Author: Cho, Junhan; Kelley-Quon, Lorraine I; Barrington-Trimis, Jessica L; Kechter, Afton; Axeen, Sarah; Leventhal, Adam M
Title: Behavioral Health Risk Factors for Nonmedical Prescription Opioid Use in Adolescence. Cord-id: b9qfbknd Document date: 2021_8_16
ID: b9qfbknd
Snippet: BACKGROUND Adolescent nonmedical prescription opioid use is associated with overdose and other adverse outcomes, but its risk factors are poorly understood. METHODS Data were drawn from a prospective cohort study of Los Angeles, California, high school students. At baseline (mean age = 14.6 years), students completed self-report screening measures of problem alcohol, cannabis, and drug use and 6 mental health problems (major depression, generalized anxiety, panic disorder, social phobia, obsessi
Document: BACKGROUND Adolescent nonmedical prescription opioid use is associated with overdose and other adverse outcomes, but its risk factors are poorly understood. METHODS Data were drawn from a prospective cohort study of Los Angeles, California, high school students. At baseline (mean age = 14.6 years), students completed self-report screening measures of problem alcohol, cannabis, and drug use and 6 mental health problems (major depression, generalized anxiety, panic disorder, social phobia, obsessive-compulsive disorder, and hypomania or mania). Past 6-month nonmedical prescription opioid use (yes or no) was assessed across 7 semiannual follow-ups. RESULTS Among baseline never users of nonmedical prescription opioids (N = 3204), average past 6-month prevalence of new nonmedical prescription opioid use across the 42-month follow-up was 4.4% (range 3.5%-6.1%). In a multivariable model co-adjusting for 9 baseline behavioral problems and other factors, major depression, hypomania or mania, cannabis, alcohol, and other drug use problems were associated with increased odds of nonmedical prescription opioid use over follow-ups. Cumulative indices of behavioral health comorbidity showed successively greater odds of subsequent nonmedical prescription opioid use for students with 1 (odds ratio [OR]: 3.74; 95% confidence interval [CI]: 2.79-5.01), 2 (OR: 8.79; 95% CI: 5.95-12.99), or 3 (OR: 9.69; 95% CI: 5.63-16.68) vs 0 baseline substance use problems, and similar increases were associated with increasing number of mental health problems (1 [OR: 1.60; 95% CI: 1.03-2.88] to all 6 [OR: 3.98; 95% CI: 1.09-14.82] vs 0). CONCLUSIONS Behavioral health problems may be associated with increased risk of subsequent nonmedical prescription opioid use during mid to late adolescence, with successively greater risk for those with greater behavioral health comorbidity. In pediatric clinical practice or school-based prevention, behavioral health screeners may be useful for identifying youth at high risk for nonmedical prescription opioid use.
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