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International variation in neighborhood walkability, transit, and recreation environments using geographic information systems: the IPEN adult study.

Adams MA, Frank LD, Schipperijn J, Smith G, Chapman J, Christiansen LB, Coffee N, Salvo D, du Toit L, Dygrýn J, Hino AA, Lai PC, Mavoa S, Pinzón JD, Van de Weghe N, Cerin E, Davey R, Macfarlane D, Owen N, Sallis JF - Int J Health Geogr (2014)

Bottom Line: Results show that comparable measures can be created across a range of cultural settings revealing profound global differences in urban form relevant to physical activity.The highly variable measures of urban form will be used to explain individuals' physical activity, sedentary behaviors, body mass index, and other health outcomes on an international basis.Present measures provide the ability to estimate dose-response relationships from projected changes to the built environment that would otherwise be impossible.

View Article: PubMed Central - PubMed

Affiliation: Exercise and Wellness Program, School of Nutrition and Health Promotion & Global Institute of Sustainability (GIOS), Arizona State University, 425 N, 5th Street (MC3020), Phoenix, Arizona. marc.adams@asu.edu.

ABSTRACT

Background: The World Health Organization recommends strategies to improve urban design, public transportation, and recreation facilities to facilitate physical activity for non-communicable disease prevention for an increasingly urbanized global population. Most evidence supporting environmental associations with physical activity comes from single countries or regions with limited variation in urban form. This paper documents variation in comparable built environment features across countries from diverse regions.

Methods: The International Physical Activity and the Environment Network (IPEN) study of adults aimed to measure the full range of variation in the built environment using geographic information systems (GIS) across 12 countries on 5 continents. Investigators in Australia, Belgium, Brazil, Colombia, the Czech Republic, Denmark, China, Mexico, New Zealand, Spain, the United Kingdom, and the United States followed a common research protocol to develop internationally comparable measures. Using detailed instructions, GIS-based measures included features such as walkability (i.e., residential density, street connectivity, mix of land uses), and access to public transit, parks, and private recreation facilities around each participant's residential address using 1-km and 500-m street network buffers.

Results: Eleven of 12 countries and 15 cities had objective GIS data on built environment features. We observed a 38-fold difference in median residential densities, a 5-fold difference in median intersection densities and an 18-fold difference in median park densities. Hong Kong had the highest and North Shore, New Zealand had the lowest median walkability index values, representing a difference of 9 standard deviations in GIS-measured walkability.

Conclusions: Results show that comparable measures can be created across a range of cultural settings revealing profound global differences in urban form relevant to physical activity. These measures allow cities to be ranked more precisely than previously possible. The highly variable measures of urban form will be used to explain individuals' physical activity, sedentary behaviors, body mass index, and other health outcomes on an international basis. Present measures provide the ability to estimate dose-response relationships from projected changes to the built environment that would otherwise be impossible.

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Aerial and ground views with walkability component and index1scores of one of the lowest walkable (North Shore, NZL) and one of the highest walkable (Hong Kong, HKG) neighborhoods in the IPEN Adult Study.1Walkability index z-score equaled the sum of z-scores for residential density, land use mix, and intersection density. Z-scores allowed for standardized pooled standard deviations necessary for comparisons across countries.
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Fig6: Aerial and ground views with walkability component and index1scores of one of the lowest walkable (North Shore, NZL) and one of the highest walkable (Hong Kong, HKG) neighborhoods in the IPEN Adult Study.1Walkability index z-score equaled the sum of z-scores for residential density, land use mix, and intersection density. Z-scores allowed for standardized pooled standard deviations necessary for comparisons across countries.

Mentions: A walkability index was computed as the sum of z-scores (i.e. standardized scores) of net residential density, land use mix, and intersection density. Z-scores were based on pooled unstandardized datasets inclusive of all cities and countries. The walkability index was adapted from Frank et al. [10] but differed from the original index in two ways: (a) land area measures were used instead of floor area measures for land use mix, and (b) “retail floor area ratios” were not included because floor areas were available in only 4 countries. The adapted version, while not the most precise version, still captured both proximity and connectivity – the two main theoretical constructs of walkability [10]. The IPEN study design maximized within-city variation in net residential density, land use mix, and intersection density and therefore the walkability index values should reflect the maximum range within each city while the comparison across cities should reflect true between-country variation.Figure 5 presents a box plot of the walkability index documenting the within- and between-country variation across 15 IPEN cities. Median walkability z-scores appeared to increase linearly across cities and ranged from a low of -1.99 in North Shore, NZL to a high of 7.05 in Hong Kong, HKG. The pooled median walkability index z-score was -0.37. Importantly, a very large difference of 9.04 standard deviations in median walkability was observed across these 15 cities representing 11 countries and 5 continents. To illustrate the magnitude difference, Figure 6 provides an example of aerial and ground views along with associated walkability and component scores for one of the lowest walkability (North Shore, NZL) and one of the highest walkability (Hong Kong, HKG) neighborhoods in the IPEN Adult Study.Figure 5


International variation in neighborhood walkability, transit, and recreation environments using geographic information systems: the IPEN adult study.

