Are liveable neighbourhoods safer neighbourhoods? Testing the rhetoric on new urbanism and safety from crime in Perth, Western Australia

Accepted Manuscript Are Liveable Neighbourhoods Safer Neighbourhoods? Testing the Rhetoric on New Urbanism and Safety from Crime in Perth, Western Australia Sarah Foster, Paula Hooper, Matthew Knuiman, Fiona Bull, Billie Giles-Corti PII:

S0277-9536(15)00242-7

DOI:

10.1016/j.socscimed.2015.04.013

Reference:

SSM 10043

To appear in:

Social Science & Medicine

Please cite this article as: Foster, S., Hooper, P., Knuiman, M., Bull, F., Giles-Corti, B., Are Liveable Neighbourhoods Safer Neighbourhoods? Testing the Rhetoric on New Urbanism and Safety from Crime in Perth, Western Australia, Social Science & Medicine (2015), doi: 10.1016/j.socscimed.2015.04.013. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Are Liveable Neighbourhoods Safer Neighbourhoods? Testing the Rhetoric on New Urbanism and Safety from Crime in Perth, Western Australia

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Sarah Fostera*, Paula Hoopera, Matthew Knuimanb, Fiona Bulla and Billie Giles-Cortic

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Centre for the Built Environment and Health, School of Sport Science, Exercise & Health and

School of Earth & Environment, The University of Western Australia (M707), 35 Stirling Highway,

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Crawley WA 6009, Australia Email: [email protected]

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Telephone: +61 8 6488 8730

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School of Population Health, The University of Western Australia, 35 Stirling Highway, Crawley

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WA 6009, Australia

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McCaughey VicHealth Centre for Community Wellbeing, Melbourne School of Population Health,

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University of Melbourne Australia

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*Corresponding Author

Acknowledgements

RESIDE was funded by grants from the Western Australian Health Promotion Foundation (Healthway) (#11828), the Australian Research Council (ARC) (#LP0455453) and supported by an Australian National Health & Medical Research Council (NHMRC) Capacity Building Grant (#458688). The first author is supported by a Healthway Health Promotion Research Fellowship (#21363); the second author by a NHRMC CRE in Healthy Liveable Communities postdoctoral

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fellowship (#1061404); and the last author by a NHMRC Principal Research Fellowship (#1004900). Nick Middleton, Sharyn Hickey, Bridget Beasley and Dr Bryan Boruff are gratefully acknowledged for their assistance and advice in the development of the GIS measures in this study, and The Western Australian Land Information Authority (©2003), Western Australian Department of

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Planning for provided the core spatial data. Crime locations were supplied courtesy of the

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Western Australia Police.

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Are Liveable Neighbourhoods Safer Neighbourhoods? Testing the Rhetoric on New Urbanism

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and Safety from Crime in Perth, Western Australia

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Abstract

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New urbanism advocates for the design of the compact, pedestrian-friendly, mixed-use

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developments thought to promote walking. New urbanist proponents also claim their

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developments incur other social and wellbeing benefits, including enhanced safety from crime;

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however there is limited empirical evidence supporting this. We tested the premise that new

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urbanism inhibits crime by examining the relationship between compliance with a planning policy

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based on new urbanism and: (1) residents’ reports of victimisation; and (2) objective crime

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measures. RESIDE Participants (n=603) who had lived in their new developments for 36 months

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completed a questionnaire that included items on their experiences of victimisation. Detailed

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measures quantifying the degree to which these developments (n=36) complied with the policy

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requirements were generated in Geographic Information Systems. Logistic regression examined

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the associations between policy compliance and self-report victimisation, and negative binomial

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log-linear models examined area-level associations between compliance and objective crime. For

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each 10% increase in overall policy compliance, the odds of being a victim reduced by 40%

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(OR=0.60, CI=0.53-0.67, p=0.000). Findings for the individual policy ‘elements’ were consistent

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with this: for each 10% increment in compliance with the community design, movement network,

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lot layout and public parkland elements, the odds of victimisation reduced by approximately 6%

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(p=0.264), 51% (p=0.001), 15% (p=0.000) and 22% (p=0.001) respectively. However, while policy

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compliance correlated with lower odds of self-report victimisation among residents, the

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associations between compliance and development-wide (objective) crime were positive but non-

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significant. The results indicate that planning policies based on new urbanism may indeed deliver

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other social and wellbeing benefits for residents, however they also hint that the design of an

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‘objectively’ safe place may differ from the design of a ‘subjectively’ safe space.

