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How much are built environments changing, and where?: Patterns of change by neighborhood sociodemographic characteristics across seven U.S. metropolitan areas
Journal article   Open access   Peer reviewed

How much are built environments changing, and where?: Patterns of change by neighborhood sociodemographic characteristics across seven U.S. metropolitan areas

Jana A Hirsch, Joe Grengs, Amy Schulz, Sara D Adar, Daniel A Rodriguez, Shannon J Brines and Ana V Diez Roux
Social science & medicine (1982), v 169
Nov 2016
DOI: https://doi.org/10.1016/j.socscimed.2016.09.032
PMID: 27701020
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://europepmc.org/articles/pmc5075249View
Accepted (AM)Open Access (License Unspecified),  Open

Abstract

Automobiles - statistics & numerical data Environment Design - statistics & numerical data Environment Design - trends Humans Population Density Residence Characteristics - statistics & numerical data Socioeconomic Factors United States Urban Population - statistics & numerical data Urban Population - trends Walking - statistics & numerical data
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.

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9 Record Views
34 citations in Web of Science
36 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

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Collaboration types
Domestic collaboration
Web of Science research areas
Public, Environmental & Occupational Health
Social Sciences, Biomedical
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