What Separates Offenders Who are Not Victimized from Offenders Who are Victimized? Results from a Nationally Representative Sample of Males and Females

ABSTRACTThere has been considerable interest in understanding victim-offender overlap, including why it occurs and the factors that are responsible for creating it. At the same time, however, there has been a lack of research examining precisely why some offenders are able to escape victimization and yet others are more susceptible to it. The current study sought to address this gap in the literature. To do so, data drawn from the National Longitudinal Study of Adolescent to Adult Health (Add Health) were analyzed. The results revealed that a range of covariates, including low self-control, delinquent peers, social support, parental criminality, intelligence, and poverty, were differentially related to the odds of being victimized among offenders over the life course. We discuss what these findings mean for research on victim-offender overlap and future research in this area.KEYWORDS: Add Healthoffendersoverlaprisk factorsvictimization AcknowledgmentsWave VI of Add Health is supported by two grants from the National Institute on Aging (1U01AG071448, principal investigator Robert A. Hummer, and 1U01AG071450, principal investigators Allison E. Aiello and Robert A. Hummer) to the University of North Carolina at Chapel Hill. Co-funding for Wave VI is being provided by the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the National Institute on Minority Health and Health Disparities, the National Institute on Drug Abuse, the NIH Office of Behavioral and Social Science Research, and the NIH Office of Disease Prevention. The content of this paper/presentation is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the University of North Carolina at Chapel Hill.Add Health was designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill. The project was funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development from 1994-2021, with cooperative funding from 23 other federal agencies and foundations. Add Health is currently directed by Robert A. Hummer; it was previously directed by Kathleen Mullan Harris (Citation2004-2021) and J. Richard Udry (Citation1994-2004).Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1. In binary logistic regression, issues can surface (e.g., as issues with prediction) when the outcome is considered rare (King & Zeng, Citation2001). There is not a consensus on when an outcome is considered rare, and there are other factors to take into account (e.g., sample size, number of predictors in the models) rather than solely focusing on the proportion of the sample that has experienced the outcome (in this case, victimization). For the most part, the outcomes used in this study would fall outside the parameters of what is considered a “rare” outcome when using binary logistic regression. Nonetheless, it is important to bear in mind that the proportion of the sample who was victimized varies significantly across the different measures which could contribute to differences in the results of the models.