Complete Streets Policies: Assessing Equity in Policy Adoption,
Active Travel to Work, and Policy Content
Jamie F. Chriqui, PhD,
1,2
MHS, Emily
Thrun,
2
MUPP,
Julien Leider,
2
MA
1Division
of Health Policy & Administration, School of Public Health, University of Illinois at Chicago
(UIC) 2Institute for Health Research and Policy, UIC
 Background
The Centers for Disease Control
recommends communities take action to
promote active transportation through
street design measures and complete
streets policies to protect and promote
health.1 Numerous communities have
adopted complete streets policies that
mandate streets to be designed to enable
safe access for pedestrians, bicyclists,
motorists, and transit riders of all ages
and abilities to safely move along and
across a street. However, very little is
known about how the diffusion of these
policies vary by socioeconomic and
demographic characteristics and whether
the policy content addresses equitable
access. For example, if wealthier towns
adopt complete streets policies, while
poorer ones do not, inequity is
exacerbated; and if poorer towns adopt
these policies but do not have the money
for new repairs or roads, then the
implementation is slower than in wealthier
towns. Even in jurisdictions that are more
mixed income, neighborhoods are
frequently divided by income, and are
often accompanied by racial segregation,
leading to similar issues. Thus, a
complete streets policy as written might
unintentionally increase disparities.
 Objectives
1. To examine the characteristics of
municipalities and counties in the United
States that have vs. have not adopted
complete streets policies.
2. To examine the association between
complete streets policy adoption and
active travel to work at the municipal and
county levels.
3. To identify equity-related provisions for
examining the content of complete
streets policies.
 Sample Frame
Municipal-level analyses: All municipalities
in the United States (N=30,642
municipalities). After accounting for missing
data, the municipal analyses included
29,244 municipalities.
County-level analyses: All counties and
consolidated cities in the United States
(N=3142 counties + 8 consolidated cities).
All 3150 counties/consolidated cities were
included in the analyses.
 Data Sources
Complete Streets Policy Data: Compiled
through primary research via the Internet with
email and telephone follow-up as part of two
separate nationwide research studies:
National Cancer Institute study of zoning and
land use reforms and as part of the Robert
Wood Johnson Foundation-supported
Bridging the Gap research project. The list of
communities was verified against the list of
policies compiled by the National Complete
Streets Coalition Policy Atlas and ChangeLab
Solutions State-level Complete Streets
Legislation analysis.2,3
Community-level Characteristics and
Active Travel Data: Community-level
socioeconomic and demographic
characteristics and active travel to work data
for all jurisdictions were obtained from the
Census Bureau’s American Community
Survey 2010-2014 5-year estimates.4
 Measures
 Regression Results
Objective 1: Characteristics of Jurisdictions w/
a Complete Streets Policy
Municipal Policy
RR
95% CI
0.70** 0.54, 0.91
County Policy
RR
95% CI
2.43
0.63, 9.33
State Policy
Region (West ref)
South
1.13
0.76, 1.69
1.43
Midwest
1.46*
1.02, 2.09
2.97*
Northeast
1.44+ 0.94, 2.21
1.53
Population Size Tertile (Large ref)
Small
0.20*** 0.15, 0.27
0.15***
Medium
0.52*** 0.41, 0.67
0.87
Median Household Income Tertile (High ref)
Low
1.09
0.79, 1.49
0.68
Middle
1.17
0.92, 1.49
0.64+
Continuous Variables
Median Age
0.99
0.85, 1.14
1.58*
% Non-Hispanic White
1.16
0.68, 1.98
0.24+
% Non-Hispanic Black
1.01
0.80, 1.29
1.17
% Hispanic
1.03
0.75, 1.41
0.65
% Occupied Housing Units 0.97
0.86, 1.10
0.89
% Renter-Occupied Units 1.01
0.76, 1.35
1.30
% Occ. Units with No Veh. 1.04
0.88, 1.23
0.73***
% Workers Walking to Work 1.04*
1.00, 1.08
1.15
% Public Transit to Work
1.29*** 1.13, 1.47
1.18+
% Workers Biking to Work 1.03
0.99, 1.08
1.10
+p<.10 *p<.05 **p<.01 ***p<.001
0.48, 4.24
1.29, 6.81
0.50, 4.68
0.05, 0.45
0.43, 1.76
0.30, 1.56
0.38, 1.08
1.07, 2.34
0.05, 1.17
0.56, 2.43
0.27, 1.58
0.69, 1.15
0.60, 2.83
0.62, 0.85
0.83, 1.59
1.00, 1.41
0.97, 1.25
OBJECTIVE 2
Having both a Municipal and State Complete Streets Policy
Is Associated with Higher Rates of Active Travel to Work
Policy: For objective 1, a dichotomous
measure of muni (or county) policy vs. none.
