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Use of a Systematic ObservationalMeasure to Assess and CompareWalkability for Older Adults inVancouver, British Columbia andPortland, Oregon NeighbourhoodsHabib Chaudhury a , Ann F. I. Sarte a , Yvonne L. Michael b , AtiyaMahmood a , Erin M. Keast c , Cristian Dogaru d & Andrew Wister aa Department of Gerontology, Simon Fraser University, Vancouver,BC, Canadab Department of Epidemiology and Biostatistics, Drexel University,Philadelphia, USAc Department of Public Health and Preventive Medicine, OregonHealth & Science University, OR, USAd College of Health and Human Sciences, Oregon State University,OR, USA

Available online: 29 Jul 2011

To cite this article: Habib Chaudhury, Ann F. I. Sarte, Yvonne L. Michael, Atiya Mahmood, Erin M.Keast, Cristian Dogaru & Andrew Wister (2011): Use of a Systematic Observational Measure to Assessand Compare Walkability for Older Adults in Vancouver, British Columbia and Portland, OregonNeighbourhoods, Journal of Urban Design, 16:4, 433-454

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Use of a Systematic Observational Measure to Assess

and Compare Walkability for Older Adults in

Vancouver, British Columbia and Portland, Oregon

Neighbourhoods

HABIB CHAUDHURY*, ANN F. I. SARTE*, YVONNE L. MICHAEL**,ATIYA MAHMOOD*, ERIN M. KEAST†, CRISTIAN DOGARU‡ &ANDREW WISTER*

*Department of Gerontology, Simon Fraser University, Vancouver, BC, Canada; **Department of

Epidemiology and Biostatistics, Drexel University, Philadelphia, USA; †Department of Public

Health and Preventive Medicine, Oregon Health & Science University, OR, USA; ‡College of

Health and Human Sciences, Oregon State University, OR, USA

ABSTRACT This study assessed neighbourhood walkability for older adults in eightneighbourhoods of Vancouver, British Columbia and Portland Oregon, utilizing the newlydeveloped environmental audit tool ‘SWEAT-R’. The discrete variable based data arecomplemented with qualitative observation data. Findings indicate that the audit tool has a95% or higher inter-rater reliability for more than 80% of the items. Neighbourhoodenvironmental data suggest that neighbourhoods in Vancouver region have more urbandesign features supportive of walking behaviour. Sidewalk and street life environmentalfeatures were relatively similar across all four Portland neighbourhoods, however, therewere notable differences in sidewalk characteristics among the four Vancouverneighbourhoods. The audit tool is useful in documenting walkable features in urban andsuburban neighbourhoods with particular relevance to older adults’ needs.

Introduction

Walkable neighbourhood design and its relevance to public health have garneredresearch attention from multiple disciplines, including health and behaviouralsciences, city planning, transportation and urban design and geography. The‘walkability’ of a neighbourhood has particular relevance to maintaining theindependence of an ever-growing elderly population that will prefer to age inplace in their own homes and communities. Statistics in the United States andCanada reflect significant population ageing. Seniors as a proportion of thenational population is the highest it has ever been in both countries, particularlyfor the 80-plus age group (Statistics Canada, 2008). Population ageing hasincreased attention on ‘active ageing’, which is defined by the World Health

Correspondence Address: Habib Chaudhury, Department of Gerontology, Simon FraserUniversity, #2800-515 West Hastings Street, Vancouver, BC, V6B 5K3 Canada. Email:chaudhury@sfu.ca

Journal of Urban Design, Vol. 16. No. 4, 433–454, November 2011

1357-4809 Print/1469-9664 Online/11/040433-22 q 2011 Taylor & FrancisDOI: 10.1080/13574809.2011.585847

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Organization (WHO) as “the process of optimizing opportunities for health,participation and security in order to enhance quality of life as people age” (WHO,2002, p. 12). Engagement in physical activity is recognized as enhancing quality oflife in older adults. Substantial evidence indicates regular engagement in at least30 minutes moderate-intensity, aerobic physical activity on five or more days perweek (or vigorous intensity aerobic physical activity at least 20 minutes a day,three days per week) improves overall well being and helps maintain functionalindependence in later life (Blumenthal & Gullette, 2002; Nelson et al., 2007).

The ageing process often accompanies declining sensory perceptions (e.g.reduced vision and hearing, difficulty in depth perception), physiological changes(e.g. reduced muscle and bone mass, slower reflexes), generalized signs ofpsychological difficulties (e.g. lower stress threshold, depression) and chronicillnesses (e.g. arthritis, diabetes, heart disease, hypertension) that contribute tochallenges in physical mobility and functioning and/or cognitive decline, which inturn pose as barriers to a full range of activities and safe/secure navigation of thebuilt environment (Calkins, 2001; Frank et al., 2003; Quadagno, 2005). Researchers(e.g. Frank et al., 2003) have argued that physical activity plays a pivotal role tocounter or delay many negative health conditions and the onset of chronic disease.In fact, regular physical activity such as walking may alleviate depression in olderadults and improve quality of life. There is an increasing salience of the localneighbourhood setting to quality of life of older adults (e.g. Abbott et al., 2009;Giles-Corti & Donovan, 2002; Kendig, 2003; Satariano & McAuley, 2003). Due to areduced level of physical functioning and/or early-mid stage dementiaconditions, older adults are more likely to use environments close to home forwalking and other physical activities either for transportation or for recreation.The added potential benefit of use of the near home environment is increasedsocial interaction, which in turn could help with mental health challenges.

Walking is recognized as the most frequent and accessible form of exercise forolder adults. Other physical activities, such as cycling, or participating instructured exercise classes at a seniors or recreational centre, are also commonlyengaged in within a person’s residential neighbourhood. These interrelated issueshave prompted development of standardized methods to measure neighbour-hood physical environmental characteristics and their associations with physicalactivity in older adults.

