Mental health and well-being within rural communities: The Australian Rural Mental Health Study
Version of Record online: 18 JAN 2010
© 2010 The Authors. Journal compilation © 2010 National Rural Health Alliance Inc.
Australian Journal of Rural Health
Volume 18, Issue 1, pages 16–24, February 2010
How to Cite
Kelly, B. J., Stain, H. J., Coleman, C., Perkins, D., Fragar, L., Fuller, J., Lewin, T. J., Lyle, D., Carr, V. J., Wilson, J. M. and Beard, J. R. (2010), Mental health and well-being within rural communities: The Australian Rural Mental Health Study. Australian Journal of Rural Health, 18: 16–24. doi: 10.1111/j.1440-1584.2009.01118.x
- Issue online: 18 JAN 2010
- Version of Record online: 18 JAN 2010
- Accepted for publication 24 November 2009.
- Composite International Diagnostic Interview;
- mental disorder;
Objective: This paper outlines the methods and baseline data from a multisite cohort study of the determinants and outcomes of mental health and well-being within rural and remote communities.
Methods: A stratified random sample of adults was drawn in non-metropolitan New South Wales using the Australian Electoral Roll, with the aim of recruiting all adult members of each household. Surveys assessed psychological symptoms, physical health and mental disorders, along with individual-, family/household- and community-level characteristics. A stratified subsample completed a telephone-administered World Mental Health-Composite International Diagnostic Interview (World Mental Health-3.0). Proxy measures of child health and well-being were obtained. Follow up of this sample will be undertaken at one, three and five years.
Results: A total of 2639 individuals were recruited (1879 households), with 28% from remote/very remote regions. A significant relationship was found between recent distress (Kessler-10 scores), age and remoteness, with a linear reduction of Kessler-10 scores with age and the lowest mean scores in remote regions.
Conclusions: Existing rurality categories cannot address the diverse socio-cultural, economic and environmental characteristics of non-metropolitan regions. While it has limitations, the dataset will enable a fine-grained examination of geographic, household and community factors and provide a unique longitudinal dataset over a five-year period.