Using built environmental observation tools: comparing two methods of creating a measure of the built environment.
OBJECTIVE
Identify an efficient method of creating a comprehensive and concise measure of the built environment integrating data from geographic information systems (GIS) and the Senior Walking Environmental Assessment Tool (SWEAT).


METHODS
Cross-sectional study using a population sample.


METHODS
Eight MUNICIPALLY defined neighborhoods in Portland, Oregon.


METHODS
Adult residents (N = 120) of audited segments (N = 363).


METHODS
We described built environmental features using SWEAT audits and GIS data. We obtained information on walking behaviors and potential confounders through in-person interviews.


METHODS
We created two sets of environmental measures, one based on the conceptual framework used to develop SWEAT and another using principal component analysis (PCA). Each measure's association with walking for transportation and exercise was then assessed and compared using logistic regression.


RESULTS
A priori measures (destinations, safety, aesthetics, and functionality) and PCA measures (accessibility, comfort/safety, maintenance, and pleasantness) were analogous in conceptual meaning and had similar associations with walking. Walking for transportation was associated with destination accessibility and functional elements, whereas walking for exercise was associated with maintenance of the walking area and protection from traffic. However, only PCA measures consistently reached statistical significance.


CONCLUSIONS
The measures created with PCA were more parsimonious than those created a priori. Performing PCA is an efficient method of combining and scoring SWEAT and GIS data.
Keast
Erin M
EM
Oregon Health & Science University, Portland, Oregon, USA.
Carlson
Nichole E
NE
Chapman
Nancy J
NJ
Michael
Yvonne L
YL
D000293:Adolescent; D000328:Adult; D002947:Cities; D003430:Cross-Sectional Studies; D004779:Environment Design; D015444:Exercise; D005191:Family Characteristics; D005260:Female; D040362:Geographic Information Systems; D015438:Health Behavior; D006801:Humans; D007182:Income; D007407:Interviews as Topic; D016013:Likelihood Functions; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D009922:Oregon; D011203:Poverty; D012106:Research; D012107:Research Design; D012111:Residence Characteristics; D016138:Walking
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