In their recent review of the state of the science for measuring the builtenvironment for physical activity, Brownson et al., (2009) identified three broadcategories of built environment measures currently in use: perceived measures(data obtained by self-report from the population of interest, e.g. seniors); archivaldatasets (often layered and analyzed with GIS information); and observationalmeasures (data obtained using systematic observational audits). Observationalaudits may be considered advantageous to use in place of, or in combination with,perceived measures in order for researchers to distinguish objective aspects of theenvironment from the perceptions of environmental quality that individualsreport in interviews or self-administered questionnaires. Observational auditsthat rely on systematic data collection by trained observers may further beappropriate when the study focus is on physical activity that occurs within theimmediate neighbourhood setting since they are designed to capture data atstreet-scale (e.g. measure elements presence of buffer zones, presence ofsidewalks, existence of kerb cuts, etc.) that are not typically available fromGeographic Information Systems (GIS). While a number of environmental audit

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tools have been developed to date (Brownson et al., 2004; Hoehner et al., 2007;Pikora et al., 2002), the majority are not designed with older adults in mind.

Gauvin et al. (2005) explored Neighbourhood Active Living Potential (NALP)for community-dwelling seniors living in urban and suburban settings inMontreal, Canada. These researchers examined three main categories using anaudit tool: Activity Friendliness (to assess the neighbourhood physicalcharacteristics); Safety (associated with the physical and social characteristics ofa neighbourhood); and Density of Destinations (neighbourhoods with low densityof destinations have a restricted number and variety of destinations for engaging inmeaningful personal or collective pursuits). The tool used by Gauvin et al. was notoriginally intended for use in research specific to older adults, and nor was theconceptual framework on which it is based directly informed by theories relevantto the elderly (Craig et al., 2002). Recently developed audit instruments that weredesigned specifically with seniors in mind include the Healthy Aging ResearchNetwork Environment Audit Tool (PRC-HAN Environmental Audit Tool)(Healthy Aging Research Network, 2003), and the Seniors Walking EnvironmentalAudit Tool (SWEAT) (Cunningham et al., 2005) and its subsequently revisedversion Seniors Walking Environmental Audit Tool - Revised (Michael et al., 2009).These tools account for street-level characteristics that are identified in theliterature to influence an older adult’s ability to be active. SWEAT and its revisedversion, SWEAT-R, were developed following an extensive review of audit toolsand literature on the physical activity of older adults (Cunningham et al., 2005). Theaudit tool organizes items into four broad topic areas that were adapted fromSPACES—Systematic Pedestrian and Cycling Environmental Scan, recognized tobe one of the earliest environmental measurement tools developed using atransdisciplinary approach (Pikora et al., 2002). Currently, there are more than 20audit tools available (Brownson et al., 2009), however, only a few have shownsensitivity to the needs of older adults. Notable environmental audit tools include:Systematic Pedestrian and Cycling Environmental Scan (SPACES), IrvineMinnesota Inventory (from University of California-Irvine and University ofMinnesota), University of Maryland Urban Design Tool, Pedestrian EnvironmentData Scan (PEDS) (from University of Maryland) and Walking Route Audit Tool forSeniors (WRATS) (from San Diego State University and University of California,San Diego). A comparative summary of these tools is presented in Table 1.

The SWEAT tool has undergone extensive inter-rater reliability testing andhas demonstrated good-to-excellent agreement on most items, and was recentlyrevised to include several additional items to improve its reliability and ease ofuse for raters (Michael et al., 2009). Both the SWEAT-R and PRC-HAN tools can beused in tandem with a qualitative observational component that solicits moredescriptive information on the neighbourhood setting by the trained observer/-auditor. This additional data gathering piece is considered a strength of both toolsas it provides contextual information above and beyond the individual ratings ofitems gathered with the structured audit tool. As far as the authors of this paperare aware, neither tool has been used to determine the walkability of Canadianneighbourhoods for older adults.

Brownson and colleagues (2009) identified the need for refinement of existingtools and methods for measuring the physical environment. For observationalmeasures that tend to be comprehensive and utilize a time-consuming andresource-heavy data collection process, efforts must be taken to test their reliabilityand validity in multiple settings, and to compare the results with other studies.

Systematic Observational Measure to Assess Walkability 435

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Table

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Thus, the present paper presents the reliability results of using the SWEAT-R in aselection of neighbourhoods within the metropolitan regions of Portland, Oregonand Vancouver, British Columbia—two regions within the northwestern part ofNorth America. The paper also compares descriptive neighbourhood datagathered using SWEAT-R in the two regions. Potential challenges in using the toolin different settings and recommendations for further tool refinement are alsoprovided. Neighbourhood data presented in this paper form part of researchactivities undertaken in the first year of a three-year study that explores physicaland social environmental characteristics of neighbourhoods and their relationshipto physical activity in older adults.

Methods

Neighbourhood Selections

Four neighbourhoods in the Portland metropolitan area and four neighbourhoodsin Metro Vancouver were audited using SWEAT-R and its secondary observationform. Similar to another study exploring neighbourhood environments andphysical activity in older adults (Gauvin et al., 2008), the current study used censustract clusters as proxies for neighbourhoods. According to Statistics Canada(2001), census tracts (CTs) are small, relatively stable geographic areas withincensus metropolitan areas with a population that usually averages 4000(minimum of 2000, maximum of 8000). CT boundaries follow permanent andeasily recognizable physical features; the area within the boundaries is ashomogenous as possible in terms of socio-economic characteristics at the time it iscreated. The US Census Bureau uses a similar definition of census tracts (2008). Inthis study, the initial pool of census tracts from which a final selection ofneighbourhoods was drawn was limited to those where individuals 65 years ofage and older comprised at least 13% of its total population. This proportion waschosen as it reflects the average percentage of seniors in both the province ofBritish Columbia and the state of Portland in 2001 national censuses. Thisminimum criterion was also to ensure that neighbourhoods representative ofareas where older adults live were identified.

