Evidence map›Paper›PMID 42791367›Full record

ArticleSocial psychiatry and psychiatric epidemiology2026

Geospatial clustering of suicide, mental health, sociodemographic and workforce features in Australia.

Jahidur Rahman Khan, Nan Hu, Michael Hodgins, Vilas Sawrikar, K Shuvo Bakar, Raghu Lingam

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Article in Social psychiatry and psychiatric epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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5 · Who and what money

Authors and funding

6 authors.

Jahidur Rahman KhanDiscipline of Paediatrics, School of Clinical Medicine, UNSW Sydney, Sydney, Australia. jahid.khan@unsw.edu.au.
Nan HuDiscipline of Paediatrics, School of Clinical Medicine, UNSW Sydney, Sydney, Australia.
Michael HodginsDiscipline of Paediatrics, School of Clinical Medicine, UNSW Sydney, Sydney, Australia.
Vilas SawrikarSchool of Psychology, University of Sydney, Sydney, Australia.
K Shuvo BakarSchool of Public Health, University of Sydney, Sydney, Australia.
Raghu LingamDiscipline of Paediatrics, School of Clinical Medicine, UNSW Sydney, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIdentifying geographic clusters with distinct profiles may support evidence-based policy and planning. This study aimed to identify clusters based on suicide rates, proportion of people reporting a mental health condition, sociodemographic characteristics, and mental health workforce features.

methodsArea-level data were obtained for 294 Statistical Area Level 3 (SA3) regions across Australia using routine administrative and census data. Hierarchical clustering of principal components identified clusters, and spatial join-count analysis assessed their spatial concentration.

resultsOur analysis found three clusters. Cluster 1 (N = 136; 46.2%) was characterised by a higher suicide rate and a high proportion of people self-reporting a mental health condition. This cluster was mainly in regional and remote areas with an older population, lower household income and educational attainment, and lower mental health workforce density. Cluster 2 (N = 146; 49.7%) had the lowest suicide rates and the lowest proportion of people reporting a mental health condition; these areas were predominantly metropolitan and characterised by a younger population, fewer Indigenous people, higher income and educational attainment, and higher mental health workforce density. Cluster 3 (N = 12; 4.1%) had the highest suicide rate yet the lowest proportion of people reporting a mental health condition. This final cluster was entirely regional and remote, had the highest Indigenous population proportion, lowest educational attainment, and lowest mental health workforce density. All clusters exhibited significant spatial clustering.

conclusionThis study highlights geographic disparities in mental health and suicide-related profiles across Australia. Prioritising community-level interventions that reduce socioeconomic disparities and improve access to mental health care is crucial in regional and remote areas.

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AustraliaGeographic ClusteringMental IllnessSuicide

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