0.99 to 3.61)	3.08 (1.91 to 4.98)	2.06 (1.28 to 3.31)
Other^e	1.73 (1.01 to 2.97)	1.29 (0.71 to 2.32)	1.37 (0.96 to 1.94)	1.24 (0.77 to 1.98)
Race and ethnicity (ref: non-Hispanic White)
Hispanic	1.64 (1.26 to 2.15)	1.22 (0.83 to 1.78)	1.23 (0.99 to 1.52)	1.23 (0.95 to 1.60)
Non-Hispanic Black	1.75 (1.00 to 3.06)	1.64 (0.95 to 2.86)	0.84 (0.59 to 1.19)	0.81 (0.55 to 1.19)
Non-Hispanic multiracial	1.32 (0.77 to 2.25)	1.09 (0.64 to 1.86)	1.36 (0.91 to 2.04)	1.23 (0.83 to 1.83)
Another non-Hispanic race^f	1.02 (0.48 to 2.16)	1.08 (0.48 to 2.45)	0.81 (0.32 to 2.07)	1.02 (0.38 to 2.78)
Sexual orientation (ref: heterosexual)
LGB or something else	2.55 (1.71 to 3.81)	1.56 (0.99 to 2.46)	1.82 (1.32 to 2.53)	1.16 (0.80 to 1.69)
Uncertain^g	1.21 (0.83 to 1.77)	0.97 (0.69 to 1.37)	0.93 (0.71 to 1.21)	0.89 (0.67 to 1.15)
Student grades (ref: A’s)
B’s	1.76 (1.05 to 2.94)	1.41 (0.83 to 2.42)	1.42 (1.03 to 1.95)	1.26 (0.92 to 1.72)
C/D/F’s	3.65 (2.26 to 5.87)	2.32 (1.34 to 4.01)	2.49 (1.95 to 3.19)	1.83 (1.38 to 2.43)
None/unspecified	3.73 (2.05 to 6.81)	2.80 (1.57 to 4.98)	2.20 (1.46 to 3.33)	2.08 (1.41 to 3.07)
Secondhand smoking/vaping exposure
Yes	5.57 (3.65 to 8.51)	4.75 (3.12 to 7.23)	4.39 (3.29 to 5.87)	3.86 (2.93 to 5.08)
Multilingual status
Yes	1.35 (0.99 to 1.86)	1.40 (0.90 to 2.17)	0.96 (0.73 to 1.26)	0.91 (0.65 to 1.27)

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Bolded text indicates statistical significance (p < .05).

Combustible includes the following products: cigarettes, cigars, hookah, roll-your-own, pipe, and bidis.

Non-combustible includes the following products: e-cigarettes, smokeless tobacco, snus, heated tobacco, nicotine pouches, and oral nicotine.

Unadjusted odds ratios (ORs) and 95% confidence intervals.

Odds ratios are adjusted (AOR) for age, gender, race and ethnicity, sexual orientation, student grades, secondhand smoking/vaping exposure, multilingual status, and discrimination indices and 95% confidence intervals.

Other includes people who responded: “Not Sure/Questioning and Decline to answer.”

Another non-Hispanic race includes respondents who identified as non-Hispanic Asian, American Indian/Alaska Native, or Native Hawaiian/Other Pacific Islander.

Uncertain includes people who responded: “Not Sure/Questioning, Don’t know, and Decline to answer.”

Female participants (vs. males) had higher odds of current non-combustible tobacco use (AOR: 1.40; 95% CI: 1.05 to 1.88). Similarly, participants identifying as non-binary or something else (vs. males) had higher odds of non-combustible tobacco use (AOR: 2.06; 95% CI: 1.28 to 3.31).

Tobacco use by product type also varied by student grades. Participants with C/D/F grades (vs. A’s) had higher odds of both current combustible (AOR: 2.32; 95% CI: 1.34 to 4.01) and non-combustible (AOR: 1.83; 95% CI: 1.38 to 2.43) tobacco use. Similarly, participants with unspecified or no reported grades (vs. A’s) had higher odds of current combustible (AOR: 2.80; 95% CI: 1.57 to 4.98) and non-combustible (AOR: 2.08; 95% CI: 1.41 to 3.07) tobacco use.

Participants exposed to secondhand smoking or vaping had higher odds of current combustible (AOR: 4.75; 95% CI: 3.12 to 7.23) and non-combustible (AOR: 3.86; 95% CI: 2.93 to 5.08) tobacco use.

Table 4 shows the adjusted associations between sociodemographic characteristics, discrimination distress sub-indices, and current tobacco use by product type. Institutional discrimination was the only subscale associated with higher odds of current combustible tobacco use (AOR: 1.30; 95% CI: 1.06 to 1.59). Sociodemographic determinants displayed a similar pattern to those observed in Table 3.

Table 4.

Bivariate and Multivariable Associations Between Educational, Institutional, and Peer Discrimination Distress and Current Combustible and Non-combustible Tobacco Use (n = 22 069)

