Journal Article

Geographic Variation in Loneliness and Social Isolation in Australia: Socio-Demographic and Healthcare Utilisation Determinants

Pourghaderi, Ahmadreza, Zoungas, Sophia, Nejati, Hossein, Le, Long Khanh-Dao, Filia, Kate, Hayes, Laura, Clifford, Sharon, Mihalopoulos, Cathrine, Lim, Michelle H., Skouteris, Helen, Rizal, Fikru, Berk, Michael, Engel, Lidia, Earnest, Arul

2026

Overview

Background: Loneliness and social isolation are major public health challenges linked to premature mortality and significant healthcare and productivity costs. However, their geographic distribution and socio-demographic determinants remain poorly understood, with few studies applying spatial methods to identify high-need areas and protective factors. Methods: This study aimed to investigate the geographic distribution and determinants of loneliness and social isolation across Australia using a spatial epidemiological approach. Utilising longitudinal data from the Household, Income and Labour Dynamics in Australia (HILDA) survey, along with Australian Bureau of Statistics (ABS) census data, greenness vegetation index and walkability index, we employed Bayesian conditional autoregressive (CAR) models to assess spatial and temporal patterns at the Statistical Area Level 3 (SA3) over a 22-year period and present the relative risks (RR) and credible intervals (CrI). Results: Our analysis revealed spatial variation in the RR of both loneliness and social isolation, with notable hotspots in socioeconomically disadvantaged areas. In multivariable models, area-level socio-economic disadvantage (as measured by the Index of Relative Socio-economic Advantage and Disadvantage, IRSAD) (RR = 0.8, 95% CrI: 0.76–0.85) for the highest quintile (most advantaged) and a higher prevalence of depression and/or anxiety (RR = 4.3, 95% CrI: 3.0–6.1) were associated independently with relative risk of loneliness but not with age structure, remoteness, green space or walkability index. For social isolation, higher average hospital admission rates per region were the strongest factor. Conclusions: The spatial heterogeneity observed in our study underscores the need for place-based public health responses, including community-based interventions and targeted resource allocation, especially in disadvantaged communities.

• Publisher: MDPI AG,Multidisciplinary Digital Publishing Institute (MDPI)
• Subject: Demographic aspects / Distribution / Geography / Health aspects / Health services utilization / Loneliness / Longitudinal studies / Medical care / Mental health / Neighborhoods / Public health / Risk factors / Social isolation / Sociodemographics / Socioeconomic factors / Surveys / Utilization