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Key Words: New urbanism; victimisation; crime; safety; planning policy; built environment

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Introduction

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New urbanism advocates for the design of the compact, pedestrian-friendly, mixed-use

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developments thought to promote walking, minimise car dependence and enhance sense of

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community (Congress for the New Urbanism, 2001; Duany et al., 2000). To some extent these

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claims are supported – the accumulated evidence suggests that developments designed in

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accordance with new urbanism principles can positively impact residents walking behaviours (Dill,

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2006; Hooper et al., 2014; Lund, 2003; Rodríguez et al., 2006), and even facilitate social contact

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between residents (Kim & Kaplan, 2004; Leyden, 2003; Talen & Koschinsky, 2014). Proponents of

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new urbanism also claim their developments incur other social benefits for residents, including

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enhanced safety from crime (Duany et al., 2000) however to date; there is little empirical evidence

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to support this assertion (Cozens, 2008; Cozens & Hillier, 2012; Schneider & Kitchen, 2007).

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There are two competing perspectives on the notion that new urbanism creates safer

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neighbourhoods. On one hand, urban planners argue that mixed-use neighbourhoods generate

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more pedestrian traffic, making streets safer through natural surveillance or ‘eyes on the street’

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(Duany et al., 2000; Jacobs, 1961; Zelinka & Brennan, 2001). Jacobs (1961) envisaged that

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pedestrians would make streets lively and interesting to watch, and in turn this would encourage

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further surveillance from adjacent buildings. This approach is embedded within new urbanism,

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despite Jacobs’ caution against transferring her ideas to suburban settings. For example, the 2

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Charter for the New Urbanism emphasises that ‘streets and squares should be safe, comfortable

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and interesting to the pedestrian’, and that by adhering to new urbanism principles (i.e., if places

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are ‘properly configured’) ‘they encourage walking and enable neighbours to know each other and

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protect their communities’ (Congress for the New Urbanism, 2001).

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Conversely, evidence from criminology links key elements of new urbanism with increased crime

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levels (Cozens, 2008; Schneider & Kitchen, 2007). For example, the non-residential land uses that

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provide destinations to walk to (e.g., shopping centres, recreational facilities and transport nodes)

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have been associated with higher levels of property crime (Beavon et al., 1994; Bowes, 2007;

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Brantingham & Brantingham, 1993; McCord et al., 2007), and the presence of drinking venues and

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alcohol sales linked with more violent crime (Gorman et al., 2001; Gruenewald et al., 2006; Popova

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et al., 2009). Similarly, street connectivity is integral to new urbanism as it provides both direct

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and varied walking routes for residents. However, better connected streets (i.e., gridded street

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layouts) are also more easily navigated by would-be offenders, with more potential ‘escape

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routes’ (Brantingham & Brantingham, 1993). Indeed, in the criminology literature there is general

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consensus that higher street connectivity increases vulnerability to crime (Cozens, 2008; Cozens &

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Hillier, 2008; Schneider & Kitchen, 2007). Still, it is also worth noting that the individual attributes

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of a compact, walkable neighbourhood rarely exist in isolation (Sallis et al., 2012), and their

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cumulative presence may be most pertinent to crime. For example, permeable streets may not

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impact crime unless destinations are present that attract potential offenders (Brantingham &

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Brantingham, 1993).

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Despite these differing perspectives on what design features constitute a safer neighbourhood,

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few empirical studies have examined the relationship between new urbanism and crime (Knowles,

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2003) and rarer still are studies that assess the degree of new urban policy implementation and 3

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residents’ experiences of crime. This study addresses this evidence gap and tests the premise that

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new urbanism can enhance personal safety by examining the relationship between compliance

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with a planning policy based on new urbanist principles and: (1) residents’ experiences of

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victimisation; and (2) crimes committed within the development.

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Methods

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Study context

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In February 1998 the Western Australian State Government began trialling the ‘Liveable

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Neighbourhoods Community Design Guidelines’ (LN). This was introduced to replace the

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conventional design codes that had facilitated car dependence and sprawl, and stimulate the

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development of sustainable suburban communities (Western Australian Planning Commission,

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2000). LN is essentially a local interpretation of New Urbanism, tailored to the Western Australian

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context and in 2001 was recognised with an annual charter award from the Congress of New

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Urbanism (Congress for the New Urbanism, 2007).

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The second edition of the guidelines published in 2000 consisted of six general design topics,

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termed ‘elements’ (Western Australian Planning Commission, 2000). Four of these elements

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(community design; movement networks; lot layout; public parkland) aimed to provide an

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alternative approach to the design of (suburban) neighbourhoods by creating more compact,

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pedestrian-friendly neighbourhoods, with good links to public transport services. The key

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intended outcomes of the LN policy were to reduce car dependence and encourage more active

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forms of transport; however the policy also aimed to enhance personal safety, primarily through

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increased surveillance and activity (Western Australian Planning Commission, 2000).

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Measuring implementation of policy requirements 4

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A process evaluation was undertaken to objectively measure the on-ground implementation of 43

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unique, quantifiable requirements from the LN policy across its four elements (community design;

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movement network; lot layout; public parkland using Geographic Information Systems (GIS).

