Year: 2023 Source: Public Health. (2023). 221(1), 39-45. DOI: 10.1016/j.puhe.2023.05.020 SIEC No: 20231879

Objectives: This study assessed the association between adverse childhood experiences (ACEs) and clustering of high-risk behaviors in a sample of high school students.

Study design: This was a cross-sectional study.

Methods: A sample of students who attended randomly selected classes in 99 high schools completed the 2019 Nevada Youth Risk Behavior Survey (N = 4959). The survey included six ACE measures: (1) physical abuse, (2) sexual abuse, (3) verbal abuse, (4) household physical abuse, (5) household mental illness, and (6) household substance abuse. Students were assigned a cumulative ACE score (range = 0-6). A count of high-risk behavior domains was created using multiple questions across the following domains: (1) violence behaviors, (2) suicidal indicators, (3) non-suicidal self-injury, (4) substance use, (5) high-risk sexual behaviors, (6) poor diet, (7) physical inactivity, and (8) high screen time (range = 0-8). The relationship between ACEs and the count of high-risk behavior domains was assessed using weighted negative binomial regression; incidence rate ratios (IRRs) were calculated adjusting for sociodemographic characteristics.

Results: More than 40% of the sampled students reported high-risk behaviors across two or more domains. There was a strong, graded relationship between cumulative ACE score and the count of high-risk behavior domains. Compared with students who experienced zero ACEs, there was an increase in the count of high-risk behavior domains among students who experienced one ACE (adjusted IRR [aIRR] = 1.22, 95% confidence interval [CI] = 1.12-1.33), two ACEs (aIRR = 1.57, 95% CI = 1.42-1.73), three ACEs (aIRR = 1.73, 95% CI = 1.54-1.94), four ACEs (aIRR = 2.07, 95% CI = 1.84-2.33), five ACEs (aIRR = 2.69, 95% CI = 2.34-3.10), and six ACEs (aIRR = 2.91, 95% CI = 2.34-3.62).

Conclusion: Trauma-informed prevention efforts may be an efficient way to address multiple adolescent risk behaviors that cluster.