Adolescent-specific risk and protective factors of substance use among high school students in the United States: A cross-sectional study

Abstract

Objective: Substance use among U.S. adolescents is a critical public health concern. This study evaluates risk and protective factors for substance use among high school students. Methods: Using data from the 2022 National Survey on Drug Use and Health, a cross-sectional analysis of 6,072 high school students was conducted. Multivariable logistic regression analyzed associations between substance use (alcohol, tobacco, illicit drugs) and adolescent-specific factors, adjusting for sex, grade, health insurance, and poverty status. Results: Overall, 35.6% of students reported using alcohol, tobacco, or illicit drugs in the past year. Antisocial behavior significantly increased the odds of alcohol (AOR = 2.54, 95% CI = 2.02–3.19), tobacco (AOR = 2.36, 95% CI = 1.92–2.89), and illicit drug use (AOR = 2.66, 95% CI = 2.22–3.19; p < .001). Religious involvement reduced the odds of alcohol (AOR = 0.79, 95% CI = 0.64–0.97, p = .026), tobacco (AOR = 0.71, 95% CI = 0.56–0.90, p = .006), and illicit drug use (AOR = 0.59, 95% CI = 0.45–0.77, p < .001). Conclusions: One in three high school students reported substance use. Antisocial behaviors increase risk, while religious involvement offers protection. Interventions targeting these factors may reduce adolescent substance use.

Plain Language Summary

High school students in the U.S. face the effects of using substances like alcohol, tobacco, and illegal drugs. Our study looked at national survey data to understand how many high school students use these substances and what factors might influence their use. We found that about one in three high school students had used these substances in the past year, and the rate of use increased as students moved from freshman to senior year. Students who argued or fought with their parents, or who were involved in school or group fights, were more likely to use these substances. On the other hand, students who participated in religious activities or held religious beliefs tended to use fewer of these substances. Based on these findings, we believe it is important to create programs that help reduce negative behaviors, like fighting, and provide positive support for students, like participation in religious groups or other community-based programs. By focusing on reducing conflict and promoting healthy, supportive environments, schools and communities can work together to guide students toward better choices and improve their overall well-being.

Keywords

Adolescents substance use factors behavior

Introduction

Substance use is a significant public health concern in the United States (U.S.). Data from the 2020 National Survey on Drug Use and Health (NSDUH) indicate that approximately 37 millions of American aged 12 and older reported using illicit drugs within the past month (NCDAS, 2023). Despite concerted efforts by policymakers and prevention organizations, nearly 47% of high school students report using an illegal drug before graduation (NCDAS, 2023). Among adolescents, substance use poses severe risks, impairing cognitive function and reducing the size of critical brain regions such as the hippocampus (Medina et al., 2007). Substance use during adolescence increases the likelihood of future substance use disorders (SUDs) and long-term health complications (Squeglia et al., 2009). Alarmingly, adolescent drug and alcohol use rates continue to rise, underscoring the limitations of existing interventions and the urgent need for further research into risk and protective factors influencing substance use among high school students.

Adolescence represents a critical period of physical and mental development characterized by significant neurological, psychological, and social changes (Bava & Tapert, 2010). During this stage, the brain undergoes substantial growth, including maturation of the prefrontal cortex and white matter connectivity, which are vital for cognitive and behavioral regulation (Bava & Tapert, 2010; Squeglia & Gray, 2016). Adolescents are particularly susceptible to external influences during this phase of neurological development. Increased sensitivity to social perception, emotional stimuli, and external stressors, such as bullying, peer pressure, and parental expectations, can lead to impulsive decision-making and increase the likelihood of substance use (Bozzini et al., 2021).

The factors influencing adolescent substance use are diverse, including individual, familial, and environmental domains. For instance, adolescents exposed to substance use in their households are at a heightened risk of developing SUDs themselves (Bozzini et al., 2021; Lander et al., 2013). Studies have demonstrated that individuals with SUDs are more likely to engage in violent behaviors toward family members, while children in such households often experience neglect and grow up in unhealthy conditions (Chermack et al., 2010; Lander et al., 2013). These conditions can impede healthy development and increase susceptibility to substance use. Although demographic and social determinants of health (SDOH) are well-documented risk factors, less is known about the influence of psychosocial behaviors, social involvement, and environmental conditions, specifically among high school adolescents.

Emerging evidence suggests that social factors, including participation in extracurricular activities, religious involvement, and community behaviors, may influence substance use behaviors among adolescents (Brennan et al., 2017; Fairclough et al., 2024; Kulis et al., 2021). However, existing studies often lack comprehensive analyses that adjust for potential confounding factors across multiple domains. Furthermore, most research does not focus exclusively on high school students, a group particularly vulnerable to the risks associated with substance use. This underscores the need for targeted studies examining specific factors such as academic performance, student behavior, parental involvement, extracurricular engagement, and religious beliefs within this population.

