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2.4.1 Composite Measures of Walkability and Safety

The Physical Activity Environments (PAE) Measure (objective composite

measure) is a comprehensive measure that includes the Utilitarian Walkability Index and the Playability Index (Frank et al., 2012; Saelens et al., 2012). This walkability index encompassed two main categories of walkability measures using a utilitarian walkability index and playability index. High physical activity environments were assumed to have a higher than median summed z-score on residential density, retail floor area ratio, land- use mix, and street connectivity, and at least one high-quality park evaluated by an audit tool, the Environmental Assessment of Public Recreation Spaces tool (Frank et al., 2012; Saelens et al., 2012). In the utilitarian walkability index, the net residential density was measured with the ratio of residential unit numbers to the land areas involved in

residential use per half-mile buffer from home. The retail floor area ratio was the ratio of building floor area to the land floor area of retails to capture parking services. Street network connectivity was captured by the ratio of the number of intersections to the area of the block group. Land use mix was a measure based on entropy capturing fıve land uses including residential, retail, entertainment, office, and civic land uses. The z-scores were computed across the different metropolitan regions separately to standardize the

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distributions of block groups in each region (Frank et al., 2010). They developed a playability index based on public park proximity and availability, and quality of features. Park accessibility was measured by enumerating parks within unit areas. Park-quality measures were captured by in-fıeld park audits for trails or paths, water features, playground equipment, and so on.

However, the walkability index was designed to focus on evaluating metropolitan cities with high-density (Frank, Andresen, & Schmid, 2004; Frank et al., 2005). Thus, to apply it to areas with low-to-medium density, it was necessary to develop a new method by adopting the ideas of the Walk Score measuring accessibility to destinations and adding evaluations of walking-friendly infrastructure (Carr, Dunsiger, & Marcus, 2010a, 2010b). From previous studies, safety-related correlates of walking are categorized into three dimensions: safety from traffic, safety from crime, and pedestrian-related safety, which includes risks related to street lighting, surveillance, dogs, the condition of pedestrian infrastructures, and air quality (Bracy et al., 2014; Foster & Giles-Corti, 2008). Composite measures for neighborhood safety were rarely addressed and were limited to audit data and survey data (Alfonzo, Boarnet, Day, Mcmillan, & Anderson, 2008; Suminski et al., 2005).

2.4.2 Discordance between Perceived and Observed Measures of Neighborhood

Environments

Most studies have found that one-third of residents live in neighborhoods where objective and perceived environments disagree with respect to neighborhood walkability (Arvidsson et al., 2012; Gebel et al., 2009; Gebel et al., 2011), which contributes to

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constrained health behaviors and weight gain (Gebel et al., 2011). Previous studies dichotomized the composite walkability score based on the median, tertile, and quartile splits within community settings (Arvidsson et al., 2012; Gebel et al., 2009; Gebel et al., 2011). The studies objectively evaluated neighborhood walkability by taking the highest quartile and lowest quartile or the highest tertile and lowest tertile (Koohsari et al., 2015; Owen et al., 2007). Twenty studies which compared perceived and objective measures were reviewed (Table 1). A common method was to select study neighborhoods using walkability by block groups and calculating concordance and discordance using sample- based median-splits (Arvidsson et al., 2012; Frank et al., 2010; Kamphuis et al., 2010). Some other studies compared perceived and objective presence/absence of destinations (e.g. recreational, PA-related, utilitarian) calculating the rate of agreement and kappa statistics (Caspi, Kawachi, Subramanian, Adamkiewicz, & Sorensen, 2012; Leslie, Sugiyama, Ierodiaconou, & Kremer, 2010). The discrete objective measures and perception measures of environments were then summarized with two-by-two tables to identify concordance and discordance between the two types of measures and to compare the compositions of the agreements and disagreements.

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Table 1 Reviews of Studies on Perceived and Objective Walkability Comparisons

References Study Area Categorization Methods

Arvidsson et al. (2012) Sweden Walkability index was composed of residential density, land use mix, and street connectivity. Sample-based median-splits were used to compare with perceived walkability.

Bailey et al. (2014) Wisconsin, U.S. Various neighborhood destinations were objectively measured within 400m buffers, covering five domains. The agreements between perceived and objective access to neighborhood destinations were evaluated.