	Combustible^a		Non-combustible^b
	Unadjusted, OR (95% CI)^c	Adjusted, AOR (95% CI)^d	Unadjusted, OR (95% CI)^c	Adjusted, AOR (95% CI)^d
Discrimination distress sub-indices (continuous)
Educational discrimination	1.32 (1.16 to 1.49)	1.02 (0.85 to 1.22)	1.24 (1.13 to 1.36)	0.99 (0.84 to 1.17)
Institutional discrimination	1.55 (1.37 to 1.76)	1.30 (1.06 to 1.59)	1.43 (1.30 to 1.58)	1.23 (0.97 to 1.57)
Peer discrimination	1.41 (1.25 to 1.60)	0.97 (0.77 to 1.21)	1.31 (1.18 to 1.46)	1.03 (0.82 to 1.29)
Covariates
Age in years (ref: 9–12)
13–15	1.59 (0.85 to 2.94)	1.54 (0.83 to 2.87)	1.97 (1.56 to 2.48)	1.97 (1.54 to 2.53)
≥16	2.06 (1.25 to 3.38)	2.06 (1.23 to 3.45)	3.20 (2.37 to 4.32)	3.26 (2.37 to 4.48)
Gender (ref: male)
Female	0.89 (0.67 to 1.19)	0.86 (0.63 to 1.17)	1.37 (1.06 to 1.78)	1.41 (1.05 to 1.90)
Nonbinary or something else	3.66 (2.08 to 6.43)	1.89 (1.00 to 3.60)	3.08 (1.91 to 4.98)	2.05 (1.29 to 3.28)
Other^e	1.73 (1.01 to 2.97)	1.29 (0.72 to 2.33)	1.37 (0.96 to 1.94)	1.23 (0.77 to 1.98)
Race and ethnicity (ref: non-Hispanic White)
Hispanic	1.64 (1.26 to 2.15)	1.20 (0.82 to 1.74)	1.23 (0.99 to 1.52)	1.22 (0.93 to 1.58)
Non-Hispanic Black	1.75 (1.00 to 3.06)	1.62 (0.94 to 2.80)	0.84 (0.59 to 1.19)	0.79 (0.53 to 1.18)
Non-Hispanic multiracial	1.32 (0.77 to 2.25)	1.07 (0.64 to 1.81)	1.36 (0.91 to 2.04)	1.20 (0.80 to 1.80)
Another non-Hispanic race^f	1.02 (0.48 to 2.16)	1.09 (0.49 to 2.44)	0.81 (0.32 to 2.07)	1.03 (0.38 to 2.82)
Sexual orientation (ref: heterosexual)
LGB or something else	2.55 (1.71 to 3.81)	1.56 (0.98 to 2.47)	1.82 (1.32 to 2.53)	1.16 (0.80 to 1.68)
Uncertain^g	1.21 (0.83 to 1.77)	0.98 (0.69 to 1.38)	0.93 (0.71 to 1.21)	0.89 (0.69 to 1.16)
Student grades (ref: A’s)
B’s	1.76 (1.05 to 2.94)	1.40 (0.82 to 2.40)	1.42 (1.03 to 1.95)	1.25 (0.91 to 1.71)
C/D/F’s	3.65 (2.26 to 5.87)	2.29 (1.32 to 3.97)	2.49 (1.95 to 3.19)	1.81 (1.37 to 2.41)
None/unspecified	3.73 (2.05 to 6.81)	2.79 (1.55 to 5.00)	2.20 (1.46 to 3.33)	2.07 (1.40 to 3.05)
Secondhand smoking/vaping exposure
Yes	5.57 (3.65 to 8.51)	4.76 (3.12 to 7.25)	4.39 (3.29 to 5.87)	3.87 (2.94 to 5.09)
Multilingual status
Yes	1.35 (0.99 to 1.86)	1.41 (0.90 to 2.20)	0.96 (0.73 to 1.26)	0.91 (0.65 to 1.27)

Open in a new tab

Bolded text indicates statistical significance (p < .05)

Combustible includes the following products: cigarettes, cigars, hookah, roll-your-own, pipe, and bidis.

Non-combustible includes the following products: e-cigarettes, smokeless tobacco, snus, heated tobacco, nicotine pouches, and oral nicotine.

Unadjusted odds ratios (ORs) and 95% confidence intervals.

Other includes people who responded: “Not Sure/Questioning and Decline to answer.”

Another non-Hispanic race includes respondents who identified as non-Hispanic Asian, American Indian/Alaska Native, or Native Hawaiian/Other Pacific Islander.

Uncertain includes people who responded: “Not Sure/Questioning, Don’t know, and Decline to answer.”

Sensitivity Analysis

Supplementary Table S4 presents the logistic regression analysis of current use of each individual tobacco product and overall discrimination distress. The adjusted models show that overall discrimination distress was associated with cigarette use (AOR: 1.27; 95% CI: 1.05 to 1.55), hookah use (AOR: 1.63; 95% CI: 1.22 to 2.17), pipe use (AOR: 1.57; 95% CI: 1.29 to 1.90), bidi use (AOR: 1.54; 95% CI: 1.10 to 2.15), e-cigarette use (AOR: 1.20; 95% CI: 1.08 to 1.34), smokeless tobacco use (AOR: 1.59; 95% CI: 1.37 to 1.84), snus use (AOR: 1.57; 95% CI: 1.15 to 2.16), heated tobacco use (AOR: 1.46; 95% CI: 1.15 to 1.85), and oral nicotine use (AOR: 1.37; 95% CI: 1.10 to 1.72).

Supplementary Table S5 presents the logistic regression results for the association between discrimination distress sub-indices and current use of each individual tobacco product. In the adjusted models, institutional discrimination distress was associated with the use of most tobacco products (eg, e-cigarettes; AOR: 1.20; 95% CI: 1.06 to 1.37), except for rolled-your-own and nicotine pouches. Peer discrimination distress was also associated with the use of hookah, pipe, bidi, e-cigarette, smokeless tobacco, snus, heated tobacco, and oral nicotine (eg, hookah; AOR: 1.51; 95% CI: 1.19 to 1.91). Educational discrimination distress was associated with the use of hookah, pipe, bidi, e-cigarette, smokeless tobacco, and oral nicotine (eg, oral nicotine; AOR: 1.21; 95% CI: 1.02 to 1.42).

Discussion

The study indicates that youth who reported more distress due to experiencing racial and ethnic discrimination currently used combustible and non-combustible tobacco products. Among the discrimination distress sub-indices, only institutional discrimination was associated with combustible tobacco use. Additionally, overall discrimination distress was associated with most tobacco products, except for cigars, rolled-your-own, and nicotine pouches. Furthermore, the discrimination distress subscales showed distinct patterns of association across use of individual tobacco products. Institutional discrimination distress was associated with use of most tobacco products, excluding roll-your-own and nicotine pouches. In contrast, peer and educational discrimination distress were linked to a narrower range of products, including hookah, pipe tobacco, e-cigarettes, and oral nicotine.