Substance use determinants may also vary depending on the specific substance. For instance, risk factors for alcohol use may differ from those for tobacco or illicit drug use (Gebeyehu & Srahbzu Biresaw, 2021; Le, 2023; Nawi et al., 2021). Although correlations exist among adolescents who use multiple substances, it remains unclear whether common risk factors contribute to these behaviors, particularly in high school populations (Nawi et al., 2021). Identifying shared and substance-specific risk factors is essential for developing targeted interventions to reduce substance use and enhance adolescents’ long-term well-being.

We hypothesize that common factors influence the use of alcohol, tobacco, and illicit drugs among high school adolescents. Using data from the 2022 NSDUH, this study aims to (1) determine the prevalence of substance use among high school students, and (2) identify common risk and protective factors associated with alcohol, tobacco, and illicit drug use in this population.

Methods

Study design and setting

This study employed a cross-sectional design using data from the NSDUH, a nationally representative survey administered annually by the Substance Abuse and Mental Health Services Administration (SAMHSA). The NSDUH targets the civilian, non-institutionalized population in the United States aged 12 years or older. Data for this study was drawn from the 2022 NSDUH dataset, comprising 59,069 participants. As the dataset includes de-identified, publicly available data, this study was exempt from review by the regional institutional review board and classified as non-human subject research.

Inclusion and exclusion criteria

Adolescents aged 12–17 who were currently attending or expected to attend high school (grades 9–12) as full-time students were included in this study. Exclusion criteria applied to participants who:1) were not high school students, (2) were not adolescents, (3) were not full-time students, (4) had unknown full-time student status, or (5) refused to disclose their full-time student status. A detailed flow diagram outlining participant inclusion and exclusion is provided in Figure 1.

Outcomes measurement: Alcohol, tobacco, and illicit drug use

The primary outcome measures included imputed data reflecting alcohol, tobacco, or illicit drug use within the past year. Alcohol use was defined from the question “any alcohol use in the past year”. Tobacco use was defined as the use of any tobacco products or nicotine vaping devices. Illicit drug use included substances such as cocaine, heroin, hallucinogens, inhalants, methamphetamine, marijuana (including hashish), and the misuse of prescription drugs such as pain relievers, sedatives, stimulants, and tranquilizers. Misuse of prescription drugs was identified through positive responses indicating use without a prescription, in greater amounts, more frequently, for longer periods, or in any manner not directed by a physician.

Risk and protective factors of substance use

The six adolescent-specific domain categories are: academic engagement and performance, student antisocial behavior, youth enrichment activities, religious involvement, parental involvement, and substance use prevention education. Table 1 summarizes the variables included in each domain and their respective measurements. A “positive” classification for a domain required at least one affirmative response within the category, whereas a “negative” classification was assigned when all responses within the category were negative.

(1) Academic engagement and performance (referred to as school performance) included school engagement (liking school), teacher’s encouragement/praise, average grades, and school attendance (e.g., skipping school).

(2) Student antisocial behavior (referred to as antisocial behavior) included arguing/fighting with parents, involvement in school fights, and participation in group fights.

(3) Youth enrichment activities included participation in youth activities, problem-solving, communication skills, and self-esteem programs.

(4) Religious beliefs and involvement (referred to as religious involvement) included attendance at religious services, the perceived importance of religious beliefs, the influence of religious beliefs on life decisions, and sharing beliefs with friends.

(5) Parental involvement included checking homework, helping with homework, assigning chores, limiting TV time, setting curfews on school nights, praising youth for their achievements, and expressing pride in their accomplishments.

(6) Substance use prevention education (referred to as prevention education) included discussions with parents about the dangers of substance use, participation in substance prevention programs outside of school, exposure to alcohol/drug prevention messages outside of school, and participation in drug or alcohol education programs at school.

Table 1.

Domain-specific Risk and Protective Factors Using Data From National Survey on Drug Use and Health (NSDUH) 2022.

