United States 

Department of 

Agriculture

Economic

Research

Service

Economic

Research

Report

Number 140

August 2012

Characteristics and Influential 

Factors of Food Deserts

Paula Dutko

Michele Ver Ploeg

Tracey Farrigan
www.ers.usda.gov

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Recommended citation format for this publication:

Dutko, Paula, Michele Ver Ploeg, and Tracey Farrigan. Characteristics and 

Influential Factors of Food Deserts, ERR-140, U.S. Department of Agriculture, Economic Research Service, August 2012.
United States

Department

of Agriculture

www.ers.usda.gov

A Report from the Economic Research Service

Abstract

USDA’s Economic Research Service previously identified more than 6,500 food desert 

tracts in the United States based on 2000 Census and 2006 data on locations of supermarkets, supercenters, and large grocery stores. In this report, we examine the socioeconomic 

and demographic characteristics of these tracts to see how they differ from other census 

tracts and the extent to which these differences influence food desert status. Relative to 

all other census tracts, food desert tracts tend to have smaller populations, higher rates 

of abandoned or vacant homes, and residents who have lower levels of education, lower 

incomes, and higher unemployment. Census tracts with higher poverty rates are more 

likely to be food deserts than otherwise similar low-income census tracts in rural and in 

very dense (highly populated) urban areas. For less dense urban areas, census tracts with 

higher concentrations of minority populations are more likely to be food deserts, while 

tracts with substantial decreases in minority populations between 1990 and 2000 were 

less likely to be identified as food deserts in 2000. 

Keywords: food deserts, food access, low income, census tracts

Acknowledgments

The authors are grateful to our reviewers, Susan Chen of the University of Alabama, Lisa 

Powell of the University of Illinois at Chicago, and Alisha Coleman-Jensen of ERS. We 

thank David Smallwood, Ephraim Leibtag, and Mary Bohman of ERS for comments on 

multiple drafts of this report. We acknowledge participants at presentations of this paper 

at the 2011 Southern Economics Association Annual Conference in Washington, DC, and 

at the AAEA/EAAE Food Environment Symposium at Tufts University in May 2012 for 

their thoughtful suggestions. Thanks also to Priscilla Smith for editing the report and to 

Cynthia A. Ray for providing design and layout. Any remaining errors and omissions are 

the sole responsibility of the authors.

Paula Dutko

Michele Ver Ploeg

Tracey Farrigan

Characteristics and Influential 

Factors of Food Deserts Economic

Research

Report

Number 140

August 2012
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Contents

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Method for Defining and Measuring Food Deserts . . . . . . . . . . . . . . . . . 5

Descriptive Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Results: Comparing Food Desert Tracts With All Other Tracts . . . . . . 9

Demographic Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Economic Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Transportation and Mobility Characteristics . . . . . . . . . . . . . . . . . . . . . 13

Changes in Food Desert Tract Characteristics Over Time . . . . . . . . . . 15

Demographic Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Economic Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Transportation and Mobility Changes . . . . . . . . . . . . . . . . . . . . . . . . . . 19

Regression Analysis: Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Selection of Independent Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Regression Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
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Summary

What Is the Issue?

USDA’s Economic Research Service previously identified approximately 

6,500 food desert tracts in the United States based on 2000 Census and 2006 

data on locations of supermarkets, supercenters, and large grocery stores. These 

food deserts are areas where people have limited access to a variety of healthy 

and affordable food. As policymakers consider interventions to increase food 

access, it is important to understand the characteristics associated with these 

areas, such as income, vehicle availability, and access to public transportation. 

In this report, we examine the socioeconomic and demographic characteristics 

of these census tracts and also examine which of these characteristics distinguish food desert tracts from other low-income census tracts. 

What Did the Study Find?

•	Areas with higher levels of poverty are more likely to be food deserts,

but for other factors, such as vehicle availability and use of public transportation, the association with food desert status varies across very dense 

urban areas, less dense urban areas, and rural areas.

•	Areas with higher poverty rates are more likely to be food deserts regardless of rural or urban designation. This result is especially true in very 

dense urban areas where other population characteristics such as racial 

composition and unemployment rates are not predictors of food desert 

status because they tend to be similar across tracts.