In order to increase variability of physical environmental features that couldbe observed using the audit tool, half of the selected neighbourhoods in eachregion were chosen to represent more traditional, urban neighbourhoods whilethe other half were chosen to represent post-war, suburban neighbourhoods. Assuch, a primary neighbourhood selection criterion was population density,measured as total population per hectare of land. This variable was chosen as asimple and straightforward measure of walkability, with less dense neighbour-hoods hypothesized to be less walkable and higher density neighbourhoodshypothesized to be more walkable. The initial pool of neighbourhoods was splitinto deciles based on density scores. Final selections were pulled from the highand low end of the population density range.1 In Portland, the final fourneighbourhood selections had a population density that ranged between 10.53and 19.37 households per hectare. The four selected Vancouver neighbourhoodshad a population density that ranged between 10.2 and 81.3.2

Median household income at the CT level was also considered in the finalneighbourhood selection process. This factor was included to increase socio-economic variability of the chosen neighbourhoods in each region. In 2001,

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average median household income in the Portland metropolitan region wasUS$46 360 while in Vancouver it was US$39 952. Of the two higher densityneighbourhoods selected in each region, one was to represent an area with lowerthan average household income while the other was to represent an area withhigher than average household income. Of the final neighbourhood selections, thehighest median household income was US$61 935 and US$59 245 in Portland andVancouver, respectively. The lowest median household income was US$30 892and US$23 965, respectively. The final selections in each region fit the matrixshown in Table 2, where x denotes a neighbourhood.

Observational Measures

Seniors Walking Environmental Assessment Tool-Revised (SWEAT-R). The originalSWEAT was developed to examine features of the physical environment withinthe neighbourhood setting that are pertinent to seniors, such as places to rest andwidth and evenness of sidewalks. It categorizes items within four broad domainsadapted from an existing conceptual framework (Pikora et al., 2002). Thesedomains include: (1) functionality, reflecting structural aspects of theneighbourhood; (2) safety from personal crime and traffic conditions; (3)aesthetics, reflecting visual appeal and quality of surroundings; and destinations,reflecting the availability of services, public transportation, and parking in thearea. SWEAT developers assessed its inter-rater reliability and found it to be goodto excellent, although functionality and destinations items were less reliable thanothers (Cunningham et al., 2005).

In 2007, the original SWEAT was revised (SWEAT-R) with the addition of newitems and the integration of items from the Irvine-Minnesota Inventory (IMI). TheIMI was designed as a comprehensive tool that is flexible enough to tailor to aperson’s specific research needs. In addition, IMI includes more items than theoriginal SWEAT on land uses (e.g. specific types of commercial, institutional andpublic space are inventoried) and items on gathering places (e.g. outdoor coffeeshops) which have been found to enhance aesthetic quality and perception ofsafety in a public space (Boarnet et al., 2006; Cunningham & Michael, 2004). Therevised SWEAT closely follows IMI’s standardized response categories, has apaper version format to ease the data collection process, and has comprehensivetraining instructions. A total of 165 items are included in SWEAT-R that eitherhave empirical evidence or are considered as influential in supporting orhindering physical activity. The items were identified after an extensive reviewand analysis of the existing environmental audit tools and related literature inbuilt environment, active living and gerontology. Figures 1–4 illustrate items thatare included in the four domains of the tool.

Table 2. Neighbourhood selection by population density and median householdincome

WALKABILITY Measured by

INCOME High LowHigh X1 X3Low X2 X4

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Conceptually, SWEAT-R acknowledges and adopts two broad types of physi-

cal activity: recreational and utilitarian physical activity. Recreational physical

activity is undertaken during a person’s leisure hours, e.g. walking for pleasure

either in a park or in a neighbourhood street. These physical activities are usually

non-purposive or purely for enjoyment (Frank et al., 2003). Utilitarian physical

activity is undertaken as a consequence of doing other things (e.g. working,

shopping, travelling, etc.) (Frank et al., 2003). The SWEAT-R was found to have

improved reliability over the original SWEAT and took less time to complete while

collecting more data (see Michael et al., 2009 for more details). The SWEAT-R tool is

available online at http://www.sfu.ca/uploads/page/07/SWEAT-R_v9_CIHR_

Revised-09-07.pdf

Secondary observation form. A secondary observation form was also developed by

Cunningham and colleagues (2005) as a companion tool to SWEAT. The form

captures global aspects of the neighbourhood and provides a qualitative assessment

of the setting from the perspective of the observers. The secondary observation form

was based on feedback received from qualitative experts and research assistants

who had used the original form. The revised form asks observers to comment on

primary and secondary land uses, quality of public gathering places, and

pedestrian safety and convenience at the neighbourhood level.

Non-continuous sidewalk can pose a significantchallenge in walking for older adults

Presence of transit stop with shelter and seatingcan serve as an easily identifiable and moreusable feature

Seating with back and side support responds wellto older adults with reduced physical functioning

Publicly accessible washroom can be an importantamenity for older adults

Figure 1. Examples of items representing the ‘Functionality’ category of SWEAT-R

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Data Collection

Paired observers training. Four research assistants (two per region) received one-and-a-half days training in Vancouver prior to data collection. Training led byresearch investigators encompassed both classroom and field components.Training manuals with detailed explanations for each item in SWEAT-R wereprovided and the secondary observation form was discussed in detail. ThePortland-based observers had previous experience in using SWEAT-R and wereundergraduate students in health-related disciplines. While Vancouver observerswere new to auditing they were completing graduate studies in gerontology at thetime of data collection and thus had an understanding of how environmentimpacts ageing. None of the observers were formally trained in any design orplanning disciplines. Observers worked in pairs but performed auditsindependently; in other words, they did not consult with each other aboutcoding decisions. A minimum number of SWEAT-R items did require actuallymeasuring features (e.g. buffer zone width and kerb height) so these were done bythe paired observers together. Each observer completed an observation form foreach of the neighbourhood settings in which they conducted observations.Observers did not consult with each other when completing the observation forms.

