Environments and Residents’ Shopping Behaviors

Urban Food Environments and
Residents’ Shopping Behaviors
Carolyn C. Cannuscio, ScD, Karyn Tappe, PhD, Amy Hillier, PhD,
Alison Buttenheim, PhD, MBA, Allison Karpyn, PhD, Karen Glanz, PhD, MPH
Background: Food environments may promote or undermine healthy behaviors, but questions
remain regarding how individuals interact with their local food environments.
Purpose: This study incorporated an urban food environment audit as well as an examination of
residents’ food shopping behaviors within that context.
Methods: In 2010, the research team audited the variety and healthfulness of foods available in 373
Philadelphia stores, using the validated Nutrition Environment Measures Survey in Stores (NEMS-S);
higher scores indicate more diverse and healthful food inventories. The team also surveyed urban
residents (n¼514) regarding their food shopping. Descriptive and multivariate analyses (conducted
in 2012) assessed variation in retail food environments and in shoppers’ store choices.
Results: Corner and convenience stores were common (78.6% of food retail outlets) and had the
lowest mean NEMS-S scores of any store type. Most participants (94.5%) did their primary food
shopping at higher-scoring chain supermarkets, and the majority of participants did not shop at the
supermarket closest to home. Supermarket offerings varied, with significantly fewer healthful foods
at supermarkets closest to the homes of disadvantaged residents. In multivariate analyses,
participants were significantly more likely to shop at supermarkets closest to home if those
supermarkets had higher NEMS-S scores.
Conclusions: These data suggest that, when possible, shoppers chose supermarkets that offered
more variety and more healthful foods. Findings from this study also reinforce concern regarding
unhealthy immediate food environments for disadvantaged residents, who disproportionately relied
on nearby stores with more limited food items. Interventions to improve nutrition and health should
address not only food store proximity but also diversity of healthful foods available.
(Am J Prev Med 2013;45(5):606–614) & 2013 American Journal of Preventive Medicine
Introduction
I
n the U.S., the majority of adults are overweight or
obese, and half of children are either overweight or at
risk of overweight.1,2 Overweight and obesity are
even higher in socioeconomically disadvantaged groups,
highlighting the importance of food and nutrition as
contributors to health disparities between rich and poor
populations.3
To explain the well-established socioeconomic gradient in health, researchers have increasingly studied
neighborhood physical and social environments as they
influence food-related behaviors and associated health
outcomes. Viewed within an ecologic framework, the
local food environment is thought to be important in
shaping the health of individuals, families, and communities.4–8 The diversity and proximity of retail food outlets
—and products, promotions, placement, and prices
within those stores9
—may influence health-relevant food
shopping behaviors and dietary patterns.10 Ample
research points to socioeconomic differences in local
food retail environments.7,8,11–13 Poorer neighborhoods
and those with a higher proportion of African American
residents often have fewer supermarkets14 and more fastfood outlets,15,16 a more restricted selection of healthful
From the Department of Family Medicine and Community Health
(Cannuscio), the Department of Biostatistics and Epidemiology (Tappe,
Glanz), Perelman School of Medicine, the Department of City and Regional
Planning (Hillier), School of Design, the School of Nursing (Buttenheim,
Glanz), University of Pennsylvania, The Food Trust (Karpyn), Philadelphia, Pennsylvania
Address correspondence to: Carolyn C. Cannuscio, ScD, University of
Pennsylvania, Department of Family Medicine and Community Health,
3620 Hamilton Walk, Rm. 145, Philadelphia PA 19104. Email:
[email protected].
0749-3797/$36.00
http://dx.doi.org/10.1016/j.amepre.2013.06.021
606 Am J Prev Med 2013;45(5):606–614 & 2013 American Journal of Preventive Medicine Published by Elsevier Inc.
options,17,18 and higher prices.19 Several studies document health disadvantages among people who live far
from supermarkets or close to fast-food outlets, including
lower rates of healthful food consumption19,20 and higher
body mass index.21,22 However, other studies report that
proximity to supermarkets or fast food23 is unrelated to
health outcomes.24,25
An influential line of research has examined the
existence and health effects of so-called food deserts—
areas with low access to affordable food.10,26,27 Despite
mixed evidence regarding the existence and health effects
of food deserts, the metaphor has inspired policies aimed
at decreasing the distance between consumers and the
places where they shop for healthful food.28
Researchers have called for a more nuanced examination of food access and food equity,25 to examine a range
of factors (including but not limited to proximity) that
influence food purchasing behavior.8,27–30 Accordingly,
this study explored an urban food environment and
individuals’ food shopping behaviors within that context.