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These detailed measures were created for 36 new housing developments being built in Perth,

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Western Australia – 19 of which purported to be developed according to LN and 17

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‘conventionally designed’ developments that matched these LN developments on size and location

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(i.e., distance from the ocean) (Hooper et al., 2014). The timing of the LN evaluation was chosen

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to coincide with the third time-point (i.e., 36 months) of the RESIDential Environments (RESIDE)

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Project, a longitudinal natural experiment evaluating the impact of LN. Full details of the process

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evaluation methods and the development of measures in GIS for each of these policy

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requirements are reported elsewhere (Hooper et al., 2014). The four elements are briefly

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summarised below.

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Community Design: sets out objectives for designing ‘complete integrated communities’, rather

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than the segregated residential (or dormitory) developments typical of conventionally planned

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suburbs (Western Australian Planning Commission, 2000). A key community design principle

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relates to the configuration of the neighbourhood and town centres, with an emphasis on creating

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more traditional main-street mixed-use centres where pedestrian-scaled, street-fronting retail

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layouts predominate. LN aims to create hubs of destinations with sufficient diversity to be useful

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walkable nodes and which act as community focal points that attract people for a variety of

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activities (Western Australian Planning Commission, 2000).

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Movement Network: LN advocates for a highly interconnected street system with good internal

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and external access aimed at reducing local travel distances and optimising walkable access to

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centres, schools, public transport and other destinations. The policy specifies standards for block 5

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sizes that create a more connected street network, based on the premise that smaller (or shorter)

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blocks create a denser network of streets, and reduce walking distances and increase route

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choices between locations (Dill, 2003; Song, 2005). Further, while the policy recognises cul-de-sac

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are a popular suburban street pattern, and as such does not prohibit their use, it applies standards

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to help limit their use and ensure they do not impede the overall connectivity of the movement

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network. These standards include specifications relating to cul-de-sac length, the provision of

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linking routes at the terminating point of the cul-de-sac, the number of residential lots that should

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be positioned on cul-de-sac and the total proportion of residential dwellings within the

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development that should be situated on these ‘dead-end streets’.

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Lot Layout: This element places an emphasis on creating greater residential densities and the

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provision of a mixture of lot sizes distributed throughout the developments to facilitate housing

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variety, choice and affordability, and to cater for increasingly diverse household types. Standards

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for the provision of smaller lots and locating of lots for mixing of compatible uses near centres and

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public transport stops are stipulated to achieve sufficient densities to support these businesses

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and services.

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Public Parkland: LN requires a minimum contribution of 10% of the gross subdivisible land area in

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new developments be provided as public parkland and identifies three different park types based

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on size and catchment areas to provide for a range of uses and activities: local parks,

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neighbourhood parks and district parks. The policy seeks to provide a range of parkland types

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which are safe and conveniently located for the majority of residents. Under LN schools are also

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encouraged to share their ovals or playing fields as community facilities for out of school hour’s

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use. Unlike current conventional development practices, LN requires that virtually all public

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parkland be overlooked by development, rather than being backed onto by development.

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Quantifying policy compliance

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Policy compliance was defined as the degree to which the construction of the developments

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adhered with, or met, the standards outlined by LN. A simple scoring system was developed to

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quantify the extent to which the 43 measureable requirements had been implemented as

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intended by the LN (Hooper et al., 2014). The level of compliance for each element and overall

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was calculated as the percentage of the maximum policy implementation score

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attainable/intended.

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Participant data

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The sample comprised a subset of participants from the larger RESIDE Project. Briefly, all people

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building homes in one of 73 new developments were invited to participate (response rate 33.4%).

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Once recruited, participants completed a questionnaire before they moved into their new home,

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and on three subsequent occasions after they relocated (at 12, 36 and 84 months). Full details are

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described elsewhere (Giles-Corti et al., 2008). RESIDE was approved by The University of Western

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Australia’s Human Research Ethics Committee.

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While 1812 participants completed the initial baseline survey, 1220 participants (67%) remained in

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the study at 36 months. This cross-sectional study focused on the subset of these RESIDE

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participants (n=603) who completed the 36 month survey and continued to live in one of the 36

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developments that were assessed for compliance with the LN policy. Of the 36 developments

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included in this study, approximately 90% were located in new Greenfield developments on the

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urban fringe. These developments were characterised by expanses of single family detached

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houses with good access to public open space and walking infrastructure (Hooper et al., 2014) but

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relatively poor access to shops and services (Christian et al., 2013; Foster et al., 2010). This

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pattern is typical of new suburban developments in Perth (Hooper et al., 2014). Australian Bureau

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of Statistics (ABS) rankings also indicated the study developments were located in areas with

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relatively low levels of socio-economic disadvantage. Furthermore, compared to the wider Perth

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metropolitan area population, our study sample was slightly older, more likely to be married and

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more affluent (Australian Bureau of Statistics, 2007), reflecting a population group able to access

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finance and purchase a new home.