•	In all but very dense urban areas, the higher the percentage of minority

population, the more likely the area is to be a food desert.

•	Residents in the Northeast are less likely to live far from a store than their

counterparts in other regions of the country with similar income levels.

•	Rural areas experiencing population growth are less likely to be

food deserts.

How Was the Study Conducted?

To provide a consistent, national-level estimate of the number of low-income 

areas in which a substantial number or share of residents is far from a supermarket or large grocery store, USDA’s Economic Research Service applied 

a census tract-level definition of food deserts—areas with limited access to 

affordable and healthy food—to the contiguous United States using 2000 

Census data. The 2000 Census data and 2006 store location data that were 

used for this analysis were the most recent demographic and store data available at the time this analysis was conducted.

This study uses data from the 1990 and 2000 Census, as well as 5-year 

average data from the 2005-2009 American Community Survey (ACS), to 

describe changes in characteristics of the 6,529 food desert census tracts over 

time, relative to changes in all other tracts. We focus particularly on population density, poverty rates, unemployment, education, race/ethnicity, income, 

and vehicle ownership status. 
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We first provide a statistical description of tracts classified as food deserts 

versus all other tracts to give a broad image of how food desert tracts differ. 

We then conduct regression analysis to determine which characteristics are 

most strongly associated with whether a low-income census tract is also 

a food desert. We model the probability that a census tract will be a food 

desert using a multivariate logit model to assess the impact of factors such 

as population and housing characteristics; racial and ethnic composition; 

unemployment; poverty; and changes in these characteristics from 1990 to 

2000. Separate analyses are performed for urban areas and rural areas in 

order to accommodate different definitions of food deserts and systematic 

differences in tract characteristics between rural and urban areas. We also 

further distinguish very dense urban areas from less dense urban areas for 

the multivariate analysis.
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Introduction

In the 2008 Food, Conservation and Energy Act (2008 Farm Act), Congress 

directed the U.S. Department of Agriculture (USDA) to assess the extent of 

areas in the United States where people have limited access to a variety of 

healthy and affordable food. Commonly referred to as “food deserts,” these 

regions of the country often feature large proportions of households with 

low incomes, inadequate access to transportation, and a limited number of 

food retailers providing fresh produce and healthy groceries for affordable 

prices. In response to this directive, USDA published Access to Affordable 

and Nutritious Food: Measuring and Understanding Food Deserts and Their 

Consequences (USDA, 2009). The report measured the extent of limited food 

access in the United States, highlighted potential sources and consequences 

of the problem, and suggested general policy solutions. The report found, 

among other conclusions, that 23.5 million people live in low-income areas 

that are further than 1 mile from a large grocery store or supermarket, and 

that 11.5 million of these people have low incomes themselves. 

Building on these findings, we examine what systematic socioeconomic and 

demographic differences exist between food deserts and other low-income areas.

Increased attention to national health issues, such as the rising incidence of 

obesity and the growing prevalence of diabetes and other weight-related diseases, 

especially in children, has made the concept of healthy food access increasingly important in the realm of public policy. New Orleans, New York City, and

Pennsylvania have implemented or are developing programs to improve access 

in underserved areas. One national effort, First Lady Michelle Obama’s Let’s 

Move! campaign, considers access to healthy food one of five pillars in the effort 

to address childhood obesity. A plan, the Healthy Food Financing Initiative 

(HFFI), has been proposed in Congress to bring affordable, nutritious food to 

areas of low access and low income. 

A working group comprised of staff from the U.S. Departments of the 

Treasury, of Health and Human Services, and of Agriculture is coordinating 

and sharing information about strategies to expand the availability of nutritious 

food in underserved areas. In cooperation with that working group, researchers 

from USDA’s Economic Research Service (ERS) developed a census tractlevel definition of food deserts in order to start identifying areas of the Nation

that may be in need of improved food access. Census tracts are identified as 

food deserts if they meet both low-income and low-food-access criteria. Using 

the specific definitions of both low income and low access (as detailed in the 

subsequent discussion), 6,529 census tracts were identified as food deserts 

across the Continental United States and mapped through an online mapping 

tool.1 These tracts were identified as food deserts based on 2000 Census data 

and 2006 data on locations of supermarkets, supercenters, and large grocery 

stores, which reflected the most recent demographic and store data available at 

the time of the analysis.