Street segments audited. SWEAT-R data were collected along a sample of streetsegments in each neighbourhood. These segments were randomly selected, with amaximum of 60 segments audited per neighbourhood. In total, 160 unique

Easily accessible park with wide walking pathssupporting of a person using a cane or walker

Grocery close to the street can provide easy accessfor walkers or people using transit

Neighbourhood shops or mall Farmer’s market can be a destination, as well as asetting for walking behaviour

Figure 2. Examples of items representing the ‘Destination’ category of SWEAT-R

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segments were observed across the four Portland metropolitan neighbourhoodsand 197 unique segments were audited across the four Vancouver metropolitanneighbourhoods.

Auditing conditions. Audits were completed from September to early Decemberin 2007. Audits in Portland were observed in 8-hour shifts over a 7-week period.Audits in Vancouver were observed in 2–6 hour shifts (average shift length was 4hours) over a 10-week period. Vancouver observers rated just over 70% of thesegments as having an ‘average’ difficulty rating, and just over 8% with a‘difficult’ or ‘very difficult’ rating. In contrast, Portland observers rated 58% ofsegments as ‘easy’, 10% as ‘average’ and less than 1% as ‘difficult’.

Portland and Vancouver have similar, temperate climates. Averagetemperature in Portland during data collection was 53.48F (sd¼ 3.4) and inVancouver it was 48.08F (sd ¼ 4.6). It was raining while audits were beingcompleted for 19% of segments in Portland and 28% of segments in Vancouver.Average time to complete SWEAT-R was almost double the time in Vancouverthan for Portland (11.2 minutes (sd ¼ 5.0) compared to 5.6 minutes (sd ¼ 3.2)).

Inter-rater Reliability Analysis of SWEAT-R by Region

Inter-rater reliability was assessed by comparing the audits of paired observers forone-quarter of the total number of segments observed in Portland and Vancouver

Nature feature such as flowers and trees can makewalking on the sidewalk more attractive

Well-maintained building may provided aperception of safety and security

Well-designed and maintained park/playground candraw people into healthy activities

Public garden can provide aesthetic merit to thesegment

Figure 3. Examples of items representing the ‘Aesthetics’ category of SWEAT-R

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neighbourhoods. SWEAT-R items were first analyzed for distribution. For mostitems the distribution was skewed or very skewed, with items having 60–80% ofthe responses coded on only one level (e.g. 80% ‘no’ and 20% ‘yes’). Due to the highoccurrence of skewed distributions and limited variance among the items, theCohen’s kappa index for inter-rater reliability was determined to be inappropriate.As Feinstein & Cicchetti (1990) and Cicchetti & Feinstein (1990) have shown, thecalculation of Cohen’s kappa would be biased, leading to the paradox of having avery high percentage agreement and a very low kappa. This outcome wasconfirmed in an initial analysis of the data. For this reason, percentage agreementwas used as the measure of reliability. A similar strategy was employed bydevelopers of the original IMI (Boarnet et al., 2006). Inter-rater reliability wascalculated by region for the four SWEAT-R domains of Functionality, Aesthetics,Safety and Destinations. Analysis was performed using Stata Data Analysis andStatistical Software (StataCorp LP, College Station TX).

Inter-rater Reliability Results

There were 87 pairs of street segment data available for inter-rater reliabilityanalysis (40 in Portland and 47 in Vancouver). Table 3 summarizes results bySWEAT-R domain and region. All SWEAT-R items that were observed in pairs,less the five measurement items, were analyzed. The measurement items

Presence of graffiti or litter can contribute tolowered perception of safety

Poor condition of sidewalk can be a major deterrentin walking for older adults

Pedestrian activated signal is a positive itemsupportive of independent mobility

Crossing 4+ lanes of traffic can pose a majorchallenge for older adults who may have a slowerpace

Figure 4. Examples of items representing the ‘Safety’ category of SWEAT-R

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(e.g. buffer width, kerb height) were not included in the reliability analysis. These

data were not coded independently as both observers needed to work together in

order to do the measurements.

Percentage agreement was 95% or higher for 86.3% and 81.4% of the SWEAT-Ritems for Portland and Vancouver, respectively. Portland-based results indicate

that at least two-thirds of items within each domain were highly reliable (i.e.

percentage agreement 95% or higher) across the two observers, with the lowestpercentage agreement found for Aesthetic items. Vancouver results were similar to

Portland for Safety and Destination items but were slightly lower for Functionality

items (88% compared to 94%), and were considerably lower for Aesthetics items

(33% compared to 66%). Of the items that received less than 95% rater agreement inVancouver, all but two Aesthetic items had a percentage agreement ranging

between 80–94%. The two Aesthetic items that fell below 80% agreement were

‘maintenance of yards’ and ‘presence of litter, graffiti, broken glass, etc.’. In

Portland, seven items (2 Functionality, 3 Aesthetics, 1 Safety, and 1 Destination)had percentage agreements between 80–94% while another 14 items (2

Functionality and 12 Safety) were between 70–79%. A Street Life item for Portland

received a percentage agreement rating of less than 70% (‘presence of buffer zone’).No clear neighbourhood-level patterns emerged from the inter-reliability results

Table 3. Inter-rater reliability of the revised Seniors Walking EnvironmentalAssessment Tool (SWEAT-R) by domain for Vancouver and Portland metropolitan

areas (2007)

Vancouver (percentageagreement) Portland (percentage agreement)

Total items $ 95% 80–94% 70–79% $ 95% 80–94% 70–79% , 70%

Functionality 83 73 10 78 2 2 1Buildingsa 53 50 3 53Sidewalksb 14 12 2 11 1 2Streetc 7 6 1 6 1Street lifed 9 5 4 8 1Aestheticse 9 3 4 6 3Safety 56 43 13 2 43 1 12Personalf 41 30 11 29 12Trafficg 15 13 2 14 1Destinationsh 13 12 1 12 1

Audit Itemsa land uses, predominant building height, vertical mixed use, distinctive building types.b sidewalk presence, continuity of sidewalks, material type(s), condition, slope, obstructions, covering.c traffic direction, street condition, street material.d bench count, bench features, buffer zone, front porch, outdoor dining.e bench condition, building condition, yard condition, bars on windows, litter, abandoned buildings,quality of public space, street tree count.f intended crossing area, marked crossing, kerb cuts, kerb cut features, stop sign, yield sign, pedestriancrossing sign, pedestrian activated signal, pedestrian signal, pedestrian overpass/underpass, light atpresent, street light count.g lanes of traffic, bike lane, traffic calming devices.h transit stop presence, dead-end/cul-de-sac, public parking, gathering places, seniors’ housing,seniors’ activity/service, public restroom.