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The RESIDE questionnaire collected information on a range of demographic variables, including

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participant age, gender, education, marital status and number of children. Self-reported

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victimisation was measured by asking participants whether they, or anyone they personally knew,

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had been the victim the following crimes in their neighbourhood in the last two years: (1)

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household burglary; (2) harassed or threatened while in public; and (3) physically attacked or

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mugged while in public. ‘Objective’ crime location data for the year matching survey completion

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were supplied by the Western Australian Police. Crime measures (counts) were created for

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offences committed within the extents of each of the study development boundaries, focusing on:

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(1) crimes committed against the person in public space (e.g., threats, disorderly behaviour,

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assault; robbery); and (2) actual and attempted burglaries.

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Statistical analysis

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All analyses were conducted in SPSS version 22. First, separate logistic regression models were

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run with generalised estimating equations (GEE) to account for clustering within residential

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development to examine associations between compliance with each of the LN elements, and

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overall policy compliance, and self-report victimisation (binary dependent variable: yes/no).

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Estimated odds ratios from these models represent the increase in odds of self-reported

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victimisation for each 10% increase in the level of compliance with the LN policy (Table 2). All 8

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models adjusted for age, gender, education, marital status, number of children living at home,

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area socio-economic status (IRSD), stage of construction and size of development.

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Next, a series of backwards stepwise elimination models were run separately for the LN

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requirements within each of the four elements to identify the specific requirements from each

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element that were most strongly associated with the victimisation outcome. At each stage, the LN

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requirement with the highest p value (and >0.05) was removed and the model re-fitted. This

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continued until all remaining LN requirements had p values ≤0.05 which constituted the (final)

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multivariate model (Table 3). Again, all models controlled for age, gender, education, marital

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status, number of children living at home, area socio-economic status (IRSD), stage of construction

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and size of development.

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Finally, negative binomial log-linear models examined the area-level associations between LN

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compliance (by element and overall) and number of crimes reported to police occurring within the

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extents of the development (Table 4). These models adjusted for area socio-economic status

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(IRSD), stage of construction and size of development. The log of the number of dwellings in the

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development was included as an offset term so that the estimated effects of compliance scores

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were on the crime rate per dwelling.

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Results

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Approximately 29% of participants reported some form of victimisation in the past two years

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within their local neighbourhood (Table 1). Table 2 presents the (adjusted) odds ratios for the

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associations between LN policy compliance and victimisation. For each 10% increase in the total

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level of compliance, the odds of being a victim reduced by 40% (OR=0.60, CI=0.53-0.67, p=0.000).

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Findings for the individual LN elements were consistent with this overall finding. For each 10% 9

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increment in compliance with the community design, movement network, lot layout and public

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parkland elements, the odds of victimisation reduced by approximately 6% (p=0.264), 51%

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(p=0.001), 15% (p=0.000) and 22% (p=0.001) respectively.

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Table 3 reports the specific requirements (of the 43 that were measured) within each LN element

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that were most strongly associated with self-reported victimisation are shown in Table 3. While

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compliance with the community design element (outlined above) was not significantly associated

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with victimisation, the configuration of the neighbourhood centre appears important. Compared

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to participants with no community centre, those with a ‘big box’ centre configuration were more

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likely to report victimisation (OR=1.42, p=0.031), whereas there was no association between

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having a main street configured centre and victimisation (p=0.676).

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Two movement network requirements were associated with reduced odds of victimisation. A

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higher sidewalk to road ratio (where higher values indicate more roads with an adjacent sidewalk)

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and higher tree density along footpaths were associated with reduced odds of victimisation

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(p=0.017 and p=0.010 respectively). The effect size for tree density along footpaths was

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considerable (OR=0.367, CI=0.17-0.78); however this requirement encapsulated the specificity of

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presence of footpaths and trees (with these trees positioned along the footpath).

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Several lot layout requirements were associated with victimisation. While the overall measure of

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the net residential dwelling density in the development was associated with increased

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victimisation (OR=1.24, p=0.000), other lot layout requirements suggest that the mix of housing

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available may be protective against victimisation. Notably, areas with more diverse housing

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indicated by the percentage of residential lots less than 350m2 (i.e., relatively small, cottage lots)

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and the number of different lot sizes present were both associated with reduced odds of 10

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victimisation (p=0.031 and p=0.018 respectively). Conversely larger mean lot sizes (a measure

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reflecting a lack of housing diversity) were associated with increased odds of victimisation

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(p=0.000).

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The public parkland element requirements stipulating proximate access to different park types

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were consistently associated with reduced odds of victimisation. A higher percentage of houses

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with a park within 400m was associated with reduced odds of victimisation (p=0.000). This

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pattern was consistent for both small (0.3 ≤ 0.5 ha) and large neighbourhood parks (1.5 ≤ 2.5 ha).

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Finally, we tested the development-level associations between LN policy compliance and objective

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measures of crime within the development (Table 4). There were no significant associations

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between LN compliance (overall, or by element) and actual or attempted burglary, or crimes

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committed against the person in public space.