The relevance of food deserts to discussions of public health and food access 

policy nationwide makes critical the task of isolating potential causes of lowaccess areas. As a first step toward understanding this relationship, we explore 

over time the demographic characteristics of the 6,529 tracts identified as food 

deserts. Using data from the 1990 and 2000 decennial censuses, as well as 

1See the Food Desert Locator: http://

www.ers.usda.gov/data-products/

food-desert-locator.aspx/.
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from the 2005-2009 American Community Survey (ACS), we compare the 

economic and demographic traits of census tracts identified as food deserts 

with traits of all other tracts, as well as how these statistics may have changed 

between survey years. We first use descriptive statistics to provide a broad 

picture of how food desert tracts differ from all other census tracts, examining 

demographic, economic and employment, population density, and commuting 

patterns of census tracts. Next, we explore more specifically the characteristics associated with combined low income and low access, using multiple 

regression analysis to examine which of these characteristics are important in 

explaining whether a low-income tract is a food desert. 

Our analysis has several practical motivations. First, we want to better

understand this national measure of food deserts and how the designation 

of some low-income tracts as food deserts breaks down along population 

and economic characteristics. Second, by contrasting the population characteristics in areas of low access with those of other low-income areas, we 

can detect any systematic differences in the composition of food deserts. 

Identifying economic and demographic characteristics that are closely associated with low access to supermarkets and grocery stores will help policymakers better understand those neighborhoods with food access limitations, 

how they have changed over time, and potential barriers other than limited 

access to healthy food faced by residents of these areas. This is useful for 

providing surveillance for areas that may be at risk of becoming food deserts 

and can aid policymakers in formulating policies suited to the specific needs 

of these communities. Finally, results from this analysis can help policymakers and public health officials develop hypotheses to study further the 

mechanisms by which food deserts arise, thus allowing policymaking to 

address root problems rather than mere symptoms. 

We next review the literature on both how community food access has been 

measured and the characteristics of areas with limited access. Then we 

describe how the census tract-based measures of food deserts were derived 

and implemented. This is followed by a presentation of the methods used in 

the analysis and, finally, by the results and conclusions. 
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Literature

Areas with limited access to healthy, affordable food often lack access to 

other services as well, such as banks, health care, transportation infrastructure, and parks or recreational areas. In addition to having poor access, residents of impoverished or deprived areas frequently face higher prices for 

food and other necessities. Poor education and limited health care services 

in conjunction with high prices for fresh produce and other healthy food 

may result in poor diet and adverse health outcomes for residents of these 

areas. Access to affordable and nutritious food may also be important for the 

effectiveness of government benefit programs: an analysis using data from an 

electronic benefits transfer (EBT) demonstration in Dayton, OH, concluded

that improved access to large grocery stores can increase the welfare of 

Supplemental Nutrition Assistance Program (SNAP) recipients by an estimated value of $2.78 to $7.76 per month (Feather, 2003). SNAP is the name

of the former Food Stamp Program. These issues have motivated researchers 

to attempt to characterize low-access areas and to determine what demographic and economic factors influence low access. 

Past studies have typically considered the correlation between demographic 

and socioeconomic characteristics such as race, ethnicity, income, education, 

deprivation, and roadway connectivity, among other features of an area, with 

the level of food store access. Most of these studies have been conducted in 

localized areas such as neighborhoods or cities, but recently two noteworthy 

studies have been conducted at a national level (Powell et al., 2006; USDA, 

2009). The localized and national studies varied in their measures of food 

store access, including distance to a supermarket, number of grocery stores or 

fast food restaurants per capita in a geographical area, vehicle ownership, and 

the ratio of stores that carry healthy food options to stores that only carry less 

healthy food options. 