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(data not shown). It should be noted that several more SWEAT-R items in Portlandthan in Vancouver were never observed to be present or exhibited no variance inresponses. Items with no variance are presented in Table 4 for both regions.

Descriptive Results from SWEAT-R Data and Qualitative Observations ofAuditors

Descriptive audit data reveal some interesting variations by region andneighbourhood type. Descriptive results summarized below are based on a selectnumber of SWEAT-R items that exhibited some degree of variation in observerresponses, and on information collected using the secondary observation forms.Segment data on which descriptive results are based were collected by theprimary observer in each region.3 Results are presented by neighbourhood typefor each region. Comparisons are then made across the two regions andneighbourhood types.

Table 5 presents SWEAT-R results by region and neighbourhood type basedon density. Each item score denotes the percentage of segments on which it wasobserved within a given neighbourhood.

Portland Metropolitan Area Neighbourhoods

Across the four Portland neighbourhoods the prevalence of buildings types wasfound to be similar regardless of neighbourhood density (e.g. single-familydetached homes, service uses, medical facilities, vertical mixed use). Both the

Table 4. Total number of SWEAT-R items with no variance by domain and region(Portland, Oregon & Vancouver, British Columbia, 2007)

Total Items Portland Vancouver

Functionality 83 20 1

Buildings 53 11a 1i

Sidewalks 14 3b 0Street 7 2c 0Street Life 9 4d 0Aesthetics 9 1e 0

Safety 56 12 2j

Personal 41 12f 2Traffic 15 0 g 0Destinations 13 2 h 0

a Presence of gym/fitness facility, harbour/marina, hospital, hotel/hospitality, industrial/manufactur-ing, institutional—other, movie theatre, museum/hall/theatre, post office, public building—other,residential—other.b Sidewalk material—brick/tile, sidewalk material—concrete, sidewalk material—other.c Street material—brick/tile, street material—other.d Features of benches when present: back support, colour contrast, clean, undamaged.e Presence of abandoned buildings.f Northwest end of segment features: overpass, yield sign; Southeast end of segment features:pedestrian signal, overpass; Midblock crossing features: timed signal, pedestrian activated signal,pedestrian signal, pedestrian overpass; Midblock kerb cut features: broad apron, colour contrastmaterial contrast, kerb cut on one sideh Presence of farmers market, gallery/museum/theatre.i Presence of commercial—other.j Northwest end of segment: overpass; Midblock crossing area: stop sign.

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Table

5.

SW

EA

T-R

resu

lts

for

ase

lect

nu

mb

ero

fit

ems

(Po

rtla

nd

OR

&V

anco

uv

erB

C,

2007

)

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oo

ds

Po

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nd

Van

cou

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Po

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cou

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SC

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Hig

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den

sity

Hig

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sity

Lo

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den

sity

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sity

(%o

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)(n

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)(n

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)(n

¼96

)

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NC

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gs,

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ks

&st

reet

life

)Buildings

Sin

gle

-fam

ily

ho

mes

(det

ach

ed)

0.87

0.32

0.89

0.80

Mu

lti-

fam

ily

dw

elli

ng

s0.

080.

480.

170.

07R

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atio

nal

use

s0.

000.

030.

050.

02C

om

mer

cial

use

s0.

170.

320.

070.

18S

erv

ice

use

s0.

070.

300.

080.

15M

edic

alfa

cili

ties

0.04

0.08

0.05

0.02

Ver

tica

lm

ixed

use

0.01

0.17

0.02

0.05

Sidew

alks

Co

nti

nu

ou

s(b

oth

sid

es)

0.50

0.67

0.10

0.19

Sid

ewal

ks

(no

sid

es)

0.15

0.03

0.64

0.28

Sid

ewal

kW

idth

(4þ

feet

)0.

740.

670.

350.

55C

on

dit

ion

(go

od

)0.

720.

640.

310.

29S

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alk

Slo

pe

(gen

tle)

0.72

0.85

0.63

0.76

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bst

ruct

ion

s0.

120.

010.

010.

03B

ench

es(1

or

mo

re)

0.07

0.41

0.10

0.16

StreetLife

Po

rch

es(a

ll/

mo

st)

0.26

0.37

0.45

0.14

Bu

ffer

(bo

thsi

des

)0.

330.

610.

110.

24P

ub

lic

Sp

ace

(no

ne)

0.91

0.43

0.83

0.69

DE

ST

INA

TIO

NS

(Fac

ilit

ies)

Res

tau

ran

ts0.

080.

160.

050.

10C

off

eesh

op

s0.

030.

090.

010.

05

(continued

)

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Table

5.

(continued

)

Nei

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Po

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Van

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Po

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nd

Van

cou

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Hig

her

den

sity

Hig

her

den

sity

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den

sity

Lo

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den

sity

(%o

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gm

ents

)(n

¼76

)(n

¼10

1)(n

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)(n

¼96

)

Sen

iors

acti

vit

ies

0.01

0.01

0.01

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Pu

bli

ctr

ansi

tst

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ual

ity

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0.86

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0.93

0.13

Bu

ild

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ined

(all

/m

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860.

650.

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om

e)0.

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(all

/m

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790.

750.

810.

