Skip to main content

The Consequences of Incarceration for Mortality in the United States

Abstract

Previous research has suggested that incarceration has negative implications for individuals’ well-being, health, and mortality. Most of these studies, however, have not followed former prisoners over an extended period and into older adult ages, when the risk of health deterioration and mortality is the greatest. Contributing to this literature, this study is the first to employ the Panel Study of Income Dynamics (PSID) to estimate the long-run association between individual incarceration and mortality over nearly 40 years. We also supplement those analyses with data from the National Longitudinal Survey of Youth 1979 (NLSY79). We then use these estimates to investigate the implications of the U.S. incarceration regime and the post-1980 incarceration boom for the U.S. health and mortality disadvantage relative to industrialized peer countries (the United Kingdom).

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3

Notes

  1. In the remainder of the text, we use the terms “effect” or “impact” of condition X on mortality as shorthand to mean the estimated regression coefficient of condition X on mortality. We do this to avoid terminological cluttering, not to equivocate. We invoke causal language only when we think it is legitimate to do so.

  2. We explored whether the association between incarceration and mortality changes after the release of inmates (not shown). Our results were consistent with the literature and previous research (i.e., the risk of mortality is highest early after release and decreases over time). However, because our sample is too small to sustain robust inferences, we did not estimate the magnitude of the differences between long- and short-term effects. This issue should be explored in future research.

  3. The distribution of the age of death is shown in Fig. S1 of the online appendix.

  4. The distribution of the age of first imprisonment is shown in Fig. S1 of the online appendix.

  5. The variability of the slope in humans is restricted to a somewhat narrow range (.05–.14) (Kirkwood 2015). We expect our estimates to be within that range. We opt for not letting the Gompertz slope be a function of covariates (some of them identical to those that modify the constant) because this leads to intractable identification problems, even in very large samples.

  6. There are many and very strong reasons to use the United Kingdom and not France or Russia as a benchmark. First, in key studies of the U.S. adult health and mortality disadvantage, the United Kingdom is used as the preferred benchmark (Banks et al. 2006) because of similarity of culture and language and contrasts of medical health care system. Ideally, we would have liked to produce a full comparison with all countries included in the National Research Council report, but that is left for future work. In terms of the criminal justice system, comparisons between the United States and the United Kingdom are not rare, either. Garland (2002), for instance, claimed that there are strong similarities in the recent criminal policies and practices, and this alone makes the comparison interesting.

  7. Had the range of values been broader, we would have proceeded differently via Bayesian computations, imposing a prior distribution on estimates. This exercise is left for future research.

References

  • Arias, E., Heron, M., & Xu, J. Q. (2017). United States life tables, 2013 (National Vital Statistics Reports, Vol. 66, No. 3). Hyattsville, MD: National Center for Health Statistics.

  • Baćak, V., & Wildeman, C. (2015). An empirical assessment of the “healthy prisoner hypothesis.” Social Science & Medicine, 138, 187–191.

  • Banks, J., Marmot, M., Oldfield, Z., & Smith, J. P. (2006). Disease and disadvantage in the United States and in England. JAMA, 295, 2037–2045.

    Article  Google Scholar 

  • Binswanger, I. A., Stern, M. F., Deyo, R. A., Heagerty, P. J., Cheadle, A., Elmore, J. G., & Koepsell, T. D. (2007). Release from prison—A high risk of death for former inmates. New England Journal of Medicine, 356, 157–165.

    Article  Google Scholar 

  • Bonczar, T. P. (2003). Prevalence of imprisonment in the U.S. population, 1974–2001 (Report). Washington, DC: U.S. Department of Justice, Office of Justice Programs.

  • Centers for Disease Control and Prevention (CDC). (2011). STDs in persons entering corrections facilities. In Sexually transmitted disease surveillance 2010 (pp. 83–86). Washington, DC: Atlanta, GA: U.S. Department of Health and Human Services.

  • Foster, H., & Hagan, J. (2014). Supportive ties in the lives of incarcerated women: Gender, race/ethnicity, and children’s human rights. Journal of Gender, Race & Justice, 17, 257–278.

    Google Scholar 

  • Freedman, V. A., Schoeni, R. F., & Schlegel, K. (2016). Panel Study of Income Dynamics: 1968–2015 death file documentation. Release 1. Ann Arbor: Institute for Social Research, University of Michigan.

  • Garland, D. (2002). The culture of control: Crime and social order in contemporary society. Chicago, IL: University of Chicago Press.

  • Gelman, A., & Carlin, J. (2014). Beyond power calculations assessing Type S (sign) and Type M (magnitude) errors. Perspectives on Psychological Science, 9, 641–651.

    Article  Google Scholar 

  • Hernán, M. A., & Robins, J. M. (2006). Estimating causal effects from epidemiological data. Journal of Epidemiology & Community Health, 60, 578–586.

    Article  Google Scholar 

  • Houle, J. N., & Martin, M. A. (2011). Does intergenerational mobility shape psychological distress? Sorokin revisited. Research in Social Stratification and Mobility, 29, 193–203.

