Author's personal copy
Changes in Physical Activity and
Travel Behaviors in Residents of a
Mixed-Use Development
Karen G. Mumford, PhD, Cheryl K. Contant, PhD, Jennifer Weissman, MPH,
Jean Wolf, PhD, Karen Glanz, PhD, MPH
Background: Mixed-use developments may be especially promising settings for encouraging walking and other types of physical activity.
Purpose: This study examined the physical activity and travel behaviors of individuals before and after
they relocated to Atlantic Station, a mixed-use redevelopment community in metropolitan Atlanta.
Methods: A survey study was conducted to compare the behaviors, experiences, and attitudes of
Atlantic Station residents before and after moving to a mixed-use neighborhood. Data were collected
in 2008 and 2009 and analyzed in 2010. Key dependent variables were self-reported physical activity
and travel behaviors including walking for recreation and transport, automobile use, and use of
public transportation.
Results: Study participants included 101 adult residents of Atlantic Station, most of whom were
female, young, and well educated. There were signifıcant increases in walking for recreation or fıtness
(46%–54%; p⬍0.05) and walking for transportation (44%– 84%; p⬍0.001) after moving into the
mixed-use development. Respondents also reported reduced automobile travel and increased time
spent using public transportation after moving to Atlantic Station. Because this study used individuals as their own controls, there is more control over confounding lifestyle variables compared to
cross-sectional studies of individuals living in different neighborhoods.
Conclusions: Adults who move to a denser, mixed-use neighborhood increase their levels of
walking for both recreation and transportation, decrease their automobile travel, and increase their
use of public transportation.
(Am J Prev Med 2011;41(5):504 –507) © 2011 American Journal of Preventive Medicine
Background
D
eveloping neighborhood settings that encourage
walking or other forms of physical activity may
be an effective strategy for decreasing overweight
and obesity.1–3 Research4 – 8 from the fıelds of public
health, city planning, and architecture have established
associations of neighborhood design with physical activ-
From the Watershed Institute for Collaborative Environmental Studies, University of Wisconsin–Eau Claire (Mumford), Eau Claire, Wisconsin; System
Academic Administration, University of Minnesota (Contant), Minneapolis,
Minnesota; the Rollins School of Public Health, Emory University (Weissman);
Geostats LP (Wolf), Atlanta, Georgia; and the Department of Epidemiology
and Biostatistics, Perelman School of Medicine and School of Nursing, University of Pennsylvania (Glanz), Philadelphia, Pennsylvania
Address correspondence to: Karen Glanz, PhD, MPH, Department of
Epidemiology and Biostatistics, Perelman School of Medicine, University
of Pennsylvania, 801 Blockley Hall, 423 Guardian Drive, Philadelphia PA
19104-6021. E-mail: kglanz@upenn.edu.
0749-3797/$17.00
doi: 10.1016/j.amepre.2011.07.016
504 Am J Prev Med 2011;41(5):504 –507
ity and travel behaviors. However, many of the studies9 –12 published to date are cross-sectional and compare
the behaviors of residents living in neighborhoods that
provide varying levels of walkability and mixed use. This
raises the question of self-selection because those more
likely to engage in physical activity may choose more
walkable settings. To address the problem of self-selection,
several studies13–16 have used longitudinal study designs
to determine whether physical activity and travel behaviors change when people move between neighborhoods
of varying levels of walkability.
A survey was used with a combined cross-sectional and
retrospective study design to examine the physical activity and travel behaviors of individuals before and after
they relocated to Atlantic Station, a mixed-use development in metropolitan Atlanta. The design treats individuals as their own “controls.” Atlantic Station has a mix of
residential, commercial, and recreational land uses; activity centers with destinations that attract people; good
© 2011 American Journal of Preventive Medicine • Published by Elsevier Inc.
Author's personal copy
Mumford et al / Am J Prev Med 2011;41(5):504 –507
walking and bicycling routes; accessible mass transit; and
pleasing streetscapes and public spaces.17–20 The current
study tests the hypothesis that relocation to a dense, walkable residential environment promotes physical activity
and pedestrian-oriented travel behaviors.
Methods
Study Site
Atlantic Station is a 138-acre mixed-use development located in
Midtown Atlanta, Georgia. In 2008, Atlantic Station had 2250
residential units (single-family homes, condominiums, lofts, and
apartments) and two small parks. The 1.4 million ft2 of offıce space
included medical, dental, and fınancial offıces and the 1.5 million
ft2 of retail space supported shops, restaurants, a grocery store, and
large retail stores. Residential units are located over or adjacent to
the retail area.
