Cumulative Adverse Childhood Experiences and Frequency of Substance Use Among US High School Students
The Pennsylvania State University - University Park Campus, College of Nursing, University Park, PA, USA
Abstract
Adverse childhood experiences (ACEs) can have lasting effects into adulthood. This study examines the relationship between ACEs and the frequency of substance use among high school students in the United States. Data were drawn from the 2023 Youth Risk Behavior Survey, a nationally representative survey of high school students. A cumulative ACE score was calculated based on 8 self-reported lifetime experiences. Multinomial logistic regression models were used to analyze the association between cumulative ACEs and substance use (alcohol, binge drinking, cannabis, and e-cigarettes). A significant positive association was found between cumulative ACEs and substance use. Higher ACE scores were associated with greater odds of substance use across all categories. Specifically, cumulative ACEs were associated with more frequent alcohol use (OR = 1.89, 95% CI = 1.48, 2.43), binge drinking (OR = 1.69, 95% CI = 1.40, 2.05), cannabis use (OR = 1.81, 95% CI = 1.65, 1.99), and e-cigarette use (OR = 1.89, 95% CI = 1.78, 2.00). Similar results were observed for occasional alcohol use (OR = 1.47, 95% CI = 1.31–1.66), binge drinking (OR = 1.53, 95% CI = 1.36–1.72), cannabis use (OR = 1.26, 95% CI = 1.01–1.57), and e-cigarette use (OR = 1.60, 95% CI = 1.32–1.94). This study highlights the significant associations between ACEs and substance use behaviors among adolescents. Addressing ACEs through comprehensive strategies, such as fostering supportive relationships, may be beneficial and promote healthier development.
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Keywords: adverse childhood experience, early adverse experiences, adolescent, risk factors, substance use
Article notes
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Received 2025 Mar 26; Revised 2025 May 8; Accepted 2025 May 12; Collection date 2025 Jan-Dec.
Introduction
Addressing substance use among teens remains a public health priority. 1 In 2023, nearly half of U.S. twelfth-grade students reported consuming alcohol in the past year, and almost a quarter reported past-month consumption. 1 One in 10 reported drinking 5 or more alcoholic drinks in a row in the last 2 weeks, and 2.2% reported drinking 10 or more drinks in a row. 1 Heavy alcohol use in late adolescence may persist into adulthood and is associated with poor functioning, diminished work capacity, alcohol dependence, and premature death.2,3 An estimated 10.3% of tenth-grade students and 18.4% of twelfth-grade students reported past-month cannabis use in 2023. 1 Cannabis use poses risks such as impaired cognition and driving, impaired respiratory functioning, and the potential development of schizophrenia. 4 Sustained cannabis use can also lead to cannabis use disorder, with an increased risk among heavier users.5,6 Past-month and daily rates of e-cigarette use were 11.9% and 2.4% among tenth graders, and 16.9% and 5.8% among twelfth graders in the U.S. in 2023, respectively. 1 E-cigarettes are among the most used tobacco products among middle and high school students in the U.S. 7 Research has shown that inhaling harmful constituents by using e-cigarettes poses respiratory risks, and that consuming nicotine is addictive and particularly harmful to young people.8 -11
Adverse childhood experiences (ACEs) are traumatic events that occur before 18 years of age and can profoundly impact lifetime health outcomes.12 -15 ACEs involve emotional, physical, or sexual abuse, emotional or physical neglect, and challenges within the household, such as parental separation or divorce, criminal behavior, and witnessing parental violence, mental illness, or substance abuse. 16 In 2023, approximately 3 in 4 high school students reported experiencing one or more ACEs, and 1 in 5 reported experiencing 4 or more ACEs. 17 Specifically, 61.5% of students reported emotional abuse, 31.8% reported experiencing physical abuse, and 18.6% reported witnessing intimate partner violence in the household. 17 ACE exposure increases the likelihood of interpersonal violence perpetration in adolescence, such as bullying, physical fighting, dating violence, and more violent behavior in adulthood.18,19
Research has shown that ACEs are associated with adverse health outcomes across the life course.20 -22 The effects of ACEs can extend beyond the immediate circumstances of those experiences, leading to long-term negative consequences. While studies have documented the relationship between ACEs and substance use, there remains a scarcity of research exploring ACEs and their association with the frequency of substance use. This study adds to the existing literature by examining the associations between ACEs and the frequency of substance use among adolescents. By drawing on nationally representative data, this research provides nuanced insights into how different types and frequencies of substance use (alcohol, binge drinking, cannabis, and e-cigarettes) are related to ACEs. Additionally, the study contributes to the broader understanding of how childhood trauma can influence health behaviors and outcomes, with implications for strategies to promote healthier developmental trajectories for adolescents.
