title: A method for analyzing changing prison populations: explaining the growth of the elderly in prison.
abstract: BACKGROUND
  For the past several decades, the U.S. prison system has witnessed a steady and persistent increase in the ages of prison populations. Given the additional costs and burdens placed on prisons as they house older inmates, this aging trend has generated intense interest among policy makers and academics who seek to understand why prison populations are getting older.
  
  
  OBJECTIVE
  This article presents a method for evaluating drivers influencing the change in age distributions among prisoners.
  
  
  METHODS
  We define a methodological approach and demonstrate its application using prison data from four states reporting to the Bureau of Justice Statistics' National Corrections Reporting Program.
  
  
  RESULTS
  We find that since 2000, the primary driver of overall growth in the elderly populations in prison (defined as inmates over 50) is the increasing admission age of offenders entering prison. Moreover, changes in offense mix and sentence length/time served over the last decade have had significantly less influence on the age composition of prison populations. We also find that the impact of explanatory factors varies across states and offense types. For example, prison admission and exit rates explain much of the change in elderly drug offenders in New York, but not elderly violent offenders, where admission age plays a much stronger explanatory role.
  
  
  CONCLUSIONS
  Our analysis offers an effective demonstration that supports the use of this method as an important and informative first step toward understanding components of change that affect the problem of prison aging.
authors.affiliation: Abt Associates, Cambridge, MA, USA jeremy_luallen@abtassoc.com.
authors.forename: Jeremy
authors.initials: J
authors.lastname: Luallen
authors.affiliation: Abt Associates, Cambridge, MA, USA.
authors.forename: Ryan
authors.initials: R
authors.lastname: Kling
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D002140:California; D003415:Crime / Q000706:statistics & numerical data; D003416:Criminal Law / Q000331:legislation & jurisprudence / Q000706:statistics & numerical data; D006801:Humans; D008875:Middle Aged; D008962:Models, Theoretical; D009518:New York; D009657:North Carolina; D011329:Prisoners / Q000706:statistics & numerical data*; D011330:Prisons / Q000706:statistics & numerical data*; D013022:South Carolina; D014481:United States; D055815:Young Adult
keywords: elderly prisoners; methodology and analytic methods; modeling prison growth