Perhaps because of the wide variety of measures used and places examined, 

study results have not reached a consensus on the characteristics of areas 

that lack access to healthy food. Studies have produced conflicting results as 

to the correlation among race, income, and access to healthy and affordable 

food. Many researchers have concluded that neighborhoods consisting 

primarily of minorities—in particular, African Americans—with low 

incomes have fewer supermarkets than wealthier, predominantly White 

neighborhoods (Berg and Murdoch, 2008; Powell et al., 2006; Block et al., 

2008; Larson et al., 2009). Others, however, have found either no correlation,

or that minority and low-income neighborhoods have a greater number of 

grocery stores and are closer to these stores than wealthier areas (Alwitt 

and Donley, 1997; Moore and Diez Roux, 2006; Opfer, 2010; and Sharkey

and Horel, 2008). These mixed results may not be surprising because these 

studies are of localized areas. However, results from the two national-level 

studies are also inconclusive. Powell et al. (2006) found that ZIP Codes with 

more minorities and lower income populations had fewer chain supermarkets 

but more nonchain supermarkets. USDA (2009) found that, on average, 

low-income and minority populations were closer to supermarkets than 

higher income individuals and non-Hispanic Whites. Multivariate analysis 

techniques, however, showed that measures of income inequality and racial 

segregation were important predictors of low access in urban core areas; the 
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most important factor in rural areas was lack of transportation infrastructure 

(USDA, 2009). 

The lack of consistent findings in this literature leads us to examine further 

the relationship between neighborhood characteristics and food access. Our

analysis builds upon previous studies and, in particular, components of USDA 

(2009) but is unique, however, in other ways. First, the census tract-based 

definition of a food desert is based on the methods and data used in the 2009 

USDA report but has been adapted to fit policy needs and to be consistent 

with multiple Federal agencies’ programs. Unlike previous studies, our 

analysis uses multiple years of census data to understand how changes in the 

population are correlated with food deserts. By using data from the 1990 and 

2000 Census and from the 2005-2009 American Community Survey, we will 

be able to assess how factors such as changes in an area’s overall population 

or changes in the ethnic and racial composition of an area are correlated with 

food access. This information could help predict which areas may be at risk of 

becoming food deserts and which areas may see improvements in food access. 
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Method for Defining and Measuring Food Deserts

The 2009 USDA report measures the distance to the nearest healthy-food 

retailer, using the locations of supermarkets and large grocery stores as a 

proxy, by referencing 1-square-kilometer grids for geographical analysis. 

These grids come from the Socioeconomic Data and Applications Center 

(SEDAC) and are based on information from the 2000 Census of Population 

(SEDAC, 2006). These population data (including socioeconomic and demographic data), which are released at the block group level, are first allocated 

to blocks and then allocated aerially down to roughly 1-square-kilometer 

grids across the Continental United States. For each grid cell, the distance 

from its geographic center to the nearest supermarket or large grocery 

store is used to measure access for people who live in that grid. Grids that 

are farther than a specified distance from the nearest supermarket or large 

grocery store are considered areas of low access, and low-access areas with 

a large percentage of low-income population are noted in particular. Use of 

the grid-level data provides two important benefits for the analysis: first, the 

data provide greater accuracy in estimating where people and households are 

located than data on larger geographic areas, such as census tracts; thus, they 

provide better precision in measuring distance to stores. Second, the process 

of allocating census data to 1-square-kilometer grid cells transforms the 

irregular shapes and sizes of census geographies or other geographies, such 

as ZIP Codes, into regular grid cells. 

While the 1-square-kilometer grid-based measures increase the precision in 

measuring where people are and how far they are from sources of healthy 

food and provide consistency in defining geographic areas across the country, 

the SEDAC grids are not widely used geographic units. Currently, no standardized nomenclature exists to identify a specific grid (as counties, ZIP 

Codes, or census tracts can be identified), and they cannot easily be linked 

to other geocoded data. For this reason, the area-based definition of a food 

desert uses the census tract as the geographic unit of analysis because it is 

more commonly used and has a standardized numbering system. 

Census tracts are subdivisions of a county, containing between 1,000 and 

8,000 people and ideally encompassing a population of about 4,000. In 

order to establish a consistent definition for national comparison, we define 

food deserts as low-income tracts in which a substantial number or proportion of the population has low access to supermarkets or large grocery 

stores. Low-income tracts are characterized by either a poverty rate equal to 

or greater than 20 percent, or a median family income that is 80 percent or 

less of the metropolitan area’s median family income (for tracts in metropolitan areas) or the statewide median family income (for tracts in nonmetropolitan areas). This definition of low-income tracts is used to designate 

tracts that are eligible for the U.S. Department of the Treasury’s New

Markets Tax Credit (NMTC) program.2 Low access is characterized by at 

least 500 people and/or 33 percent of the tract population residing more than 

1 mile from a supermarket or large grocery in urban areas, and more than 10 

miles in rural areas.3

2For additional information on 

the NMTC, see: http://www.cdfifund.gov/what_we_do/programs_

id.asp?programID=5/.