In a racially and socioeconomically heterogeneous neighborhood, we hypothesized that travel beyond the closest
supermarket would be more common among people who
lived near supermarkets with lower quality and less
healthful food options (as measured by NEMS-S).
Methods
Study Area
Thirty city blocks were selected in a stratified random sample of six
contiguous ZIP codes. The source population in this 18-squaremile section of West and Southwest Philadelphia is 75% black/
African-American, 15% white, 6% Asian, and 1% Hispanic, and
28% of households live in poverty, according to the 2010 U.S.
Census.
Audit of Food Stores
To measure the availability of healthful foods within the study
area, trained staff members conducted audits in 2010 using the
NEMS-S, which has high inter-rater and test–retest reliability.17
The NEMS-S instrument identifies food items available in retail
establishments, including both regular items (e.g., whole milk or
ground beef) and more healthful alternatives (e.g., reduced fat milk
and lean beef or turkey). NEMS-S also measures the quality of
fresh fruits and vegetables (acceptable/unacceptable) and price.
Higher scores indicated that stores stocked more diverse and
healthful food items. Scoring is described in Appendix A (available
online at www.ajpmonline.org and elsewhere).17,31,32 All stores
within the study neighborhood, as well as out-of-neighborhood
shops identified by participants as primary shopping destinations,
were included in the NEMS-S audit, for a total of 373 stores.
Primary food shopping destinations were identified in response to
the question What is the name of the store or market where you do
most of your food shopping?
Stores were classified as follows: large chain supermarkets and
big box stores (e.g., Target, Wal-Mart); medium-sized, nonchain
grocers (more than one register; 3þ aisles); corner and convenience stores (only one register), chain pharmacies, and dollar
stores; and “other” stores, including specialty shops and produce
stores.33
The location of the primary food shopping destination and the
centroid of the residents’ city blocks (a proxy for home address)
were geocoded in ArcGIS 10.1. City blocks were, on average, 500
feet long, as calculated in ArcGIS; distances from block centroids
to participants’ homes were therefore modest.
Surveys
During summer 2010, the team conducted door-to-door surveys
(Appendix B, available online at www.ajpmonline.org), visiting
each housing unit on the 30 study blocks at different times to
administer the survey to an adult (aged Z18 years) who did most
of the food shopping. After three attempts, the interviewers left a
paper survey to be returned by mail. Interviewers reached a
resident at 47% of occupied properties and completed surveys at
83% of those properties. Only 8% of residents refused to
participate. More detailed survey information is available as
supplementary online material and elsewhere.34
Human Subjects
This protocol was approved by the University of Pennsylvania’s
Institutional Review Board, which granted a waiver of documentation of informed consent.
Data Analysis
For the 373 stores included in the NEMS-S audit, the team used
analysis of variance to compare total NEMS scores, capturing the
variety and healthfulness of foods available, across store types
(referred to hereafter as supermarkets; medium-sized grocers;
corner and convenience stores; and other stores). Then t-tests
were used to compare mean NEMS-S scores across sociodemographic groups, considering differences among both supermarkets
closest to participants’ homes and among primary shopping
destinations.
To assess sociodemographic variation in store choice and transit
mode, bivariate analyses were conducted, using chi-square tests to
compare proportions and t-tests to compare means.