Methods
Data
This study used data from the 2023 Youth Risk Behavior Survey (YRBS), a national survey conducted by the Centers for Disease Control and Prevention (CDC). The YRBS provides comprehensive, nationally representative data on high school students (grades 9–12) attending public, Catholic, and private schools across the United States. The survey gathers information on students’ demographics, health behaviors, substance use, and related experiences. To ensure the representativeness of the national high school population, the YRBS employs a 3-stage cluster sampling design. Schools were selected systematically with a probability proportional to their enrollment in grades 9 to 12, starting from a random point. Within each selected school, all classes in a specific required subject or those meeting at a particular time of day formed the sampling frame. From this frame, classes were randomly selected using systematic equal probability sampling. To account for nonresponse and maintain representativeness, weighting was applied to each student’s data.
Measures
Dependent Variables
This study examined 4 dependent variables: alcohol use, binge drinking, cannabis use, and e-cigarette use. Alcohol Use: Alcohol use was assessed with the survey question: “During the past 30 days, on how many days did you have at least one drink of alcohol?” Response options included 0 days, 1 or 2 days, 3 to 5 days, 6 to 9 days, 10 to 19 days, 20 to 29 days, and all 30 days. These responses were grouped into 4 categories: none (0 days), rarely (1-5 days), sometimes (6-19 days), and often (20+ days). Binge Drinking: Binge drinking was determined using the question: “During the past 30 days, on how many days did you have 4 or more drinks of alcohol in a row, within a couple of hours (if female), or 5 or more drinks in a row, within a couple of hours (if male)?” Response options were 0 days, 1 day, 2 days, 3 to 5 days, 6 to 9 days, 10 to 19 days, and 20 or more days. These were categorized as none (0 days), rarely (1-2 days), sometimes (3-5 days), and often (6+ days). Cannabis Use: Cannabis use was assessed with the question: “During the past 30 days, how many times did you use marijuana?” Response options included 0 times, 1 or 2 times, 3 to 9 times, 10 to 19 times, 20 to 39 times, and 40 or more times. Responses were categorized as none (0 times), rarely (1 or 2 times), sometimes (3-19 times), and often (20+ times). E-cigarette Use: E-cigarette use was measured with the survey question: “During the past 30 days, how many days did you use an electronic vapor product?” The response options were identical to those for alcohol use and were categorized in the same way: none (0 days), rarely (1-5 days), sometimes (6-19 days), and often (20+ days). While we used the same derived descriptors for each substance for ease of reference, each category (i.e., “none,” “rarely,” “sometimes,” and “often”) differs for binge drinking and cannabis use due to cell size and available response options.