Use of alternative transportation is promoted at Atlantic Station
by free shuttles to a nearby transit station, and assistance is available to help with car or van pools and guaranteed rides home.
Public buses provide service to the site. Bicycle lanes and sidewalks
are on all surface streets throughout Atlantic Station.
Study Design and Recruitment
In the original design of this research, subjects were to be
studied in their pre-move location and again several months
after moving to Atlantic Station. Because of the downturn in the
housing market in 2008, the design was modifıed to collect
pre-move recall data and post-move data from those who had
already moved to Atlantic Station. Therefore, a survey with
recall was used to analyze the pre- and post-move behaviors of
current Atlantic Station residents.
Recruitment letters and e-mails were sent to 2053 Atlantic Station addresses. Residents were excluded if they were aged ⬍18
years, unable to understand and speak English, were pregnant, had
physical impairments that limited their ability to walk, or had lived
at Atlantic Station for less than 3 months or more than 2 years. One
adult per household participated in the study. Follow-up phone
calls were conducted with 428 people, of whom 106 refused to
participate. Of the remaining 322, there were 117 (36.3%) eligible
to participate and 205 (63.7%) ineligible. Sixteen recruits withdrew,
for a fınal study sample of 101 (86.3% of those screened and
eligible).
All consent forms and surveys were completed onsite at Atlantic
Station in 2008 and 2009. The 148-item self-administered survey was
divided into two sections: (1) questions about neighborhood characteristics and activities before moving to Atlantic Station (pre-move
recall data); and (2) similar questions after moving to Atlantic Station.
Items included physical activity and travel behaviors, health status,
and demographics. Individuals completed both sections of the survey
in one sitting. The survey was constructed carefully to minimize confusion and spillover of pre-move information into the post-move
survey sections, and staff explained the survey structure when distributing the survey. Most survey questions came from validated instruments such as the Neighborhood Environment Walkability Scale
(NEWS)9 and the International Physical Activity Questionnaire
(IPAQ).21
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505
Dependent and Independent Variables and Potential Covariates
Categorical physical activity outcomes included prevalence of walking
for recreation and engagement in moderate or vigorous physical activity. Categorical travel outcomes included the prevalence of walking
for transportation, travel by automobile, and travel by public transportation. Continuous physical activity outcomes included the number of
days and minutes per week residents walked for recreation and the
number of days and minutes per week residents engaged in weekly
vigorous or moderate levels of physical activity. Continuous pre- and
post-move travel outcomes included the number of days and minutes
per week residents walked for transportation and traveled by car or by
public transportation. Independent variables and covariates included
demographic variables (e.g., age, gender, race); health status (selfreported health and fıtness status); and pre-move neighborhood type.
Statistical Analysis
The Wilcoxon Signed Rank Paired Test was used for continuous
variables because of the non-normal distribution of pre- and postmove variables. For categorical variables, McNemar’s chi-squared test
and matched ORs were used. Chi-squared and Fisher’s exact tests were
used to test associations between categorical variables. The KruskallWallis nonparametric test of signifıcance was used to assess associations between categorical demographic and continuous physical activity variables. All analyses were conducted in 2009 and 2010.
Results
Of the 101 study participants, most were female (67%); aged
ⱕ34 years (64%); white (47%) or black (33%); did not have
children (92%); had household incomes of $60,000 or more
(75%); and had completed college or some graduate education (77%). Most moved to Atlantic Station from urban
(47%) or suburban (41%) neighborhoods.
Mean days of recreational walking per week increased
signifıcantly (from 2.1 days to 3.0 days, p⬍0.02), but no
other recreational walking or physical activity measures
differed between pre- and post-move settings. Walking
for transportation purposes and use of public transportation increased after subjects moved to Atlantic Station
(Table 1). Study participants were almost twice as likely to
report walking for transportation (84% vs 44%; p⬍0.001)
and 1.5 times more likely to use public transportation at
Atlantic Station compared to their pre-move neighborhood (42% vs 24%; p⬍0.005). Both mean number of days
per week (4.52 vs 2.76; p⬍0.0001) and mean minutes per
week of transportation-related walking (85.5 vs 46.1;
p⬍0.0001) increased after individuals moved to Atlantic
Station.