    Article  Google Scholar 

  • Human Mortality Database. (n.d.). Berkeley, CA (USA), and Rostock, Germany: University of California, Berkeley (US), and Max Planck Institute for Demographic Research (Germany). Available from http://www.mortality.org

  • Kirkwood, T. B. L. (2015). Deciphering death: A commentary on Gompertz (1825) “On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies.” Philosophical Transactions of the Royal Society B: Biological Sciences, 370, 2014379. https://doi.org/10.1098/rstb.2014.0379

  • Massoglia, M. (2008a). Incarceration as exposure: The prison, infectious disease, and other stress-related illnesses. Journal of Health and Social Behavior, 49, 56–71.

    Article  Google Scholar 

  • Massoglia, M. (2008b). Incarceration, health, and racial disparities in health. Law & Society Review, 42, 275–306.

    Article  Google Scholar 

  • Massoglia, M., Pare, P.-P., Schnittker, J., & Gagnon, A. (2014). The relationship between incarceration and premature adult mortality: Gender specific evidence. Social Science Research, 46, 142–154.

  • Massoglia, M., & Pridemore, W. A. (2015). Incarceration and health. Annual Review of Sociology, 41, 291–310.

  • Massoglia, M., & Warner, C. (2011). The consequences of incarceration. Criminology & Public Policy, 10, 851–863.

    Article  Google Scholar 

  • Mumola, C. J. (2007). Medical causes of death in state prisons, 2001–2004 (Bureau of Justice Statistics data brief). Washington, DC: U.S. Department of Justice, Office of Justice Programs, Bureau of Justice Statistics.

  • National Center for Health Statistics (NCHS). (2018). Health, United States, 2017: With special features on racial and ethnic health disparities (Report). Hyattsville, MD: NCHS.

  • National Research Council. (2014). The growth of incarceration in the United States: Exploring causes and consequences (Report). Washington, DC: National Academies Press.

  • Olshansky, S. J., Antonucci, T., Berkman, L., Binstock, R. H., Boersch-Supan, A., Cacioppo, J. T., . . . Rowe, J. (2012). Differences in life expectancy due to race and educational differences are widening, and many may not catch up. Health Affairs, 31, 1803–1813.

  • Pager, D. (2003). The mark of a criminal record. American Journal of Sociology, 108, 937–975.

    Article  Google Scholar 

  • Patterson, E. J. (2010). Incarcerating death: Mortality in U.S. state correctional facilities, 1985–1998. Demography, 47, 587–607.

    Article  Google Scholar 

  • Patterson, E. J. (2013). The dose–response of time served in prison on mortality: New York State, 1989–2003. American Journal of Public Health, 103, 523–528.

    Article  Google Scholar 

  • Rosen, D. L., Schoenbach, V. J., & Wohl, D. A. (2008). All-cause and cause-specific mortality among men released from state prison, 1980–2005. American Journal of Public Health, 98, 2278–2284.

    Article  Google Scholar 

  • Schnittker, J., & John, A. (2007). Enduring stigma: The long-term effects of incarceration on health. Journal of Health and Social Behavior, 48, 115–130.

    Article  Google Scholar 

  • Shannon, S. K. S., Uggen, C., Schnittker, J., Thompson, M., Wakefield, S., & Massoglia, M. (2017). The growth, scope, and spatial distribution of people with felony records in the United States, 1948–2010. Demography, 54, 1795–1818.

    Article  Google Scholar 

  • Spaulding, A. C., Seals, R. M., McCallum, V. A., Perez, S. D., Brzozowski, A. K., & Steenland, N. K. (2011). Prisoner survival inside and outside of the institution: Implications for health-care planning. American Journal of Epidemiology, 173, 479–487.

    Article  Google Scholar 

  • Turney, K. (2015). Hopelessly devoted? Relationship quality during and after incarceration. Journal of Marriage and Family, 77, 480–495.

    Article  Google Scholar 

  • Uggen, C., Manza, J., & Thompson, M. (2006). Citizenship, democracy, and the civic reintegration of criminal offenders. Annals of the American Academy of Political and Social Science, 605, 281–310.

    Article  Google Scholar 

  • van der Wal, W. M., & Geskus, R. B. (2011). ipw: An R package for inverse probability weighting. Journal of Statistical Software, 43(13), 1–23.

    Article  Google Scholar 

  • Western, B. (2002). The impact of incarceration on wage mobility and inequality. American Sociological Review, 67, 526–546.

    Article  Google Scholar 

  • Wildeman, C. (2009). Parental imprisonment, the prison boom, and the concentration of childhood disadvantage. Demography, 46, 265–280.

    Article  Google Scholar 

  • Wildeman, C. (2016). Incarceration and population health in wealthy democracies. Criminology, 54, 360–382.

    Article  Google Scholar 

  • Wildeman, C., & Wang, E. A. (2017). Mass incarceration, public health, and widening inequality in the USA. Lancet, 389, 1464–1474.

    Article  Google Scholar 

Download references

Acknowledgments

The University of Wisconsin–Madison researchers are supported by core grants to the Center for Demography and Ecology, University of Wisconsin (R24 HD047873), and to the Center for Demography of Health and Aging, University of Wisconsin (P30 AG017266), as well as a small grant for research using PSID data through the National Institute on Aging (P01AG029409).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sebastian Daza.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

ESM 1

(PDF 340 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Daza, S., Palloni, A. & Jones, J. The Consequences of Incarceration for Mortality in the United States. Demography 57, 577–598 (2020). https://doi.org/10.1007/s13524-020-00869-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13524-020-00869-5

Keywords

  • Incarceration
  • Mortality
  • United States
  • United Kingdom
  • Health Inequality