Ball et al. (2008) Australia The presence/absence of 8 PA facilities was objectively measured within 2km. The agreements between perceived and objective proximity to PA facilities were evaluated. Barnes, Bell, Freedman,

Colabianchi, and Liese (2015)

South Carolina, U.S.

The presence/absence of retail food outlets was objectively measured within 1km buffers. The agreements between perceived and objective access to food outlets were evaluated.

Boehmer, Hoehner, Deshpande, Ramirez, and Brownson (2007)

Georgia & Missouri, U.S.

Audits were conducted to measure recreational facilities, land uses, infrastructures, and aesthetics within 400m buffers. Without the discordance measure, logistic regressions of obesity were estimated separately.

Boehmer, Hoehner, Wyrwich, Ramirez, and Brownson (2006)

Georgia & Missouri, U.S.

Audits were conducted to measure recreational facilities, land uses, infrastructures, and aesthetics within 400m buffers. The kappa statistics were used to evaluate the percentage of agreements between survey and audit items.

Caspi et al. (2012) Massachusetts, U.S. The presence of supermarkets was objectively measured within 1km buffers. The agreements between perceived and objective proximity to supermarkets were evaluated. Gebel et al. (2009) Australia Walkability was composed of dwelling density, intersection

density, land use mix, and net retail area. Measures were converted into deciles, ranging from 1 to 10, and summed across four dimensions. The first and fourth quartiles were selected.

Gebel et al. (2011) Australia Follow-up study of Gebel et al. (2009); the same method was used.

Kamphuis et al. (2010) Netherlands Aesthetic, design, lack of traffic safety, lack of social safety, and destination features were measured by audits. Summed scores for each domain were dichotomized by a median-split. Perceived neighborhood unattractiveness and lack of safety were regressed on the five domains of objective features. Kirtland et al. (2003) South Carolina,

U.S. The presence/absence of destinations and walking/biking paths were measured by survey and objectively. Kappa statistics were used to identify concordance between perceptions and objective measures.

Koohsari et al. (2015) Australia Street connectivity and land use mix were identified within 1 mile buffers. Values were categorized into tertiles and matched, selecting the first and third tertiles for both perceived and objective walkability.

Lackey and Kaczynski

(2009) Canada Perception and objective measures of the presence/absence of parks within 750m were compared. Leslie et al. (2010) Australia NDVIs were measured within 400m buffers. The top 20%

and bottom 20% were selected. Perceived greenness measured with a 4-point scale was compared with NDVIs with kappa statistics.

Lin and Moudon (2010) Washington, U.S. Grocery stores, schools, and sidewalks were objectively measured within 1km airline buffer (logged length or counts). Logistic regression models were estimated to compare subjective and objective measures.

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Table 1 Continued

References Study Area Categorization Methods

Ma and Dill (2015) Oregon, U.S. Bike environments (off-street bike trails, bike lanes, streets to bike on, and places to bike to) were objectively measured within 1/2mile circular buffers. Models were estimated to compare subjective and objective measures.

Macintyre, Macdonald,

and Ellaway (2008) Scotland The presence/absence of public green parks was measured within 1/2mile buffers. The agreements between objective and self-reported proximity were evaluated by percentage agreement and kappa statistics.

McCormack, Cerin, Leslie,

Du Toit, and Owen (2007) Australia Distances libraries, cafés, bus or train stops, parks, bush lands, and to destinations (shops, supermarkets, post offices, sports fields) were measured with five distance interval categories. Walkability was evaluated with intersection density, residential density, and land-use mix. McGinn, Evenson,

Herring, Huston, and Rodriguez (2007)

NC & MS, U.S. Creating three components (speed, volume, and

intersections), exploratory factor analyses of traffic volume, traffic speed, street connectivity, and traffic crashes were conducted. Sample-based median-splits were performed by counties (e.g. >5 crashes / 1,000 inhabitants).

Owen et al. (2007) Australia Walkability was measured with residential density, street connectivity, land use mix, and, net retail area. Scores were converted into deciles, scored from 1 to 10, and summed by four dimensions. The first and fourth quartiles were selected.

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