This section briefly examines the process of undertaking the literature reviews reported in chapters one and two, as a precursor to examining the methods that were used to address the central research questions. The first literature review examined evidence on the contribution of community resource access to health and wellbeing; and the second examined the main planning and policy drivers in community resource location and allocation, both internationally and in New
Zealand.
For each literature review, a similar strategy was used. The first phase of each
search began with readings that were either based on personal knowledge or were
provided references of other relevant material for attention, and allowed identification of keywords for more widespread literature search ing.
In the second phase, keyword searches in relevant databases were undertaken. The searches required a number of iterations to narrow the literature down to appropriate articles. To examine the contribution of community resources to health and wellbeing, a keyword search of the Medline, Current Contents and Geobase on line databases were undertaken to identify journal articles. A range of keywords were used, including "amenity", "facilities", "health services", "access" and "accessibility", "health", "wellbeing", "physical activity", "obesity", "place", "social capital", and "social connections".
Examination of the planning and policy determinants of urban community resource access was u n dertaken using the Expanded Academic, Index New Zealand, Science Direct, JSTOR and Geobase databases. Keywords used in the search included
"urban amenity", "access" "policy", "planning", "theory", "location", "facility",
"urban design", "sustainability" and "Agenda 2 1 ".
Further searches were undertaken using Massey University and the University of Auckland's online catalogues for reports and publications on these topics. Another search stage identified appropriate literature from the bibliographies of publications selected in the preceding stages.
Acq uaintance with the literature identified a number of relevant organisations with Internet websites and publications available for down loading, ranging from large scale government bodies and NGOs through to smaller NGOs and research organisations. Accordingly, relevant reports and publications available online from these organisations were obtained.
Through reading the widespread range of literature, key themes were identified and synthesised to identify findings. The process of synthesis was an iterative one, requiring repeated reading and summary of findings and themes, which were constantly related back to the overall research topic.
Measuring and analysing accessibility
In order to measure the distribution of access to community resources in each city, an area-level accessibility index was developed. This index was used as a basis for examining associations of community resource access with socio-economic
population patterns. The analyses are undertaken at two distinct geographic scales: the neigh bourhood street block level (Census meshblocks), and the aggregated city level. Using this approach, it is possible to explore the distribution of community resources both within each city, as well as between the two cities.
Community Resource Accessibility Index
The tool used to measure resource access in the two cities under investigation was the Community Resource Accessibility Index (CRAI), which was developed using geographic information systems (GIS). The CRAI is an area-level indicator of relative access to urban services, facilities and amenities.
Composition of the CRA'
I n this study, the New Zealand Census meshblock forms the basic u n it of analysis. Meshblocks are the smallest area unit available for analysis. In urban settings a m eshblock approximates one or several street blocks. The centroid (nominal centre) of each meshblock is used as a p roxy for the l ocation of people's homes.
Across New Zealand, Census meshblocks had a mean population of 97 people (at
the time of the 200 I Census), but in the areas under study, the mean population was 1 37. The availability of such "small area microdata" is a critical feature of New Zealand population data that is not available in many other countries, such as the U K (Brown et al. 2000). The small geographic and population size of the Census mesh block provides a finely-grained means of area-level analysis, and avoids some
of the problems associated with the ecological fallacy resulting from aggregation to
large areas, as discussed later in this chapter.
An important feature of this research is its focus on urban community resource
access. Therefore, only those mesh blocks that could be classified as u rban were included in the analysis. Statistics New Zealand's categorisation of Census
meshblocks as urban or non-urban was applied to eliminate non-urban meshblocks. This had the effect of removing 1 8 mesh blocks within the Waitakere Ranges, west of Waitakere City, and retaining all meshblocks i n North Shore City. The final dataset contained 2,5 3 2 meshblocks defined as urban by Statistics New Zealand, comprising 1 ,424 from North Shore City and I , I 08 from Waitakere (referred to in the analysis as the "Waitakere urban area").
The CRAI is made up of 36 types of services, facilities and amenities (called sub
domains), which were operating or in existence in 200 I . The CRAI is grouped into six domains:
I . Sport and recreational facilities (including parks, beaches, libraries and sports clubrooms)
2. Public transport and commu nication (bus, train and ferry routes, and public
telephones)
3. Shopping facilities (including dairies, cafes, banks, supermarkets and service stations)
4. Educational facilities (ranging from pre-school through to tertiary)
5. Health facilities (including GP clinics, Plunket4, pharmacies and hospitals)
6. Social and cultural facilities (including community centres, marae, churches
and Citizens' Advice Bureaux)
As the above list of domains makes clear, the term "community resources", as used in this research , brings together a range of publicly-provided resources, such as parks and community facilities, as well as privately provided resources, such as dairies and pharmacies, and those that are provided by both public and private sectors, such as schools and health facilities. The scope of community resources therefore extends further than much previous research, which has often focused on what Pinch ( / 985) calls "collective consumption". Pinch described collective consumption as "those goods and services provided through the public sector on a non-market basis, which reveal variations i n both quantity and quality between areas" (Pinch 1 985, p. 1 4). I nclusion of market-oriented resources therefore provides a richer representation of local environments than those based on solely publicly-provided resources.