These findings align with previous literature demonstrating the impact of racial discrimination on youth tobacco use, suggesting that youth experiencing discrimination based on race and ethnicity may turn to substance use as a coping mechanism.¹⁸^,²⁰^,²¹^,³² Youth who experience discrimination may engage in tobacco use for multiple reasons, such as mitigating stress, regulating negative emotions, seeking social inclusion, or asserting a sense of autonomy.^32–34 Tobacco use can function as a maladaptive coping mechanism to address the psychological distress associated with perceived mistreatment or marginalization. Additionally, environments where tobacco use is prevalent may further reinforce these behaviors, particularly among youth facing identity-related challenges and striving for social belonging.^34–36 This effect is observed in our findings, as youth who reported exposure to secondhand vaping or smoking showed significantly higher odds of current use of both combustible and non-combustible tobacco products. These findings are supported by the Social Ecological Model, which highlights how health behaviors like tobacco use are influenced by interconnected factors at individual, social, and systemic levels.³⁴^,³⁷^,³⁸ The availability of tobacco products, peer behaviors, and regulatory policies contribute to shaping these patterns, as suggested by the observed association between secondhand vaping or smoking exposure and higher odds of tobacco use among youth in our findings.³⁴ Given that racial discrimination is a known social determinant of health, addressing it in prevention efforts is crucial to reducing tobacco use and supporting youth mental health.³⁹

Among the discrimination distress sub-indices, only institutional discrimination was associated with increased odds of combustible tobacco product consumption. These findings suggest that certain discrimination scenarios, such as being hassled by police or store staff, were associated with higher odds of combustible tobacco product consumption among youth. Previous research has shown that these types of racial- or ethnic-based mistreatment were more prominent among African American and Hispanic youth.³⁰^,⁴⁰ In their 2000 study, Fisher et al. found that African American and Hispanic youth reported higher instances of being treated unfairly by police or store staff compared to their NH White peers.³⁰ A 2021 study further supports this disparity, highlighting that Black and Latina/x/o youth continue to experience ethnic-racial police discrimination at significantly higher rates than their White peers.⁴¹ These experiences were linked to increased psychological distress, which may contribute to higher rates of combustible tobacco product consumption as a coping mechanism.³⁰ Experiencing unfair treatment by police can induce significant stress among minority youth, leading to adverse psychological outcomes such as increased anxiety, depression, and feelings of hopelessness.⁴²^,⁴³ This stress may drive some youth to engage in maladaptive coping strategies, including the use of tobacco products, to manage their emotional distress.⁴⁰ Research indicates that such experiences are linked to higher rates of substance use among youth.⁴⁰^,⁴⁴

While both combustible and non-combustible tobacco products are used among marginalized youth experiencing discrimination distress, their health risks differ significantly. Combustible products, such as cigarettes and hookah, are linked to greater long-term health consequences, including respiratory diseases, cardiovascular issues, and cancer.⁴⁵^,⁴⁶ In contrast, non-combustible products, such as e-cigarettes and oral nicotine, are generally considered less harmful but still contribute to nicotine addiction and long-term dependence.⁴⁶^,⁴⁷ Given these differences, efforts to reduce tobacco use should be mindful of the elevated rates of combustible product use among youth affected by discrimination distress, particularly those experiencing institutional discrimination, while also recognizing the importance of non-combustible use in this population.

Racial discrimination, gender and sexual disparities, age, and academic challenges are significant drivers of combustible and non-combustible tobacco product consumption among youth. These challenges are further compounded by structural racism, which entrenches systemic inequities through discriminatory policies, practices, and ideologies that disproportionately harm marginalized groups.¹²^,⁴⁸ Youth, a critical period for cementing future behaviors,¹⁰^,⁴⁹ is often shaped by these inequities, resulting in marginalized youth experiencing greater vulnerability to harmful coping mechanisms such as tobacco use.¹¹ Comprehensive and targeted policies must not only address individual and interpersonal challenges but also dismantle structural barriers that perpetuate exclusion and inequity. Improving the conditions of marginalized groups requires addressing the root causes of systemic mistreatment, ensuring youth can explore, grow, and thrive without struggling to achieve equal treatment.⁴⁸ Future research should examine how social, structural, and environmental drivers, such as product availability, may operate differently across racial and ethnic groups to better inform equitable interventions.

Limitations

This study provides valuable insight into the relationships between discrimination distress and combustible and non-combustible tobacco use among youth; however, several limitations should be considered. First, the data are cross-sectional, which limits the ability to establish causal relationships between discrimination distress and tobacco use and raises the possibility of reverse causality, where tobacco use may invite discrimination. Second, the self-reported nature of the data may introduce recall or social desirability bias, particularly on sensitive topics such as discrimination distress and current tobacco use. Third, to address missing data, multiple imputation was employed under the assumption of Missing at Random, which is widely recognized as a robust approach for handling missingness in large datasets.²⁷^,⁵⁰ This method preserved the integrity of the data structure and ensured the inclusion of all key variables in the analysis.²⁸ However, this approach relies on the assumption that missingness is solely dependent on observed data, which may not fully account for unobserved factors influencing data gaps.²⁸

Conclusion

This study contributes to the growing literature on the impact of perceived racial and ethnic discrimination on tobacco consumption among youth. Our findings indicate that distress due to racial and ethnic discrimination is significantly associated with current use of both combustible and non-combustible tobacco products in this population. Adjusting by key sociodemographic variables, we identified certain minority groups at higher risk for current tobacco use. Notably, institutional discrimination emerged as the only significant predictor of combustible tobacco product use. These results underscore the urgent need for comprehensive and targeted policies aimed at reducing tobacco use and addressing the underlying experiences of racial and ethnic discrimination that disproportionately affect marginalized youth.

Supplementary Material

tob-Meman-discrim-distress-NTR-Supp_mat_V3_ntaf166

tob-meman-discrim-distress-ntr-supp_mat_v3_ntaf166.pdf^{(158.1KB, pdf)}

Contributor Information

Meman Diaby, Center for Health, Engagement, and Transformation, College of Medicine, University of Kentucky, Lexington, KY, USA.

Osayande Agbonlahor, Department of Preventive Medicine, University of Mississippi Medical Center, Jackson, MS, USA.

Maggie K Richardson, Department of Educational, School, & Counseling Psychology, College of Education, University of Kentucky, Lexington, KY, USA.

Joy L Hart, Department of Communication, College of Arts and Sciences, University of Louisville, Louisville, KY, USA; Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY, USA; American Heart Association Tobacco Center for Regulatory Science, Dallas, TX, USA.