Mean days per week of automobile travel decreased (5.5–
4.7 days; p⬍0.0001) as did mean minutes per week of automobile travel (636 –328 minutes; p⬍0.0001). However,
other measures of public transportation use did not differ.
Covariate analyses showed that the only variable that explained minutes per week of travel by car in the post-move
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Mumford et al / Am J Prev Med 2011;41(5):504 –507
506
neighborhood was
income. Those making $60,000 –$90,000
in household income
traveled more minutes per week (435.2
minutes) than any of
the other income categories (less than
$40,000, 163.8 minutes; $40,000 to
59,999, 175.6 minutes; more than
$90,000, 365.4 minutes; p⬍0.02).
Table 1. Walking, physical activity, and travel behaviors in the pre- and post-move
neighborhoods (N⫽101), % or M (SD)
Pre-move
neighborhood
Post-move
neighborhood
p-value
44
84
⬍0.0001
Walking for transportation
Yesa
b
Days/week
b
Minutes/week
2.76 (5.19)
4.52 (4.50)
⬍0.0001
46.1 (131.4)
85.5 (140.5)
⬍0.0001
Walking for recreation
Yesa
Days/week
46
b
b
Minutes/week
54
n.s.
2.09 (4.11)
2.96 (4.63)
⬍0.02
98.5 (236)
105.9 (204)
n.s.
Moderate physical activity
Discussion
Yesa
28
Adults who moved
Days/week
to a denser, mixedMinutes/weekb
use neighborhood inVigorous physical activity
creased their levels of
walking for transporYesa
tation, decreased their
Days/weekb
automobile travel and
Minutes/weekb
increased their use of
Automobile travel
public transportation.
As in other studies,
Yesa
the increases in walkDays/weekb
ing were more for
Minutes/weekb
transportation rather
Public transportation
than recreation purposes.10 There were
Yesa
no signifıcant associaDays/weekb
tions between demoMinutes/weekb
graphic or health staa
tus characteristics and
McNemar’s test
b
Wilcoxon signed rank test
walking for transporn.s., not significant (p⬎0.10)
tation after moving to
Atlantic Station, suggesting that the post-move changes are not limited to any
specifıc subgroup. The idea of “engineering” utilitarian
walking back into people’s daily lives could contribute to
reducing obesity and chronic disease.
Because the study design used individuals as their
own controls, there was more control over confounding lifestyle variables than in previous cross-sectional
studies of individuals living in different neighborhoods. However, these fındings are exploratory rather
than defınitive, because of the relatively small sample size,
generally affluent and well-educated study participants,
and the skewed distribution of physical activity data. The
b
25
n.s.
0.62 (1.26)
0.57 (1.17)
n.s.
45.6 (105.8)
34.5 (84.5)
n.s.
53
56
n.s.
1.84 (2.13)
1.87 (2.04)
n.s.
123.6 (187.3)
109.1 (161.3)
n.s.
90
88
n.s.
⬍0.001
5.52 (2.38)
4.66 (2.65)
635.6 (653.6)
327.6 (435.0)
⬍0.0001
24
42
⬍0.005
0.97 (2.05)
1.24 (1.98)
n.s.
53.8 (145.2)
83.5 (275.4)
n.s.
use of recall-based pre-move data introduces important limitations, as does the lack of a control group. The planned
design would have made a stronger “natural experiment”
but could not be implemented because of non-study-related
external events. Given the implausibility of randomly assigning people to live in different environments, this research makes important strides toward a research design
that can help rule out alternative explanations for changes in
walking and travel behaviors.
The authors gratefully acknowledge the assistance of Andrea
Winquist, Patrick Neubert, Kelsey Sprague, Nicole Dubruiel,
www.ajpmonline.org
Author's personal copy
Mumford et al / Am J Prev Med 2011;41(5):504 –507
Ross Brownson, Christy Hoehner, Cheryl Carnoske, Brian
Leary, and Peter Curnyn.
This publication was supported by Cooperative Agreement
Number U48 DP 000043 from the CDC to the Emory Prevention Research Center. The fındings and conclusions in this
journal article are those of the authors and do not necessarily
represent the offıcial position of the CDC. KG’s effort was
supported in part by a Distinguished Scholar Award from the
Georgia Cancer Coalition.
No fınancial disclosures were reported by the authors of this
paper.
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