82L

itte

r(y

es)

0.12

0.21

0.00

0.13

SA

FE

TY

&C

OM

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RT

(Per

son

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safe

ty)

4þ

lan

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affi

c0.

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240.

060.

10M

ean

no

.o

fst

reet

lig

hts

2.25

3.91

2.06

3.33

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nes

0.03

0.14

0.08

0.05

Tra

ffic

calm

ing

dev

ices

0.28

0.81

0.61

0.67

Kerbcuts

Bo

thsi

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(NW

corn

er)

0.22

0.49

0.13

0.25

Bo

thsi

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(SE

corn

er)

0.17

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0.14

0.26

DA

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ION

SL

evel

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(hig

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Mea

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(in

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.85.

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0.12

0.34

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‘higher’ density and ‘lower’ density neighbourhoods had similar rates of single-family detached homes on street segments. There was double the proportion ofsegments with multi-family dwellings in the lower density neighbourhoods thanthe higher density neighbourhoods audited in Portland. Observer commentsindicate that in the lower density neighbourhoods, housing stock varied in qualityby neighbourhood income. As such, houses observed in higher-incomeneighbourhoods were largely upscale whereas in the lower-income neighbour-hoods the houses were smaller, older and poorly maintained.

There was a comparatively higher presence of commercial land use in thehigher density neighbourhoods compared to the lower density neighbourhoods inPortland. Observer comments further reveal that commercial types in higherdensity neighbourhoods varied by neighbourhood income. In the lower-incomeneighbourhood, observers described a busy, commercial area where restaurants,cafes and small shops were clustered. Alternatively, commercial propertyidentified in the higher density, lower-income neighbourhood was described as‘strip mall after strip mall’ with the presence of big-box stores, fast-foodrestaurants and rental shops. Indoor recreational uses (e.g. gym and fitnessfacilities) were not observed in higher density neighbourhoods but were observedin lower density neighbourhoods. In general, types of destinations (e.g.restaurants, coffee shops, seniors’ activities) did not differ significantly byneighbourhood density. Public space was not often observed in higher or lowerdensity neighbourhoods. Scores for SWEAT-R items related to the aestheticquality of a street did not vary significantly between neighbourhoods.

Differences were observed between neighbourhoods for items related tosidewalk functionality. Higher density neighbourhoods had a higher proportionof street segments with continuous sidewalks on both sides of the street thanlower density neighbourhoods (50% compared to 10%). Sidewalk width was alsoobserved to be greater in higher density neighbourhoods compared to lowerdensity neighbourhoods (74% of sidewalks were 4 foot wide or greater in higherdensity neighbourhoods compared to only 35% of sidewalks in lower densityneighbourhoods). When sidewalks were present, their condition was rated asgood on just over 70% of street segments in the higher density neighbourhoodscompared to just over 30% in the lower density neighbourhoods. There was also asignificantly high proportion of street segments in the lower density neighbour-hoods where no sidewalks were present at all (64%). SWEAT-R data on safety andcomfort features were generally similar between the two neighbourhood typesexcept for presence of traffic calming devices; these features were observed moreoften in the lower density Portland neighbourhoods. On the other hand, presenceof kerb cuts was slightly higher in higher density neighbourhoods compared tolower density neighbourhoods.

Metro Vancouver Neighbourhoods

Presence of building types were found to differ by neighbourhood density inVancouver, with single-family homes being observed more than twice as often inthe lower density neighbourhoods compared to the higher density neighbour-hoods (present on 80% compared to 32% of street segments, respectively).Correspondingly, multi-family dwellings were more prevalent in higher densitycompared to lower density neighbourhood street segments. Higher densityneighbourhoods also had a higher proportion of street segments where

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commercial property, service uses, medical facilities and vertical mixed usebuildings were observed. Presence of certain types of destinations, such asrestaurants and coffee shops, did not differ substantially between neighbourhoodtypes. Nor did the presence of features related to aesthetic quality, althoughbuildings were observed to be well maintained more often in the lower densityneighbourhoods compared to the higher density neighbourhoods (88% comparedto 65% of street segments, respectively).

Variation in sidewalk characteristics did not differ substantially byneighbourhood density, except in terms of sidewalk characteristics. Presence ofcontinuous sidewalks on both sides of any given street segment was observedmore often in higher density neighbourhoods than in lower density neighbour-hoods. Moreover, only 3% of street segments in higher density neighbourhoodshad no sidewalks present on either side while 28% of street segments in the lowerdensity neighbourhoods did not. Buffers between sidewalks and street traffic weremore common on street segments in higher density neighbourhoods compared tolower density neighbourhoods (61% and 245, respectively). Prevalence of streetswith four or more lanes of traffic was evidently high in the higher densityneighbourhoods compared to lower density neighbourhoods; traffic calmingdevices and bike lanes were also more prevalent in higher density neighbour-hoods. Kerb cuts at both ends of the street were more prevalent in higher densityneighbourhoods. Street life characteristics varied somewhat by neighbourhooddensity; for example, all or most residences had front porches on 37% of observedstreet segments in higher density neighbourhoods compared to 14% in the lowerdensity neighbourhoods.

Variations by Neighbourhood Type and Region

Portland higher density neighbourhoods had SWEAT-R results more consistentwith lower density neighbourhoods in both regions. It was quite clear that theVancouver high density neighbourhood had the highest occurrence of mixedresidential/commercial uses, including a comparatively greater proportion ofmulti-family dwellings and commercial and service uses observed on itssegments compared to all other neighbourhoods. Portland neighbourhoodstended to be rated higher in quality of public space although the presence ofpublic space in Portland neighbourhoods was relatively low compared toVancouver neighbourhoods, where presence of parks, playgrounds, outdoorfitness areas was common in both the higher and lower density neighbourhoods.Quality of Vancouver neighbourhoods’ public space was primarily rated as just‘neutral’ than it was ‘high’.