The full list of domains and sub-domains is detailed in Table 3 (p. 1 20).5
The CRAI was developed using ArcView 3.2a GIS software for geocoding and network analysis, and Microsoft Access and SAS for the development of the accessibility index itself. What fol lows is a summary of the methodology used i n the development of the CRA!. The methodology for the development of the CRAI is explained in m ore detail in Witten et al (2003) and Exeter et al (2003). The author of this thesis collaborated extensively in the development of the CRAI, and in the drafting of each of these publications (Exeter et al. 2003; Witten et al. 2003).
It should be noted however that the analysis of CRAI data in this research is based on 200 I meshblock bou ndaries, rather than the 1 996 meshblocks wh ich we re applied in Witten et al.
Facilities chosen for inclusion in the CRAI were open-entry, non-specialist services, where comparable data was avai lable in both cities. The community resou rces used in this research have been selected on the basis of being potentially health promoting. The assumption therefore is that the community resources included in this study all have "positive externalities", or will produce gen erally beneficial effects for those living in close proximity (Pinch 1 985).
Table 3: Domain and Subdomain data
1 .0 I Low
1 .02 Sports & Leisure Facilities
1 .03 1 .04 High 2000 1 000 15000 Mobile hsoo Base
booo
Choice Count Count Count If---
-.-..-
- I 2 3 31 .05 Arts & Crafts 1 500 Count 4
1 .06 etc. 1 500 Count is
Domain 3: Sho��inK facilities
3.0 1
3.02
3.03 Fruit & stores 3.04 Service station 3.05 Bank 1 000 12000 2000 1 500 1 500 Y/N
-
.-
3.08 MallDomain 4: Educational facilities
4.0 1 reo 4.02 Primary school Y/N 750 1 000 Count 4.03 2000 Count 4.04
�ooo
Count 3 4.05 institutionsbooo
----
... Domain 5: Health-
5.0 I Primary Care I 000 5.02It
500 5.03I
A&E 150005.04
!
P1unket Maori well childI
__
6.03 6.04 Centres Houses Y/N ,I I IY/N Community Halls 6.05
It is i m portant to note that the CRAI only inclu ded services, facilities and amenities where a physical location could be assigned. Therefore, organ isations such as crafts gu il ds or sports clubs that do not operate a pu rpose-built facil ity were not inc luded in the CRAI. However, the community centre or sports centre that they might use was included in the CRAI.
In the development of the CRAI, the location of over 4,200 services, facil ities and amenities across North Shore and Waitakere Cities were compiled into a database. These were then geocoded - a process in which a map reference is ass igned to the service, facility or amen ity. The eRAI was developed to contribute to a study, funded by the Health Research Cou ncil of New Zealand, examin ing the role of local environments in the health and well-being of caregivers of young children (aged up to ten years). The range of facilities included in the CRAI, and other decisions
regarding choice issues and ranking of different resou rces, were therefore
constructed with this popu lation group in mind. These issues were incorporated into the development of the index after consultation with a foc us group of
caregivers of d iffe rent ethnicities. For other popu lation groups, such as older people, a similar range of resources would be included, although the way they may rank them may differ.
Network analysis and relative accessibility
Various means of measuring geographic access ibility have been developed since the I 970s. One of the most straightforward means is the contai ner model, in which access is measured by a simple count of the number of facilities or services that lie
withi n a particular geograph ic unit. This however is also one of the most criticised, in that the m odel excludes services, facilities and amenities that lie outside each geographic unit's boundaries, even if they are in close proximity Uoseph and Phillips
1 984; Talen and Anselin 1 998). To overcome such problems, gravity models are
commonly employed. These are based on identifying facilities or services that can be reached from specific points using distances or travel times (Lovett et al. 2000; McLafferty 1 982; Mladenka 1 978; Talen and Anselin 1 998).
Using a gravity model approach, the CRAI measures relative IDeational accessibility to
community resources, using the meshblock centroid (the nominal centre of the
meshblock) as a proxy for location of people's homes. The index is relative in the
sense that measures of accessibility are based on data detail ing the availability of facilities within the entire study area, rather than using an "optimal" measure of
accessibility. The i ndex is IDeational in the sense that access is based on distance to
services, facilities and amenities, rather than use or satisfaction.
Use of gravity models as a means of investigating access is not without its
detractors. A key criticism is that distance measures convey an assumption that all journeys made by the population begin in the same place - such as in this research, the meshblock centroid which acts as a proxy for location of homes in a given area (Pirie 1 979). Given the population group (caregivers of young children) that is the particular focus of the CRAI, this is not an unreasonable assumption, and the small scale of the Census meshblock prevents over-generalisation at larger area scales.
