Perceived Discrimination and Nicotine Product Use: Findings from a Youth and Young Adult Sample (2022-2023)

Abstract

This cross-sectional study explores associations between perceived discrimination and nicotine product use. Data were collected from participants of the Truth Longitudinal Cohort, a national sample of youth and young adults. The analytic sample included participants surveyed between October 2022 to February 2023, who provided information on ever and past 30-day cigarette and e-cigarette use, perceived discrimination via the Everyday Discrimination Scale, and covariates (N = 5953). Multinomial logistic regression models were applied to the data to explore associations between perceived discrimination and nicotine product use. Results demonstrated that higher levels of perceived discrimination were associated with greater odds of current e-cigarette use, current or former cigarette use, current dual use of e-cigarettes and cigarettes, former e-cigarette use, and former dual use of e-cigarettes and cigarettes, relative to never users of cigarettes or e-cigarettes. Additional research is needed to determine the mechanisms by which perceived discrimination might influence use of nicotine products – especially given that associations were also found between gender identity, race and ethnicity, perceived financial situation, household smoker status, and sensation seeking with nicotine product use.

Keywords

perceived discrimination e-cigarettes cigarettes dual use nicotine youth young adults

Introduction

Electronic cigarettes (e-cigarettes) are the most used nicotine product among adolescents¹ and second-most used among adults, after cigarettes, and many young people also report dual product use.² Estimates from the 2023 National Youth Tobacco Survey (NYTS) indicate that 4.6% of middle school and 10.0% of high school students report current e-cigarette use, while 1.1% of middle school and 1.9% of high school students report current cigarette use.³ Additionally, 2.5% of middle school students and 3.9% of high school students report current use of multiple tobacco products.³ Among young adults (aged 18-24 years), 5.3% report cigarette use, 11.0% report e-cigarette use either “every day” or “some days”, and 3.4% also report the use of two or more tobacco products.²

Given such frequent levels of individual and poly-tobacco product use among young people, it is important to explore contributing factors such as perceived discrimination, which refers to a person’s perception of unfair treatment due to one or more individual characteristics such as age, race, ethnicity, gender identity, or socioeconomic status.⁴ Previous studies have found that perceived discrimination has been associated with increased risk for nicotine product use,^5,6 such as cigarette smoking,^7,8 greater smoking frequency,^8-10 greater vaping frequency,⁴ and lower likelihood of tobacco cessation.¹¹ Perceived discrimination has also been associated with other negative health outcomes, such as poor mental health and low levels of social connectedness.¹² Individuals experiencing discrimination have reported substance use as a means to mitigate poor mental health symptomatology.¹³ Further, minority stress models suggest that marginalized populations are more likely to use nicotine products (and other substances) to cope with increased stressors related to their identities.⁴ The experience of discrimination can activate stress responses within the body, leading to increases in allostatic load, or the cumulative effect of chronic stress on mental and physical health, and symptoms of poor mental health. Such symptoms include anxiety, depression, and stress – which have also been associated with e-cigarette and cigarette use.¹⁴

Although there is an established literature demonstrating the relationship between perceived discrimination and nicotine product use,^10,15-20 most studies have focused on associations between perceived discrimination and smoking behaviors among either youth (high school students)^18,19 or adult samples (aged 18 years and older).^16,17,20 There is a need to explore associations between perceived discrimination and dual use of cigarettes and e-cigarettes, given the increased prevalence of current dual use among youth and young adults and potential negative health effects associated with the dual use of e-cigarettes and cigarettes. The present study expands upon existing work by examining associations between perceived discrimination and cigarette, e-cigarette, and dual use of cigarettes and e-cigarettes among youths and young adults (aged 15 to 24 years at the time of study enrollment). Given the exploratory nature of this study, there were no a priori hypotheses regarding which nicotine products (i.e., e-cigarettes, cigarettes, or dual use of both nicotine products) would have the strongest association with perceived discrimination.