Shyanika W Rose, Center for Health, Engagement, and Transformation, College of Medicine, University of Kentucky, Lexington, KY, USA; Department of Behavioral Science, College of Medicine, University of Kentucky, Lexington, KY, USA; Markey Cancer Center, College of Medicine, University of Kentucky, Lexington, KY, USA.

Delvon T Mattingly, Center for Health, Engagement, and Transformation, College of Medicine, University of Kentucky, Lexington, KY, USA; Department of Behavioral Science, College of Medicine, University of Kentucky, Lexington, KY, USA; Markey Cancer Center, College of Medicine, University of Kentucky, Lexington, KY, USA.

Author Contributions

Meman Diaby (Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Writing—original draft, Writing—review & editing [lead], Validation [equal]), Osayande Agbonlahor (Conceptualization, Investigation [supporting], Validation, Writing—review & editing [equal]), Maggie K. Richardson (Validation, Writing—review & editing [equal]), Joy L. Hart (Conceptualization [supporting], Funding acquisition, Validation, Writing—review & editing [equal]), Shyanika W. Rose (Funding acquisition, Supervision, Validation, Writing—review & editing [equal]), and Delvon Mattingly (Conceptualization, Investigation, Methodology, Resources, Supervision [lead], Data curation, Formal analysis, Software [supporting], Funding acquisition, Validation, Writing—review & editing [equal])

Declaration of Interests

None declared.

Funding

This research was supported, in part, by grants from the National Heart, Lung, and Blood Institute of the National Institutes of Health (NIH) and the Center for Tobacco Products (U54HL120163), the National Institute on Drug Abuse (NIDA) of the NIH and the Center for Tobacco Products (U54DA058256), the National Cancer Institute of the NIH (3R01CA251478-04S1), NIDA (L60DA061514, R25DA054015), and the American Heart Association (20YVNR35500014). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH, the Food and Drug Administration, or the American Heart Association. The funding sponsors had no role in study design; data collection, analyses, or interpretation; manuscript preparation; or the decision to publish the results.

Data Availability

The data that support the findings of this study are openly available at the Centers for Disease Control and Prevention (CDC) (Link).

References:

