Skip to main content

Advertisement

Log in

Mental health in the suburbs: an investigation of differences in the prevalence of depression across Canberra suburbs using data from the PATH Through Life Study

  • Original Article
  • Published:
Journal of Public Health Aims and scope Submit manuscript

Abstract

Aim

International research has shown that the characteristics of areas such as neighbourhood socioeconomic disadvantage, are associated with mental health; however, multilevel modelling approaches have shown that little variance in depression scores is explained at the area level. This study investigated the distribution of depression across suburbs in the Canberra and surrounding region of Australia, and the influence of area- and individual-level measures of socioeconomic position.

Subject and methods

Analysis of data is taken from Wave 3 of the Personality and Total Health (PATH) through Life study with 3,342 respondents aged 28–32 years or 48–52 years who were residents of Canberra and Queanbeyan. Depression was assessed with the Patient Health Questionnaire. Multilevel logistic regression models were used to evaluate variance components and compare suburb measures of socioeconomic circumstances and respondent-reported household income.

Results

Less than 1% of variance in the distribution of depression was explained at the area level. While area-level socioeconomic measures were associated with depression; this effect was weak and largely explained by the inclusion of individual-level income. Further analysis did demonstrate a non-linear relationship between area-level socioeconomic measures and depression, with some evidence of an association between the most disadvantaged suburbs and greater prevalence of depression over and above the effect of individual characteristics.

Conclusion

We found little evidence of variance in depression at the area level but did find that the prevalence of depression was elevated in the most disadvantaged suburbs. Individual risk factors appear to have the strongest influence on depression.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Anstey KJ, Christensen H, Butterworth P, Easteal S, Mackinnon A, Jacomb T, Maxwell K, Rodgers B, Windsor TD, Cherbuin N, Jorm AF (2011) Cohort profile: The PATH Through Life project. Int J Epidemiol doi:10.1093/ije/dyr025

  • Australian Bureau of Statistics (2004) Australian standard geographical classification (ASGC). ABS, Canberra

    Google Scholar 

  • Australian Bureau of Statistics (2008a) Information paper: an introduction to socio-economic indexes for areas (SEIFA), 2006 ABS, Canberra

  • Australian Bureau of Statistics (2008b) Socio-economic indexes for areas (SEIFA), Data only, 2006 ABS, Canberra

  • Bayer JK, Hiscock H, Morton-Allen E, Ukoumunne OC, Wake M (2007) Prevention of mental health problems: rationale for a universal approach. Arch Dis Child 92(1):34–38

    Article  PubMed  CAS  Google Scholar 

  • Butterworth P, Rodgers B, Jorm AF (2006) Examining geographic and household variation in mental health in Australia. Aust New Zealand J Psychiarty 40(5):491–497

    Article  Google Scholar 

  • Butterworth P, Rodgers B, Windsor TD (2009) Financial hardship, socio-economic position and depression: results from the PATH Through Life Survey. Social Sci Med 69:229–237

    Article  Google Scholar 

  • Crump C, Sundquist K, Sundquist J, Winkleby MA (2011) Neighborhood deprivation and psychiatric medication prescription: a Swedish national multilevel study. Ann Epidemiol 21:231–237

    Article  PubMed  Google Scholar 

  • Diez-Roux AV (2000) Multilevel analysis in public health research. Annu Rev Public Health 21:171–192

    Article  PubMed  CAS  Google Scholar 

  • Faris REL, Dunham HW (1939) Mental disorders in urban areas. University of Chicago Press, Chicago

    Google Scholar 

  • Fortney J, Rushton G, Wood S, Zhang L, Xu S, Dong F, Rost K (2007) Community-level risk factors for depression hospitalizations. Adm Policy Ment Health Ment Health Serv Res 34(4):343–352

    Article  Google Scholar 

  • Haines VA, Beggs JJ, Hurlbert JS (2011) Neighborhood disadvantage, network social capital, and depressive symptoms. J Health Soc Behav 52(1):58–73

    Article  PubMed  Google Scholar 

  • Link BG, Phelan J (1995) Social conditions as fundamental causes of disease. J Health Soc Behav 35:80–94