Independent Variables
The primary independent variable in this study was the cumulative count of adverse childhood experiences. These counts were derived from 8 self-reported lifetime experiences, which align with the original ACEs included in the CDC-Kaiser Permanente ACEs study. 12 Table 1 presents details on the questions and their operationalization in this study. Additionally, grade level (9th-12th), self-reported sex (male/female), sexual identity (heterosexual, gay or lesbian, bisexual, and other), and race/ethnicity (non-Hispanic white, non-Hispanic Black, non-Hispanic other, and Hispanic) were included as confounders. The “other” sexual identity category included students who reported “I describe my sexual identity in some other way” or “I am not sure about my sexual identity (questioning).” The non-Hispanic other category included students identifying as non-Hispanic Asian, non-Hispanic American Indian or Alaska Native, non-Hispanic Native Hawaiian or Other Pacific Islander, and those reporting multiple non-Hispanic races.
| Variable | Question | Response options | Analytic coding |
|---|---|---|---|
| Emotional abuse | During your life, how often has a parent or other adult in your home insulted you or put you down? | Never, rarely, sometimes, most of the time, or always | Yes (rarely, sometimes, most of the time, or always) vs. No (never) |
| Physical abuse | During your life, how often has a parent or other adult in your home hit, beat, kicked, or physically hurt you in any way? | Never, rarely, sometimes, most of the time, or always | Yes (rarely, sometimes, most of the time, or always) vs. No (never) |
| Sexual abuse | Has an adult or person at least 5 years older than you ever made you do sexual things that you did not want to do? | Yes or no | Yes vs. No |
| Physical neglect | During your life, how often has there been an adult in your household who tried hard to make sure your basic needs were met, such as looking after your safety and making sure you had clean clothes and enough to eat? | Never, rarely, sometimes, most of the time, or always | Yes (rarely, sometimes, most of the time, or always) vs. No (never) |
| Witnessed intimate partner violence | During your life, how often have your parents or other adults in your home slapped, hit, kicked, punched, or beat each other up? | Never, rarely, sometimes, most of the time, or always | Yes (rarely, sometimes, most of the time, or always) vs. No (never) |
| Household substance use | Have you ever lived with a parent or guardian who was having a problem with alcohol or drug use? | Yes or no | Yes vs. No |
| Household poor mental health | Have you ever lived with a parent or guardian who had severe depression, anxiety, or another mental illness, or was suicidal? | Yes or no | Yes vs. No |
| Parent or guardian incarcerated or detained | Have you ever been separated from a parent or guardian because they went to jail, prison, or a detention center? | Yes or no | Yes vs. No |
Statistical Analyses
Descriptive statistics were calculated for the 2023 YRBS data to provide an overview of the high school student study population. In addition to descriptive analyses, separate multinomial logistic regression models were used to examine the associations between the primary independent variable, cumulative ACEs, and the dependent variables: alcohol use, binge drinking, cannabis use, and e-cigarette use. All models were adjusted for grade level, self-reported sex, sexual identity, and race/ethnicity. To account for the complex survey design of the YRBS, the analyses incorporated sampling weights, survey strata, and cluster adjustments. All statistical analyses were performed using R software.
Results
Table 2 provides an overview of the weighted characteristics of the 2023 YRBS study sample. The mean cumulative ACE count was 1.76 (SD = 1.24), indicating that students, on average, reported nearly two adverse experiences during their lifetime. The sample distribution across grade levels was as follows: 25.49% in 9th grade, 26.13% in 10th grade, 23.71% in 11th grade, and 24.66% in 12th grade. Regarding self-reported sex, 51.66% identified as male and 48.34% as female. In terms of sexual identity, most students (75.31%) identified as heterosexual, while 3.81% identified as gay or lesbian, 12.02% as bisexual, and 8.86% fell into the “other” category. The race/ethnicity composition of the sample was 46.84% identifying as non-Hispanic White, 15.40% as non-Hispanic Black, 10.52% as non-Hispanic Other, and 27.24% as Hispanic. Substance use behaviors varied across the sample. For alcohol use, 78.10% of students reported no use in the past 30 days, while 17.96% were rare users, 3.35% were occasional users, and 0.58% were frequent users. Binge drinking was not commonly reported, with 91.44% of students indicating no binge drinking in the past 30 days; 5.09% were rare binge drinkers, 2.03% occasional, and 1.44% frequent. Cannabis use was also uncommon, with 82.71% reporting no use, 6.49% rare use, 6.18% occasional use, and 4.62% frequent use. E-cigarette use followed a similar pattern, with 83.24% reporting no use, 6.98% rare use, 3.51% occasional use, and 6.27% frequent use.