1. World Health Organization . Tobacco. In: World Health Organization. July 31. 2023: Accessed November 11, 2024. https://www.who.int/news-room/fact-sheets/detail/tobacco.
2. Birdsey J, Cornelius M, Jamal A, et al. Tobacco product use among U.S. middle and high school students — National Youth Tobacco Survey, 2023. MMWR Morb Mortal Wkly Rep. 2023;72(44):1173–1182. 10.15585/mmwr.mm7244a1. [DOI] [PMC free article] [PubMed] [Google Scholar]
3. Jamal A, Park-Lee E, Birdsey J, et al. Tobacco product use among middle and high school students — National Youth Tobacco Survey, United States, 2024. MMWR Morb Mortal Wkly Rep. 2024;73(41):917–924. 10.15585/mmwr.mm7341a2. [DOI] [PMC free article] [PubMed] [Google Scholar]
4. Miech RA, Johnston LD, Patrick ME, O’Malley PM. Monitoring the Future National Survey Results on Drug Use, 1975–2023: Overview and Detailed Results for Secondary School Students. Ann Arbor, MI: Institute for Social Research, University of Michigan; 2024: https://monitoringthefuture.org/results/annual-reports/. [Google Scholar]
5. Cavazos-Rehg PA, Krauss MJ, Spitznagel EL, Grucza RA, Bierut LJ. Youth tobacco use type and associations with substance use disorders. Addiction. 2014;109(8):1371–1380. 10.1111/add.12567. [DOI] [PMC free article] [PubMed] [Google Scholar]
6. Lydon DM, Wilson SJ, Child A, Geier CF. Adolescent brain maturation and smoking: what we know and where we’re headed. Neurosci Biobehav Rev. 2014;45:323–342. 10.1016/j.neubiorev.2014.07.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
7. U.S. Center for Disease Control and Prevention . Youth and tobacco use. In: Smoking and Tobacco Use. October 17. 2024: Accessed December 17, 2024. https://www.cdc.gov/tobacco/php/data-statistics/youth-data-tobacco/index.html.
8. Emlaw JE, Ajibewa TA, Toledo-Corral CM, Hasson RE. Racial discrimination and hypothalamic-pituitary-adrenal Axis dysregulation in adolescents with overweight and obesity: does context matter? Psychosom Med. 2023;85(8):691–698. 10.1097/PSY.0000000000001235. [DOI] [PMC free article] [PubMed] [Google Scholar]
9. Purnell JQ, Peppone LJ, Alcaraz K, et al. Perceived discrimination, psychological distress, and current smoking status: results from the Behavioral risk factor surveillance system reactions to race module, 2004–2008. Am J Public Health. 2012;102(5):844–851. 10.2105/AJPH.2012.300694. [DOI] [PMC free article] [PubMed] [Google Scholar]
10. Yang TC, Chen IC, Choi S, won, Kurtulus A. Linking perceived discrimination during adolescence to health during mid-adulthood: self-esteem and risk-behavior mechanisms. Soc Sci Med. 1982;232(232):434–443. 10.1016/j.socscimed.2018.06.012. [DOI] [Google Scholar]
11. Benner AD, Wang Y, Shen Y, Boyle AE, Polk R, Cheng YP. Racial/ethnic discrimination and well-being during adolescence: A meta-analytic review. Am Psychol. 2018;73(7):855–883. 10.1037/amp0000204. [DOI] [PMC free article] [PubMed] [Google Scholar]
12. Trent M, Dooley DG, Dougé J, et al. The impact of racism on Child and adolescent health. Pediatrics. 2019;144(2):e20191765. 10.1542/peds.2019-1765. [DOI] [PubMed] [Google Scholar]
13. Cahill M, Illback R, Peiper N. Perceived racial discrimination, psychological distress, and suicidal behavior in adolescence: secondary analysis of cross-sectional data from a Statewide youth survey. Healthcare. 2024;12(10):1011. 10.3390/healthcare12101011. [DOI] [PMC free article] [PubMed] [Google Scholar]
14. Mattingly DT, Diaby M, Agbonlahor O, et al. Disparities in discrimination distress among US youth at the intersection of gender, race, and ethnicity. AJPM Focus. 2025;4(4):100360. 10.1016/j.focus.2025.100360. [DOI] [PMC free article] [PubMed] [Google Scholar]
15. Gibbons FX, Gerrard M, Fleischli ME, Simons RL, Kingsbury JH. Perceived racial discrimination and healthy behavior among African Americans. Health Psychol. 2021;40(3):155–165. 10.1037/hea0001056. [DOI] [PMC free article] [PubMed] [Google Scholar]
16. Mattingly DT, Mezuk B, Elliott MR, Fleischer NL. Discrimination and tobacco use outcomes among US adults: effect modification by race/ethnicity. J Racial Ethn Health Disparities. 2024;11(1):395–405. 10.1007/s40615-023-01527-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
17. Unger JB. Perceived discrimination as a risk factor for use of emerging tobacco products: more similarities than differences across demographic groups and attributions for discrimination. Subst Use Misuse. 2018;53(10):1638–1644. 10.1080/10826084.2017.1421226. [DOI] [PMC free article] [PubMed] [Google Scholar]
18. Dai HD, Thiel G, Hafer D. Perceived racism and discrimination and youth substance use in the United States – intersections with sex and ethnicity. Prev Med. 2024;178:107811. 10.1016/j.ypmed.2023.107811. [DOI] [PMC free article] [PubMed] [Google Scholar]
19. Schwartz SJ, Unger JB, Baezconde-Garbanati L, et al. Trajectories of cultural stressors and effects on mental health and substance use among Hispanic immigrant adolescents. J Adolesc Health Off Publ Soc Adolesc Med. 2015;56(4):433–439. 10.1016/j.jadohealth.2014.12.011. [DOI] [Google Scholar]
20. Harris CD, Dutra LM, Donaldson CD, et al. Racial and nonracial discrimination and tobacco use among high school students in California. Soc Sci Med. 2025;365:117574. 10.1016/j.socscimed.2024.117574. [DOI] [PubMed] [Google Scholar]
21. Donaldson CD, Stupplebeen DA, Couch ET, et al. Perceived discrimination and youth vaping: the role of intersectional identities. Drug Alcohol Depend. 2024;260:111313. 10.1016/j.drugalcdep.2024.111313. [DOI] [PMC free article] [PubMed] [Google Scholar]
22. Jackson A, Fleischli ME, Haeny AM, et al. Association of non-cigarette tobacco advertisements and racial discrimination with non-cigarette tobacco product use among black adults. Nicotine Tob Res. 2023;25(4):781–787. 10.1093/ntr/ntac226. [DOI] [PMC free article] [PubMed] [Google Scholar]
23. U.S. Center for Disease Control and Prevention . Youth tobacco product use at a 25-year low, yet disparities persist. In: CDC Newsroom. October 21. 2024: Accessed November 13, 2024. https://www.cdc.gov/media/releases/2024/p1017-youth-tobacco-use.html.
24. U.S. Center for Disease Control and Prevention . Surgeon General’s report: Eliminating tobacco-related disease and death: Addressing disparities. In: Tobacco - Surgeon General’s Reports.November 18. 2024: Accessed November 22, 2024. https://www.cdc.gov/tobacco-surgeon-general-reports/about/2024-end-tobacco-disparities.html.
25. Office on Smoking and Health . 2023 National Youth Tobacco Survey: Methodology report. In: US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health. 2024.
26. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Epidemiol Camb Mass. 2007;18(6):800–804. 10.1097/EDE.0b013e3181577654. [DOI] [Google Scholar]
27. Buuren SV, Groothuis-Oudshoorn K. Mice : multivariate imputation by chained equations in R. J Stat Softw. 2011;45(3). 10.18637/jss.v045.i03. [DOI] [Google Scholar]
28. Kalpourtzi N, Carpenter JR, Touloumi G. Handling missing values in surveys with complex study design: A simulation study. J Surv Stat Methodol. 2024;12(1):105–129. 10.1093/jssam/smac039. [DOI] [Google Scholar]
29. Rubin DB. Multiple Imputation for Nonresponse in Surveys. 1st ed. Wiley; 1987. doi: 10.1002/9780470316696 [DOI] [Google Scholar]
30. Fisher CB, Wallace SA, Fenton RE. Discrimination distress during adolescence. J Youth Adolesc. 2000;29(6):679–695. 10.1023/A:1026455906512. [DOI] [Google Scholar]
31. StataCorp . Stata statistical software Release 18. Published online. 2023.
32. Keum BT, Cano MÁ, Valdovinos IC, Boland D, zhané. Impact of online and offline racism on cigarette smoking, marijuana use, and vaping via depressive/anxiety symptoms among racially minoritized emerging adults. Am J Orthop. 2023;93(5):450–459. 10.1037/ort0000691. [DOI] [Google Scholar]
33. Andersen SL. Stress, sensitive periods, and substance abuse. Neurobiol Stress. 2019;10:100140. 10.1016/j.ynstr.2018.100140. [DOI] [PMC free article] [PubMed] [Google Scholar]
34. Assari S, Zare H. Socioeconomic status partially mediates the effects of structural racism on youth tobacco use initiation. Glob J Epidemiol Infect Dis. 2024;4(1):44–59. 10.31586/gjeid.2024.1032. [DOI] [Google Scholar]
35. Bacio GA, Estrada Y, Huang S, Martínez M, Sardinas K, Prado G. Ecodevelopmental predictors of early initiation of alcohol, tobacco, and drug use among Hispanic adolescents. J Sch Psychol. 2015;53(3):195–208. 10.1016/j.jsp.2015.02.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
36. Stritzel H. Peer and community influences on adolescent substance use in the context of adverse childhood experiences. Sociol Perspect SP Off Publ Pac Sociol Assoc. 2021;65(2):413–432. 10.1177/07311214211018718. [DOI] [Google Scholar]
37. Cherry K, Susman D. A comprehensive guide to the Bronfenbrenner ecological model. Verywell Mind August 16. 2023; Accessed November 15, 2024. https://www.verywellmind.com/bronfenbrenner-ecological-model-7643403. [Google Scholar]
38. Henderson DX, DeCuir-Gunby J, Gill V. “It really takes a village”: A socio-ecological model of resilience for prevention among economically disadvantaged ethnic minority youth. J Prim Prev. 2016;37(5):469–485. 10.1007/s10935-016-0446-3. [DOI] [PubMed] [Google Scholar]
39. Pearson JL, Waa A, Siddiqi K, Edwards R, Nez Henderson P, Webb HM. Naming racism, not race, as a determinant of tobacco-related health disparities. Nicotine Tob Res. 2021;23(6):885–887. 10.1093/ntr/ntab059. [DOI] [PMC free article] [PubMed] [Google Scholar]
40. Mattingly DT, Howard LC, Krueger EA, Fleischer NL, Hughes-Halbert C, Leventhal AM. Change in distress about police brutality and substance use among young people, 2017–2020. Drug Alcohol Depend. 2022;237:109530. 10.1016/j.drugalcdep.2022.109530. [DOI] [PMC free article] [PubMed] [Google Scholar]
41. Zeiders KH, Umaña-Taylor AJ, Carbajal S, Pech A. Police discrimination among black, Latina/x/o, and white adolescents: examining frequency and relations to academic functioning. J Adolesc. 2021;90(1):91–99. 10.1016/j.adolescence.2021.06.001. [DOI] [PubMed] [Google Scholar]
42. Alang S, McAlpine D, McClain M. Police encounters as stressors: associations with depression and anxiety across race. Socius. 2021;7:2378023121998128. 10.1177/2378023121998128. [DOI] [Google Scholar]
43. Jackson DB. The case for conceptualizing youth-police contact as a racialized adverse childhood experience. Am J Public Health. 2021;111(7):1189–1191. 10.2105/AJPH.2021.306324. [DOI] [PMC free article] [PubMed] [Google Scholar]
44. Jindal M, Mistry KB, Trent M, McRae A, Thornton RLJ. Police exposures and the health and well-being of black youth in the US: A systematic review. JAMA Pediatr. 2022;176(1):78–88. 10.1001/jamapediatrics.2021.2929. [DOI] [PubMed] [Google Scholar]
45. Kang D, Choi KH. Combustible cigarette smoking harms nearly every organ in the body. Eur Heart J. 2025;46(10):982–982. 10.1093/eurheartj/ehae896. [DOI] [PubMed] [Google Scholar]
46. American Cancer Society medical and editorial content team . Is any type of tobacco product safe? American Cancer Society November 19. 2024; Accessed March 17, 2025. https://www.cancer.org/cancer/risk-prevention/tobacco/is-any-type-of-smoking-safe.html.
47. Camacho OM, Ebajemito JK, Coburn S, Prasad K, Costigan S, Murphy JJ. Evidence from the scientific assessment of electronic cigarettes and their role in tobacco harm reduction. Contrib Tob Nicotine Res. 2021;30(2):63–108. 10.2478/cttr-2021-0007. [DOI] [Google Scholar]
48. Bailey ZD, Krieger N, Agénor M, Graves J, Linos N, Bassett MT. Structural racism and health inequities in the USA: evidence and interventions. Lancet. 2017;389(10077):1453–1463. 10.1016/S0140-6736(17)30569-X. [DOI] [PubMed] [Google Scholar]
49. World Health Organization . Coming of age: adolescent health. 2022; Accessed November 15, 2024. https://www.who.int/news-room/spotlight/coming-of-age-adolescent-health.
50. Rubin DB. Inference and missing data. Biometrika. 1976;63(3):581–592. 10.1093/biomet/63.3.581. [DOI] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