NSDUH variable	NSDUH questionnaire	Measurement
School performance (yes or no) – Protective factor
SCHFELT	Which of the statements below best describes how you felt overall about going to school during the past 12 months?	Yes = Liked a lot/Kind of liked
SCHFELT		No = Didn’t like/Hated
TCHGJOB	During the past 12 months, how often did your teachers at school let you know when you were doing a good job with your schoolwork?	Yes = Always/Sometimes
TCHGJOB		No = Seldom/Never
AVGGRADE	What were your grades for the last semester or grading period you completed?	Yes = grade A, B, or C
AVGGRADE		No = Grade D or lower
EDUSKPCOM	What is your best estimate of the number of whole days of school you missed because you skipped or ‘cut’ or just didn’t want to be there during the past 30 days?	Yes = 0 day skipped
EDUSKPCOM		No = 1–30 days skipped
Antisocial behavior (yes or no) – Risk factor
ARGUPAR	During the past 12 months, how many times have you argued or had a fight with at least one of your parents?	Yes = 10 or more times
ARGUPAR		No = 9 or fewer times
YOFIGHT2	During the past 12 months, how many times have you gotten into a serious fight at school or work?	Yes = One or more times
YOFIGHT2		No = None
YOGRPFT2	During the past 12 months, how many times have you taken part in a fight where a group of your friends fought against another group?	Yes = One or more times
YOGRPFT2		No = None
Youth enrichment activities (yes or no) – Protective factor
PRBSOLV2	During the past 12 months have you participated in a problem solving, communication skills or self-esteem group?	Yes = Yes
PRBSOLV2		No = No
YTHACT2	YTHACT2 reports over the following four youth activity questions: School-based (YESCHACT), community-based (YECOMACT), church or faith-based (YEFAIACT), or other activities (YEOTHACT)	Yes = two or more activities
YTHACT2		No = none or one activity
Religious involvement (yes or no) --- protective factor
RLGATTD	During the past 12 months, how many times did you attend religious services? Please do not include special occasions such as weddings, funerals, or other special events in your answer	Yes = 25 or more times
RLGATTD		No = fewer than 25 times
RLGIMPT	Your religious beliefs are a very important part of your life. For each statement, please indicate whether you strongly disagree, disagree, agree, or strongly agree	Yes = agree/Strongly agree
RLGIMPT		No = Strongly disagree/Disagree
RLGDCSN	Your religious beliefs influence how you make decisions in your life. For each statement, please indicate whether you strongly disagree, disagree, agree, or strongly agree	Yes = agree/Strongly agree
RLGDCSN		No = Strongly disagree/Disagree
RLGFRND	It is important that your friends share your religious beliefs. For each statement, please indicate whether you strongly disagree, disagree, agree, or strongly agree	Yes = agree/Strongly agree
RLGFRND		No = Strongly disagree/Disagree
Parental involvement (yes or no) --- protective factor
PARCHKHW	During the past 12 months, how often did your parents check on whether you had done your homework?	Yes = always/Sometimes
PARCHKHW		No = seldom/Never
PARHLPHW	During the past 12 months, how often did your parents provide help with your homework when you needed it?	Yes = always/Sometimes
PARHLPHW		No = seldom/Never
PRCHORE2	During the past 12 months, how often did your parents make you do chores around the house?	Yes = always/Sometimes
PRCHORE2		No = seldom/Never
PRLMTTV2	During the past 12 months, how often did your parents limit the amount of time you watched TV?	Yes = always/Sometimes
PRLMTTV2		No = seldom/Never
PARLMTSN	During the past 12 months, how often did your parents limit the amount of time you went out with friends on school nights?	Yes = always/Sometimes
PARLMTSN		No = seldom/Never
PRGDJOB2	During the past 12 months, how often did your parents let you know when you’d done a good job?	Yes = always/Sometimes
PRGDJOB2		No = seldom/Never
PRPROUD2	During the past 12 months, how often did your parents tell you they were proud of you for something you had done?	Yes = always/Sometimes
PRPROUD2		No = seldom/Never
Substance use prevention education (yes or no) -- protective factor
PRVDRGO2	During the past 12 months have you participated in an alcohol, tobacco or drug prevention program outside of school, where you learn about the dangers of using, and how to resist using, alcohol, tobacco, or drugs?	Yes = yes
PRVDRGO2		No = No
PRTALK3	During the past 12 months, have you talked with at least one of your parents about the dangers of tobacco, alcohol, or drug use?	Yes = yes
PRTALK3		No = No
DRPRVME3	During the past 12 months have you seen or heard any alcohol or drug prevention messages from sources outside school such as posters, pamphlets, radio, or TV?	Yes = yes
DRPRVME3		No = No
ANYEDUC3	During the past 12 months have you had a special class about drugs or alcohol in school? During the past 12 months have you had films, lectures, discussions, or printed information about drugs or alcohol in one of your regular school classes such as health or physical education? During the past 12 months have you had films, lectures, discussions, or printed information about drugs or alcohol outside of one of your regular classes such as in a special assembly?	Yes = yes (yes to any of the questions listed)
ANYEDUC3		No = No (no to all the questions listed)

Other explanatory variables

Other explanatory variables included socio-demographics. Socio-demographics included high school grades (9^th, 10^th, 11^th, and 12^th grades), sex (male and female), race and ethnicity [non-Hispanic White (NHW), non-Hispanic Black (NHB), Hispanic, and others], English proficiency (very well/well vs. not well/not at all), health insurance coverage (yes vs. no), household poverty level (poor, near poor, above near poor), and family assistance, which included the use of food stamps, public assistance, or the need for welfare, job, or child care. Missing data handling varied; while high school grades, sex, and English proficiency data were not imputed, other sociodemographic variables included imputed values, as NSDUH prohibits missing responses to gender-related questions since 2002. A comprehensive description and interpretation of all the variables utilized in this study (not listed in Table 1) are provided in Supplemental Table 1.

