Dataset Information

Neighborhood Sociodemographics and Change in Built Infrastructure.

ABSTRACT: While increasing evidence suggests an association between physical infrastructure in neighbourhoods and health outcomes, relatively little research examines how neighbourhoods change physically over time and how these physical improvements are spatially distributed across populations. This paper describes the change over 25 years (1985-2010) in bicycle lanes, off-road trails, bus transit service, and parks, and spatial clusters of changes in these domains relative to neighbourhood sociodemographics in four U.S. cities that are diverse in terms of geography, size and population. Across all four cities, we identified increases in bicycle lanes, off-road trails, and bus transit service, with spatial clustering in these changes that related to neighbourhood sociodemographics. Overall, we found evidence of positive changes in physical infrastructure commonly identified as supportive of physical activity. However, the patterning of infrastructure change by sociodemographic change encourages attention to the equity in infrastructure improvements across neighbourhoods.

SUBMITTER: Hirsch JA

PROVIDER: S-EPMC5353850 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Neighborhood Sociodemographics and Change in Built Infrastructure.

Hirsch Jana A JA Green Geoffrey F GF Peterson Marc M Rodriguez Daniel A DA Gordon-Larsen Penny P

Journal of urbanism 20160810 2

While increasing evidence suggests an association between physical infrastructure in neighbourhoods and health outcomes, relatively little research examines how neighbourhoods change physically over time and how these physical improvements are spatially distributed across populations. This paper describes the change over 25 years (1985-2010) in bicycle lanes, off-road trails, bus transit service, and parks, and spatial clusters of changes in these domains relative to neighbourhood sociodemograph ...[more]

PMID: 28316645

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Project description:ObjectiveTo examine associations between neighborhood built environment (BE) variables, residential property values, and longitudinal 1- and 2-year changes in body mass index (BMI).MethodsThe Seattle Obesity Study III was a prospective cohort study of adults with geocoded residential addresses, conducted in King, Pierce, and Yakima Counties in Washington State. Measured heights and weights were obtained at baseline (n = 879), year 1 (n = 727), and year 2 (n = 679). Tax parcel residential property values served as proxies for individual socioeconomic status. Residential unit and road intersection density were captured using Euclidean-based SmartMaps at 800 m buffers. Counts of supermarket (0 versus. 1+) and fast-food restaurant availability (0, 1-3, 4+) were measured using network based SmartMaps at 1600 m buffers. Density measures and residential property values were categorized into tertiles. Linear mixed-effects models tested whether baseline BE variables and property values were associated with differential changes in BMI at year 1 or year 2, adjusting for age, gender, race/ethnicity, education, home ownership, and county of residence. These associations were then tested for potential disparities by age group, gender, race/ethnicity, and education.ResultsRoad intersection density, access to food sources, and residential property values were inversely associated with BMI at baseline. At year 1, participants in the 3rd tertile of density metrics and with 4+ fast-food restaurants nearby showed less BMI gain compared to those in the 1st tertile or with 0 restaurants. At year 2, higher residential property values were predictive of lower BMI gain. There was evidence of differential associations by age group, gender, and education but not race/ethnicity.ConclusionInverse associations between BE metrics and residential property values at baseline demonstrated mixed associations with 1- and 2-year BMI change. More work is needed to understand how individual-level sociodemographic factors moderate associations between the BE, property values, and BMI change.

Project description:Investments in neighborhood built environments could increase physical activity and overall health. Disproportionate distribution of these changes in advantaged neighborhoods could inflate health disparities. Little information exists on where changes are occurring. This paper aims to 1) identify changes in the built environment in neighborhoods and 2) investigate associations between high levels of change and sociodemographic characteristics. Using Geographic Information Systems, neighborhood land-use, local destinations (for walking, social engagement, and physical activity), and sociodemographics were characterized in 2000 and 2010 for seven U.S. cities. Linear and change on change models estimated associations of built environment changes with baseline (2000) and change (2010-2000) in sociodemographics. Spatial patterns were assessed using Global Moran's I to measure overall clustering of change and Local Moran's I to identify statistically significant clusters of high increases surrounded by high increases (HH). Sociodemographic characteristics were compared between HH cluster and other tracts using Analysis of Variance (ANOVA). We observed small land-use changes but increases in the destination types. Greater increases in destinations were associated with higher percentage non-Hispanic whites, percentage households with no vehicle, and median household income. Associations were present for both baseline sociodemographics and changes over time. Greater increases in destinations were associated with lower baseline percentage over 65 but higher increases in percentage over 65 between 2000 and 2010. Global Moran's indicated changes were spatially clustered. HH cluster tracts started with a higher percentage non-Hispanic whites and higher percentage of households without vehicles. Between 2000 and 2010, HH cluster tracts experienced increases in percent non-Hispanic white, greater increases in median household income, and larger decreases in percent of households without a vehicle. Changes in the built environment are occurring in neighborhoods across a diverse set of U.S. metropolitan areas, but are patterned such that they may lead to increased health disparities over time.

Project description:BACKGROUND:Context-free outcome measures, such as overall leisure-time physical activity (LTPA), are habitually applied to study the neighborhood built environment correlates of physical activity. This cross sectional study identifies and empirically tests potential methodological limitations related to the use of context-free measures and discusses how these may help in the interpretation of inconsistent associations between participation in moderate-to-vigorous LTPA and objectively measured neighborhood-level built environment attributes. METHODS:We employ a public participation geographic information system (PPGIS), an advanced participatory mapping method, to study the spatial distribution of moderate-to-vigorous LTPA among adult urban Finnish residents (n 1322). Secondary sources of GIS land-use and sport facility data were used to disaggregate respondent-mapped LTPA by the behavioral context, such as indoor and outdoor sport facilities, green spaces, and other public open spaces. Associations between the use of the identified LTPA settings and a range of objectively measured neighborhood built environment attributes were studied with multilevel logistic regression models. RESULTS:Disaggregated by behavioral context, we observed varied and partly opposite built environment correlates for LTPA. The use of indoor and outdoor sport facilities showed no significant associations with their neighborhood availability, but were significantly associated with personal-level attributes. By contrast, participation in LTPA in green and built public open space shared significant associations with access to and availability of neighborhood green space that persisted after controlling for personal-level covariates. Moreover, neighborhood distances up to 1600 m poorly captured participation in moderate-to-vigorous LTPA, as, on average, 40% of visits were located further from home. However, we found the immediate home environment to be an important LTPA setting for the least active participants. CONCLUSIONS:This study demonstrates that LTPA can be a highly heterogeneous measure regarding both the spatial distribution and the environmental correlates of behavioral contexts. The results show that context-free LTPA outcome measures yield inconsistent associations with built environment exposure variables, challenging the applicability of such measures in designing neighborhood-level built environment interventions.

Dataset Information

Neighborhood Sociodemographics and Change in Built Infrastructure.

Publications

Neighborhood Sociodemographics and Change in Built Infrastructure.

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