Across both regions sidewalk functionality items, such as presence ofcontinuous sidewalks and good sidewalk condition, were more prevalent inhigher density than lower density neighbourhoods. Lower density neighbour-hoods in both regions tended to have similar presence of traffic calming deviceswhereas the Vancouver higher density neighbourhoods had a significantly greaterpresence of such devices compared to Portland higher density neighbourhoods.Vancouver higher density neighbourhoods also had a greater number of segmentswith bike lanes, and Vancouver neighbourhoods were more likely to supportpublic transit (e.g. presence of bus stops) than were Portland neighbourhoods.

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Discussion

Results in both regions revealed that a majority of SWEAT-R items had high inter-rater reliability, confirming the tool’s usefulness in both Canadian and USneighbourhoods. Some items were less reliable in Vancouver neighbourhoodscompared to Portland neighbourhoods. This regional discrepancy may be due tothe less experienced Vancouver-based observers. In addition, qualitatively-oriented rating items such as street condition, sidewalk condition and buildingcondition that were found to be somewhat less reliable (80–94%) than otherSWEAT-R items (95% or higher) in Vancouver may benefit from furtherrefinement in SWEAT-R training protocol. Distinguishing between possibleresponse categories of ‘good’ versus ‘neutral’ or ‘poor’, or ‘some/a lot’ versus‘few/none’, may leave too much to the individual observer’s interpretation. Forexample, response options of ‘good,’ ‘moderate’ and ‘poor’ for the item ‘conditionof the sidewalk’ are somewhat open to individual observer’s assessment. Refiningdefinitions for what constitutes ‘good’, ‘poor’ etc. could improve reliabilitybetween rater assessments. For example, inclusion of photographs to exemplifyeach response category in the training manual would clarify and reinforce thedifferentiation across response categories. Further, training for SWEAT-R couldalso explicitly discuss how to minimize impact of personal design/aestheticsensibility in contaminating observations.

In Portland, a low inter-rater reliability result for personal safety items wasdue to consistent miscoding by one observer for items that should have beencoded as ‘not applicable’ rather than ‘no/not present’. This miscoding error couldbe corrected by clarifying instructions for completing SWEAT-R. (SWEAT-Rdata were re-coded to appropriate skip patterns before running statistics so lowinter-rater reliability for these items did not affect descriptive results). Buffer zonepresence was a street life item that received a percentage agreement rating of lessthan 70% in Portland and less than 85% in Vancouver. These results suggest thatthe definition of buffer zone could be further clarified in training.

Regional Differences by Neighbourhood Type

Environmental audit data revealed less neighbourhood variation for Portlandcompared to Vancouver. Portland neighbourhoods in this study had a highproportion of single-family residential regardless of their density. In contrast,Vancouver neighbourhoods exhibited greater variety of residential types anddesign complexity, with single-family homes predominant in lower densityneighbourhoods and a mix of single-family homes and multi-family dwellingtypes in higher density neighbourhoods. There was higher presence of mixed usein the Vancouver neighbourhoods compared to the Portland ones. The presence ofcommercial and service uses were relatively similar across three of the fourVancouver neighbourhoods. The presence of vertical mixed use buildings wasalso greater in high density neighbourhoods compared to lower densityneighbourhoods in Metro Vancouver. Indeed, density measures on which initialneighbourhood selections were based confirm that density is much greater inVancouver compared to Portland neighbourhoods. This is an interesting findinggiven the similar topography, climate and population (population of Portland andVancouver metros are 2.2 and 2.1 million respectively) of the two metropolitan

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areas, and indicates different regional planning policies and programmes that

might be at work.

In both regions, higher density neighbourhoods also had higher proportion of

sidewalks, which is indicative of a possible association between residential

density and walkability in these regions. Sidewalk and street life features were

relatively similar across all four Portland neighbourhoods; in contrast there were

notable differences in sidewalk characteristics between Vancouver neighbour-

hoods, with higher density neighbourhoods having more favourable features

such as continuous sidewalks, high maintenance of sidewalks, and presence of

buffer zones and benches. This indicates that the higher density neighbourhoods

in Vancouver are more walkable for older adults than the lower density

neighbourhoods. In both regions, buildings and yards were generally well

maintained and public spaces were perceived to be good quality in the higher-

income neighbourhoods.

However, quality of public spaces was much higher in Portland neighbour-

hoods compared to Vancouver neighbourhoods. It would be useful to develop a

mirco-environmental audit of the quality of public spaces in future studies.

Presence of kerb cuts was highest in the higher density/lower-income Portland

neighbourhood compared to other neighbourhoods, while kerb cuts were more

common in the Vancouver higher density neighbourhoods, regardless of

neighbourhood income. In Portland, the higher density/higher-income neigh-

bourhood had a relatively low presence of traffic calming devices compared to the

other three neighbourhoods; in contrast, the presence of traffic calming devices

was lowest in the lower density/lower-income neighbourhood compared to the

other three Metro Vancouver neighbourhoods.

In general, neighbourhood descriptions based on secondary observation

forms did not differ significantly between the two observers in each region.

Moreover, there appeared to be advantages to having both observers complete

secondary observation forms independently. Although their general assessments

tended to be similar, the two observers often described different neighbourhood

characteristics to support their ratings, and in this way, their observations were

complementary. No major discrepancies were identified between paired

observers in this study. However, if any discrepancies are found between

observers in future studies, investigators should initiate discussions with

observers to identify points of contention and determine whether consensus/a-

greement can be reached.

Qualitative neighbourhood descriptions highlighted environmental features

that could impact walkability that are not fully captured by the SWEAT-R audit

tool. For example, while the higher density/lower-income Portland neighbour-

hood had characteristics conducive to walking (e.g. commercial and service uses,

continuous sidewalks and marked crossings), it also had characteristics not

conducive to walking (e.g. busy, multiple lanes of heavy traffic) that in the end

may more influence older pedestrians’ perceptions of safety. Qualitative data on

Vancouver neighbourhoods also underscored complexities in understanding the

physical and social conditions that could impact walking and other physical

activities. For example, there appeared to be much variation in safe and

pedestrian/senior friendly areas within each of the neighbourhoods observed.