For Objective 2, separate categorical variable
for each analysis (muni and county) that
measured: muni (county) policy only, state
policy only, both muni (county) and state
policy; referent was no policy.
Community Characteristics: Tertiles of
population size and median household
income, median age of residents,
race/ethnicity percentages, % occupied
housing, % renter-occupied housing, %
occupied units with no vehicle, and region.
We also are evaluating the content of our full
sample of 841 jurisdictions (state/MPO/
county/municipal/town) for equity-related
provisions:
• Identifies specific users: pedestrians,
bicyclists, motorists, public transit users,
emergency vehicles, all ages,
seniors/elderly, children/youth, all
abilities, people with disabilities, all
income levels, low-income levels,
minorities, immigrants, all users
• Identifies benefits associated with policy:
equity, economic, health/PA,
accessibility, ADA access, safety,
environmental, convenience/comfort,
quality of life, compliance with
rules/policy
• Identifies locational prioritization of
projects in proximity to certain areas
including: priority population areas (e.g.
youth, disabled); affordable housing;
high-need areas; and specific
neighborhoods
• Performance/evaluation measures that
include equity-related components.
• Equity specifically mentioned in policy
 References
Having both a County and State Complete Streets Policy
Is Associated with Higher Rates of Active Travel to Work
Active Travel to Work: % that walk, bike,
walk or bike, take public transit, or any active
travel (walk, bike, or public transit use).
 Analyses
Data linked using FIPS codes. Separate
analyses conducted at county/consolidated
city and muni levels. All analyses weighted for
population size. Multivariate regressions
examined the association between (1) the
characteristics and policy adoption (logistic)
and (2) the association between policy
adoption and active travel to work measures
(linear). Adjusted prevalence measures were
calculated to predict rates of active travel by
policy category. In Q1, categorical variables
presented as relative risk of adopting a policy
vs. not; continuous measures compare the
RR at the 75th vs. 25th percentiles. County
analyses clustered on state, municipal
analyses clustered on state and county.
 Measuring Equity in Policies
(Objective 3)
 Summary of Findings
Complete streets policies are more common:
• In counties with an older median population age
• In the Midwest (compared to the West) (muni & county)
Complete streets policies are less common in:
• Municipalities with small and medium size populations
(compared to large)
• Counties with a small population (compared to large)
• Counties with more occupied units with no vehicles
Higher rates of active travel to work are associated with:
• Having both a municipal AND state policy
• Having both a county AND state policy
In other words, local and state policies help to reinforce
each other
(1) Centers for Disease Control and Prevention. CDC
Recommendations for Improving Health through
Transportation Policy. Centers for Disease Control
and Prevention 2010 April; Available:
http://www.cdc.gov/transportation/docs/transportatio
n-fact-sheet.pdf. Accessed September 4, 2015.
(2) Smart Growth America and the National Complete
Streets Coalition. Policy Atlas 2016; Available:
http://www.smartgrowthamerica.org/completestreets/changing-policy/complete-streets-atlas.
Accessed January 26, 2016.
(3) ChangeLab Solutions. 2016. Available at:
http://www.changelabsolutions.org/. Accessed
January 26, 2016.
(4) Census Bureau. American Community Survey
Summary File Data, 5-year estimates, 2010-2014.
Available at: http://census.gov/programssurveys/acs/data/summary-file.html. Accessed
December 5, 2015.
 Funding Support
Funding for this study was provided by the
National Cancer Institute, National Institutes of
Health under grant number R01CA158035, the
UIC Center for Clinical and Translational Science
UL1RR029879 (for the REDCap databases), and
from the Robert Wood Johnson Foundation
Healthy Eating Research Program Commissioned
Research, Equity in Complete Streets Policies.
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