Adams MA, Frank LD, Schipperijn J, Smith G, Chapman J, Christiansen LB, Coffee N, Salvo D, du Toit L, Dygrýn J, Hino AA, Lai PC, Mavoa S, Pinzón JD, Van de Weghe N, Cerin E, Davey R, Macfarlane D, Owen N, Sallis JF - Int J Health Geogr (2014)

Aerial and ground views with walkability component and index1scores of one of the lowest walkable (North Shore, NZL) and one of the highest walkable (Hong Kong, HKG) neighborhoods in the IPEN Adult Study.1Walkability index z-score equaled the sum of z-scores for residential density, land use mix, and intersection density. Z-scores allowed for standardized pooled standard deviations necessary for comparisons across countries.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4221715&req=5

Fig6: Aerial and ground views with walkability component and index1scores of one of the lowest walkable (North Shore, NZL) and one of the highest walkable (Hong Kong, HKG) neighborhoods in the IPEN Adult Study.1Walkability index z-score equaled the sum of z-scores for residential density, land use mix, and intersection density. Z-scores allowed for standardized pooled standard deviations necessary for comparisons across countries.
Mentions: A walkability index was computed as the sum of z-scores (i.e. standardized scores) of net residential density, land use mix, and intersection density. Z-scores were based on pooled unstandardized datasets inclusive of all cities and countries. The walkability index was adapted from Frank et al. [10] but differed from the original index in two ways: (a) land area measures were used instead of floor area measures for land use mix, and (b) “retail floor area ratios” were not included because floor areas were available in only 4 countries. The adapted version, while not the most precise version, still captured both proximity and connectivity – the two main theoretical constructs of walkability [10]. The IPEN study design maximized within-city variation in net residential density, land use mix, and intersection density and therefore the walkability index values should reflect the maximum range within each city while the comparison across cities should reflect true between-country variation.Figure 5 presents a box plot of the walkability index documenting the within- and between-country variation across 15 IPEN cities. Median walkability z-scores appeared to increase linearly across cities and ranged from a low of -1.99 in North Shore, NZL to a high of 7.05 in Hong Kong, HKG. The pooled median walkability index z-score was -0.37. Importantly, a very large difference of 9.04 standard deviations in median walkability was observed across these 15 cities representing 11 countries and 5 continents. To illustrate the magnitude difference, Figure 6 provides an example of aerial and ground views along with associated walkability and component scores for one of the lowest walkability (North Shore, NZL) and one of the highest walkability (Hong Kong, HKG) neighborhoods in the IPEN Adult Study.Figure 5

Bottom Line: Results show that comparable measures can be created across a range of cultural settings revealing profound global differences in urban form relevant to physical activity.The highly variable measures of urban form will be used to explain individuals' physical activity, sedentary behaviors, body mass index, and other health outcomes on an international basis.Present measures provide the ability to estimate dose-response relationships from projected changes to the built environment that would otherwise be impossible.

View Article: PubMed Central - PubMed

Affiliation: Exercise and Wellness Program, School of Nutrition and Health Promotion & Global Institute of Sustainability (GIOS), Arizona State University, 425 N, 5th Street (MC3020), Phoenix, Arizona. marc.adams@asu.edu.

ABSTRACT

Background: The World Health Organization recommends strategies to improve urban design, public transportation, and recreation facilities to facilitate physical activity for non-communicable disease prevention for an increasingly urbanized global population. Most evidence supporting environmental associations with physical activity comes from single countries or regions with limited variation in urban form. This paper documents variation in comparable built environment features across countries from diverse regions.

Methods: The International Physical Activity and the Environment Network (IPEN) study of adults aimed to measure the full range of variation in the built environment using geographic information systems (GIS) across 12 countries on 5 continents. Investigators in Australia, Belgium, Brazil, Colombia, the Czech Republic, Denmark, China, Mexico, New Zealand, Spain, the United Kingdom, and the United States followed a common research protocol to develop internationally comparable measures. Using detailed instructions, GIS-based measures included features such as walkability (i.e., residential density, street connectivity, mix of land uses), and access to public transit, parks, and private recreation facilities around each participant's residential address using 1-km and 500-m street network buffers.

Results: Eleven of 12 countries and 15 cities had objective GIS data on built environment features. We observed a 38-fold difference in median residential densities, a 5-fold difference in median intersection densities and an 18-fold difference in median park densities. Hong Kong had the highest and North Shore, New Zealand had the lowest median walkability index values, representing a difference of 9 standard deviations in GIS-measured walkability.

Conclusions: Results show that comparable measures can be created across a range of cultural settings revealing profound global differences in urban form relevant to physical activity. These measures allow cities to be ranked more precisely than previously possible. The highly variable measures of urban form will be used to explain individuals' physical activity, sedentary behaviors, body mass index, and other health outcomes on an international basis. Present measures provide the ability to estimate dose-response relationships from projected changes to the built environment that would otherwise be impossible.

Show MeSH
Related in: MedlinePlus