| Variables | Sample a (n = 12 340) |
|---|---|
| Cumulative adverse childhood experiences | 1.76 (1.24) |
| Grade levels | |
| 9th | 25.49 (23.76, 27.23) |
| 10th | 26.13 (24.51, 27.76) |
| 11th | 23.71 (21.84, 25.58) |
| 12th | 24.66 (22.37, 26.96) |
| Self-reported sex | |
| Male | 51.66 (49.02, 54.29) |
| Female | 48.34 (45.71, 50.98) |
| Sexual identity | |
| Heterosexual | 75.31 (72.85, 77.78) |
| Gay or lesbian | 3.81 (3.30, 4.32) |
| Bisexual | 12.02 (10.58, 13.45) |
| Other | 8.86 (7.83, 9.89) |
| Race/ethnicity | |
| Non-Hispanic white | 46.84 (41.19, 52.49) |
| Non-Hispanic black | 15.40 (9.91, 20.90) |
| Non-Hispanic other | 10.52 (8.41, 12.63) |
| Hispanic | 27.24 (21.79, 32.69) |
| Alcohol use | |
| None (0 days) | 78.10 (76.23, 79.97) |
| Rarely (between 1 and 5 days) | 17.96 (16.57, 19.36) |
| Sometimes (between 5 and 19 days) | 3.35 (2.54, 4.17) |
| Often (at least 20 days) | 0.58 (0.41, 0.76) |
| Binge drinking | |
| None (0 days) | 91.44 (90.00, 92.89) |
| Rarely (1 or 2 days) | 5.09 (4.33, 5.84) |
| Sometimes (between 3 and 5 days) | 2.03 (1.53, 2.54) |
| Often (at least 6 days) | 1.44 (0.93, 1.94) |
| Cannabis use | |
| None (0 times) | 82.71 (81.13, 84.28) |
| Rarely (1 or 2 times) | 6.49 (5.72, 7.25) |
| Sometimes (between 3 and 19 times) | 6.18 (5.37, 6.99) |
| Often (at least 20 times) | 4.62 (3.80, 5.44) |
| E-cigarette use | |
| None (0 days) | 83.24 (81.67, 84.81) |
| Rarely (between 1 and 5 days) | 6.98 (6.17, 7.79) |
| Sometimes (between 5 and 19 days) | 3.51 (2.78, 4.23) |
| Often (at least 20 days) | 6.27 (5.18, 7.36) |
Table 3 presents the odds ratios (ORs) and 95% confidence intervals (CIs) from a multinomial logistic regression model examining the relationship between cumulative ACEs and alcohol use levels compared to the non-use category (reference group). The results demonstrate a significant positive association between cumulative ACEs and all levels of alcohol use, indicating that higher ACE counts are associated with greater odds of heavier alcohol use. Specifically, cumulative ACEs were significantly associated with the odds of rare alcohol use (OR = 1.33, 95% CI = 1.26–1.40), occasional alcohol use (OR = 1.47, 95% CI = 1.31–1.66), and frequent alcohol use (OR = 1.89, 95% CI = 1.48–2.43) compared to non-use.
