Journal
INTERNATIONAL JOURNAL OF BEHAVIORAL NUTRITION AND PHYSICAL ACTIVITY
Volume 14, Issue -, Pages -Publisher
BMC
DOI: 10.1186/s12966-017-0621-9
Keywords
Transport walking; Planning policy; Built environment; Urban design; Neighbourhood activity/town centre; Cluster analysis; Land use mix; Geographic information systems
Categories
Funding
- NHMRC Senior Principal Research Fellow Award [1107672]
- Centre for Research Excellence in Healthy, Liveable Communities [1061404]
- Australian Prevention Partnership Centre [9100001]
- University of Melbourne International Research Scholarship (MIRS)
- North & West Metropolitan Region Victorian Department of Health
- NHMRC CRE in Healthy Liveable Communities [1061404]
- National Health and Medical Research Council of Australia [1061404] Funding Source: NHMRC
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Background: Evidence-based metrics are needed to inform urban policy to create healthy walkable communities. Most active living research has developed metrics of the environment around residential addresses, ignoring other important walking locations. Therefore, this study examined: metrics for built environment features surrounding local shopping centres, (known in Melbourne, Australia as neighbourhood activity centres (NACs) which are typically anchored by a supermarket); the association between NACs and transport walking; and, policy compliance for supermarket provision. Methods: In this observational study, cluster analysis was used to categorize 534 NACs in Melbourne, Australia by their built environment features. The NACS were linked to eligible Victorian Integrated Survey of Travel Activity 2009-2010 (VISTA) survey participants (n=19,984). Adjusted multilevel logistic regressions estimated associations between each cluster typology and two outcomes of daily walking: any transport walking; and, any 'neighbourhood' transport walking. Distance between residential dwellings and closest NAC was assessed to evaluate compliance with local planning policy on supermarket locations. Results: Metrics for 19 built environment features were estimated and three NAC clusters associated with walkability were identified. NACs with significantly higher street connectivity (mean: 161, SD:20), destination diversity (mean: 16, SD:0.4); and net residential density (mean: 77, SD:65) were interpreted as being 'highly walkable' when compared with 'low walkable' NACs, which had lower street connectivity (mean: 57, SD:15); destination diversity (mean: 11, SD:3); and net residential density (mean: 10, SD: 3). The odds of any daily transport walking was 5.85 times higher (95% CI: 4.22, 8.11), and for any 'neighborhood' transport walking 8.66 (95% CI: 5.89, 12.72) times higher, for residents whose closest NAC was highly walkable compared with those living near low walkable NACs. Only highly walkable NACs met the policy requirement that residents live within 1km of a local supermarket. Conclusions: Built environment features surrounding NACs must reach certain levels to encourage walking and deliver walkable communities. Research and metrics about the type and quantity of built environment features around both walking trip origins and destinations is needed to inform urban planning policies and urban design guidelines.
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