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Data from: Intersection of neighborhood dynamics and socioeconomic status in small-area walkability: The Heart Healthy Hoods project

RMIT University, Australia
Hannah Badland (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=https://figshare.com/articles/MOESM1_of_Intersection_of_neighborhood_dynamics_and_socioeconomic_status_in_small-area_walkability_the_Heart_Healthy_Hoods_project/5085736&rft.title=Data from: Intersection of neighborhood dynamics and socioeconomic status in small-area walkability: The Heart Healthy Hoods project&rft.identifier=5c8454ea8599fd367d03cd4c6ae41421&rft.publisher=RMIT University, Australia&rft.description=Attached files provides supplementary data for linked article. Background Previous studies found a complex relationship between area-level socioeconomic status (SES) and walkability. These studies did not include neighborhood dynamics. Our aim was to study the association between area-level SES and walkability in the city of Madrid (Spain) evaluating the potential effect modification of neighborhood dynamics. Methods All census sections of the city of Madrid (n = 2415) were included. Area-level SES was measured using a composite index of 7 indicators in 4 domains (education, wealth, occupation and living conditions). Two neighborhood dynamics factors were computed: gentrification, proxied by change in education levels in the previous 10 years, and neighborhood age, proxied by median year of construction of housing units in the area. Walkability was measured using a composite index of 4 indicators (Residential Density, Population Density, Retail Destinations and Street Connectivity). We modeled the association using linear mixed models with random intercepts. Results Area-level SES and walkability were inversely and significantly associated. Areas with lower SES showed the highest walkability. This pattern did not hold for areas with an increase in education level, where the association was flat (no decrease in walkability with higher SES). Moreover, the association was attenuated in newly built areas: the association was stronger in areas built before 1975, weaker in areas built between 1975 and 1990 and flat in areas built from 1990 on. Conclusion Areas with higher neighborhood socioeconomic status had lower walkability in Madrid. This disadvantage in walkability was not present in recently built or gentrified areas.&rft.creator=Hannah Badland&rft.date=2018&rft.relation=https://dx.doi.org/10.1186/s12942-017-0095-7&rft_rights=Further information about rights and usage of ACS publications and supplementary data can be found here: http://pubs.acs.org/page/copyright/permissions.html.&rft_rights=CC BY-NC: Attribution-Noncommercial 3.0 AU http://creativecommons.org/licenses/by-nc/3.0/au&rft_subject=GIS&rft_subject=Neighborhood/pace&rft_subject=Physical activity&rft_subject=Urbanisation&rft_subject=Urban Design&rft_subject=BUILT ENVIRONMENT AND DESIGN&rft_subject=URBAN AND REGIONAL PLANNING&rft.type=dataset&rft.language=English Access the data

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CC BY-NC: Attribution-Noncommercial 3.0 AU
http://creativecommons.org/licenses/by-nc/3.0/au

Further information about rights and usage of ACS publications and supplementary data can be found here: http://pubs.acs.org/page/copyright/permissions.html.

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Attached files provides supplementary data for linked article. Background Previous studies found a complex relationship between area-level socioeconomic status (SES) and walkability. These studies did not include neighborhood dynamics. Our aim was to study the association between area-level SES and walkability in the city of Madrid (Spain) evaluating the potential effect modification of neighborhood dynamics. Methods All census sections of the city of Madrid (n = 2415) were included. Area-level SES was measured using a composite index of 7 indicators in 4 domains (education, wealth, occupation and living conditions). Two neighborhood dynamics factors were computed: gentrification, proxied by change in education levels in the previous 10 years, and neighborhood age, proxied by median year of construction of housing units in the area. Walkability was measured using a composite index of 4 indicators (Residential Density, Population Density, Retail Destinations and Street Connectivity). We modeled the association using linear mixed models with random intercepts. Results Area-level SES and walkability were inversely and significantly associated. Areas with lower SES showed the highest walkability. This pattern did not hold for areas with an increase in education level, where the association was flat (no decrease in walkability with higher SES). Moreover, the association was attenuated in newly built areas: the association was stronger in areas built before 1975, weaker in areas built between 1975 and 1990 and flat in areas built from 1990 on. Conclusion Areas with higher neighborhood socioeconomic status had lower walkability in Madrid. This disadvantage in walkability was not present in recently built or gentrified areas.

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