Data analysis

Weighted percentages were calculated for each variable and the association of risk and protective factors with substance use outcomes were tested using the Rao-Scott Chi-square tests. Multivariable logistic regression analyses were performed to identify factors, particularly those in the six adolescent-specific domains, associated with alcohol, tobacco, and illicit drug use in the past year. Analyses adjusted for sociodemographic variables (sex, race and ethnicity, English proficiency, insurance status, household poverty level, and family assistance). Adjusted odds ratios (AORs) with 95% confidence intervals (CIs) and p-values were reported. All analyses, including weighted replicates, were conducted using STATA 14.2 (College Station, TX).

Reporting guideline

This study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (Von et al., 2007).

Results

From the initial 59,069 participants in the NSDUH 2022 dataset, we excluded 51,919 individuals who were not high school students (grades 9–12), 804 individuals who were not adolescents (aged outside the 12–17 range), 217 individuals who were not full-time students, 56 individuals with uncertain student status, and one individual who refused to disclose their student status. After these exclusions, the final study sample comprised 6,072 individuals, representing a weighted population of 13,131,547 US high school students. A detailed study flow diagram is provided in Figure 1.

Table 2 presents the unweighted population distributions and weighted percentages for key variables associated with alcohol, tobacco, and illicit drug use. Overall, 35.6% reported any use of alcohol or tobacco or illicit drugs (data not reported in tabular form). 23.5% of high school students reported using alcohol followed by tobacco use (19.6%) and illicit drug use (18.0%, Table 2). When substance use was examined across different grade levels, a gradual increase in the percentage of alcohol, tobacco, and illicit drug use was observed from 9th-grade to 12th-grade students (Table 2). Additionally, a higher proportion of NHW high school students reported alcohol use compared to Hispanic students (26.5% vs. 15.1%, p < .001, Table 2).

Table-2.

Numbers and Weighted Percentages of Alcohol, Tobacco, and Illicit Drug Use by Risk and Protective Factors Among Full-Time High School Students (Aged 12–17 years) in the U.S. National Survey of Drug Use and Health (NSDUH) 2022.

Variables --- n (wt%)	Alcohol use	p	Tobacco use	p	Illicit drug use	p
Substance use outcome (yes)	1468 (23.5)		1281 (19.6)		1182 (18.0)
Six domain categories
School performance		0.2436		0.0228		<0.001
Negative	23 (35.3)		23 (41.6)		27 (63.5)
Positive	1396 (23.4)		1200 (19.0)		1095 (17.3)
Antisocial behavior		<0.001		<0.001		<0.001
Yes	656 (34.1)		618 (29.9)		578 (29.2)
No	797 (18.7)		649 (14.8)		591 (12.8)
Youth enrichment activity		<0.001		0.7140		0.6554
Yes	432 (18.8)		484 (19.1)		436 (18.5)
No	1025 (26.3)		785 (19.8)		733 (17.7)
Religious involvement		0.0012		0.0030		<0.001
Positive	831 (21.7)		743 (17.8)		645 (15.4)
Negative	610 (27.7)		511 (23.2)		509 (23.2)
Parental involvement		0.0944		0.1529		0.0954
Positive	1430 (23.3)		1233 (19.3)		1140 (17.7)
Negative	21 (40.8)		25 (32.8)		22 (34.0)
Prevention education		0.8601		0.0286		0.0206
Positive	1299 (23.6)		1105 (18.9)		1021 (17.1)
Negative	132 (24.2)		138 (25.2)		119 (24.2)
Socio-demographic factors
School grade		<0.001		<0.001		<0.001
9^th grade	233 (13.2)		266 (14.9)		213 (11.8)
10^th grade	389 (18.8)		342 (18.3)		318 (16.4)
11^th grade	482 (32.0)		387 (22.0)		375 (21.1)
12^th grade	364 (37.3)		286 (26.7)		276 (26.0)
Sex		0.0118		0.0023		0.0179
Male	676 (21.1)		571 (16.8)		543 (16.2)
Female	792 (26.0)		710 (22.4)		639 (19.8)
Race and ethnicity		<0.001		0.3889		0.4983
NHW	806 (26.5)		621 (19.7)		562 (17.8)
NHB	137 (15.1)		171 (20.4)		178 (19.8)
Hispanic	362 (24.5)		330 (20.5)		306 (18.5)
Others	163 (17.0)		159 (15.4)		136 (15.3)
English Speaking		0.3787		0.5625		0.1849
Very well/Well	1455 (23.6)		1259 (19.4)		1168 (18.0)
Poor/Not at all	9 (14.7)		16 (24.5)		5 (6.9)
Health insurance		0.8476		0.4292		0.3335
Yes	1435 (23.6)		1240 (19.4)		1157 (18.2)
No	33 (22.4)		41 (23.1)		25 (13.6)
Household poverty level		<0.001		0.2320		0.6249
Poor	215 (17.3)		257 (21.3)		223 (18.3)
Near poor	288 (21.0)		331 (21.1)		290 (19.3)
Above near poor	965 (26.4)		693 (18.4)		669 (17.4)
Received family assistance		0.0086		0.0582		0.1440
No	320 (19.3)		388 (22.3)		339 (19.8)
Yes	1148 (24.9)		893 (18.7)		843 (17.4)

Based on a total of 6,072 individuals included in this study. Individuals were divided into two group based on whether they used alcohol, tobacco, or illicit drug in the past 12 months (yes vs. no). Weighted percentages were calculated for each variable and compared using the Rao-Scott Chi-square test for categorical variables. Abbreviation: n, number; wt%, weighted percentage; NHW, non-Hispanic White; NHB, non-Hispanic Black.