3The 1-square-kilometer grids are 

still used to calculate the number of 

people who are more than 1 or 10 miles 

from a supermarket, which are then

aggregated to the census tract level.
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Information on supermarket and large grocery store locations comes from 

a directory of supermarkets and large grocery stores, defined as food stores 

with at least $2 million in sales that contain all the major food departments 

found in a traditional supermarket. The directory was developed from a list 

of stores authorized to receive Supplemental Nutrition Assistance Program

(SNAP) benefits and was augmented by data from Trade Dimensions’

TDLinx (a Nielsen company), a proprietary source of individual supermarket

store listings. Both sets of data were provided for the year 2006.

Using this definition, we identified 6,529 census tracts that met the definition 

of “food desert” based on data from the 2000 Census of the Population, the 

most recent detailed demographic data available at the time of the analysis. 

Table 1 provides a breakdown of the number and percentage of all tracts that 

are food deserts over all census tracts, for tracts that are designated as NMTC

low-income tracts, and separately for rural and urban areas. Our descriptive analysis compares the demographic characteristics of those 6,529 tracts 

relative to the characteristics of all census tracts that are not considered food 

deserts by rural and urban status. We also compare changes in these characteristics over time to explore how demographic shifts might be associated 

with food desert areas. Our multivariate analysis only considers census tracts

that are designated as low-income tracts. 

Table 1

Number and percentage of food desert tracts by rural and urban status and by low-income status

Overall Rural Urban

Food desert tracts 6,529 2,204 4,175

Number of low-income tracts 24,927 6,519 17,940

Total number of tracts 64,999 13,827 50,784

Percent

Food desert tracts as percentage 

of low-income tracts

26.2 33.8 23.3

Food desert tracts as percentage 

of total tracts

10.0 15.9 8.2 

Note: Totals for rural and urban sets exclude tracts with greater than 50 percent of the population living in group quarters, which eliminates 710 

tracts—116 rural and 594 urban.

Low-income census tracts are those with: a poverty rate > 20 percent; median family income < 80 percent of statewide median family income 

(tracts outside metro areas) or median family income < 80 percent of the greater of statewide median family income (tracts outside metro areas) 

or the median family income of the metropolitan area.

Source: Authors’ calculations using Census 1990 data and Census 2000 data from National Change Database as well as U.S. Department of 

Commerce, U.S. Census Bureau, American Community Survey 2005-09 data.

Key Terms

Food desert

A census tract that meets both low-income and low-access 

criteria including:

1. poverty rate is greater than or equal to 20 percent 

OR median family income does not exceed 80 percent

statewide (rural/urban) or metro-area (urban) median 

family income;

2. at least 500 people or 33 percent of the population 

located more than 1 mile (urban) or 10 miles (rural) 

from the nearest supermarket or large grocery store.

Low-income area

A tract in which the poverty rate is greater than or equal to 20 

percent; or in which median family income does not exceed 80 

percent of the statewide or metro-area median family income

Low-income household

A household with income less than the Federal poverty level: 

$17,050 for a family of four in 2000.

Rural area

Includes areas defined by Rural-Urban Commuting Area 

codes as large rural, small rural, and isolated rural areas.
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Descriptive Analyses