Methods

Sample

Data was obtained from the Truth Longitudinal Cohort (TLC), a nationally representative, probability-based cohort that was originally established in 2014 to evaluate the truth® national tobacco use prevention campaign. TLC participants (residing in the United States and aged 15-24 years at the time of study enrollment) were primarily recruited via address-based sampling. A large refreshment sample was recruited to address the attrition and aging of the original cohort. Additional information regarding the methodology of the TLC are published elsewhere.²¹ Households with 15-17 year old residents were selected for participation in the TLC and parents or guardians were asked to complete electronic parental consent and background demographics via online survey upon enrollment. Then, selected youth participants were asked to complete assent prior to completion of the online survey. Selected 18-24-year-old participants were asked to provide electronic consent and then begin the online survey. The study protocol was approved by Advarra Institutional Review Board (Pro00009087). All study procedures involving human participants were conducted in accordance with the 1964 Helsinki Declaration and its later amendments.

The analytic sample for this study was limited to participants who completed the survey from October 2022 to February 2023 (N = 6003). During this data collection period, participants were provided the Everyday Discrimination Scale – a validated measure of perceived discrimination.²² To assess associations between perceived discrimination and nicotine product use, the analytic sample was further limited to those who provided answers to questions on the Everyday Discrimination Scale, ever and past 30-day use of cigarettes and e-cigarettes, and covariates (N = 5953).

Measures

The main outcome of interest was nicotine product use, which was determined from items measuring ever use (i.e., never vs ever used in the participants’ lifetime) and frequency of use of cigarettes and e-cigarettes in the past 30 days. Use of any of these products on at least one day of the past 30 days was indicative of current use (i.e., ever, but not current use in the past 30 days vs current use in the past 30 days). Responses to these survey items were combined and re-categorized into 1) never use of cigarettes and e-cigarettes, 2) current (i.e., past 30-day-use) or former (i.e., ever, but not current) use of cigarettes, 3) current dual use of cigarettes and e-cigarettes, 4) former e-cigarette use, and 5) former dual use of cigarettes and e-cigarettes.

The main predictor of interest was perceived discrimination. Perceived discrimination was measured using the Everyday Discrimination Scale, where respondents were asked: “In your day-to-day life, how often do any of the following happen to you?” Items included: “You are treated with less courtesy than other people”, “You receive poorer service than other people at restaurants or stores”, “People act as if they think you are not smart”, “People act as if they are afraid of you”, and “You are threatened or harassed”. Response options were scored on a 0-5 scale with “Never” = 0, “Less than once a year” = 1, “A few times a year” = 2, “A few times a month” = 3, “At least once a week” = 4, and “Almost every day” = 5. To score this scale, item responses were summed, so that higher scores are indicative of more frequent experiences of discrimination.²³ The correlation between all items was found to be high (all correlations >0.70) and the five items had a Cronbach’s alpha of 0.943. A summed score was generated based on responses to the Everyday Discrimination Scale (range: 1-25), with an average score of 4.7 (SD = 0.10). Everyday Discrimination Scale scores were used as a proxy measure of perceived discrimination and included as the primary predictor in multinomial logistic regressions predicting nicotine product use.

Covariates included age [range: 15-30 years; categorized into 15-20 years (38.6%), 21-24 years (25.6%), 25-30 years (35.8%)], gender [male (48.4%), female (49.2%), nonbinary or a different gender identity (2.4%)], race and ethnicity [non-Hispanic, White (45.0%); non-Hispanic, Black (11.1%); Hispanic or Latino (19.7%); non-Hispanic, Asian (5.0%); non-Hispanic, another race and ethnicity (18.8%)], perceived financial situation [doesn’t meet basic expenses or just meets basic expenses (19.8%); meets needs with a little left or lives comfortably (80.1%)], household smoker [yes (21.4%), no (78.1%)], and sensation seeking [low (88.2%), high (11.8%), based on a threshold score of ≥4]. Sensation seeking was measured by the following items, to which participants indicated their level of agreement with the item (on a 5-point Likert scale from strongly disagree to strongly agree): “I would like to explore strange places”, “I would like to try parachute-jumping”, “I like wild parties”, “I get restless when I spend too much time at home”, “I like spending time with family”. Responses are summed and then a threshold of 4 is implemented to indicate either low (<4) or high (≥4) sensation seeking.