Students exhibiting antisocial behaviors demonstrated significantly higher substance use across all categories, with usage rates of 32.1% versus 17.5% for alcohol, 28.4% versus 12.5% for tobacco, and 27.4% versus 10.2% for illicit drugs (all p < .001). In contrast, religious involvement emerged as a protective factor against the use of all substances (Table 2).

To further determine the association between key variables (i.e., six specific domain categories) and the substance use outcomes (alcohol, tobacco, and illicit drug use), separate multivariable logistic regression analyses on each of the outcomes were conducted, controlling for sex, race and ethnicity, health insurance, poverty status, receipt of family assistance and grade. Antisocial behavior demonstrated a strong positive association with all substance use (alcohol AOR = 2.54 with 95% CI of 2.02–3.19, p < .001; tobacco AOR = 2.36, 95% CI 1.92–2.89, p < .001; and illicit drug AOR = 2.66, 95% CI 2.22–3.19, p < .001, Table 3). Conversely, religious involvement had a strong negative association with all substance use (alcohol AOR = 0.79, 95% CI 0.64–0.97, p = .026; tobacco AOR = 0.71, 95% CI 0.56–0.90, p = .006; and illicit drug AOR = 0.59, 95% CI 0.45–0.77, p < .001, Table 3). Among sociodemographic factors, females were more likely than males to use tobacco (AOR = 1.37, 95% CI = 1.07–1.73, p = .012, Table 3).

Table-3.

Factors Associated With Substance Use Among High School Adolescents National Survey of Drug Use and Health (NSDUH) 2022.

	Alcohol use		Tobacco use		Illicit drug use
	AOR [95% CI]	p-value	AOR [95% CI]	p-value	AOR [95% CI]	p-value
Adolescent-specific domains
School performance
Negative (Ref)
Positive	0.93 [0.30–2.86]	0.893	0.46 [0.14–1.46]	0.182	0.22 [0.09–0.55]	0.002
Antisocial behavior
No (Ref)
Yes	2.54 [2.02–3.19]	<0.001	2.36 [1.92–2.89]	<0.001	2.66 [2.22–3.19]	<0.001
Youth enrichment activity
No (Ref)
Yes	0.71 [0.57–0.89]	0.003	0.92 [0.72–1.19]	0.525	1.04 [0.80–1.36]	0.764
Religious involvement
Negative (Ref)
Positive	0.79 [0.64–0.97]	0.026	0.71 [0.56–0.90]	0.006	0.59 [0.45–0.77]	<0.001
Parent involvement
Negative (Ref)
Positive	0.47 [0.14–1.55]	0.211	0.63 [0.20–1.99]	0.422	0.55 [0.15–1.95]	0.343
Prevention education
Negative (Ref)
Positive	0.95 [0.64–1.42]	0.812	0.73 [0.51–1.04]	0.082	0.70 [0.47–1.04]	0.078
Sociodemographic factors
School grade
9^th grade (Ref)
10^th grade	1.48 [1.07–2.05]	0.019	1.24 [0.92–1.67]	0.152	1.59 [1.12–2.27]	0.011
11^th grade	3.27 [2.35–4.55]	<0.001	1.59 [1.15–2.21]	0.006	2.32 [1.58–3.41]	<0.001
12^th grade	4.21 [2.99–5.94]	<0.001	2.07 [1.51–2.84]	<0.001	2.99 [2.11–4.22]	<0.001
Sex
Male (Ref)
Female	1.25 [0.99–1.56]	0.058	1.37 [1.07–1.73]	0.012	1.16 [0.92–1.45]	0.195
Race and ethnicity
NHW (Ref)
NHB	0.57 [0.41–0.79]	0.001	0.98 [0.73–1.32]	0.914	1.20 [0.88–1.63]	0.235
Hispanic	1.00 [0.76–1.33]	0.983	0.93 [0.70–1.22]	0.579	0.99 [0.77–1.26]	0.915
Others	0.57 [0.35–0.91]	0.021	0.77 [0.48–1.24]	0.277	0.82 [0.52–1.30]	0.394
English (Ref)
Poor/Not at all
Very well/Well	1.22 [0.37–3.99]	0.739	0.76 [0.29–2.01]	0.570	2.55 [0.46–14.27]	0.280
Health insurance
No (Ref)
Yes	0.90 [0.47–1.73]	0.752	0.69 [0.38–1.25]	0.215	1.17 [0.52–2.65]	0.702
Household poverty level
Poor (Ref)
Near poor	1.02 [0.68–1.53]	0.910	0.94 [0.66–1.33]	0.709	1.01 [0.64–1.57]	0.974
Above near poor	1.43 [0.99–2.05]	0.056	0.88 [0.58–1.33]	0.522	1.00 [0.64–1.56]	0.995
Family assistance received
No (Ref)
Yes	0.89 [0.65–1.24]	0.490	1.18 [0.83–1.69]	0.344	1.09 [0.79–1.49]	0.594