tob-Meman-discrim-distress-NTR-Supp_mat_V3_ntaf166

tob-meman-discrim-distress-ntr-supp_mat_v3_ntaf166.pdf^{(158.1KB, pdf)}

Data Availability Statement

The data that support the findings of this study are openly available at the Centers for Disease Control and Prevention (CDC) (Link).

[ref1] 1. World Health Organization . Tobacco. In: World Health Organization. July 31. 2023: Accessed November 11, 2024. https://www.who.int/news-room/fact-sheets/detail/tobacco.

[ref2] 2. Birdsey J, Cornelius M, Jamal A, et al. Tobacco product use among U.S. middle and high school students — National Youth Tobacco Survey, 2023. MMWR Morb Mortal Wkly Rep. 2023;72(44):1173–1182. 10.15585/mmwr.mm7244a1. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref3] 3. Jamal A, Park-Lee E, Birdsey J, et al. Tobacco product use among middle and high school students — National Youth Tobacco Survey, United States, 2024. MMWR Morb Mortal Wkly Rep. 2024;73(41):917–924. 10.15585/mmwr.mm7341a2. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref4] 4. Miech RA, Johnston LD, Patrick ME, O’Malley PM. Monitoring the Future National Survey Results on Drug Use, 1975–2023: Overview and Detailed Results for Secondary School Students. Ann Arbor, MI: Institute for Social Research, University of Michigan; 2024: https://monitoringthefuture.org/results/annual-reports/. [Google Scholar]

[ref5] 5. Cavazos-Rehg PA, Krauss MJ, Spitznagel EL, Grucza RA, Bierut LJ. Youth tobacco use type and associations with substance use disorders. Addiction. 2014;109(8):1371–1380. 10.1111/add.12567. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref6] 6. Lydon DM, Wilson SJ, Child A, Geier CF. Adolescent brain maturation and smoking: what we know and where we’re headed. Neurosci Biobehav Rev. 2014;45:323–342. 10.1016/j.neubiorev.2014.07.003. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref7] 7. U.S. Center for Disease Control and Prevention . Youth and tobacco use. In: Smoking and Tobacco Use. October 17. 2024: Accessed December 17, 2024. https://www.cdc.gov/tobacco/php/data-statistics/youth-data-tobacco/index.html.