Statistical Analysis

Sample characteristics are presented as unweighted frequencies and weighted percentages. A multinomial logistic regression model was applied to the data. Prior to the implementation of the multinomial logistic regression model, assumptions were tested. Specifically, the variance inflation factor [VIF, calculated as 1/(1-R²) where R² is the coefficient of determination from a regression²⁴] was used to identify multicollinearity in regression models. There was no evidence of significant multicollinearity (all VIF <5). Hausman tests²⁵ and Small-Hsiao tests²⁶ were used to test for the assumption of independence of irrelevant alternatives (IIA). Both Hausman and Small-Hsiao tests indicated no evidence of a violation of IIA. Adjusted odds ratios (AOR) and 95% confidence intervals (CI) for each variable included in multinomial logistic regression models are reported. Covariates were included in multinomial logistic regression models to address potential sources of bias and confounding. Multinomial logistic regression models including interactions between perceived discrimination and age, gender identity, race and ethnicity, and perceived financial situation were conducted as sensitivity analyses. Since none of the interaction terms were statistically significant, results are not reported for these models including interaction effects. Analyses for this study were conducted using Stata 18 (Stata Corp, LLC; College Station, TX, USA).²⁷

Results

Participants were combined into nicotine product use categories based on e-cigarette and cigarette use behavior. As shown in Table 1, 53.2% of the sample reported never use of e-cigarettes or cigarettes, 13.8% reported former dual use of e-cigarettes and cigarettes, 11.8% reported former e-cigarette use, 10.2% reported current e-cigarette use, 4.7% reported former cigarette use, 4.1% reported current dual use of e-cigarettes and cigarettes, and 2.2% reported current cigarette use. Due to the low rates of current cigarette use within our sample, current and former cigarette use were combined for our subsequent analyses.

Table 1.

Sample Characteristics of Youth and Young Adults in the Truth Longitudinal Cohort, Wave 13 (N = 6003).

Sample characteristic	Frequency (N)	Weighted percent (weighted %)
Dual use status (missing = 1)
Never used e-cigarettes or cigarettes	3134	53.2
Current e-cigarette user	706	10.2
Current cigarette user	120	2.2
Former cigarette user	204	4.7
Current dual user of e-cigarettes and cigarettes	264	4.1
Former e-cigarette user	844	11.8
Former dual user of e-cigarettes and cigarettes	730	13.8
Age (in years, missing = 0)
15-20	2565	38.6
21-24	2287	25.6
25-30	1151	35.8
Gender identity (missing = 1)
Male	2437	48.4
Female	3381	49.2
Non-binary or a different gender identity	184	2.4
Race and ethnicity (missing = 19)
Non-Hispanic, White	2972	45.0
Non-Hispanic, Black	429	11.1
Non-Hispanic, Asian	261	5.0
Non-Hispanic, multiracial	1290	18.8
Hispanic or Latino	1032	19.7
Perceived financial situation (missing = 4)
Don’t meet basic expenses or just meet basic expenses	1358	19.8
Meet needs with a little left or lives comfortably	4641	80.1
Household smokers (missing = 25)
No household smokers	4635	78.1
At least one individual in household smokes	1343	21.4
Sensation seeking
Low sensation seeking (score <4)	5273	88.2
High sensation seeking (score ≥4)	730	11.8
	Mean	Standard deviation (SD)
Perceived discrimination scale (range: 1-25, missing = 5)	4.7	0.10

As shown in Table 2, perceived discrimination was associated with increased odds of current e-cigarette use (OR = 1.07, 95% CI: 1.05, 1.09), current or former cigarette use (OR = 1.06, 95% CI: 1.04, 1.09), current dual use of e-cigarettes and cigarettes (OR = 1.12, 95% CI: 1.09, 1.14), former e-cigarette use (OR = 1.04, 95% CI: 1.02, 1.06), and former dual use of e-cigarettes and cigarettes (OR = 1.06, 95% CI: 1.05, 1.08), when compared to never users of either product.