Based on a total of 5,593 individuals included in this study after the exclusion of individuals with missing information. The association between six adolescent-specific domain categories and substance outcomes (alcohol, tobacco, or illicit drug uses in the past 12 months (yes vs. no) were determined by multivariable logistic regression. Abbreviation: AOR, adjusted odds ratios; CI, confidence interval; NHW, non-Hispanic White; NHB, non-Hispanic Black; SDOH, social determinants of health.

Discussion

This study found that the prevalence of substance uses among high school adolescents ranged from 18.0% to 23.5%, with alcohol being the most used substance. Two common factors, antisocial behavior and religious involvement, were identified as influencing substance use, including alcohol, tobacco, and illicit drugs. Specifically, antisocial behavior was a risk factor, as it was positively associated with substance use, while religious involvement was negatively associated. Identifying these factors can aid teachers, parents, and policymakers in implementing effective interventions to reduce substance use among high school adolescents. Reducing substance use is essential to prevent substance-related negative outcomes, minimize mental health disorders, and avoid the development of addictive behaviors, especially during adolescence. Our study focused on high school adolescents, a vulnerable population, and provides a comprehensive analysis of factors influencing substance use, contributing valuable insights that can guide future interventions.

Substance use trends in adolescents can sometimes predict future patterns in adults, as behaviors established in adolescence often continue into adulthood (Whyte et al., 2018). According to the 2022 SAMHSA report, nearly 50% of individuals aged 12 and older reported alcohol use in the past month, approximately 25% reported tobacco use, and 16% reported illicit drug use (Administration), 2023). The prevalence of substance uses among adolescents, 20–30% for alcohol, 10–15% for tobacco and marijuana, remains lower than that among adults (Administration), 2023; Volkow et al., 2021). Our findings align with these reports, with the lower prevalence among adolescents possibly reflecting the continuation of substance use patterns established in adolescence. This trend is further supported by the increasing prevalence of substance use as grade levels rise among high school students (Table 2).

Students exhibiting antisocial behavior were positively associated with substance use, which aligns with previous studies showing this association in adolescents using illicit drugs (Brennan et al., 2017; Trucco, 2020). Our study expands this association to include all types of substance use, including alcohol and tobacco. These findings emphasize the need for early intervention and appropriate support to guide adolescents toward healthier behaviors. Conversely, religious involvement served as protective factors against substance use (Fairclough et al., 2024). Many religions explicitly discourage substance use, viewing it as harmful to spiritual well-being (Grim & Grim, 2019). Adolescents who actively engage in religious communities may benefit from peer influence and strong social support, leading to lower substance use rates (Peviani et al., 2020).

Other factors associated with substance use in this study were also identified. Generally, males are more likely to engage in substance use than females (Rehm & Shield, 2019). However, recent trends suggest that this gap is narrowing, a shift observed among high school girls as well (McHugh et al., 2018). In our study, female adolescents were more likely to use substances than their male counterparts. One possible explanation is that adolescent girls may experience higher levels of stress, anxiety, and depression compared to boys, which can increase the likelihood of substance use (Esmaeelzadeh et al., 2018; Morken et al., 2023). Studies suggest that females may develop substance dependence more quickly than males, contributing to higher rates of use (Becker et al., 2017; Bobzean et al., 2014). Additionally, NHW adolescents had higher rates of alcohol use compared to other racial and ethnic groups, possibly influenced by parental attitudes. Research suggests that cultural norms and beliefs among NHWs may be more permissive regarding alcohol use, contributing to a higher rate of alcohol use (Sudhinaraset et al., 2016). Understanding these cultural and community differences is essential for designing targeted prevention and intervention strategies.

This study has several strengths. First, it focused on high school adolescents, a vulnerable population, providing a comprehensive analysis of their substance use, an area that is less frequently studied in literature. Second, it utilized a nationally representative dataset to examine substance use among high school adolescents, yielding results that align with other studies, further confirming the high prevalence of substance use in this population. Third, the study identified substance use trends from freshman to senior years, revealing a pattern that suggests potential substance dependency development during adolescence, highlighting the need for early interventions. Lastly, by identifying two key factors influencing adolescent substance use, the study can help guide the implementation of more effective strategies.

The study also has limitations. While we conducted a comprehensive analysis of the factors associated with substance use, including six specific domains, other potential influencing factors may not have been included, which could affect the study’s findings. Additionally, we categorized substances into three broad groups without identifying the specific substances used, which limits our ability to analyze individual product use or determine factors associated with each product. This study was limited to analyzing the prevalence of substance use and did not examine the impact or magnitude of its effects on adolescent populations.