Multivariate Poisson regression analyses were conducted to
understand predictors of store choice. This specification allows us
to calculate relative risks for a high-prevalence outcome. The
outcome of interest was whether or not the participant traveled
beyond the supermarket closest to home to conduct primary food
shopping. For this analysis, we standardized NEMS-S scores across
the samples of stores and then assigned these store-level standardized NEMS-S scores to individuals based on their closest
supermarket. Covariates included demographic measures (age,
gender, race) and socioeconomic variables (education, employment, public assistance, and car ownership), which were theorized
to be important correlates of both the quality of the local food
environment and individual food-related behavior.3,15 The model
also controlled for clustering by block and included indicators of
shoppers’ stated priorities for value, variety, quality, or convenience. The analytic sample included only survey respondents who
Cannuscio et al / Am J Prev Med 2013;45(5):606–614 607
November 2013
reported doing their primary food shopping at supermarkets
(94.5% of the total sample).
Analyses were performed in 2012 using SPSS version 19.0 and
Stata version 12.0.
Results
Survey Participation and Characteristics of
Study Participants
Of the 514 survey respondents, 66% were women, 73%
were black, 17% were white, and 10% “other”—comparable to area Census figures. Participants ranged in age
from 18 to 97 years, with a median age of 45 years. Fortyeight percent of survey participants had children aged
o 18 years in the household, compared to only 30% of
households in the study area.
Food Retail Environments
Corner and convenience stores accounted for the largest
proportion (78.6%) of food retail outlets. For 89.3% of survey
respondents, corner and convenience stores were the food
establishments closest to home, yet less than 1% of respondents elected to do their primary food shopping there. Most
participants (94.5%) did their primary food shopping at
supermarkets; participants named 60 different supermarkets
as their primary shopping destinations. There was substantial
variation across store types in the variety and healthfulness of
foods available, based on NEMS-S ratings. Scores were
significantly lower at corner and convenience stores than at
medium-sized grocers and supermarkets (Table 1).
In bivariate analyses restricted to supermarkets, there
was a pattern of less diverse and less healthful food
offerings at the stores nearest to the homes of poorer (i.e.,
those who received public assistance); less educated; and
black (compared to white) participants. Additionally,
within each sociodemographic stratum, mean NEMS-S
scores were higher for the primary food shopping
destination than for the supermarkets closest to home.
This suggests that participants elected, on average, to
shop at stores that offered more diverse and healthful
food options than were available near home. Nonetheless, the primary shopping destinations reported by
socially disadvantaged respondents (i.e., people on public
assistance) had significantly lower NEMS-S scores (and
therefore fewer healthful food items) than stores chosen
by more advantaged participants (Table 2).
Travel Distance and Mode of Transit
Approximately one third of all participants conducted their
primary food shopping at the supermarket closest to home
(Table 3). On average, participants traveled more than a
mile beyond the closest supermarket to reach their
preferred shopping destinations; distance traveled did not
differ significantly by race or socioeconomic status. The
majority of participants (70%) used cars (their own, shared,
or a friend’s) for food shopping, but there were clear
socioeconomic differences in mode of transit. For example,
57.7% of participants receiving public assistance traveled
by car to shop, as did 75.7% of participants not using public
assistance (po0.001).
Participants’ Primary Food Shopping
Destinations
Table 4 summarizes Poisson regression analyses that
examined the likelihood of traveling beyond the closest
Table 1. The urban food retail environment: store types, objective ratings, proximity, and use for primary shopping
Store types
n (%) of
stores
surveyed,
N¼373
NEMS-S
total
score,
M (SD)a
n (%) of respondents
for whom this type
of store is the store closest
to home, N¼516
n (%) of respondents
who choose this type
of store for primary grocery
shopping, N¼510
Large chain supermarkets
and “big box” stores
54 (14.5) 38.41 (7.58) 3 (0.6) 482 (94.5)
Medium groceries 15 (4.0) 21.67 (4.75) 52 (10.1) 11 (2.2)
Corner stores,
convenience stores,
chain pharmacies, and
dollar stores
293 (78.6) 11.11 (6.10) 461 (89.3) 2 (0.4)
Other 11 (2.9) 15.64 (5.70) 0 (0.0) 15 (2.9)
Note: Higher NEMS-S scores are preferable (i.e., they indicate better availability of healthful foods). Numbers in the last two columns vary because of
missing data regarding primary shopping destination.
a
Mean NEMS-S total scores were significantly different (po0.05) across store types. NEMS includes 11 measures of store nutrition environments that
assess the availability and pricing differences between healthier and less-healthy options: milk, fresh fruits and vegetables, ground beef, hot dogs,
frozen dinners, baked goods, beverages (soda/juice), whole grain bread, baked chips, and cereal.
