Development of the Australian neighborhood social fragmentation index and its association with spatial variation in depression across communities
We know little about how community structures influence the risk of common mental illnesses. This study presents a new way to establish links between depression and social fragmentation, thereby identifying pathways to better target mental health services and prevention programs to the right people in the right place.
A principal components analysis (PCA) was conducted to develop the proposed Australian neighborhood social fragmentation index (ANSFI). General practice clinical data were used to identify cases of diagnosed depression. The association between ANSFI and depression was explored using multilevel logistic regression. Spatial hot spots (clusters) of depression prevalence and social fragmentation at the statistical area level 1 (SA1) were examined.
Two components of social fragmentation emerged, reflecting fragmentation related to family structure and mobility. Individuals treated for depression in primary care were more likely to live in neighborhoods with lower socioeconomic status and with higher social fragmentation related to family structure. A 1-SD increase in social fragmentation was associated with a 16% higher depression prevalence (95% CI 11%, 20%). However, the association attenuated with adjustment for neighborhood socio-economic status. Considerable spatial variation in social fragmentation and depression patterns across communities was observed.
Developing a social fragmentation index for the first time in Australia at a small area level generates a new line of knowledge on the impact of community structures on health risks. Findings may extend our understanding of the mechanisms that drive geographical variation in the incidence of common mental disorders and mental health care.
KeywordsSocial fragmentation index Depression Mental disorders Geographic information systems (GIS) Primary care
We would like to thank Australian Research Council‘s support of data collection via Dr Bagheri’s DECRA (DE140101570). PJB and ALC are supported by NHMRC fellowships 1083311 and 1122544. We also thank all 16 general practices from the west Adelaide area that provided clinical data.
Compliance with ethical standards
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
- 1.World Health Organization (2014) Mental health: strengthening our response. WHO. http://www.who.int/mediacentre/factsheets/fs220/en/. Accessed 12 Sept 2016
- 3.Wittchen HU, Jacobi F, Rehm J, Gustavsson A, Svensson M, Jönsson B, Olesen J, Allgulander C, Alonso J, Faravelli C, Fratiglioni L, Jennum P, Lieb R, Maercker A, van Os J, Preisig M, Salvador-Carulla L, Simon R, Steinhausen HC (2011) The size and burden of mental disorders and other disorders of the brain in Europe 2010. Eur Neuropsychopharmacol 21(9):655–679. https://doi.org/10.1016/j.euroneuro.2011.07.018 CrossRefPubMedGoogle Scholar
- 4.RANZCP (2016) Economic cost of serious mental illness and comorbidities in Australia and New Zealand. RANZCP. https://www.ranzcp.org/Files/Publications/RANZCP-Serious-Mental-Illness.aspx. Accessed 9 Oct 2016
- 6.Lee Y-C, Chatterton ML, Magnus A, Mohebbi M, Le LK-D, Mihalopoulos C (2017) Cost of high prevalence mental disorders: findings from the 2007 Australian national survey of mental health and wellbeing. Aust N Z J Psychiatry 51(12):1198–1211. https://doi.org/10.1177/0004867417710730 CrossRefPubMedGoogle Scholar
- 7.Berkman LF, Glass T (2000) Social integration, social networks, social support, and health. In: Berkman LF, Glass T (eds) Social epidemiology. Oxford University Press, New York, pp 137–173Google Scholar