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Conclusions

SWEAT-R and its supplementary secondary observation form provideddescriptive physical environmental information on Portland and Vancouvermetropolitan neighbourhoods for this study of physical activity of older adults.The results indicated that SWEAT-R inter-rater reliability was high for a broadrange of items across its four domains of Functionality, Aesthetics, Safety andDestinations. While inter-rater reliability was similar across the two regions,slightly lower levels observed in Vancouver may have been due to lessexperienced observers and/or indicate potential challenges in using the tool inmore complex neighbourhood environments compared to those where single-family homes predominate. Further investigation is needed to determine whetherinter-rater agreement is compromised when more items on the tool are observedto be present and to a varying degree. (For example, could it be that informationoverload or observer fatigue occurs when auditing more complex, relatively highdensity urban environments?)

Environmental audit data made it possible to compare the presence (orabsence) of neighbourhood environmental features considered conducive towalking in the two regions. Both Portland and Vancouver are known to beprogressive in their policies and strategies for urban sustainability and enhancingthe quality of life of the ageing population (particularly when compared to otherregions in the United States and Canada). Data collected on the sampleneighbourhoods suggest that Metro Vancouver neighbourhoods are moreconducive to walking than Portland metropolitan neighbourhoods. This studydid not conduct a comparative examination of the planning policies andregulations between the two regions. Incorporation of policy analysis tocontextualize SWEAT-R findings in the future will help to identify possiblepolicy-practice implications. Nevertheless, the four neighbourhoods in Portlandregion had less variability in terms of residential density compared to the fourVancouver neighbourhoods based on the initial GIS based neighbourhoodselection process. Subsequent phases of this study will evaluate correlationsbetween self-reported physical activity of seniors who live in the neighbourhoodsand neighbourhood characteristics based on environmental audit data. Inaddition, use of GIS to map environmental and survey data will reveal any spatialvariations within and across neighbourhoods and regions.

Limitations

The use of the SWEAT-R audit tool in an American and Canadian region was bothan opportunity and a source of limitation. In Vancouver it was possible to test thetool’s effectiveness in a region and in neighbourhood settings with greater densityand variability of features than in Portland. However, an important limitation inthis study was that the process used to select neighbourhood selections differed.Moreover, the number of segments observed differed between the two regionsand within neighbourhoods. Consequently, individual SWEAT-R item scorestended to be inflated for neighbourhoods where fewer segments were audited.Future studies should guard against similar limitations. In addition, future studiesneed to use SWEAT-R in more cities with more contrasting built form, naturallandscape and climate than what was present in Vancouver and Portland in orderto have greater confidence on the reliability of the tool and potential refinements.

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Implications

This newly developed audit tool SWEAT-R has several implications for urbandesign theory and practice. First, it provides a comprehensive method ofmeasuring the neighbourhood built environment with sensitivity to age-relatedbarriers. Although there are several audit tools available, not much has been doneto take into account the needs of various population groups based on age, physicalability and cultural background. Given that physical inactivity is a major publichealth concern, more comprehensive and sensitive tools are required to capturethe environmental features that can influence physical activity.

Theoretically, this tool makes it possible to examine the relationship of thequality of the built environment and active living for a population with diversephysical abilities. Second, based on this study’s inter-rater reliability data,SWEAT-R can be used by urban designers and planners with confidence tosystematically audit the neighbourhood built form features in order to assess theextent in which they are supportive of active lifestyle for adults in general, withparticular sensitivity to older adults’ needs. As we have an increasing ageingpopulation, there will be growing recognition of the need to create neighbourhoodenvironments that are truly responsive to the diverse physical and social issues ofpopulation. A systematic and fine-grained documentation of the built form at thesegment level across various neighbourhoods would provide hard evidence forplanners to identify needs and opportunities, and subsequently, justify the needfor environmental modifications. This is particularly relevant for municipalitieswith higher concentrations of older adults, as city planners, urban designers orengineers can use the environmental audit data to critically evaluate thecharacteristics of the neighbourhoods and advocate policy change andprogramme implementation. Third, older adults themselves can use the tool asa mechanism to increase their sensitivity of the neighbourhood built environmentand identify areas for improvement. Older adults can be provided with a shorttraining session on the use of the tool and implications of the data collected inorder to collect objective data that could be used to substantiate particularenvironmental needs in their neighbourhoods to the respective city council,advocate environmental intervention in critical neighbourhood locations, andimpact policy decisions. Overall, the use of such a tool by older adults themselvescan raise their awareness of the physical condition of their neighbourhoods andincrease the likelihood of them becoming more engaged neighbourhood citizens.

Acknowledgements

This research was supported by an operating grant from the Canadian Institutesof Health Research (CIHR). The authors wish to thank Dr Michael Hayes foraccess to the GIS data used in the neighbourhood selection process for MetroVancouver. They also express appreciation to Tracy Dodge, Rob Oswald, ChrisAu-Yeung, Mary Sepulveda and Adrienne Wedding for their contributions to datacollection.

Notes

1. For Portland neighbourhood selections, the initial pool of neighbourhoods to choose from werelimited to 12 neighbourhoods already selected for participation in an ongoing study of communitydwelling older adults (Michael et al., 2009). This pool included neighbourhoods that were

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geographically distributed throughout the metropolitan region, and represented traditional as wellas suburban areas. All census tracts in the Metro Vancouver region were included in the initial poolfrom which final selections were drawn.

2. Adjacent census tracts for the two higher density neighbourhood selections in the Metro Vancouverarea were also audited because of the limited number of street segments in the census tract that metthe initial selection criteria. Adjacent census tracts had similar characteristics to the initial censustract selection.

3. During data cleaning, items were recorded according to the appropriate skip pattern; in otherwords, if the observer indicated that a crossing area was not present, then all subsequent crossingarea items were automatically set to ‘not applicable’.

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