Our findings suggest that different socio-economic factors, such as sex, race, ethnicity, and household poverty level, may influence substance use. Thus, future studies should include analyses that consider cultural and community-level factors or conduct sub-cohort analyses to further explore factors associated with substance use among high school adolescents.

Conclusion

One in three high school students reported alcohol, tobacco or illicit drug use. Alcohol was the most used. Antisocial behavior by students was a risk factor for substance use across all categories, while religious involvement served as a protective factor against substance use. These findings highlight the need for early and effective interventions to reduce substance use among high school adolescents.

Supplemental Material

Supplemental Material - Adolescent-specific risk and protective factors of substance use among high school students in the United States: A cross-sectional study

Supplemental Material for Adolescent-specific risk and protective factors of substance use among high school students in the United States: A cross-sectional study by Richard C. Wang, Daniel I. Lipin, Thomas K. Swoboda, and Usha Sambamoorthi in Clinical Child Psychology and Psychiatry.

Footnotes

Author contributions

RCW: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing-original draft, and Writing-review & editing. DIL: Conceptualization, Methodology, Supervisions, Validation, and Writing-review & editing. TKS: Data curation, Investigation, Supervisions, Validation, and Writing-review & editing. US: Conceptualization, Formal analysis, Methodology, Supervisions, Validation, and Writing-review & editing. All authors critically reviewed and revised the manuscript and approved the final manuscript as submitted.

Declaration of conflicting interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Usha Sambamoorthi received funding supported by the National Institute on Minority Health and Health Disparities through the Texas Center for Health Disparities (NIMHD) 5S21MD012472-05, and the National Institute of Health/Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity Grant # 1OT2OD032581-01. Role of Funders: The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding organizations. The funding organizations had no role in the design, preparation, review, or approval of this paper.

Ethical statement

ORCID iD

Richard C Wang

Data Availability Statement

Data is publicly available at website: .

Supplemental Material

Supplemental material for this article is available online.

Author biographies

Richard Wang is an 11th grade high school student at St. Mark's School of Texas, who has published three papers in the field of health care under the guidance of Drs. Daniel Lipin, Thomas Swoboda, and Usha Sambamoorthi.

Daniel Lipin is a biology teacher and research advisor at St. Mark's School of Texas.

Thomas Swoboda is a full professor and associate Dean for Clinical Education at Roseman University, College of Medicine, who has published many papers in the field of medicine and public health.

Usha Sambamoorthi is a full professor, Associate Dean of College of Pharmacy at University of North Texas Health Science Center, who has published nearly 300 papers in the field of health care.

References

Bava

Tapert

S. F.

(2010). Adolescent brain development and the risk for alcohol and other drug problems. Neuropsychology Review, 20(4), 398–413. https://doi.org/10.1007/s11065-010-9146-6

Becker

J. B.

McClellan

M. L.

Reed

B. G.

(2017). Sex differences, gender and addiction. Journal of Neuroscience Research, 95(1–2), 136–147. https://doi.org/10.1002/jnr.23963

Bobzean

S. A.

DeNobrega

A. K.

Perrotti

L. I.

(2014). Sex differences in the neurobiology of drug addiction. Experimental Neurology, 259, 64–74. https://doi.org/10.1016/j.expneurol.2014.01.022

Bozzini

A. B.

Bauer

Maruyama

Simoes

Matijasevich

(2021). Factors associated with risk behaviors in adolescence: A systematic review. Revista Brasileira de Psiquiatria, 43(2), 210–221. https://doi.org/10.1590/1516-4446-2019-0835

Brennan

G. M.

Hyde

L. W.

Baskin-Sommers

A. R.

(2017). Antisocial pathways associated with substance use disorders: Characterizing etiological underpinnings and implications for treatment. Current Opinion in Behavioral Sciences, 13, 124–129. https://doi.org/10.1016/j.cobeha.2016.11.014

Chermack

S. T.

Grogan-Kaylor

Perron

B. E.

Murray

R. L.

De Chavez

Walton

M. A.

(2010). Violence among men and women in substance use disorder treatment: A multi-level event-based analysis. Drug and Alcohol Dependence, 112(3), 194–200. https://doi.org/10.1016/j.drugalcdep.2010.06.005

Esmaeelzadeh

Moraros

Thorpe

Bird

(2018). The association between depression, anxiety and substance use among Canadian post-secondary students. Neuropsychiatric Disease and Treatment, 14, 3241–3251. https://doi.org/10.2147/NDT.S187419

Fairclough

Abd-Elmonem

Merrin

G. J.

Hong

J. S.

Voisin

D. R.

(2024). Religiosity and associations with substance use and delinquency among urban African American adolescents. Journal of Religion and Health, 63(1), 531–550. https://doi.org/10.1007/s10943-023-01916-2

Gebeyehu

E. T.

Srahbzu Biresaw

(2021). Alcohol use and its associated factors among adolescents aged 15-19 Years at governmental high schools of Aksum Town, Tigray, Ethiopia, 2019: A cross-sectional study. Journal of addiction, 2021, Article 5518946. https://doi.org/10.1155/2021/5518946

10.