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Discussion

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New urbanism is frequently espoused as generating multiple community benefits, including the

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promotion of walking, public transport use and sense of community, and even enhanced

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community safety (Duany et al., 2000). However, the purported social benefits of new urbanism

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are rarely substantiated in evidence. This study provides empirical evidence that new urbanist

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design has the potential to discourage neighbourhood crime. We tested the impact of compliance

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with a new urbanism inspired planning policy on residents’ experiences of victimisation, and found

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that self-report victimisation reduced with increasing overall policy compliance. This pattern was

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consistent for the four policy ‘elements’ that comprised the overall LN compliance score (albeit

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non-significant for the ‘community design’ element). Furthermore, within each LN ‘element’,

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several individual requirements were significantly associated with victimisation.

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The LN ‘community design’ element emphasises the creation of more traditional main-street

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mixed-use centres where pedestrian-scaled, street-fronting retail layouts predominate (Western

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Australian Planning Commission, 2000). Notably, the ‘community design’ requirements relating to

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the town centre configuration were associated with victimisation, with participants in

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developments served by a ‘big box’ centre more likely to report being a victim. In this context, ‘big

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box’ neighbourhood centres were characterised by clusters of shops and services that

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accommodated the day-to-day needs of local residents, typically surrounded by a generous car

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park provision. These areas can be hostile or intimidating landscapes for pedestrians and cyclists

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as there are often insufficient footpaths, marked crossing areas and traffic controls. Pedestrians

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are often forced to navigate through vast expanses of parking where cars have ‘right of way’

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(Falconer, 2008). By contrast, the main street configured centres position parking at the rear of

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buildings, preserving the connection between the building and street with increased potential for

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natural surveillance. Jacobs (1961) theorised that business proprietors would act as ‘sidewalk

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guardians’ – monitoring interactions and intervening at signs of trouble (Jacobs, 1961). Further,

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pedestrian oriented main streets are thought to encourage social interactions between local

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residents, and have been linked to greater sense of community (Pendola & Gen, 2008) and social

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capital (Wood et al., 2010) - constructs which correlate with enhanced feelings of safety (Foster et

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al., 2010; Wood et al., 2008). For example, Wood et al. (2010) observed a positive association

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between commercial floor area ratio (i.e., a measure of walkable site design where higher values

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indicate less surface area for parking, with shops and services positioned closer to the sidewalk)

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and sense of community (Wood et al., 2010).

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Two individual ‘movement network’ requirements were significantly (negatively) associated with

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victimisation: the proportion of streets with adjacent sidewalks and tree density along footpaths. 12

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Both requirements contribute to a superior environment for pedestrians, and have been found to

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be associated with higher levels of walking among residents (Hooper et al., 2014), potentially

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increasing natural surveillance. Our finding relating to the presence of street trees and

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victimisation warrants further discussion. To date, there is mixed evidence on the relationship

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between vegetation and crime. Vegetation can conceal perpetrators as they select a target,

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commit an offence and flee the scene (Nasar et al., 1993), which is thought to promote fear by

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limiting visibility in the immediate vicinity (Nasar & Jones, 1997). However, in residential settings,

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vegetation has been associated with less fear of crime (Nasar, 1982), a greater sense of safety

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among residents (Kuo et al., 1998; Maas et al., 2009) and lower reported crime (Kuo & Sullivan,

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2001b). Indeed, Donovan and Prestemon (2012) suggest the type and location of vegetation may

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account for conflicting findings (Donovan & Prestemon, 2012). They found that smaller trees on

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residential lots (i.e., that impede visibility) were associated with increased crime, whereas street

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trees (or larger private trees) were associated with lower crime rates. Further, while street trees

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contribute to a more pleasant environment (Cervero & Kockelman, 1997) they also act to slow

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traffic speeds, increasing the safety of the street for pedestrians and cyclists (Burden, 2006; City of

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Melbourne, 2011; Western Australian Planning Commission, 2009) and affording more effective

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natural surveillance from vehicles.

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This connection between vegetation and victimisation was also confirmed by the ‘public parkland’

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element results. LN aims to ensure that the design of development surrounding parks provides

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high levels of visual supervision by residents to enhance personal and property security,

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deterrence of crime and vandalism, and promotion of safety for park users (Western Australian

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Planning Commission, 2000). Three specific requirements were negatively associated with

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victimisation, and all related to the proportion of dwellings within 400m of a park. While there

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were some significant results based on park size (i.e., local or large neighbourhood park), the 13

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effect size was greatest for the proportion of dwellings within 400m of ‘any park’. This is

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consistent with a recent evidence review that concluded: ‘the greener the residential setting, the

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safer it is perceived’ (Maruthaveeran & van den Bosch, 2014 p.13). Indeed, our study emphasised

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the relevance of both park access and street trees to residents’ reports of victimisation. Several

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potential pathways could explain this connection between green vegetation/space, and

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victimisation: (1) an aesthetically pleasing public realm might draw residents into the streets and

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parks, enhancing natural surveillance; (2) visually appealing streetscapes might attract further

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surveillance from surrounding houses, regardless of whether residents are ‘people watching’; (3)

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green vegetation can create a calming restorative environment that helps alleviate feelings of

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anger, frustration and aggression (Kuo & Sullivan, 2001a); and (4) attractive public spaces provide

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settings where people can gather, interact and develop social ties (Bedimo-Rung et al., 2005;

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Chiesura, 2004; Kuo et al., 1998; Wolch et al., 2014), potentially enhancing safety. Indeed, a

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comparison of new urbanist and traditional developments attributed the greater sense of

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community in new urbanist communities to more natural features and shared spaces (Kim &

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Kaplan, 2004).