| Alcohol use | |||
|---|---|---|---|
| Rarely b vs None a | Sometimes c vs None a | Often d vs None a | |
| Variables | OR (95% CI) | OR (95% CI) | OR (95% CI) |
| Cumulative adverse childhood experiences | 1.33 (1.26, 1.40) | 1.47 (1.31, 1.66) | 1.89 (1.48, 2.43) |
| Grade levels | |||
| 9th | Reference | Reference | Reference |
| 10th | 1.48 (1.15, 1.91) | 1.37 (0.86, 2.18) | 1.33 (0.44, 4.00) |
| 11th | 1.79 (1.42, 2.26) | 2.05 (1.22, 3.45) | 2.45 (0.90, 6.69) |
| 12th | 2.77 (2.17, 3.52) | 4.03 (2.37, 6.87) | 1.51 (0.58, 3.93) |
| Self-reported sex | |||
| Male | Reference | Reference | Reference |
| Female | 1.23 (1.03, 1.48) | 1.08 (0.71, 1.67) | 0.39 (0.17, 0.90) |
| Sexual identity | |||
| Heterosexual | Reference | Reference | Reference |
| Gay or lesbian | 1.07 (0.73, 1.56) | 0.96 (0.46, 2.03) | 1.60 (0.45, 5.70) |
| Bisexual | 0.91 (0.68, 1.21) | 0.93 (0.66, 1.30) | 2.41 (1.05, 5.53) |
| Other | 0.79 (0.63, 0.98) | 0.56 (0.34, 0.90) | 1.54 (0.34, 7.04) |
| Race/ethnicity | |||
| Non-Hispanic white | Reference | Reference | Reference |
| Non-Hispanic black | 0.59 (0.44, 0.79) | 0.36 (0.21, 0.62) | 1.47 (0.47, 4.63) |
| Non-Hispanic other | 0.66 (0.52, 0.84) | 0.50 (0.31, 0.82) | 1.34 (0.55, 3.29) |
| Hispanic | 0.76 (0.61, 0.96) | 0.42 (0.25, 0.71) | 1.19 (0.65, 2.20) |
In terms of demographics, grade level was also significantly associated with alcohol use, with older students showing higher odds of use. Compared to 9th graders, 12th graders had the highest odds of rare (OR = 2.77, 95% CI = 2.17–3.52) and occasional (OR = 4.03, 95% CI = 2.37–6.87) alcohol use relative to non-users. Compared to males, females had 23% higher odds of rare alcohol use (OR = 1.23, 95% CI = 1.03–1.48) relative to non-users. However, females had significantly lower odds of frequent alcohol use (OR = 0.39, 95% CI = 0.17–0.90). Bisexual individuals had significantly higher odds of frequent alcohol use compared to heterosexuals (OR = 2.41, 95% CI = 1.05–5.53). Compared to non-Hispanic white students, non-Hispanic Black, non-Hispanic other, and Hispanic students had significantly lower odds of both rare and occasional alcohol use relative to non-use.
Table 4 reports on the relationship between cumulative ACEs and binge drinking days. The analysis reveals that each additional ACE was significantly associated with more binge drinking days (rare, OR = 1.35, 95% CI = 1.23–1.48; occasional, OR = 1.53, 95% CI = 1.36–1.72; often, OR = 1.69, 95% CI = 1.40–2.05). Older students, particularly those in 12th grade, had markedly higher odds of binge drinking across all binge drinking days measures compared to 9th graders. Females were more likely than males to have rare binge drinking (OR = 1.46, 95% CI = 1.08–1.97). Additionally, non-Hispanic Black students had significantly lower odds of binge drinking at all levels compared to non-Hispanic white students.