[ref8] 8. Emlaw JE, Ajibewa TA, Toledo-Corral CM, Hasson RE. Racial discrimination and hypothalamic-pituitary-adrenal Axis dysregulation in adolescents with overweight and obesity: does context matter? Psychosom Med. 2023;85(8):691–698. 10.1097/PSY.0000000000001235. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref9] 9. Purnell JQ, Peppone LJ, Alcaraz K, et al. Perceived discrimination, psychological distress, and current smoking status: results from the Behavioral risk factor surveillance system reactions to race module, 2004–2008. Am J Public Health. 2012;102(5):844–851. 10.2105/AJPH.2012.300694. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref10] 10. Yang TC, Chen IC, Choi S, won, Kurtulus A. Linking perceived discrimination during adolescence to health during mid-adulthood: self-esteem and risk-behavior mechanisms. Soc Sci Med. 1982;232(232):434–443. 10.1016/j.socscimed.2018.06.012. [DOI] [Google Scholar]

[ref11] 11. Benner AD, Wang Y, Shen Y, Boyle AE, Polk R, Cheng YP. Racial/ethnic discrimination and well-being during adolescence: A meta-analytic review. Am Psychol. 2018;73(7):855–883. 10.1037/amp0000204. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref12] 12. Trent M, Dooley DG, Dougé J, et al. The impact of racism on Child and adolescent health. Pediatrics. 2019;144(2):e20191765. 10.1542/peds.2019-1765. [DOI] [PubMed] [Google Scholar]

[ref13] 13. Cahill M, Illback R, Peiper N. Perceived racial discrimination, psychological distress, and suicidal behavior in adolescence: secondary analysis of cross-sectional data from a Statewide youth survey. Healthcare. 2024;12(10):1011. 10.3390/healthcare12101011. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref14] 14. Mattingly DT, Diaby M, Agbonlahor O, et al. Disparities in discrimination distress among US youth at the intersection of gender, race, and ethnicity. AJPM Focus. 2025;4(4):100360. 10.1016/j.focus.2025.100360. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref15] 15. Gibbons FX, Gerrard M, Fleischli ME, Simons RL, Kingsbury JH. Perceived racial discrimination and healthy behavior among African Americans. Health Psychol. 2021;40(3):155–165. 10.1037/hea0001056. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref16] 16. Mattingly DT, Mezuk B, Elliott MR, Fleischer NL. Discrimination and tobacco use outcomes among US adults: effect modification by race/ethnicity. J Racial Ethn Health Disparities. 2024;11(1):395–405. 10.1007/s40615-023-01527-3. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref17] 17. Unger JB. Perceived discrimination as a risk factor for use of emerging tobacco products: more similarities than differences across demographic groups and attributions for discrimination. Subst Use Misuse. 2018;53(10):1638–1644. 10.1080/10826084.2017.1421226. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref18] 18. Dai HD, Thiel G, Hafer D. Perceived racism and discrimination and youth substance use in the United States – intersections with sex and ethnicity. Prev Med. 2024;178:107811. 10.1016/j.ypmed.2023.107811. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref19] 19. Schwartz SJ, Unger JB, Baezconde-Garbanati L, et al. Trajectories of cultural stressors and effects on mental health and substance use among Hispanic immigrant adolescents. J Adolesc Health Off Publ Soc Adolesc Med. 2015;56(4):433–439. 10.1016/j.jadohealth.2014.12.011. [DOI] [Google Scholar]

[ref20] 20. Harris CD, Dutra LM, Donaldson CD, et al. Racial and nonracial discrimination and tobacco use among high school students in California. Soc Sci Med. 2025;365:117574. 10.1016/j.socscimed.2024.117574. [DOI] [PubMed] [Google Scholar]

[ref21] 21. Donaldson CD, Stupplebeen DA, Couch ET, et al. Perceived discrimination and youth vaping: the role of intersectional identities. Drug Alcohol Depend. 2024;260:111313. 10.1016/j.drugalcdep.2024.111313. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref22] 22. Jackson A, Fleischli ME, Haeny AM, et al. Association of non-cigarette tobacco advertisements and racial discrimination with non-cigarette tobacco product use among black adults. Nicotine Tob Res. 2023;25(4):781–787. 10.1093/ntr/ntac226. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref23] 23. U.S. Center for Disease Control and Prevention . Youth tobacco product use at a 25-year low, yet disparities persist. In: CDC Newsroom. October 21. 2024: Accessed November 13, 2024. https://www.cdc.gov/media/releases/2024/p1017-youth-tobacco-use.html.

[ref24] 24. U.S. Center for Disease Control and Prevention . Surgeon General’s report: Eliminating tobacco-related disease and death: Addressing disparities. In: Tobacco - Surgeon General’s Reports.November 18. 2024: Accessed November 22, 2024. https://www.cdc.gov/tobacco-surgeon-general-reports/about/2024-end-tobacco-disparities.html.

[ref25] 25. Office on Smoking and Health . 2023 National Youth Tobacco Survey: Methodology report. In: US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health. 2024.

[ref26] 26. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Epidemiol Camb Mass. 2007;18(6):800–804. 10.1097/EDE.0b013e3181577654. [DOI] [Google Scholar]

[ref27] 27. Buuren SV, Groothuis-Oudshoorn K. Mice : multivariate imputation by chained equations in R. J Stat Softw. 2011;45(3). 10.18637/jss.v045.i03. [DOI] [Google Scholar]

[ref28] 28. Kalpourtzi N, Carpenter JR, Touloumi G. Handling missing values in surveys with complex study design: A simulation study. J Surv Stat Methodol. 2024;12(1):105–129. 10.1093/jssam/smac039. [DOI] [Google Scholar]

[ref29] 29. Rubin DB. Multiple Imputation for Nonresponse in Surveys. 1st ed. Wiley; 1987. doi: 10.1002/9780470316696 [DOI] [Google Scholar]

[ref30] 30. Fisher CB, Wallace SA, Fenton RE. Discrimination distress during adolescence. J Youth Adolesc. 2000;29(6):679–695. 10.1023/A:1026455906512. [DOI] [Google Scholar]

[ref31] 31. StataCorp . Stata statistical software Release 18. Published online. 2023.