Table 2.

Multinomial Logistic Regression Models Predicting Nicotine Product Use (N = 5953).

	Current E-cigarette use odds ratio (95%confidence interval)	Current or former cigarette use odds ratio (95%confidence interval)	Current dual use of E-cigarettes and cigarettes odds ratio (95%confidence interval)	Former E-cigarette use odds ratio (95%confidence interval)	Former dual use of E-cigarettes and cigarettes odds ratio (95%confidence interval)
Perceived discrimination (for any reason)	1.07 (1.05, 1.09)	1.06 (1.04, 1.09)	1.12 (1.09, 1.14)	1.04 (1.02, 1.06)	1.06 (1.05, 1.08)
Age (years)
15-20	Reference	Reference	Reference	Reference	Reference
21-24	1.63 (1.35, 1.96)	3.90 (2.81, 5.41)	2.61 (1.94, 3.53)	1.54 (1.30, 1.82)	2.57 (2.09, 3.15)
25-30	1.13 (0.86, 1.47)	8.96 (6.38, 12.58)	2.28 (1.54, 3.39)	1.21 (0.96, 1.52)	4.84 (3.88, 6.05)
Gender identity
Male	Reference	Reference	Reference	Reference	Reference
Female	1.06 (0.89, 1.27)	0.84 (0.66, 1.07)	0.90 (0.69. 1.19)	1.50 (1.27, 1.76)	1.10 (0.93, 1.31)
Non-binary or a different gender identity	0.58 (0.33, 1.00)	0.75 (0.37, 1.52)	0.72 (0.36, 1.46)	1.23 (0.78, 1.93)	0.84 (0.50, 1.39)
Race and ethnicity
Non-Hispanic, White	Reference	Reference	Reference	Reference	Reference
Non-Hispanic, Black	0.64 (0.44, 0.92)	1.41 (0.93, 2.15)	0.75 (0.45, 1.28)	0.89 (0.65, 1.23)	0.76 (0.53, 1.08)
Non-Hispanic, Asian	0.73 (0.47, 1.14)	0.67 (0.34, 1.32)	0.40 (0.16, 1.00)	0.87 (0.60, 1.27)	0.49 (0.30, 0.81)
Non-Hispanic, multiracial	1.06 (0.86, 1.32)	1.41 (1.05, 1.90)	1.00 (0.71, 1.41)	1.09 (0.89, 1.33)	1.10 (0.89, 1.37)
Hispanic or Latino	1.02 (0.81, 1.30)	0.98 (0.69, 1.39)	1.10 (0.77, 1.58)	1.21 (0.98, 1.50)	1.21 (0.96, 1.51)
Perceived financial situation
Don’t meet basic expenses or just meet basic expenses	Reference	Reference	Reference	Reference	Reference
Meet needs with a little left or lives comfortably	0.73 (0.60, 0.90)	0.69 (0.53, 0.90)	0.68 (0.51, 0.91)	1.05 (0.86, 1.27)	0.80 (0.65, 0.97)
Household smokers
No household smokers	Reference	Reference	Reference	Reference	Reference
At least one individual in household smokes	4.63 (3.84, 5.58)	2.94 (2.25, 3.86)	7.68 (5.82, 10.14)	1.72 (1.41, 2.09)	1.81 (1.47, 2.23)
Sensation seeking
Low sensation seeking (score <4)	Reference	Reference	Reference	Reference	Reference
High sensation seeking (score ≥4)	2.55 (1.68, 3.89)	2.26 (1.24, 4.09)	3.86 (2.33, 6.40)	1.62 (1.02, 2.56)	2.52 (1.63, 3.90)
Constant	0.11 (0.08, 0.14)	0.02 (0.02, 0.04)	0.02 (0.01, 0.03)	0.12 (0.09, 0.16)	0.08 (0.06, 0.11)

Note. Bold text indicates statistically significant associations where P-value <.05. The reference group for this model is “never used e-cigarettes or cigarettes”.