| Binge drinking | |||
|---|---|---|---|
| Rarely b vs None a | Sometimes c vs None a | Often d vs None a | |
| Variables | OR (95% CI) | OR (95% CI) | OR (95% CI) |
| Cumulative adverse childhood experiences | 1.35 (1.23, 1.48) | 1.53 (1.36, 1.72) | 1.69 (1.40, 2.05) |
| Grade levels | |||
| 9th | Reference | Reference | Reference |
| 10th | 1.84 (1.13, 3.02) | 2.07 (1.05, 4.06) | 1.40 (0.60, 3.30) |
| 11th | 2.80 (2.05, 3.83) | 3.58 (2.04, 6.30) | 3.72 (1.67, 8.27) |
| 12th | 3.93 (2.70, 5.73) | 6.84 (4.17, 11.24) | 6.20 (3.09, 12.44) |
| Self-reported sex | |||
| Male | Reference | Reference | Reference |
| Female | 1.46 (1.08, 1.97) | 1.27 (0.83, 1.93) | 0.63 (0.37, 1.06) |
| Sexual identity | |||
| Heterosexual | Reference | Reference | Reference |
| Gay or lesbian | 0.57 (0.29, 1.12) | 0.83 (0.35, 2.00) | 0.52 (0.14, 1.93) |
| Bisexual | 0.79 (0.52, 1.20) | 0.39 (0.21, 0.72) | 1.05 (0.55, 1.98) |
| Other | 0.81 (0.52, 1.25) | 0.45 (0.20, 1.02) | 0.70 (0.24, 2.00) |
| Race/ethnicity | |||
| Non-Hispanic white | Reference | Reference | Reference |
| Non-Hispanic black | 0.42 (0.24, 0.73) | 0.14 (0.04, 0.58) | 0.33 (0.14, 0.81) |
| Non-Hispanic other | 0.76 (0.52, 1.10) | 0.44 (0.23, 0.81) | 0.39 (0.18, 0.81) |
| Hispanic | 0.76 (0.56, 1.02) | 0.36 (0.21, 0.61) | 0.38 (0.17, 0.83) |
In Table 5, the analysis of cumulative ACEs and cannabis use frequency reveals a significant association, with ACE associated with higher odds of cannabis use (rare, OR = 1.30, 95% CI = 1.10–1.55; occasional, OR = 1.60, 95% CI = 1.46–1.76; often, OR = 1.81, 95% CI = 1.65–1.99). Higher grade levels were equally associated with more cannabis use, particularly among 12th graders compared to 9th graders. Gender differences were observed, with females showing higher odds of occasional use (OR = 1.26, 95% CI = 1.01–1.57) but lower odds of frequent use (OR = 0.60, 95% CI = 0.45–0.80) compared to males. Additionally, bisexual students had higher odds of cannabis use across all frequencies, while gay or lesbian students had elevated odds of rare use compared to heterosexual peers.
| Cannabis use | |||
|---|---|---|---|
| Rare b vs None a | Sometimes c vs None a | Often d vs None a | |
| Variables | OR (95% CI) | OR (95% CI) | OR (95% CI) |
| Cumulative adverse childhood experiences | 1.30 (1.10, 1.55) | 1.60 (1.46, 1.76) | 1.81 (1.65, 1.99) |
| Grade levels | |||
| 9th | Reference | Reference | Reference |
| 10th | 1.23 (0.74, 2.04) | 1.35 (1.03, 1.78) | 1.74 (1.16, 2.61) |
| 11th | 1.75 (1.08, 2.84) | 1.68 (1.27, 2.23) | 2.71 (1.79, 4.09) |
| 12th | 2.70 (1.62, 4.49) | 2.87 (1.98, 4.17) | 3.32 (2.23, 4.95) |
| Self-reported sex | |||
| Male | Reference | Reference | Reference |
| Female | 1.01 (0.76, 1.34) | 1.26 (1.01, 1.57) | 0.60 (0.45, 0.80) |
| Sexual identity | |||
| Heterosexual | Reference | Reference | Reference |
| Gay or lesbian | 1.89 (1.10, 3.26) | 0.73 (0.45, 1.19) | 1.54 (0.80, 2.96) |
| Bisexual | 1.84 (1.42, 2.40) | 1.43 (1.06, 1.91) | 1.47 (1.07, 2.01) |
| Other | 1.47 (1.03, 2.09) | 0.85 (0.64, 1.12) | 1.14 (0.73, 1.79) |
| Race/ethnicity | |||