Other research into accessibility examines subjective perceptions or satisfaction with resources (Sooman and Macintyre 1 995). Such research complements distance-based analyses of community resource access such as the
eRAI,
and provides insights into facility use, and the benefits of use to local populations. However, while subjective satisfaction adds the dimension of people's experiences of community resources, research indicates that such measures may be affected by lack of knowledge of alternatives. As discussed in chapter one, Macintyre and Ellaway's Glasgow study found spatial measurement of resou rce access yielded different results from people's subjective perceptions of the same environments, suggesting knowledge and experience affect levels of satisfaction (Macintyre and Ellaway 2000). Thus, non-subjective distance-based measures provide an important indicator of access that complements perception-based measures. Analysis of community resource access in the research undertaken in this thesis will therefore use non-subjective measures alluded to by Macintyre and Ellaway (2000), in terms of the number of facilities, services and amenities within varying d istances of points within the cities under examination.Network analysis was used to determine accessibility, based on the community
resources that could be reached from the centroid of each meshblock using road
networks. Use of network analysis is well-established in accessibility research, and
overcomes problems of Euclidean (or "crow-flies") approaches that fail to take
account of barriers between points that may impede access, such as tidal inlets or
motorways (Cromley and McLafferty 2002; Talen and Anselin 1 998). It should be
also h as its limitations. It does not for example take into account traffic volu mes, travel-times or i mpedances such as one-way streets (Cromley and McLafferty 2002) . Nevertheless, this form of network analysis is considerably more precise than Euclidean analysis, and un like approaches based on travel times, does not assume a particular mode of transport.
Relative accessibility was determined by defi ning an accessible distance from each meshblock centroid and identifying the number of facilities with in that distance. Because expectations of what would be a reasonable travelling distance differ according to the types of community resou rce, a variety of distances were applied to determine accessibility. For exam ple, a small local park or a dairy (store) woul d b e considered a neighbourhood fac il ity, while a com munity centre would b e
located at a subu rban scale, wh ile a hospital or tertiary institute wou ld be considered to be a district or regional facility. With this in mind, resource
accessibil ity was calculated independently for each subdomain at distances of SOOm, 7S0m, I SOOm, 2000m, 3000m and 5000m from each meshblock centroid. For the purpose of constructing the index, an accessible distance was defined as the distance whereby 50% of the meshblocks in the combined cities under study had access to at least one service, amenity or facility in a subdomain.
Figu re I (p. 1 26) illustrates the process of defining network study areas, withi n
which a l l services, facilities and amen ities were counted. T h e figu re shows the
network distances. This process was repeated from every meshblock centroid in the study area.
Quality scores were also assigned to three subdomains. Facilities within the parks sub-domain were given a value between I and 3, reflecting categorisation as low, medium or high quality, depending on the range of park facilities, based on council information on the number of facilities available at each park. Public transport facilities were also assigned a value between I and 3, based on the number of bus, train or ferry routes passing within specified distances of each meshblock centroid. libraries were assigned a quality score of I (Iow) or 2 (high) for mobile and base libraries respectively, on the basis of the extended range of services available at base libraries.
Each subdomain was assigned its median accessible distance, and its ranking
specified by the focus group of caregivers. Subdomains were also assigned a choice dimension, indicating whether caregivers felt it was important to have a range of each type of facilities to choose from (such as educational or recreational facilities), or whether it was important for each type of facility to simply be present (such as dairies or banks). Where a number of facilities were i dentified for a subdomain, al l facilities within the median distance from a mesh block centroid were counted. Where simply the presence of a facility was deemed necessary, only one of each type of facility within the median distance was counted. The choice labels are also detailed in Table 3, with "Y/N" indicating that only presence or absence was
cou nted, and "Cou nt" indicating all facilities of that subdomain within the accessible
range were counted.
Figure I: Network analysis, based from mesh block centroid within Devonport
DSe .. Droom D 750m D 1000m _1500m D :2000m D :DOOm Drooom • Centrad 1.500 3.000
Accessibil ity for each facil ity i ncluded within each subdomain was calculated by
weighti ng the number of facilities by the qual ity, and also by the inverse of the rank
assigned to each facil ity, then summed within each meshblock. All accessibil ity
scores were then summed for eac h subdomain, and then sum med by domai n.
These domain level scores were then standardised to create a score ranging
between zero and five and then sum med over the domains to create an overall accessibil ity score for each meshbl ock. This scal ing ensured that each domain had
each of the six domain, the maximum C RAI score was 30. However, in its
completed form, the in dex has a range of mesh block-level scores rangi ng from zero to a maxim u m score of 26.8 (indicating no meshblock had maximum access across all domains).
Limitations of the CRAI
The approach of using an index developed for a specific population group has its lim itations. In particu lar, it is cu rrently unclear to what extent the CRAI can be applied to a general population group, or to population groups other than
caregivers. Not only will the weightings differ for other population groups, but it is possi ble that other types of com munity resou rces could be included, such as pubs or youth centres.
It is clear, though, that in any study, choices need to be made. It would have been possible to do a stand-alone analysis using preferences based on general population or another popu lation group using a separate focus group to establish weightings. However, the lin kages with the wider research programme on caregivers would have been lost. Instead, a decision was made to use the eRAI data i n its