    Google Scholar 

  • Lowe B, Spitzer RL, Grafe K, Kroenke K, Quenter A, Zipfel S, Buchholz C, Witte S, Herzog W (2004) Comparative validity of three screening questionnaires for DSM-IV depressive disorders and physicians’ diagnoses. J Affect Disord 78(2):131–140

    Article  PubMed  Google Scholar 

  • Mair C, Diez-Roux AV, Galea S (2008) Are neighbourhood characteristics associated with depressive symptoms? A review of evidence. J Epidemiol Community Health 62:940–946

    PubMed  CAS  Google Scholar 

  • Mirowsky J, Ross CE (1999) Economic hardship across the life course. Am Sociol Rev 64(4):549–569

    Google Scholar 

  • Mirowsky J, Ross CE (2001) Age and the effect of economic hardship on depression. J Health Soc Behav 42:132–150

    Article  PubMed  CAS  Google Scholar 

  • Page A, Morrell S, Taylor R, Carter G, Dudley M (2006) Divergent trends in suicide by socio-economic status in Australia. Soc Psychiatry Psychiatr Epidemiol 41(11):911–917

    Article  PubMed  Google Scholar 

  • Pickett KE, Pearl M (2001) Multilevel analyses of neighbourhood socioeconomic context and health outcomes: a critical review. J Epidemiol Community Health 55(2):111–122

    Article  PubMed  CAS  Google Scholar 

  • Pikhartova J, Chandola T, Kubinova R, Bobak M, Nicholson A, Pikhart H (2009) Neighbourhood socioeconomic indicators and depressive symptoms in the Czech Republic: a population based study. Int J Public Health 54:283–293

    Article  PubMed  Google Scholar 

  • Ross CE (2000) Neighborhood disadvantage and adult depression. J Health Soc Behav 41(2):177–187

    Article  Google Scholar 

  • Snijders TAB, Bosker RJ (1999) Multilevel analysis: an introduction to basic and advanced multilevel modeling. Sage, Thousand Oaks, CA

  • Spitzer RL, Williams JBW, Kroenke K, Linzer M, Degruy FV, Hahn SR, Brody D, Johnson JG (1994) Utility of new procedure for diagnosing mental-disorders in primary-care: the Prime-MD-1000 Study. JAMA 272(22):1749–1756

    Article  PubMed  CAS  Google Scholar 

  • Spitzer RL, Kroenke K, Williams JBW (1999) Validation and utility of a self-report version of PRIME-MD: The PHQ primary care study. JAMA 282(18):1737–1744

    Article  PubMed  CAS  Google Scholar 

  • Wainwright NWJ, Surtees PG (2004) Area and individual circumstances and mood disorder prevalence. Br J Psychiatry 185:227–232

    Article  PubMed  Google Scholar 

  • Weich S (2005) Absence of spatial variation in rates of the common mental disorders. J Epidemiol Community Health 59:254–257

    Article  PubMed  Google Scholar 

  • Weich S, Holt G, Twigg L, Jones K, Lewis G (2003a) Geographic variation in the prevalence of common mental disorders in Britain: a multilevel investigation. Am J Epidemiol 157(8):730–737

    Article  PubMed  Google Scholar 

  • Weich S, Twigg L, Holt G, Lewis G, Jones K (2003b) Contextual risk factors for the common mental disorders in Britain: a multilevel investigation of the effects of place. J Epidemiol Community Health 57(8):616–621

    Article  PubMed  CAS  Google Scholar 

  • Weiss L, Ompad D, Galea S, Vlahov D (2007) Defining neighborhood boundaries for urban health research. Am J Prev Med 32:S154–S159

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

Thanks to K. Anstey, H. Christensen, A. Mackinnon, S. Easteal, T. Jacomb, K. Maxwell and the team of PATH interviewers for their contribution to the research. Funding for data collection was provided by Unit Grant 973302 and Program Grant 179805 from the National Health and Medical Research Council (NHMRC). P. Butterworth was funded by NHMRC Fellowship No. 525410.

Conflict of interest

The authors declare that they have no conflict of interest.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Peter Butterworth.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Butterworth, P., Leach, L.S. & Olesen, S.C. Mental health in the suburbs: an investigation of differences in the prevalence of depression across Canberra suburbs using data from the PATH Through Life Study. J Public Health 20, 525–531 (2012). https://doi.org/10.1007/s10389-011-0482-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10389-011-0482-7

Keywords

Navigation