Cited by 351Urban Green Space and HealthEnvironmental Justice and Health DisparitiesHealth disparities and outcomes

The DOI matches its Crossref record; 66 of the 67 references it cites were found in a registry or an index.

Do low-income neighbourhoods have the least green space? A cross-sectional study of Australia’s most populous cities

Open access
Astell-Burt, Thomas, Feng, Xiaoqi, Mavoa, Suzanne, Badland, Hannah M, Giles-Corti, Billie·2014·BMC Public Health

Abstract

BACKGROUND: An inequitable distribution of parks and other 'green spaces' could exacerbate health inequalities if people on lower incomes, who are already at greater risk of preventable diseases, have poorer access. METHODS: The availability of green space within 1 kilometre of a Statistical Area 1 (SA1) was linked to data from the 2011 Australian census for Sydney (n = 4.6 M residents); Melbourne (n = 4.2 M); Brisbane (n = 2.2 M); Perth (n = 1.8 M); and Adelaide (n = 1.3 M). Socioeconomic circumstances were measured via the percentage population of each SA1 living on < $21,000 per annum. Negative binomial and logit regression models were used to investigate association between the availability of green space in relation to neighbourhood socioeconomic circumstances, adjusting for city and population density. RESULTS: Green space availability was substantively lower in SA1s with a higher percentage of low income residents (e.g. an incidence rate ratio of 0.82 (95% confidence interval (95% CI) 0.75, 0.89) was observed for SA1s containing ≥20% versus 0-1% low income residents). This association varied between cities (p < 0.001). Adelaide reported the least equitable distribution of green space, with approximately 20% greenery in the most affluent areas versus 12% availability in the least affluent. Although Melbourne had a smaller proportion of SA1s in the top quintile of green space availability (13.8%), the distribution of greenery was the most equitable of all the cities, with only a 0.5% difference in the availability of green space between SA1s containing 0-1% low income households versus those with ≥20%. Inequity of access, however, was reported across all cities when using logit regression to examine the availability of at least 20% (odds ratio 0.74, 95% CI 0.59, 0.93) or 40% (0.45, 0.29, 0.69) green space availability in the more disadvantaged versus affluent neighbourhoods. CONCLUSION: Affirmative action on green space planning is required to redress the socioeconomic inequity of access to this important public health resource.

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Crossref · 10.1186/1471-2458-14-292

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Figure 1 Spatial patterning of green space in Australia’s most populous cities.
Figure 1 Spatial patterning of green space in Australia’s most populous cities.CC BY · PubMed Central
Figure 2 Patterning of green space by neighbourhood socioeconomic circumstance and city.
Figure 2 Patterning of green space by neighbourhood socioeconomic circumstance and city.CC BY · PubMed Central
Figure 3 Patterning of green space by neighbourhood socioeconomic circumstance and city, using three binary definitions of green space availability. Panel A: Outcome >=10% green space. Panel B: Outcome >=20% green space. Panel C: Outcome >=40% green space (enlarged inset).
Figure 3 Patterning of green space by neighbourhood socioeconomic circumstance and city, using three binary definitions of green space availability. Panel A: Outcome >=10% green space. Panel B: Outcome >=20% green space. Panel C: Outcome >=40% green space (enlarged inset).CC BY · PubMed Central

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Cites

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Research works printed but not linked: 8

  1. The Scottish Government: Good places, better health in Scotland. 2008, The Scottish Government: Edinburgh
  2. Department of Sustainability and Environment: Victorian Planning Provisions. 2013, Melbourne: Victorian State Government
  3. Western Australian Planning Commission: Liveable neighbourhoods: a Western Australian Government Sustainable Cities Initiative. 2004, Western Australian Planning Commission: Perth, WA
  4. Australian Bureau of Statistics: 3218.0 - Regional Population Growth, Australia, 2011: Population estimates and Australia’s new statistical geography. 2012, Canberra: Australian Bureau of Statistics
  5. Australian Bureau of Statistics: Australian Statistical Geography Standard (ASGS): Volume 4 - Significant Urban Areas, Urban Centres and Localities, Section of State. 2011, Canberra: Australian Bureau of Statistics
  6. Australian Bureau of Statistics: Australian Statistical Geography Standard (ASGS): Volume 1 - Main Structure and Greater Capital City Statistical Areas. 2011, Canberra:
  7. Australian Bureau of Statistics: Information paper, Draft Mesh Blocks. 2005, Canberra: Australian Bureau of Statistics
  8. Pink B: Technical Paper: Socio-Economic Indexes for Areas (SEIFA). 2011, Australian Bureau of Statistics: Canberra

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Metadata

Authors
Astell-Burt, T., Feng, X., Mavoa, S., Badland, H. M., & Giles-Corti, B.
Affiliations
  • Western Sydney University (AU)
  • The University of Melbourne (AU)
Venue
BMC Public Health
Published
2014-03-31
Volume
14
Issue
1
Pages
292-292
ISSN
1471-2458 (ISSN-L)
OpenAlex
W2149511701
Cited by
351
References
67
Citations by year
2026: 19 · 2025: 42 · 2024: 55 · 2023: 43 · 2022: 40 · 2021: 53 · 2020: 31 · 2019: 19 · 2018: 16 · 2017: 18 · 2016: 8 · 2015: 6 · 2014: 1
FWCI
7.23
Type
journal article
Language
en
Open access
Locations
  • BMC Public Health (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Minerva Access (University of Melbourne) (submittedVersion, cc-by)
  • Research Online (University of Wollongong) (submittedVersion)
  • RMIT Research Repository (RMIT University Library) (submittedVersion)
  • Figshare (submittedVersion)
  • St Andrews Research Repository (St Andrews Research Repository) (submittedVersion, cc-by)
Funders
  • National Heart Foundation of Australia
  • National Health and Medical Research Council (1004900)
Topics
  • Social Sciences › Urban Studies › Urban Green Space and Health
  • Social Sciences › Sociology and Political Science › Environmental Justice and Health Disparities
  • Social Sciences › Health › Health disparities and outcomes
Keywords
green spaces, parks, low-income neighbourhoods, green space accessibility, health disparities, urban vegetation, green space planning, Australian cities, population density
MeSH terms
Australia, Cities, Cross-Sectional Studies, Environment Design, Plants, Poverty Areas, Residence Characteristics, Socioeconomic Factors, Urban Population, Logistic Models

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