| Non-Hispanic white | Reference | Reference | Reference |
| Non-Hispanic black | 1.06 (0.73, 1.55) | 1.15 (0.76, 1.73) | 1.05 (0.77, 1.43) |
| Non-Hispanic other | 0.89 (0.62, 1.29) | 0.90 (0.61, 1.35) | 0.87 (0.61, 1.24) |
| Hispanic | 1.02 (0.75, 1.38) | 0.87 (0.66, 1.16) | 0.98 (0.57, 1.67) |
The association between cumulative ACEs and e-cigarette use is shown in Table 6. It indicates a significant association with more frequent e-cigarette use (rare, OR = 1.39, 95% CI = 1.26–1.54; occasional, OR = 1.60, 95% CI = 1.32–1.94; often, OR = 1.89, 95% CI = 1.78–2.00). Higher grade levels were associated with higher e-cigarette use, with older students more likely to use e-cigarettes. A significant association was equally found for sexual orientation also plays a role, with gay or lesbian (OR = 1.57, 95% CI = 1.04–2.39) and bisexual (OR = 1.42, 95% CI = 1.01–1.99) students having higher odds of rare use compared to non-users. Furthermore, non-Hispanic Black, non-Hispanic other, and Hispanic students showed lower odds of frequent e-cigarette use compared to their non-Hispanic white counterparts.
| E-cigarette use | |||
|---|---|---|---|
| Rarely b vs None a | Sometimes c vs None a | Often d vs None a | |
| Variables | OR (95% CI) | OR (95% CI) | OR (95% CI) |
| Cumulative adverse childhood experiences | 1.39 (1.26, 1.54) | 1.60 (1.32, 1.94) | 1.89 (1.78, 2.00) |
| Grade levels | |||
| 9th | Reference | Reference | Reference |
| 10th | 1.18 (0.86, 1.63) | 1.60 (1.05, 2.42) | 1.42 (1.13, 1.80) |
| 11th | 1.67 (1.13, 2.45) | 1.86 (1.22, 2.83) | 1.91 (1.34, 2.72) |
| 12th | 1.66 (1.22, 2.28) | 2.47 (1.37, 4.46) | 2.68 (2.05, 3.49) |
| Self-reported sex | |||
| Male | Reference | Reference | Reference |
| Female | 1.23 (0.99, 1.52) | 1.23 (0.77, 1.95) | 1.20 (0.93, 1.54) |
| Sexual identity | |||
| Heterosexual | Reference | Reference | Reference |
| Gay or lesbian | 1.57 (1.04, 2.39) | 0.80 (0.33, 1.97) | 0.81 (0.40, 1.67) |
| Bisexual | 1.42 (1.01, 1.99) | 1.08 (0.69, 1.69) | 1.07 (0.81, 1.40) |
| Other | 0.84 (0.63, 1.14) | 1.64 (1.00, 2.70) | 0.58 (0.39, 0.86) |
| Race/ethnicity | |||
| Non-Hispanic white | Reference | Reference | Reference |
| Non-Hispanic black | 1.15 (0.77, 1.73) | 0.81 (0.51, 1.29) | 0.42 (0.28, 0.64) |
| Non-Hispanic other | 0.91 (0.63, 1.32) | 0.49 (0.28, 0.87) | 0.52 (0.34, 0.81) |
| Hispanic | 1.01 (0.78, 1.29) | 0.98 (0.64, 1.49) | 0.60 (0.42, 0.85) |
Discussion
This study sheds light on the significant relationship between ACEs and substance use behaviors among adolescents, utilizing a nationally representative dataset. The findings highlight the critical need to address ACEs as a public health priority, given their strong association with increased substance use, including alcohol, binge drinking, cannabis, and e-cigarettes. Overall, the results show a significant positive association between cumulative ACEs and substance use, indicating that higher ACE counts are associated with higher odds of frequent substance use. Additionally, our results reveal statistically significant variations in substance use frequency by grade, sex, sexual identity, and race/ethnicity.