Also shown in Table 2 are associations between age, gender identity, race and ethnicity, perceived financial situation, household smoking, sensation seeking, and nicotine product use. While there are several significant findings regarding covariates, the most consistent patterns are found for age, financial situation, household smoking, and sensation seeking. Participants aged 21- to 24-years-old were more likely to be in each nicotine product usage category, relative to 15- to 20-year-olds, while 25- to 30-year-olds were only more likely than 15- to 20-year-olds to be in categories involving combustible cigarettes (current or former cigarette user, current dual use, and former dual use). A more secure financial situation predicted lower likelihood of nicotine product usage, when compared to less secure financial situations, for all categories other than former e-cigarette usage (OR = 1.05, 95% CI: (0.86, 1.27). Residing with a household smoker was associated with greater odds of any nicotine use category, relative to not living with any household smoker. Finally, those scoring higher in sensation seeking were more likely to report behavior consistent with each nicotine product usage category than those with low sensation seeking scores. Although the effects of statistical interactions between perceived discrimination and age, gender identity, race and ethnicity, perceived financial situation, and household smoking were included in sensitivity analyses, none were statistically significant.

Discussion

This study examined associations between perceived discrimination and nicotine product use among a youth and young adult sample. Results demonstrate that perceived discrimination (for any reason) is associated with current e-cigarette use, current or former cigarette use, current dual use of e-cigarettes and cigarettes, former e-cigarette use, and former dual use of e-cigarettes and cigarettes. Given the overlap in estimates and 95% confidence intervals across nicotine product use groupings, estimated effects are not significantly different from one another. These results align with the findings of another recent study demonstrating that perceived discrimination (for any reason) was associated with an increased risk of nicotine product use (i.e., e-cigarettes, cigars, cigarettes, pipes, and hookah).²⁰ Current study results also demonstrate associations between gender identity, race and ethnicity, perceived financial situation, household smoker status, and sensation seeking with nicotine product use.

More research is needed to explore potential mechanisms explaining the relationship between perceived discrimination and nicotine product use. For example, future studies may want to determine whether individuals who perceive discrimination are using nicotine products as a means for coping with poor mental health, such as anxiety, depression, and stress, or determine which social influences have an effect on the association between perceived discrimination and nicotine product use. Given that the estimated odds ratios for associations between race and ethnicity and nicotine product use categories demonstrate different directions of effects, there is a need to investigate potential interactions between race and ethnicity categories with perceived discrimination. However, results from the present study suggest that much larger sample sizes are required to conduct this research. Future studies also need to consider existing gaps in research related to perceived discrimination and nicotine product use among historically marginalized and understudied racial and ethnic groups, such as those who identify as Asian American, Native Hawaiian, Pacific Islander, American Indian, Alaskan Native, and multiracial.²⁸

Limitations

Findings are based on a sample of youth and young adults from the Truth Longitudinal Cohort (TLC). Although the TLC is a nationally representative sample of youth and young adults, findings may not be generalizable to other populations with different characteristics. Additionally, the reliability and interpretations of the findings are potentially limited by small sample size. As a result, the broad characterization of nicotine product use in this study does not account for specific patterns of use. Related to this point, the restricted age range and gender categories may simplify any age- or gender-related differences that may exist in other population samples. Larger sample sizes are needed for future research to determine reliability and generalizability of findings and further investigate variability in nicotine product behaviors and how these behaviors may differ across sociodemographic factors (i.e., age, gender identity, race and ethnicity). Larger sample sizes will also allow for the use of alternative statistical approaches to characterize nicotine product use and associations with sociodemographic factors, such as latent class analyses and propensity scoring models. Additionally, since nicotine product use is self-reported, the study sample may be subjected to social desirability and recall bias. To reduce social desirability biases, participants are told that their responses are confidential. Increasing the frequency of contact with participants and/or minimizing the time between assessments may help to reduce recall bias. Since this study reflects cross-sectional associations, no causal associations between perceived discrimination and nicotine product use can be established. No power analyses were performed for this study.