NEMS-S, Nutrition Environment Measure Survey for Stores
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www.ajpmonline.org
supermarket to home in order to conduct primary food
shopping, controlling for a range of covariates. Notably,
standardized NEMS-S scores for the supermarket closest
to home were strongly associated with participants’ store
choices. An increase of one standard deviation in NEMSS score for the supermarket closest to home was
associated with a 26% lower prevalence of traveling
beyond that store to shop for groceries. In other words,
people were more likely to shop near home if the local
supermarket had more diverse, healthful food offerings.
Compared to their more advantaged peers, people who
were on public assistance had significantly lower prevalence of traveling beyond the closest supermarket; they
were more likely to shop near home, controlling for the
quality of the local supermarket. The model offers
some insight into how shoppers’ stated priorities shaped
their decisions regarding where to shop for groceries.
Prioritizing convenience and value were strongly associated with choosing to shop at the supermarket closest
to home.
Discussion
This study adds three findings to scientific and policy
debates regarding the existence and potential health
effects of “food deserts,” and about relevant food access
policies. First, the audit of 373 food retail outlets covered
an urban environment that was saturated with convenience and corner stores. However, urban residents did not
conduct their primary food shopping at these proximate
and ubiquitous shops, which are often a source of
impulse purchases, snack foods, tobacco, and beverages.
Participants instead chose to shop for groceries primarily
at large chain supermarkets, which have more variety and
more healthful foods and sometimes lower prices. Nonetheless, corner and convenience stores, as major elements
of the urban food environment, still may exert a negative
influence on nutrition, obesity, and health, through their
provision of easy access to cheap, highly caloric, and
unhealthy snack foods.35,36 According to data from this
study, these shops should not be misconstrued as primary
food shopping destinations, even for lower-SES urban
residents who often live near them.
Second, although participants overwhelmingly conducted their primary food shopping at supermarkets,
they did not necessarily shop at the supermarkets closest
to their homes; this finding has been reported in a prior
study.37 Instead, many participants opted for more
distant stores that offered more diverse and healthful
foods, as measured by NEMS-S. (Notably, these stores
may sell more of all types of foods—healthful and
otherwise.) According to these data, proximity was not
the primary driver of store choice. However, the distance
to the primary supermarket where respondents shopped
was not extremely far; the median distance was 1.34
miles. There was no estimation made of the specific
burden or time cost associated with travel beyond the
closest supermarket, which likely varies by mode of
transportation and socioeconomic status and may substantially constrain grocery shopping behavior.27,37,38
Third, in this assessment of store food environments,
there were fewer healthful food items at the supermarkets
—often discount chains—closest to the homes of less
educated, black, and lower-SES participants. Interestingly, on average, participants chose as their primary
shopping destinations stores that had higher NEMS-S
scores than observed at stores closest to their homes.
However, compared to people not on public assistance,
those on public assistance had lower-scoring stores close
to home and shopped at lower-scoring stores. These
lower-income participants may be more constrained by
mode of transit. A less healthy immediate food environment may perpetuate or exacerbate suboptimal
nutrition-related behaviors and poor health, while close
Table 2. Healthfulness and diversity of foods available:
mean (SD) NEMS scores
Supermarket
closest to
home
Primary food
shopping
destination
Overall sample 32.4 (10.4) 44.3 (18.2)
Gender NS NS
Female 32.1 (10.0) 44.2 (17.7)
Male 32.9 (10.9) 43.7 (18.2)
Race NS
Black 31.4 (9.4)*** 44.1 (18.3)
Not black 35.1 (11.9)*** 44.7 (18.0)
Education NS
High school
education or less
29.1 (9.8)*** 44.6 (20.4)
More than high
school education
34.4 (10.1)*** 44.0 (16.6)
Employment NS NS
Not employed 31.6 (9.5) 43.1 (17.4)
Employed 32.8 (10.7) 44.8 (18.6)
Receipt of public
assistance
Yes 30.1 (9.3)*** 41.3 (16.5)*
No 33.3 (10.7)*** 45.3 (18.4)*
Note: Boldface indicates significance. Analyses were done using t-tests.