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The final LN element focuses on ‘lot layout’ and includes requirements relating to lot size, housing

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diversity and residential density. While development-wide residential density was positively

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associated with being a victim, the other lot layout findings suggested that, independent of overall

343

density, the design and form of density could mitigate reports of victimisation. For instance,

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requirements relating to the provision of smaller lots (i.e., less than 350m2) and a greater diversity

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of lot sizes were significantly associated with reduced odds of victimisation. Further, as mean lot

346

sizes increased within the development, so too did self-report victimisation. On balance, these

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results indicate that, while density per se may increase the odds of victimisation, the design of

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residential lots and range of housing stock available in the development may enhance safety. In

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this primarily residential (suburban) setting, small lots are situated closer to the street (i.e., smaller

350

setbacks), increasing the visual connection between the residence and street. Indeed, LN

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recognises that the height, character and visual permeability of lot boundaries and fences impacts

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the potential for surveillance from the building over the park or street. The policy also aims to

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provide lots without street frontages being dominated by garages and parked cars (Western

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Australian Planning Commission, 2000). This stands in contrast to the conventional style of

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residential construction where the dwelling is typically set back from the street on a large lot,

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served by a drive way and often behind, or obscured by, a garage or car-port.

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The notion that house design can help augment safety is supported by other research in the same

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developments which indicated that house designs that created opportunities for natural

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surveillance (e.g., visible windows, verandahs) contributed to less graffiti and disorder in the street

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(Foster et al., 2011). Furthermore, by providing diverse housing options, developments cater to a

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broader population (e.g., young people, retirees, mixed incomes), where residents’ different daily

363

schedules and use of space ensure the more continuous presence of ‘eyes on the street’ or

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guardians monitoring the neighbourhood over different time-frames (Jacobs, 1961). The charter

365

of new urbanism states that ‘within neighbourhoods a broad range of housing types and price

366

levels can bring people of diverse ages, races and incomes into daily interaction, strengthening the

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personal and civic bonds essential to an authentic community’ (Congress for the New Urbanism,

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2001). To some extent, our findings indicate that adherence to the urbanism planning principles

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intended to enhance social equity (Talen, 2002) could produce co- benefits, including community

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safety.

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371 372

Our study examined associations between LN and both residents’ reports of victimisation and

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development-level crime (i.e., crimes reported to police). Results indicate that the 15

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implementation of LN impacts residents’ experiences of crime, or at the very least indicates they

375

are less aware or attuned to local crime. Conversely, LN policy compliance correlated with slightly

376

more development-wide crime, although these latter results were non-significant. Nonetheless,

377

these contrasting findings may help bridge the urban planning and criminology perspectives on

378

the design features that constitute a ‘safe’ neighbourhood. They hint that the design of an

379

‘objectively’ safe place may differ from the design of a ‘subjectively’ safe space. This notion could

380

be further complicated by the nuances of how residents’ perceptions of safety from crime are

381

measured. For example, other research set in these same developments suggests key attributes

382

of a compact walkable neighbourhood (e.g., retail) impact fear of crime (i.e., an emotional

383

reaction to crime) and perceptions of crime (i.e., a cognitive assessment of crime) differently

384

(Foster et al., 2010; Foster et al., 2013a; Foster et al., 2013b). While residents may perceive crime

385

to be present (or even problematic) in their local area, if the crime they perceive does not cause

386

them to feel unsafe, or fearful, it may not negatively impact their day-to-day experiences (Foster &

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Giles-Corti, 2008).

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Limitations:

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This study had several limitations. First, we focused primarily on self-reported victimisation, which

391

combined three types of crime (i.e., household burglary, harassment or threatening behaviour,

392

physical attack or mugging) and included both direct and indirect victimisation (i.e., hearing about

393

a crime second hand from a friend or family member) (Austin et al., 2002; Hale, 1996). While it

394

could be anticipated that this outcome would better capture local crime than other self-report

395

measures (such as fear of crime or perceptions of crime), it should not be regarded as a proxy for

396

reported crime within the development as: (1) it includes offences that would often not be

397

reported to police (e.g., minor harassment or threatening behaviour); (2) participants who are

398

more fearful about crime could have a heightened awareness and recollection of offences

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committed against both themselves and their friends and family; and (3) it focuses on offences

400

within the neighbourhood, however the area that residents perceive as constituting their

401

‘neighbourhood’ does not necessarily match their ‘development’ (i.e., the scale of analysis for the

402

reported crime outcome). Arbitrarily defined neighbourhoods may bear little resemblance to

403

what a person actually perceives their neighbourhood to be (Chaix et al., 2009; Smith et al., 2010).