- 9.Pearson AL, Ivory V, Breetzke G, Lovasi GS (2014) Are feelings of peace or depression the drivers of the relationship between neighbourhood social fragmentation and mental health in Aotearoa/New Zealand? Health Place 26:1–6. https://doi.org/10.1016/j.healthplace.2013.11.002 CrossRefPubMedGoogle Scholar
- 10.Curtis S, Copeland A, Fagg J, Congdon P, Almog M, Fitzpatrick J (2006) The ecological relationship between deprivation, social isolation and rates of hospital admission for acute psychiatric care: a comparison of London and New York City. Health Place 12(1):19–37. https://doi.org/10.1016/j.healthplace.2004.07.002 CrossRefPubMedGoogle Scholar
- 13.Sampson RJ, Morenoff JD, Gannon-Rowley T (2002) Assessing “Neighborhood effects”: social processes and new directions in research. Ann Rev Sociol 28(1):443–478. https://doi.org/10.1146/annurev.soc.28.110601.141114 CrossRefGoogle Scholar
- 18.Fagg J, Curtis S, Stansfeld SA, Cattell V, Tupuola AM (1982) Arephin M (2008) Area social fragmentation, social support for individuals and psychosocial health in young adults: evidence from a national survey in England. Soc Sci Med 66(2):242–254. https://doi.org/10.1016/j.socscimed.2007.07.032 CrossRefGoogle Scholar
- 31.van Baal PH, Engelfriet PM, Hoogenveen RT, Poos MJ, van den Dungen C, Boshuizen HC (2011) Estimating and comparing incidence and prevalence of chronic diseases by combining GP registry data: the role of uncertainty. BMC Public Health 11:163. https://doi.org/10.1186/1471-2458-11-163 CrossRefPubMedPubMedCentralGoogle Scholar
- 33.Gabert R, Thomson B, Gakidou E, Roth G (2016) Identifying high-risk neighborhoods using electronic medical records: a population-based approach for targeting diabetes prevention and treatment interventions. PLoS One 11(7):e0159227. https://doi.org/10.1371/journal.pone.0159227 CrossRefPubMedPubMedCentralGoogle Scholar
- 35.Bagheri N, McRae I, Konings P, Butler D, Douglas K, Del Fante P, Adams R (2014) Undiagnosed diabetes from cross-sectional GP practice data: an approach to identify communities with high likelihood of undiagnosed diabetes. BMJ Open 4(7):1–10. https://doi.org/10.1136/bmjopen-2014-005305 CrossRefGoogle Scholar
- 37.Australian Bureau of Statistics Australian Statistical Geography Standard (ASGS). http://www.abs.gov.au/websitedbs/D3310114.nsf/home/Australian+Statistical+Geography+Standard+(ASGS). Accessed 24 Aug 2018
- 42.Takagi D, Kondo K, Kondo N, Cable N, Ki Ikeda, Kawachi I (2013) Social disorganization/social fragmentation and risk of depression among older people in Japan: multilevel investigation of indices of social distance. Soc Sci Med 83:81–89. https://doi.org/10.1016/j.socscimed.2013.01.001 CrossRefPubMedGoogle Scholar
- 47.Organisation WH (2016) Shanghai declaration on promoting health in the 2030 agenda for sustainable developmen. https://www.who.int/healthpromotion/conferences/9gchp/shanghai-declaration/en/. Accessed 20 Oct 2018
- 48.Salinas-Pérez JA, García-Alonso CR, Molina-Parrilla C, Jordà-Sampietro E, Salvador-Carulla L (2012) Identification and location of hot and cold spots of treated prevalence of depression in Catalonia (Spain). Int J Health Geograph 11(1):36. https://doi.org/10.1186/1476-072X-11-36 CrossRefGoogle Scholar
- 49.Rodero-Cosano ML, Salinas-Pérez JA, González-Caballero JL, García-Alonso CR, Lagares-Franco C, Salvador-Carulla L (2016) A multi-level analysis of the relationship between spatial clusters of outpatient-treated depression, risk factors and mental health service planning in Catalonia (Spain). J Affect Disord 201:42–49. https://doi.org/10.1016/j.jad.2016.04.024 CrossRefPubMedGoogle Scholar
- 50.Furst M, Reynolds J, Salinas JA, Tsou C, Rock D, Hopkins J, Bell T, Woods L, McLoughlin L, Stretton A, Mendoza J, Bagheri N, Salvador-Carulla L (2018) The integrated atlas of mental health of the perth north primary health network region. Australian National University and Western Australia Primary Health Alliance (WAPHA), PerthGoogle Scholar