*po0.05; **po0.01; ***po0.05
NEMS, Nutrition Environment Measure Survey; NS, not significant
Cannuscio et al / Am J Prev Med 2013;45(5):606–614 609
November 2013
Table 3. Store choice and mode of transport: unadjusted relationships with participant characteristics
Percentage who shop primarily at:
Mode of transport to primary shopping
destination (% sample):
Supermarket
closest to
home
Beyond the
closest
supermarket χ2
; p
Walk/
bicycle,
n¼86
(17%)
Public
transit/taxi,
n¼66,
(13%)
Car,
n¼355
(70%) χ2
; p
Age, years 5.02; p¼0.17 26.17
po0.01
N¼477 N¼494
18–29 35.0 65.0 30.8 8.7 60.6
30–44 33.6 66.4 18.3 16.2 65.5
45–59 23.1 76.9 14.2 10.4 75.4
Z60 31.2 68.8 7.0 16.7 76.3
Race 5.37; p¼0.68 19.54
po0.01
N¼480 N¼496
White 34.6 65.4 26.5 12.0 61.4
Black 27.7 72.3 12.4 13.3 74.3
Other 42.3 57.7 31.4 15.7 52.9
Gender Fisher’s exact
test
9.37
p¼0.01 po0.01
N¼483 N¼499
Female 26.6 73.4 13.5 12.8 73.7
Male 37.4 62.6 23.8 14.0 62.2
Household annual
income
Fisher’s exact
test
25.97
p¼0.64 po0.001
N¼374 N¼386
Z25,000 31.5 68.5 13.2 7.4 79.3
o25,000 28.9 71.1 23.6 20.8 55.6
Any public assistance Fisher’s exact
test
16.68
p¼0.34 po0.001
N¼487 N¼502
No 28.7 71.3 13.6 10.7 75.7
Yes 33.3 66.7 23.7 18.6 57.7
Own a car Fisher’s exact
test
173.63
p¼0.17 po0.01
(continued on next page)
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proximity to higher-quality supermarkets may be associated with healthier behaviors (e.g., fruit and vegetable
consumption) among Supplemental Nutrition Assistance
Program participants.39 Ensuring healthful options in the
immediate local food environment, or providing transportation to healthful options, remains an important
issue for vulnerable populations.
When possible, consumers in this study chose objectively
“better”—that is, more diverse and healthful—shopping
destinations, whether or not they were explicitly aware of
why they were choosing those higher-quality supermarkets.
In the $400-million National Healthy Food Financing
Initiative, the aim is to ensure that families will have access
to fresh food “right in their community.”
40,41 Data presented here indicate that shoppers consider a range of
factors, not just proximity, in choosing where to shop. Food
offerings matter, too. Further research must explicitly
elaborate on the cost–quality–time tradeoffs shoppers make
in deciding where to shop for food, in order to inform
interventions to encourage healthful food purchases.
Strengths and Limitations
This study benefits from the combination of objective
food environment audits and survey data regarding
individual behaviors and priorities within that context.
A limitation is the focus on participants’ primary food
shopping destinations. Many people shop for food at
multiple locations—perhaps emphasizing destination
shopping for large-volume purchases and using nearby
shops for frequently used or specialty items, or for
convenience or impulse purchases, not assessed in the
present study. The proximity and concentration of
corner and convenience stores has been linked to less
healthy dietary practices.42 These smaller shopping trips,
along with restaurant and takeout meals, which are
unaccounted for in the current study, may have important cumulative effects on diet quality, overall nutrition,
and health.13
In addition, this study focused on a particular area in a
large, densely populated city with mixed-use zoning and
an active food advocacy and policy environment. Even in
Table 3. (continued)
Percentage who shop primarily at:
Mode of transport to primary shopping
destination (% sample):
Supermarket
closest to
home
Beyond the
closest
supermarket χ2
; p
Walk/
bicycle,
n¼86
(17%)
Public
transit/taxi,
n¼66,
(13%)
Car,
n¼355
(70%) χ2
; p
N¼485 N¼501
No 35.0 65.0 33.5 34.2 32.3
Yes 28.7 71.3 9.4 2.4 88.2
Work status Fisher’s exact
test p¼0.22
5.23
N¼483 p¼0.07
N¼500
Not currently
working
27.1 72.9 14.5 17.2 68.3
Working part-time
or full-time
32.8 67.2 18.5 10.5 71.0
BMI 1.97; p¼0.58 17.18
po0.01
N¼451 N¼467
Normal 33.3 66.7 23.9 14.2 61.9
Overweight 31.9 68.1 15.5 7.7 76.8
Obese class I–II 27.8 72.2 12.4 17.8 69.8
Obese class III 21.1 78.9 10.0 11.7 78.3
Note: Sample sizes reflect the total number of people who responded to the relevant survey questions.