404

Nonetheless, the self-report victimisation measure enabled us to examine participants’ relatively

405

recent experiences of crime in the vicinity of their residential development. Second, our sample

406

comprised participants that remained in their new neighbourhoods after 36 months, however we

407

cannot discount the possibility that participants who found crime to be problematic in their new

408

neighbourhoods may have moved away. Third, our study participants were all homeowners living

409

in single family detached housing, typically located in new suburban green field developments

410

with relatively low crime rates. This sample was not representative of the wider Perth

411

metropolitan area as it reflected a group that was both willing and financially able to move to a

412

new home on the urban fringe. However, while it is possible our findings are specific to this

413

somewhat ‘middleclass’ sample, they are nonetheless directly applicable to many new suburban

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areas unfolding throughout Australia and the United States (US) that typically incorporate

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conventional design principles. Finally, our study was cross-sectional so causality cannot be

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determined.

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However, this study also has several strengths. Precise, policy-specific measures of new

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developments were created in GIS – providing objective measures of the on-ground

420

implementation of the LN policy. While overall levels of policy compliance were low (Hooper et

421

al., 2014), our findings confirm that with more faithful adherence to the LN policy requirements,

422

residents tend to experience less crime. Furthermore, our evaluation was comprehensive in its

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423

examination policy compliance and both residents’ reports of victimisation and crimes reported to

424

police.

425

Conclusion

427

This study provides empirical evidence that new urbanist design can impact neighbourhood crime.

428

Our findings revealed that increased compliance with a new urbanist inspired planning policy

429

correlated with lower odds of self-report victimisation among residents. Furthermore, our

430

unpacking of the individual requirements that comprised the policy ‘elements’ underscored the

431

importance of the town centre configuration, a comprehensive network of footpaths (ideally with

432

tree coverage), proximate access to parks, and the provision of diverse housing stock. However, it

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should also be noted that our findings for policy compliance and actual development-wide crime

434

were positive but non-significant. To some extent, these results bridge the opposing perspectives

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from planning and criminology disciplines on what constitutes a ‘safe’ neighbourhood. Indeed,

436

this dichotomy raises important questions about the type of environments in which people enjoy

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and want to live. For some, crime might be a necessary and acceptable trade-off for living in a

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(potentially) more vibrant, liveable walkable community (Foster et al., 2014).

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Smith, G., Gidlow, C., Davey, R., & Foster, C. (2010). What is my walking neighbourhood? A pilot study of English adults' definitions of their local walking neighbourhoods. International Journal of Behavioral Nutrition and Physical Activity, 7, 34. Song, Y. (2005). Smart Growth and Urban Development Pattern: A Comparative Study. International Regional Science Review, 28, 239-265. Talen, E. (2002). The social goals of new urbanism. Housing Policy Debate, 13, 165-188. Talen, E., & Koschinsky, J. (2014). Compact, Walkable, Diverse Neighborhoods:Assessing Effects on Residents. Housing Policy Debate, 24, 717-750. Western Australian Planning Commission. (2000). Liveable Neighbourhoods. Perth: State of Western Australia. Western Australian Planning Commission. (2009). Street Trees and Utility Planning Discussion Paper. Perth, WA. Wolch, J.R., Byrne, J., & Newell, J.P. (2014). Urban green space, public health, and environmental justice: The challenge of making cities ‘just green enough’. Landscape and Urban Planning, 125, 234-244. Wood, L., Frank, L.D., & Giles-Corti, B. (2010). Sense of community and its relationship with walking and neighborhood design. Social Science and Medicine. Wood, L., Shannon, T., Bulsara, M., Pikora, T., McCormack, G., & Giles-Corti, B. (2008). The anatomy of the safe and social suburb: an exploratory study of the built environment, social capital and residents' perceptions of safety. Health and Place, 14, 15-31. Zelinka, A., & Brennan, D. (2001). Safescape. Chicago: American Planning Association.

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Table 1 Characteristics of the 603 RESIDE participants from the 36 residential developments Characteristic

Gender (male) Mean age (SD) Education Secondary or less Trade/certificate Bachelor or higher Marital status Married/defacto Separated/divorced Single Children at home (yes) Victimisation (yes)

Percentage 37.5% 43.2 (11.7) 33.3% 39.3% 27.4%

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86.7% 9.6% 3.6% 52.6% 28.9%

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Victimisation1 OR (95% CI)

LN compliance

Mean (SD)

Total LN compliance

47.23 (7.07)

0.60 (0.53,0.67)

0.000

Community Design

37.21 (22.22)

0.94 (0.83,1.05)

0.264

Movement Network

46.96 (4.79)

0.49 (0.31,0.76)

0.001

Lot Layout

45.99 (18.35)

0.84 (0.77,0.93)

Public Parkland

50.82 (11.07)

0.78 (0.67,0.90)

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p

0.000 0.001

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*Separate models depict the increase in odds of victimisation for each 10% increase in the level of policy compliance. 1 All models control for age, gender, education, marital status, number of children, area socio-economic status, stage of construction and size of development. Bold denotes p≤0.05.

