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Criminal Offending and Mortality over the Full Life-Course: A 70-Year Follow-up of the Cambridge–Somerville Youth Study

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Abstract

Objectives

To investigate the relationship between criminal offending and mortality over the full life-course of treatment group participants in the Cambridge–Somerville Youth Study (CSYS).

Methods

The CSYS is a delinquency prevention experiment and prospective longitudinal survey of the development of offending. Begun in 1939, the study involves 506 at-risk boys, ages 5–13 years (mean birth year = 1928), from Cambridge and Somerville, Massachusetts. Following the analytic strategy of Joan McCord, participants are drawn from the study’s longitudinal arm (N = 253). Data include court convictions of criminal offenses collected during middle age (mean = 47) and death records collected during old age (up to age 89). Death records were collected for 216 participants or 85.4% of the sample.

Results

Life-course persistent offenders experience earlier mortality compared to non-offenders (by about 7 years) and adolescent-limited offenders (by about 8 years). While life-course persistent offenders are not more likely to die early (< 40 years) compared to other trajectory groups, they are more likely to experience premature mortality from late middle age into old age. Life-course persistent offenders are also more likely to experience unnatural deaths, with alcoholism confounding the relationship.

Conclusions

That group differences in mortality risk did not emerge until age 55 (while offending is in decline) suggests that the relationship between offending and mortality is not direct and may be spurious. Knowledge about the relationship between criminal offending and mortality can be greatly improved by following participants into old age.

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Notes

  1. As Moffitt (1993: p. 679) writes, “The prognosis for the life-course-persistent person is bleak: Drug and alcohol addiction; unsatisfactory employment; unpaid debts; homelessness; drunk driving; violent assault; multiple and unstable relationships; spouse battery; abandoned, neglected, or abused children; and psychiatric illness have all been reported at very high rates for offenders who persist past the age of 25.” On the other hand, “Unlike their life-course-persistent peers, whose behavior was described as inflexible and refractory to changing circumstances, adolescence-limited delinquents are likely to engage in antisocial behavior in situations where such responses seem profitable to them, but they are also able to abandon antisocial behavior when prosocial styles are more rewarding” (Moffitt 1993: p. 686).

  2. The authors note that the entire sample—both offending and non-offending groups—had “much higher mortality rates than the general [Dutch] population” (van de Weijer et al. 2016: p. 96).

  3. While the authors were quick to point out that the direct and indirect causal perspective could not be ruled out, they also indicated that the timing between (known) offenses and death suggested a spurious relationship.

  4. According to McCord (1984: p. 523), “When a boy was dropped from the treatment program, his matched mate was dropped from the control group.” A comparison of all of the remaining pairs indicated that there were no “reliable differences” between the two groups on a wide range of variables (e.g., age, IQ, referral to the study as “average” or “difficult,” mental health; see also Powers and Witmer 1951: pp. 80–81).

  5. This is consistent with expected age of mortality for the 1930 male birth cohort: 66 (Bell and Miller 2005: p. 98).

  6. As such, there are seven age categories at which convictions were originally recorded: under 18, 18–24, 25–29, 30–34, 35–39, 40–44, and 45+.

  7. For adult and juvenile convictions, “serious convictions” are a subset of the “all convictions” measure (i.e., the models do not contain mutually exclusive samples).

  8. As Farrington (2011) notes, the primary family-related risk factors are parental conflict, parental absence, lack of supervision, large families, and young parents.

  9. Hyperactivity is one of the three core symptoms of Attention Deficit Hyperactivity Disorder (ADHD). While self-control as a personality trait was not measurable with the study data, we note that hyperactivity shares variance with inattention and impulsivity, the two remaining symptoms of ADHD and two of the six core dimensions of low self-control (Gottfredson and Hirschi 1990). Additionally, research has demonstrated that hyperactivity via ADHD is associated with increased criminal behavior (Pratt et al. 2002) predominantly through low self-control (Unnever et al. 2003). We thus consider hyperactivity a proxy for self-control.

