More deprived areas need greater resources for mental health

Aust N Z J Psychiatry. 2003 Aug;37(4):437-44. doi: 10.1046/j.1440-1614.2003.01206.x.

Abstract

Objective: This study set out to investigate the relationship in New Zealand between the newly developed small area index of socio-economic deprivation, NZDep96, and measures of psychiatric bed utilisation. It aims to contribute to the debate on resource allocation and to estimate the distribution of beds required in relation to levels of deprivation.

Method: A cohort study of 872 persons admitted to the psychiatric in-patient unit within Counties Manukau, involving 1299 episodes of in-patient care between 1998 and 2000. The annual period prevalence of admission and the rate of total occupied bed days were calculated for the different deciles of deprivation, standardized for age and gender.

Results: There was a three-fold gradient in admission prevalence and in total occupied bed days between persons living in the most and least deprived areas.

Conclusions: Mental health services need to be organized and funded in ways that take account of the high use of in-patient care among those living in deprived areas. Further research is required to explore the relationship between socio-economic deprivation and use of community mental health services.

MeSH terms

  • Adult
  • Beds / statistics & numerical data
  • Cohort Studies
  • Community Mental Health Services / economics
  • Community Mental Health Services / organization & administration
  • Community Mental Health Services / statistics & numerical data*
  • Female
  • Health Resources* / economics
  • Health Resources* / statistics & numerical data
  • Health Services Needs and Demand / economics
  • Health Services Needs and Demand / statistics & numerical data*
  • Hospitals, Psychiatric / economics
  • Hospitals, Psychiatric / statistics & numerical data*
  • Humans
  • Inpatients / statistics & numerical data
  • Length of Stay / statistics & numerical data
  • Male
  • New Zealand
  • Poverty Areas*
  • Small-Area Analysis