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. 2014 Aug;53(8):888-98, 898.e1-2.
doi: 10.1016/j.jaac.2014.05.007. Epub 2014 Jun 12.

Crime and psychiatric disorders among youth in the US population: an analysis of the National Comorbidity Survey-Adolescent Supplement

Kendell L Coker  1 , Philip H Smith  2 , Alexander Westphal  3 , Howard V Zonana  1 , Sherry A McKee  4
Affiliations

Crime and psychiatric disorders among youth in the US population: an analysis of the National Comorbidity Survey-Adolescent Supplement

Kendell L Coker et al. J Am Acad Child Adolesc Psychiatry. 2014 Aug.

Abstract

Objective: Current knowledge regarding psychiatric disorders and crime in youth is limited to juvenile justice and community samples. This study examined relationships between psychiatric disorders and self-reported crime involvement in a sample of youth representative of the US population.

Method: The National Comorbidity Survey-Adolescent Supplement (N = 10,123; ages 13-17 years; 2001-2004) was used to examine the relationship between lifetime DSM-IV-based diagnoses, reported crime (property, violent, other), and arrest history. Logistic regression compared the odds of reported crime involvement with specific psychiatric disorders to those without any diagnoses, and examined the odds of crime by psychiatric comorbidity.

Results: Prevalence of crime was 18.4%. Youth with lifetime psychiatric disorders, compared to no disorders, had significantly greater odds of crime, including violent crime. For violent crime resulting in arrest, conduct disorder (CD) (odds ratio OR = 57.5; 95% CI = 30.4, 108.8), alcohol use disorders (OR = 19.5; 95% CI = 8.8, 43.2), and drug use disorders (OR = 16.1; 95% CI = 9.3, 27.7) had the greatest odds with similar findings for violent crime with no arrest. Psychiatric comorbidity increased the odds of crime. Youth with 3 or more diagnoses (16.0% of population) accounted for 54.1% of those reporting arrest for violent crime. Youth with at least 1 diagnosis committed 85.8% of crime, which was reduced to 67.9% by removing individuals with CD. Importantly, 88.2% of youth with mental illness reported never having committed any crime.

Conclusion: Our findings highlight the importance of improving access to mental health services for youthful offenders in community settings, given the substantial associations found between mental illness and crime in this nationally representative epidemiological sample.

Keywords: US population; arrest; crime; psychiatric disorders; youth.

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Conflict of interest statement

Disclosure: Drs. Coker, Smith, and Zonana report no biomedical financial interests or potential conflicts of interest.

Figures

Figure 1
Figure 1
Percentages of crime accounted for by those with varying numbers of psychiatric diagnoses, relative to population prevalence. Note: Estimates were calculated using logistic regression, accounting for the survey design. Results showed that despite making up a smaller portion of the total population, adolescents with substantial psychiatric comorbidity accounted for a much larger portion of reported crime. For example, those with no psychiatric diagnoses made up over 50% of the population, and accounted for 15.8% of those never arrested who committed violent crime, whereas those with 3 or more diagnoses made up only 16.0% of the population, and accounted for 48.4% of those never arrested who committed violent crime.
Figure 2
Figure 2
Population attributable fraction (PAF) of those who committed any crime, by number of diagnoses. Note: results are presented both with and without those with conduct disorder (CD) included in the sample. One could expect up to 86% of crime to be reduced if there were no mental illness (68% when those with CD were eliminated from the sample). PAF calculated using the following formula: PAF = Pe(RRe – 1)/[1 + Pe(RRe – 1)], where Pe is the prevalence of the exposure group and RRe is the relative risk associated with the exposure group. To obtain RRe, odds ratios were calculated using logistic regression, accounting for the survey design and adjusting for income, age, gender, and race/ethnicity. These odds ratios (ORe) were then converted to RRe using the following formula: RRe = ORe/[(l — P0) + (P0 * ORe)], where P0 is the prevalence of the outcome in the non-exposed group (0 diagnoses).
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