Several factors have been noted in the literature on why ACEs may have long-lasting effects and potential heterogeneous differences among groups. Chronic environmental stressors encountered early in life impose biological costs, which can affect individuals’ susceptibility to stress and disease. 23 A systematic review and meta-analysis found that exposure to ACEs is related to diminished cortisol and cardiovascular reactivity, suggesting that ACEs may contribute to poor health outcomes through changes in biological stress reactivity systems. 24 Prior studies have also reported that ACEs are associated with genetic, metabolic, inflammatory, and neuroendocrine biomarkers, including composite indices representing multiple physiological systems.25,26 These physiological disruptions can become biologically embedded,25,26 and higher levels of childhood adversity may lead to heightened costs and dysfunctional stress reactivity later in life.27,28 Thus, it is plausible that ACEs contribute to maladaptive strategies to cope with stress, 29 and that more cumulative ACEs may lead to or exacerbate the frequency of unhealthy coping strategies, such as substance use, among high school students.
Previous research has noted differences in sociodemographic characteristics in exposure to ACEs. For example, Merrick et al 30 found that individuals identifying as gay/lesbian or bisexual reported significantly higher ACE exposure than those identifying as straight. Additionally, those identifying as Black, Hispanic, and multiracial reported significantly higher ACE exposure compared to those identifying as white. 30 Andersen and Blosnich found that sexual minority adults had higher rates of ACEs compared to heterosexual adults. 31 Another study found significant differences in specific ACE exposure by sociodemographic characteristics, with females, younger adults, sexual minorities, and multiracial groups generally at greater risk. 32 One study found that Black and Hispanic children were exposed to more ACEs than white children. 33 Furthermore, racial differences in coping styles may play a role in resilience to ACEs and their adverse effects. 34
The results of this study suggest several implications for public health. Addressing ACEs not only benefits the overall well-being of adolescents but may also mitigate some of the adverse effects of heavy substance use. There is no one-size-fits-all approach to preventing ACEs, but a comprehensive public health strategy is likely to be effective. 35 Developing safe, stable, and nurturing relationships at medical, community, and familial levels is crucial for buffering against childhood adversity and building resilience among those who experience it. 36 These relationships foster healthy, adaptive skills needed to cope with future adversity. 36 Identifying and intervening in ACEs through trauma-informed care in healthcare and service agencies can reduce the severity and acute consequences of ACEs and address their longer-term effects. 37 Clinical practitioners should focus on routinely screening for ACEs and trauma, using culturally appropriate assessment tools, addressing somatic and mental health problems related to trauma, fostering resilience, and providing connections to supports and services. 38 Although there is limited evidence for their effectiveness, cross-sector support interventions, such as case management or wraparound services for children, educational interventions, and cognitive behavioral therapy, may hold promise for improving outcomes for individuals who have experienced ACEs.39,40
This study has some limitations that are worth noting. First, self-reported survey data may be subject to recall and social desirability biases. Second, the analytic design of this study does not allow for causal conclusions. Third, the results may not be generalizable to youth not attending schools, as the data came from a school-based survey.
Conclusion
This study highlights the significant associations between ACEs and substance use behaviors among adolescents. Our findings indicate that higher ACE counts are associated with more frequent substance use, including alcohol, binge drinking, cannabis, and e-cigarettes. The study also reveals important variations in substance use by grade, sex, sexual identity, and race/ethnicity. The results suggest the need for targeted interventions to address ACEs through comprehensive public health strategies, trauma-informed care, and supportive relationships. These efforts can potentially mitigate the adverse effects of substance use and promote healthier developmental trajectories for adolescents. While the harms of youth substance use and the effects of ACEs have been well-documented, our study adds to the literature by focusing on the frequency of substance use in relation to cumulative ACEs. Prevention and intervention efforts to reduce ACEs and foster resilience may help decrease the likelihood of substance use and its associated harms, ensuring that support for youth is grounded in a deep understanding of their experiences and challenges.
Footnotes
Footnote Group
References
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References
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