  10. The best fit number of groups was first calculated with one zero-order polynomial followed by quadratic polynomials, testing one-group through ten-group solutions. A three-group solution achieved the lowest BIC for both the “all convictions” trajectories (− 601.68) and “felony convictions” trajectories (− 359.71). Second, best fit polynomial groups were estimated for each trajectory, ranging from zero-order (i.e., flat) to cubic. The best fit polynomial group trajectories were zero—linear—quadratic (0, 1, 2) for the “all convictions” model (BIC = − 599.70), and zero—linear–linear (0, 1, 1) for the “felony convictions” model (BIC = − 354.89).

  11. Group-based trajectory modeling was performed using the “traj” command in Stata 15 (see Jones and Nagin 2013).

  12. As acknowledged by Piquero et al. (2014: p. 460), “early death reduces the number of convictions that a man would have received so in a way these relationships are underestimated.” When deaths prior to age 50 were dropped in sensitivity analysis, the relationship between adult felony convictions and age of mortality reached statistical significance (b = − 6.33, p = .001). All other findings in Tables 2 and 3 were generally consistent when early deaths were dropped, however.

  13. Each logistic regression model used the same model specification as the OLS regression shown in Table 2, but control variables are omitted from Table 3 for ease of interpretation. Similar to Table 2, most control variables were not associated with age of mortality. Exceptions are race—black participants were more likely to die by ages 45 (OR 4.42, p = .02), 50 (OR 3.63, p = .03), and 55 (OR  4.42, p = .02) in the all convictions model—and alcoholism—alcoholic participants were more likely to die by ages 60 (OR 1.85, p = .03) and 65 (OR 1.82, p = .04) in the felony convictions model.

  14. Separate logit models were estimated with the adolescent-limited group as reference category. Similar findings emerged. For the all convictions trajectories, life-course persistent offenders were more likely to die by age 45 (OR 4.68), age 55 (OR 4.18), age 65 (OR 2.55), and age 70 (OR 3.67). For the felony convictions trajectories, life-course persistent offenders were more likely to die by age 55 (OR 3.93), age 70 (OR 6.62), and age 75 (OR 8.58). No differences in age of mortality emerged between the adolescent-limited and non-offender groups.

  15. All members of the life-course persistent offender group had died by age 85, and all members of the life-course persistent felony offender group had died by age 80, so death by age 80 is the final category displayed in Table 3.

  16. The control variable for frequent smoker was omitted because no child smokers died due to unnatural causes.

  17. Similar findings emerge when the adolescent-limited group is used as the reference category. After adding controls, life-course persistent offenders are more likely to die by unnatural causes than adolescent-limited offenders for the any convictions trajectories (OR 5.03, p = .02), as well as for felony convictions trajectories (OR 4.47, p = .05). After adding alcoholism, however, this relationship was no longer significant.

  18. Consistent with this viewpoint, our results indicated that hyperactivity was inversely (albeit not significantly) related to age of death.

  19. When unnatural deaths were removed from the analyses, the significant relationship between life-course persistent offending and mortality remained.

  20. This is consistent with earlier research on the full life-course, such as Laub and Vaillant’s (2000: p. 100) finding that among delinquents “only alcohol abuse was significantly related to mortality” and that “[w]hen alcohol abuse was controlled, dysfunctional upbringing, years or education, number of times in jail, and unofficial delinquency made no further contributions toward explaining mortality.”.

  21. Importantly, the state dependence hypothesis could not be fully explored due to lack of information on why most offenders desisted by early adulthood (i.e., adolescent-limited trajectory).

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Acknowledgments

We wish to thank the journal editor and the anonymous reviewers for especially helpful comments.

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Authors and Affiliations

  1. Florida State University, Tallahassee, FL, USA

    Steven N. Zane

  2. School of Criminology and Criminal Justice, Northeastern University, Churchill Hall, 360 Huntington Avenue, Boston, MA, 02115, USA

    Brandon C. Welsh & Gregory M. Zimmerman

  3. Netherlands Institute for the Study of Crime and Law Enforcement, Amsterdam, The Netherlands

    Brandon C. Welsh

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  1. Steven N. Zane
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Correspondence to Brandon C. Welsh.

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Zane, S.N., Welsh, B.C. & Zimmerman, G.M. Criminal Offending and Mortality over the Full Life-Course: A 70-Year Follow-up of the Cambridge–Somerville Youth Study. J Quant Criminol 35, 691–713 (2019). https://doi.org/10.1007/s10940-018-9399-4

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