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. 2025 Jul;36(3):e70074.
doi: 10.1002/hpja.70074.

Non-Linear Socioeconomic Inequality in the Distribution of Food Outlets in Metropolitan Melbourne and Regional Victoria, Australia

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Non-Linear Socioeconomic Inequality in the Distribution of Food Outlets in Metropolitan Melbourne and Regional Victoria, Australia

Melvin Barrientos Marzan et al. Health Promot J Austr. 2025 Jul.

Abstract

Issue addressed: Socioeconomic disparities in food environments significantly impact diet quality and health outcomes, yet comparative evidence between metropolitan and regional areas remains limited. We examined spatial and temporal changes in food outlet availability in Victoria, Australia from 2019 to 2023.

Methods: Geospatial data from OpenStreetMap was used to classify food outlets into healthy, less healthy, and unhealthy categories. Outlet densities were calculated within 500 m (walkable) and 2000 m (short driving) buffers from Statistical Area Level 1 centroids. Socioeconomic disparities were assessed using the Index of Relative Socio-economic Advantage and Disadvantage quintiles. Gini coefficients quantified inequality, while Kruskal-Wallis tests, Dunn's post hoc tests, and k-means clustering identified socio-spatial patterns.

Results: In metropolitan Melbourne, both highly disadvantaged (quintile 1) and affluent areas (quintiles 4-5) had significantly higher densities of food outlets (e.g., 2.3 vs. 2.7 healthy outlets per 1000 people within 500 m in 2023), while mid-range socioeconomic areas (quintiles 2-3) had notably lower availability. Regional Victoria exhibited similar trends, with mid-range areas consistently underserved. From 2019 to 2023, Melbourne's Gini coefficients for healthy outlet access improved slightly (0.45-0.43), whereas regional areas worsened (0.52-0.55). Clustering revealed limited healthy food availability in disadvantaged rural clusters and high densities of unhealthy options in urban regional centres.

Conclusions: Food outlet availability in Victoria shows distinct non-linear socioeconomic disparities, disproportionately disadvantaging mid-range socioeconomic areas.

So what: Strategic urban planning and targeted policy interventions in underserved suburban and regional locations are essential for mitigating inequalities and promoting healthier communities.

Keywords: Australia; Melbourne; Victoria; food environment; inequality.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Chloropleth map of food environment clusters in Metropolitan Melbourne. Cluster 1: High IRSAD (Mean IRSAD: 9.0), high density of all food outlets; Cluster 2: High IRSAD (Mean IRSAD: 9.0), very high density of unhealthy and less healthy food outlets; Cluster 3: Average IRSAD (Mean IRSAD: 6.0), low density of all food outlets; Cluster 4: Low IRSAD (Mean IRSAD: 5.0), sparse density of all food outlets; Cluster 5: Low IRSAD (Mean IRSAD: 5.0), moderate density of all food outlets.
FIGURE 2
FIGURE 2
Choropleth map of food environment clusters in Regional Victoria. Cluster 1: Lowest IRSAD (Mean IRSAD: 2.0), low density of all food outlets; Cluster 2: Low IRSAD (Mean IRSAD: 3.0), moderate density of all food outlets; Cluster 3: Moderate IRSAD (Mean IRSAD: 4.0), very high density of unhealthy and less healthy food outlets; Cluster 4: Higher IRSAD (Mean IRSAD: 5.0), sparse food environment.

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