title: The Growth of Older Inmate Populations: How Population Aging Explains Rising Age at Admission.
abstract: OBJECTIVE
  Older inmates are the fastest growing segment of the prison population; however, the reasons for this are not well understood. One explanation is that the general population is aging, driving prison age distributions to change. For this article, we study the role of population aging in prison growth by investigating how the baby boom phenomenon of post-World War II has contributed to the growth of older inmate populations.
  
  
  METHODS
  We identify the impact of population aging using simulation methods that explain prison growth as the combination of criminal justice processes.
  
  
  RESULTS
  Overall, we find evidence that population aging has played a significant role in explaining the growth of older inmate populations, in particular among inmates aged between 50 and 64 years, contributing to as much as half of the observed increase in these groups since 2000.
  
  
  CONCLUSIONS
  This finding stands in contrast to the notion that population aging has little explanatory power in describing the growth of prison populations and implies that older inmate groups are more sensitive to compositional changes in the general population. We argue that prediction-based modeling of prison growth should more seriously consider the impacts and consequences of demographic shifts among older prisoner populations.
authors: Abt Associates, Cambridge, Massachusetts.
authors: Jeremy
authors: J
authors: Luallen
authors: Abt Associates, Cambridge, Massachusetts.
authors: Christopher
authors: C
authors: Cutler
mesh_terms: D000367:Age Factors; D000368:Aged; D015331:Cohort Studies; D003415:Crime / Q000706:statistics & numerical data / Q000639:trends; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D011157:Population Dynamics / Q000639:trends*; D011329:Prisoners / Q000706:statistics & numerical data*; D011330:Prisons / Q000706:statistics & numerical data* / Q000639:trends*
keywords: Cohort analysis; Crime; Longitudinal methods; Populations aging