Format

Send to

Choose Destination
Soc Sci Med. 2016 Nov;169:97-105. doi: 10.1016/j.socscimed.2016.09.032. Epub 2016 Sep 23.

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

Author information

1
Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA. Electronic address: hijana@mailbox.sc.edu.
2
Department of Urban & Regional Planning, University of Michigan, Ann Arbor, MI, USA. Electronic address: grengs@umich.edu.
3
Department of Health Behavior & Health Education, University of Michigan, Ann Arbor, MI, USA. Electronic address: amy@schulz.com.
4
Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA. Electronic address: sadar@umich.edu.
5
Department of City & Regional Planning and Institute for the Environment, University of North Carolina, Chapel Hill, NC, USA. Electronic address: danrod@berkeley.edu.
6
Environmental Spatial Analysis Lab, University of Michigan, Ann Arbor, MI, USA. Electronic address: sjbrines@umich.edu.
7
Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA. Electronic address: avd37@drexel.edu.

Abstract

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.

PMID:
27701020
PMCID:
PMC5075249
DOI:
10.1016/j.socscimed.2016.09.032
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Elsevier Science Icon for PubMed Central
Loading ...
Support Center