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Table 2: Associations between LN policy compliance, overall and by element, and victimisation.

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Table 3: Associations between compliance with specific design requirements from each LN element associated and victimisation. Victimisation Liveable Neighbourhoods Policy Requirement n

OR (95% CI)

p

Community Design None

93

1.00

Big Box

395

1.42 (1.03, 1.96)

0.031

Main St

115

0.93 (0.65, 1.32)

0.676

603

0.98 (0.96, 1.00)

0.017

603

0.37 (0.17, 0.78)

0.010

Movement Network 1

Sidewalk to road ratio [OR for 1 unit increase in sidewalk:road ratio] 2

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Tree density along footpaths [OR for 1 unit increase in number of trees per km of footpath] Lot Layout 3

Residential dwelling density (development wide) [OR for 1 unit increase in #dwellings ÷ land (ha) zoned residential]

Mean residential lot size [OR for 1 unit increase in mean lot size] 4

603

Number of different lot sizes present [OR for 1 unit increase in different lot sizes present]

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Public Parkland

1.24 (1.16, 1.32)

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Percent of residential lots ≤350m [OR for 1 unit increase]

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Configuration of neighbourhood centre ≤1600m

Percent houses within 400m of any park [OR for 1 unit increase]

0.000

603

0.97 (0.95, 1.00)

0.031

603

1.01 (1.01, 1.01)

0.000

603

0.72 (0.56, 0.95)

0.018

603

0.98 (0.97, 0.99)

0.000

603

0.99 (0.99, 1.00)

0.043

603

0.99 (0.99, 1.00)

0.000

5

Percent houses within 400m of a local neighbourhood park [OR for 1 unit increase]

Final models for each Liveable Neighbourhoods element derived from backwards stepwise elimination. Models depict the increase in odds of victimisation for each 10% increase in the level of compliance with each specific requirement. All models adjust for demographic characteristics (age; gender; education, marital status, children ≤18 years and under living at home), area socio-economic status, stage of construction and scale of development. Bold denotes p≤0.05. 1 Sidewalk to road ratio = length of all footpath segments alongside/adjacent to/parallel with the roads ÷ length of all roads. 2 Tree density along footpaths = number of trees along footpaths (within a 5m buffer) ÷ length (km) of footpaths within the development. 3 Residential density (development wide) = Net residential dwelling density = number of residential dwellings ÷ area (ha) of residentially zoned (and constructed) land. 4 Lot mix score = the number of different lot sizes present (categories: ≤350m2; >350 - ≤550m2; >550 - ≤750m2; >750 ≤950m2; >950 m2) (value from 1-5). 5 Local neighbourhood park is classified as 0.3 ≤ 0.5 ha. 6 A large neighbourhood park is classified as 1.5 ≤ 2.5 ha. Note: ‘Sidewalk’ refers to footpaths adjacent to roads, whereas ‘footpath’ refers to all sealed paths regardless of location.

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Percent houses within 400m of a large neighbourhood park [OR for 1 unit increase]

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Table 4: Associations between LN policy compliance, overall and by element, and crime reported within the development.

LN compliance

Crimes against person in public RR CI p

Total LN compliance

1.39

0.76,2.54

0.281

1.58

0.71,3.50

0.259

Community Design

1.05

0.83,1.32

0.692

1.11

0.86,1.47

0.420

Movement Network

0.93

0.49,1.76

0.814

1.55

Lot Layout

1.24

0.96,1.60

0.107

1.11

Public Parkland

1.07

0.82,1.40

0.621

1.13

0.374

0.76,1.62

0.573

0.74,1.74

0.565

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0.59,4.05

Separate negative binomial log-linear models for number of crimes adjust for area socio-economic status, stage of construction and scale of development, with log of number of dwellings included as an offset term. RR: Relative increase in crime rate per dwelling associated with a 10% increase in compliance. Crime against the person in public space: Range 0-26; mean=3.03 (SD=5.69) Actual and attempted burglary: Range 0-146; mean=23.22 (SD=31.00)

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Actual & attempted burglary RR CI p

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ACCEPTED MANUSCRIPT Research Highlights

There is limited evidence that new urbanism design principles can help limit crime.

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We tested the impact of compliance with a new urban style planning policy on crime. For each 10% increase in compliance, self-report victimisation fell by 40% (p=0.000).

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Associations between policy compliance and objective crime were non-significant.

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New urbanism may deliver additional social and wellbeing benefits for local residents.