Future studies are needed to determine associations between specific attributions for perceived discrimination and nicotine product use, since sample sizes limit the ability to report stratified models based on attributions for perceived discrimination. Additional studies are needed to validate results and determine how associations may change over time. Longitudinal studies will be useful in confirming whether increases in perceived discrimination also led to increases in nicotine product use.

Conclusion

Despite these study limitations, the current study demonstrates associations between perceived discrimination and nicotine product use among a youth and young adult sample. Results highlight the need to consider perceived discrimination as a significant risk factor for nicotine product use (and its associated health burdens) among youth and young adults. Additional research is needed to explore the mechanisms by which perceived discrimination may affect use of cigarettes, e-cigarettes, and poly nicotine product use by young people.

Footnotes

Acknowledgements

The authors would like to thank the participants of the Truth Longitudinal Cohort who contributed their data to this research.

ORCID iDs

Elizabeth K. Do

Kristiann Koris

Alexander P. D’Esterre

Shreya Tulsiani

Ethical Statement

Author Contributions

Elizabeth K. Do: conceptualization, methodology, data analysis, writing – original draft, writing – review &editing, supervision, project administration; Karl Braganza: data analysis, writing - original draft, writing – review & editing, project administration; Kristiann Koris: writing – original draft, writing – review & editing; Alexander P. D’Esterre: data analysis, writing – original draft, writing – review & editing; Shreya Tulsiani: writing – original draft, writing – review & editing; Elizabeth C. Hair: writing – original draft, writing – review & editing, supervision.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

A data sharing agreement is required for the use of all data. Truth Initiative does not share data with tobacco industry representatives or affiliated researchers. Investigators seeking access to data used in the study should make a written request to Truth Initiative and submit a detailed research plan including the purpose of the proposed research, required variables, duration of the analysis phase, IRB approval with FWA information and documentation of investigator training in human subjects. Approved investigators may access datasets via an analytic Portal owned and administered by Truth Initiative.*

References

Cooper

Park-Lee

Ren

Cornelius

Jamal

Cullen

. Notes from the field: E-cigarette use among middle and high school students — United States, 2022. MMWR Morb Mortal Wkly Rep. 2022;71(40):1283-1285. doi:10.15585/mmwr.mm7140a3

Cornelius

Loretan

Jamal

, et al. Tobacco product use among adults – United States, 2021. MMWR Morb Mortal Wkly Rep. 2023;72:475-483. doi:10.15585/mmwr.mm7218a1

Birdsey

Cornelius

Jamal

, 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. doi:10.15585/mmwr.mm7244a1

Fahey

Morris

Robinson

Pebley

. Association between perceived discrimination and vaping among college students. Subst Use Misuse. 2021;56(5):738-741. doi:10.1080/10826084.2021.1887250

Banks

Kohn-Wood

Spencer

. An examination of the African American experience of everyday discrimination and symptoms of psychological distress. Community Ment Health J. 2006;42(6):555-570. doi:10.1007/s10597-006-9052-9

Xiong

Xia

. Perceived discrimination and aggression among Chinese migrant adolescents: a moderated mediation model. Front Psychol. 2021;12:651270. https://www.frontiersin.org/articles/10.3389/fpsyg.2021.651270. Accessed 21 September 2023.

Guthrie

Young

Williams

Boyd

Kintner

. African American girls’ smoking habits and day-to-day experiences with racial discrimination. Nurs Res. 2002;51(3):183-190.

Hicks

Kogan

. The influence of racial discrimination on smoking among young black men: a prospective analysis. J Ethn Subst Abuse. 2020;19(2):311-326. doi:10.1080/15332640.2018.1511493

Allem

Soto

Baezconde-Garbanati

Sussman

Unger

. Cultural and social influences on adolescent smoking dissipate by emerging adulthood among Hispanics in Southern California. J Immigr Minority Health. 2015;17(1):192-197. doi:10.1007/s10903-013-9910-9

10.