Grim

B. J.

Grim

M. E.

(2019). Belief, behavior, and belonging: How faith is indispensable in preventing and recovering from substance abuse. Journal of Religion and Health, 58(5), 1713–1750. https://doi.org/10.1007/s10943-019-00876-w

11.

Kulis

S. S.

Garcia-Perez

Marsiglia

F. F.

Ayers

S. L.

(2021). Testing a culturally adapted youth substance use prevention program in a Mexican border city: Mantente REAL. Substance Use & Misuse, 56(2), 245–257. https://doi.org/10.1080/10826084.2020.1858103

12.

Lander

Howsare

Byrne

(2013). The impact of substance use disorders on families and children: From theory to practice. Social Work in Public Health, 28(3–4), 194–205. https://doi.org/10.1080/19371918.2013.759005

13.

T. T. T.

(2023). Key risk factors associated with electronic nicotine delivery systems use among adolescents. JAMA Network Open, 6(10), Article e2337101. https://doi.org/10.1001/jamanetworkopen.2023.37101

14.

McHugh

R. K.

Votaw

V. R.

Sugarman

D. E.

Greenfield

S. F.

(2018). Sex and gender differences in substance use disorders. Clinical Psychology Review, 66, 12–23. https://doi.org/10.1016/j.cpr.2017.10.012

15.

Medina

K. L.

Schweinsburg

A. D.

Cohen-Zion

Nagel

B. J.

Tapert

S. F.

(2007). Effects of alcohol and combined marijuana and alcohol use during adolescence on hippocampal volume and asymmetry. Neurotoxicology and Teratology, 29(1), 141–152. https://doi.org/10.1016/j.ntt.2006.10.010

16.

Morken

I. S.

Viddal

K. R.

von Soest

Wichstrom

(2023). Explaining the female preponderance in adolescent depression-A four-wave cohort study. Research on child and adolescent psychopathology, 51(6), 859–869. https://doi.org/10.1007/s10802-023-01031-6

17.

Nawi

A. M.

Ismail

Ibrahim

Hassan

M. R.

Manaf

M. R. A.

Amit

Ibrahim

Shafurdin

N. S.

(2021). Risk and protective factors of drug abuse among adolescents: A systematic review. BMC Public Health, 21(1), 2088. https://doi.org/10.1186/s12889-021-11906-2

18.

NCDAS . (2023). National center for drug abuse statistics. Drug Abuse Statistics. Vol. 2024.

19.

Peviani

K. M.

Brieant

Holmes

C. J.

King-Casas

Kim-Spoon

(2020). Religious social support protects against social risks for adolescent substance use. Journal of Research on Adolescence: The Official Journal of the Society for Research on Adolescence, 30(2), 361–371. https://doi.org/10.1111/jora.12529

20.

Rehm

Shield

K. D.

(2019). Global burden of disease and the impact of mental and addictive disorders. Current Psychiatry Reports, 21(2), 10. https://doi.org/10.1007/s11920-019-0997-0

21.

Squeglia

L. M.

Gray

K. M.

(2016). Alcohol and drug use and the developing brain. Current Psychiatry Reports, 18(5), 46. https://doi.org/10.1007/s11920-016-0689-y

22.

Squeglia

L. M.

Jacobus

Tapert

S. F.

(2009). The influence of substance use on adolescent brain development. Clinical EEG and Neuroscience, 40(1), 31–38. https://doi.org/10.1177/155005940904000110

23.

Substance Abuse and Mental Health Services Administration (2023). Key substance use and mental health indicators in the United States: Results from the 2022 national survey on drug use and health. Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration. Vol. 2024.

24.

Sudhinaraset

Wigglesworth

Takeuchi

D. T.

(2016). Social and cultural contexts of alcohol use: Influences in a social-ecological framework. Alcohol Research: Current Reviews, 38(1), 35–45.

25.

Trucco

E. M.

(2020). A review of psychosocial factors linked to adolescent substance use. Pharmacology, Biochemistry and Behavior, 196, Article 172969. https://doi.org/10.1016/j.pbb.2020.172969

26.

Volkow

N. D.

Han

Einstein

E. B.

Compton

W. M.

(2021). Prevalence of substance use disorders by time since first substance use among young people in the US. JAMA Pediatrics, 175(6), 640–643. https://doi.org/10.1001/jamapediatrics.2020.6981

27.

Von

E. E.

Altman

D. G.

Egger

Pocock

S. J.

Gotzsche

P. C.

Vandenbroucke

J. P.

(2007). The strengthening the reporting of observational studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. Annals of Internal Medicine, 147(8), 573–577.

28.

Whyte

A. J.

Torregrossa

M. M.

Barker

J. M.

Gourley

S. L.

(2018). Editorial: Long-Term consequences of adolescent drug use: Evidence from pre-clinical and clinical models. Frontiers in Behavioral Neuroscience, 12, 83. https://doi.org/10.3389/fnbeh.2018.00083

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