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Handbook on Crime and Deviance pp 433–468Cite as

Developmental Sequences and Comorbidity of Substance Use and Violence

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Part of the book series: Handbooks of Sociology and Social Research ((HSSR))

Throughout the world, violence is among the leading causes of death for people age 15–44 years (Krug, Dahlberg, Mercy, Zwi, & Lozano, 2002). Uniformly, alcohol and drug use are risk factors that are associated with violence within this age group. In fact, alcohol use is implicated in about half the incidents of violent crime (Murdoch, Pihl, & Ross, 1990).

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Notes

  1. 1.

    A middle cohort was followed from approximately age 9 to 13, but follow-ups were discontinued until a recent follow-up at age 21.

  2. 2.

    Creating a summative measure assumes that the different beverages were consumed on different days, which may not be the case.

  3. 3.

    The intercept was centered at Time 1 (by means of a zero loading on growth factors at Time 1), and slope factor loadings were set according to the interval between assessments (i.e., 1 year).

  4. 4.

    Our findings differ from those of Lacourse et al. (2008), who found that a four-class model fit the data best for the older PYS cohort from ages 13 to 25. There are several possible reasons for the difference in these findings: (1) Lacourse et al. used a combined measure of self and other reports with official conviction reports; (2) Lacourse et al. focused only on serious violence (i.e., they omitted gang fighting); and (3) Lacourse et al. used Proc Traj to conduct the analyses, whereas we used Mplus. These differences highlight the importance of considering sample and measures when evaluating the results of trajectory analyses.

  5. 5.

    We also hand-calculated estimates of concordance that were weighted by probability of group membership. Findings were similar in magnitude but were lower when using weighted estimates. For Table 21.2, χ2 (4, N=506) = 12.26, p < .01 with weighted estimates versus χ2 (4, N=506) = 13.35, p < .01 using posterior probabilities. For Table 21.3 (concordance in adolescence), χ2 (2, N=506) = 34.81, p < .001 with weighted estimates versus χ2 (2, N=506) = 43.63, p < .001 with using posterior probabilities. For Table 21.3 (concordance in young adulthood), χ2 (2, N=486) = 2.91, ns, with weighted estimates versus χ2 (2, N=486) = 5.86, ns with using posterior probabilities. For Table 21.4 (concordance of violence in adolescence and drinking in young adulthood) χ2 (2, N=486) = 0.11, ns with weighted estimates versus χ2 (2, N=486) = 0.11, ns using posterior probabilities. For Table 21.4 (concordance of violence in young adulthood and drinking in young adulthood), χ2 (2, N=486) = .04, ns with weighted estimates versus χ2 (2, N=486) = 2.66, ns; Φ = 0.07 using posterior probabilities. In addition, significant cell chi-squares showed a very similar pattern, with the exception that those with high violence were significantly less likely to belong to the high-drinking group (Table 21.2) using the weighted estimates.

  6. 6.

    We also considered using two other measures of alcohol involvement, volume (frequency * quantity), and heavy episodic drinking (which was operationalized as 6+ drinks/occasion in these data). However, the zero-order associations between violence and alcohol involvement were stronger for drinking frequency than for the other measures of use (data not shown). Jackson and Sher (2005) found that there was similarity in trajectory shape across different indices of alcohol involvement, although, not unexpectedly, group prevalence rates varied across measures.

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Acknowledgments

Portions of this chapter were excerpted from White and Gorman (2000). Preparation of this chapter was supported, in part, by grants from the National Institute on Drug Abuse (DA411018 and DA17552), the National Institute on Alcohol Abuse and Alcoholism (K01 AA13938), the National Institute on Mental Health (MH73941 and MH50778), and the U.S. Department of Justice (96-MU-FX-0020). Points of view or opinions in this chapter are those of the authors and do not necessarily represent the official positions or policies of the U.S. Department of Justice or the National Institutes on Drug Abuse, Alcohol Abuse and Alcoholism and Mental Health. The authors thank Judit Ward, Dan Calandro and James Cox for their help with the literature search and references.

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  1. Rutgers, The State University of New Jersey, Piscataway, NJ, USA

    Helene Raskin White

  2. Brown University, Providence, RI, USA

    Kristina M. Jackson

  3. University of Pittsburgh, Pittsburgh, PA, USA

    Rolf Loeber

  4. Free University, Amsterdam, The Netherlands

    Rolf Loeber

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  1. School of Criminal Justice, University at Albany, Washington Ave. 1400, Albany, 12222, USA

    Marvin D. Krohn

  2. School of Criminal Justice, University at Albany, Washington Ave. 1400, Albany, 12222, U.S.A.

    Alan J. Lizotte

  3. School of Criminal Justice, University at Albany, Washington Ave. 1400, Albany, 12222, U.S.A.

    Gina Penly Hall

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White, H.R., Jackson, K.M., Loeber, R. (2009). Developmental Sequences and Comorbidity of Substance Use and Violence. In: Krohn, M., Lizotte, A., Hall, G. (eds) Handbook on Crime and Deviance. Handbooks of Sociology and Social Research. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0245-0_21

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