Brondolo

Monge

Agosta

, et al. Perceived ethnic discrimination and cigarette smoking: examining the moderating effects of race/ethnicity and gender in a sample of Black and Latino urban adults. J Behav Med. 2015;38(4):689-700. doi:10.1007/s10865-015-9645-2

11.

Webb Hooper

Calixte-Civil

Verzijl

, et al. Associations between perceived racial discrimination and tobacco cessation among diverse treatment seekers. Ethn Dis. 2020;30(3):411-420. doi:10.18865/ed.30.3.411

12.

Mpofu

Cooper

Ashley

, et al. Perceived racism and demographic, mental health, and behavioral characteristics among high school students during the COVID-19 pandemic — adolescent behaviors and experiences survey, United States, January–June 2021. MMWR Suppl. 2022;71(3):22-27. doi:10.15585/mmwr.su7103a4

13.

Smart Richman

Blodorn

Major

. An identity-based motivational model of the effects of perceived discrimination on health-related behaviors. Group Process Intergr Relat. 2016;19(4):415-425. doi:10.1177/1368430216634192

14.

Tulsiani

Koris

Minter

Hair

. Depression, anxiety, stress, and current e-cigarette use: results from the truth longitudinal cohort of youth and young adults (2022-2023). J Affect Disord. 2024;365:628-633. doi:10.1016/j.jad.2024.08.127

15.

Hirschtick

Mattingly

Cho

, et al. Exclusive, dual, and polytobacco use among US adults by sociodemographic factors: results from 3 nationally representative surveys. Am J Health Promot. 2021;35(3):377-387. doi:10.1177/0890117120964065

16.

Mattingly

Mezuk

Elliott

Fleischer

. Discrimination and tobacco use outcomes among US adults: effect modification by race/ethnicity. J Racial Ethn Health Dispar. 2023;11:395-405. doi:10.1007/s40615-023-01527-3, Published online 25 January.

17.

Purnell

Peppone

Alcaraz

, 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. doi:10.2105/AJPH.2012.300694

18.

Dai

Thiel

Hafer

. Perceived racism and discrimination and youth substance use in the United States – intersections with sex and ethnicity. Prev Med. 2024;178:107811. doi:10.1016/j.ypmed.2023.107811

19.

Baiden

Onyeaka

Aneni

, et al. Perceived racial discrimination and polysubstance use among racial/ethnic minority adolescents in the United States. Drug Alcohol Depend. 2023;248:109894. doi:10.1016/j.drugalcdep.2023.109894

20.

Unger

. 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. doi:10.1080/10826084.2017.1421226

21.

Cantrell

Hair

Smith

, et al. Recruiting and retaining youth and young adults: challenges and opportunities in survey research for tobacco control. Tob Control. 2018;27(2):147-154. doi:10.1136/tobaccocontrol-2016-053504

22.

Williams

Yan

Jackson

Anderson

. Racial differences in physical and mental health: socio-economic status, stress and discrimination. J Health Psychol. 1997;2(3):335-351. doi:10.1177/135910539700200305

23.

Michaels

Thomas

Reeves

, et al. Coding the everyday discrimination scale: implications for exposure assessment and associations with hypertension and depression among a cross section of mid-life African American women. J Epidemiol Community Health. 2019;73(6):577-584. doi:10.1136/jech-2018-211230

24.

Hair

Black

Babin

Anderson

Tatham

. Multivariate Data Analysis. 6th ed. Hoboken, NJ: Pearson Pretince Hall; 2006.

25.

Hausman

. Specification tests in econometrics. Econometrica. 1978;46:1251-1271.

26.

Small

Hsiao

. Multinomial Logit Specification Tests. International Economic Review. 1985;26(3):619-27.

27.

StataCorp . 2023. Stata Statistical Software: Release 18 . College Station, TX: StataCorp LLC.

28.

Cruz

Rose

Lienemann

, et al. Pro-tobacco marketing and anti-tobacco campaigns aimed at vulnerable populations: a review of the literature. Tob Induc Dis. 2019;17:68. doi:10.18332/tid/111397