[ref32] 32. Keum BT, Cano MÁ, Valdovinos IC, Boland D, zhané. Impact of online and offline racism on cigarette smoking, marijuana use, and vaping via depressive/anxiety symptoms among racially minoritized emerging adults. Am J Orthop. 2023;93(5):450–459. 10.1037/ort0000691. [DOI] [Google Scholar]

[ref33] 33. Andersen SL. Stress, sensitive periods, and substance abuse. Neurobiol Stress. 2019;10:100140. 10.1016/j.ynstr.2018.100140. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref34] 34. Assari S, Zare H. Socioeconomic status partially mediates the effects of structural racism on youth tobacco use initiation. Glob J Epidemiol Infect Dis. 2024;4(1):44–59. 10.31586/gjeid.2024.1032. [DOI] [Google Scholar]

[ref35] 35. Bacio GA, Estrada Y, Huang S, Martínez M, Sardinas K, Prado G. Ecodevelopmental predictors of early initiation of alcohol, tobacco, and drug use among Hispanic adolescents. J Sch Psychol. 2015;53(3):195–208. 10.1016/j.jsp.2015.02.001. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref36] 36. Stritzel H. Peer and community influences on adolescent substance use in the context of adverse childhood experiences. Sociol Perspect SP Off Publ Pac Sociol Assoc. 2021;65(2):413–432. 10.1177/07311214211018718. [DOI] [Google Scholar]

[ref37] 37. Cherry K, Susman D. A comprehensive guide to the Bronfenbrenner ecological model. Verywell Mind August 16. 2023; Accessed November 15, 2024. https://www.verywellmind.com/bronfenbrenner-ecological-model-7643403. [Google Scholar]

[ref38] 38. Henderson DX, DeCuir-Gunby J, Gill V. “It really takes a village”: A socio-ecological model of resilience for prevention among economically disadvantaged ethnic minority youth. J Prim Prev. 2016;37(5):469–485. 10.1007/s10935-016-0446-3. [DOI] [PubMed] [Google Scholar]

[ref39] 39. Pearson JL, Waa A, Siddiqi K, Edwards R, Nez Henderson P, Webb HM. Naming racism, not race, as a determinant of tobacco-related health disparities. Nicotine Tob Res. 2021;23(6):885–887. 10.1093/ntr/ntab059. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref40] 40. Mattingly DT, Howard LC, Krueger EA, Fleischer NL, Hughes-Halbert C, Leventhal AM. Change in distress about police brutality and substance use among young people, 2017–2020. Drug Alcohol Depend. 2022;237:109530. 10.1016/j.drugalcdep.2022.109530. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref41] 41. Zeiders KH, Umaña-Taylor AJ, Carbajal S, Pech A. Police discrimination among black, Latina/x/o, and white adolescents: examining frequency and relations to academic functioning. J Adolesc. 2021;90(1):91–99. 10.1016/j.adolescence.2021.06.001. [DOI] [PubMed] [Google Scholar]

[ref42] 42. Alang S, McAlpine D, McClain M. Police encounters as stressors: associations with depression and anxiety across race. Socius. 2021;7:2378023121998128. 10.1177/2378023121998128. [DOI] [Google Scholar]

[ref43] 43. Jackson DB. The case for conceptualizing youth-police contact as a racialized adverse childhood experience. Am J Public Health. 2021;111(7):1189–1191. 10.2105/AJPH.2021.306324. [DOI] [PMC free article] [PubMed] [Google Scholar]

[ref44] 44. Jindal M, Mistry KB, Trent M, McRae A, Thornton RLJ. Police exposures and the health and well-being of black youth in the US: A systematic review. JAMA Pediatr. 2022;176(1):78–88. 10.1001/jamapediatrics.2021.2929. [DOI] [PubMed] [Google Scholar]

[ref45] 45. Kang D, Choi KH. Combustible cigarette smoking harms nearly every organ in the body. Eur Heart J. 2025;46(10):982–982. 10.1093/eurheartj/ehae896. [DOI] [PubMed] [Google Scholar]

[ref46] 46. American Cancer Society medical and editorial content team . Is any type of tobacco product safe? American Cancer Society November 19. 2024; Accessed March 17, 2025. https://www.cancer.org/cancer/risk-prevention/tobacco/is-any-type-of-smoking-safe.html.

[ref47] 47. Camacho OM, Ebajemito JK, Coburn S, Prasad K, Costigan S, Murphy JJ. Evidence from the scientific assessment of electronic cigarettes and their role in tobacco harm reduction. Contrib Tob Nicotine Res. 2021;30(2):63–108. 10.2478/cttr-2021-0007. [DOI] [Google Scholar]

[ref48] 48. Bailey ZD, Krieger N, Agénor M, Graves J, Linos N, Bassett MT. Structural racism and health inequities in the USA: evidence and interventions. Lancet. 2017;389(10077):1453–1463. 10.1016/S0140-6736(17)30569-X. [DOI] [PubMed] [Google Scholar]

[ref49] 49. World Health Organization . Coming of age: adolescent health. 2022; Accessed November 15, 2024. https://www.who.int/news-room/spotlight/coming-of-age-adolescent-health.

[ref50] 50. Rubin DB. Inference and missing data. Biometrika. 1976;63(3):581–592. 10.1093/biomet/63.3.581. [DOI] [Google Scholar]

PERMALINK

Discrimination Distress and Current Combustible and Non-combustible Tobacco Product Use Among US Youth, 2023

Meman Diaby, MS

Osayande Agbonlahor, MD, PhD

Maggie K Richardson, MS, MA

Joy L Hart, PhD

Shyanika W Rose, MA, PhD

Delvon T Mattingly, PhD

Roles

Abstract

Introduction

Methods

Results

Conclusion

Implications

Introduction

Methods

Data and Participants

Measures

Discrimination Distress

Current Tobacco Use

Covariates

Statistical Analysis

Results

Distribution of Participant Characteristics

Table 1.

Current Tobacco Product Use by Covariate Characteristics and Discrimination Distress

Table 2.

Associations Between Discrimination Distress and Current Tobacco Use

Table 3.

Table 4.

Sensitivity Analysis

Discussion

Limitations

Conclusion

Supplementary Material

Contributor Information

Author Contributions

Declaration of Interests

Funding

Data Availability

References:

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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