NEMS-S, Nutrition Environment Measure Survey for Stores
Cannuscio et al / Am J Prev Med 2013;45(5):606–614 611
November 2013
this mixed-income area with a relatively large proportion
of the population on public assistance, Philadelphia has
a range of nearby food retail and transportation
options, allowing many residents to exercise a degree of
choice. By the 1990s, Philadelphia had fewer supermarkets per capita than all but one other major U.S.
city.43 Today, Philadelphia is the poorest and one of the
most obese of the ten largest U.S. cities44 but also has
been the site of intensive food activism and supermarket
development over the last decade43—and obesity rates
may be declining.45 The results would likely be different
in a less densely populated urban environment, in one
with fewer or less varied retail food outlets or less
accessible public transit, and certainly in a suburban or
rural setting.21,46
Conclusion
This study echoes the call for a reframing of the food
desert debate to focus not just on proximity but on a
broader definition of food access—and one that prioritizes diverse offerings of healthful foods. Clearly, healthful foods remain unequally distributed in this urban
setting as they are elsewhere.10,24 Past research has
examined the relationship between perceived healthy
food availability and objective measures of availability,
which may offer insights regarding primary drivers of
food shopping locations and specific purchases.47 Future
studies should further examine people’s interactions with
local food environments, including subjective reasons for
choosing to shop at particular stores as well as their
(objectively measured) purchases within those stores.9,48
In Philadelphia as in many areas across the U.S., much
work remains to achieve equitable access to healthy foods
—a precondition for health.
We thank our research participants, community advisory
board, and data collection team. We are especially indebted
to Latifah Griffin and Nikki Thomas for their contributions to
study management. This work was supported by Agriculture
and Food Research Initiative Grant no. 2010-85215-20659
from the USDA National Institute of Food and Agriculture
Human Nutrition and Obesity Program.
Dr. Karpyn works for The Food Trust, a nonprofit that
conducts research and advocacy efforts to promote food access
and good nutrition.
No financial disclosures have been reported by the authors
of this paper.
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Table 4. Correlates of travel beyond the supermarket
closest to home in order to do primary grocery shopping:
results of Poisson regression analysis
Prevalence ratio
(95% CI) p-value
Total NEMS-S score for
closest supermarketa 0.74 (0.68, 0.81) o0.001
Age (measured in 10-year
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0.96 (0.93, 0.99) o0.001
Race/ethnicity
White 1.00 (ref)
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Other 0.83 (0.58, 1.19) o0.31
Gender
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Female 1.12 (0.98, 1.27) o0.1
Any public assistance
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Yes 0.83 (0.70,0.99) o0.03
Education
College graduate 1.0
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High school or less 0.96 (0.82, 1.13) po0.65
Own a car
No 1.00 (ref)
Yes 1.09 (0.92, 1.29) 0.33
Employment status
Not working 1.00 (ref)
Working part-time or
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0.90 (0.81,1.00) o0.06
Stated reason for choosing
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Variety of selections 0.93 (0.81, 1.08) o0.37
Quality of selections 1.07 (0.95, 1.22) o0.26
Convenience 0.64 (0.49,0.84) o0.001
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Appendix
Supplementary data
Supplementary data associated with this article can be found, in the
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614 Cannuscio et al / Am J Prev Med 2013;45(5):606–614
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