Tract-level data from the 1990 and 2000 Census of the Population as well as 

from the 2005-2009 American Community Survey are used for population 

characteristics. Food desert status is determined based on year 2000 population data and store location data as of 2006. At the time of this report, food 

desert status has only been identified for this one year and thus is constant 

from one survey year to the next; thus the group of food desert tracts and 

the group of non-food desert tracts consist of the same tracts in each survey 

year. Our analysis compares statistics for the tracts identified as food deserts

based on the 2000 Census data and 2006 store locations with statistics for 

other tracts. We also calculate differences in characteristics of food deserts 

from 1990 to 2000, 2000 to 2005/2009, and over the entire period and 

compare these to changes in the same statistics for all other tracts. We use 

5-year average data from the 2005-09 ACS to provide a recent picture of the 

demographics of food desert tracts.4 We conduct and present these analyses 

separately for rural and urban tracts, as demographics tend to differ significantly between rural and urban areas. Rural Urban Commuting Area (RUCA) 

codes designate each tract as urban or rural.5 RUCA codes use census tracts 

to identify urban cores and adjacent areas that are integrated with these urban 

cores. Ten primary codes and 33 secondary codes are assigned based on the 

designation of areas as metropolitan or micropolitan, and high-commuting 

or low-commuting. We use a 4-category classification that allocates the 33 

RUCA secondary codes into urban, large rural, small rural, or isolated areas.6

We then combine large rural, small rural and isolated areas to create a single, 

broad rural category. 

Group quarters typically have institutional cafeterias and retail food facilities that are not counted in our list of supermarkets and large grocery stores. 

Some tracts that are dominated by university, prison, or military populations 

may appear to be food deserts, but because their populations are likely to 

be unique, we eliminate all tracts in which more than 50 percent of the total 

population resides in group quarters. This results in the exclusion of 105 rural 

and 557 urban tracts in 1990, 116 rural and 594 urban tracts in 2000, and 139 

rural and 600 urban tracts in 2005/09.

For the purpose of comparing the same tracts over time, we convert data for 

1990 census tracts to their corresponding Census 2000 tracts7 using a set of 

correspondence codes provided by Census.8 Tracts used in the 2005-09 ACS 

are generally the same tracts as identified in the 2000 Census and require 

little altering. A small number of tracts listed in the 2005-09 ACS data 

using their 2010 tract identification required reconciliation with their 2000 

definitions.9 We also convert all variables expressed in dollars to year 2000 

dollar-equivalents using the Consumer Price Index for All Urban Consumers 

(CPI-U) provided by the Bureau of Labor Statistics.10

To compare food desert tracts with non-food desert tracts in each individual 

year, we conduct t-tests grouping variables by food desert status. For interyear comparison, we aggregate each variable to its average value by food 

desert status and by survey year and perform t-tests comparing average 

values for food desert tracts with average values for other tracts for each 

survey. Differences in values between 1990 and 2000, between 2000 and 

4The ACS replaces the long-form 

Census after 2000 and provides much 

of the same data as the Decennial 

Census long form. We use the 5-year 

data as they are the only increments for 

which tract-level data are available for 

most variables.

5For more information, see: http://

www.ers.usda.gov/data-products/

rural-urban-commuting-area-codes.aspx/.

6For more information, see: http://

depts.washington.edu/uwruca/rucamaps.php./

7Census tracts are delineated by local 

census statistical area committees and 

may be be revised or redefined due to 

physical changes to the area, such as 

major roadways dividing a tract, or 

population growth or decline.

8A detailed description of the methods used to convert tracts across years 

is available upon request.

9Tracts included in the ACS data 

using their 2010 tract numbers are 

listed with their corresponding 2000 

tract number on the Census website, 

available at: http://www.census.gov/

acs/www/Downloads/geography/areas_published/BlockGroupsTable.pdf/.

10For more information, see: ftp://ftp.

bls.gov/pub/special.requests/cpi/cpiai.txt/. 
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2005/2009, and over the entire 1990-2005/2009 period are obtained as 

the difference calculated by each t-test. Changes reported are thus slightly 

different than those calculated by directly comparing variable means 

computed individually by year, as the Stata t-test command we used drops 

unmatched observations for each variable. Because tract boundaries change 

from one data year to another as the population changes, data from the year 

2000 reflect more tracts than from 1990; and data from the 2005-09 ACS 

reflect more total tracts than in 2000. When Stata conducts t-tests for a particular statistic between 2 years, the observation for a tract will be omitted if it 

is not reported in both years.
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Results: Comparing Food Desert Tracts With 

All Other Tracts

Our analysis compares economic and demographic characteristics of food

desert tracts and non-food desert tracts separately for rural and urban areas 

to control for the differences between these two populations. For the most 

part, our results suggest that differences between food desert tracts and other 

tracts are consistent regardless of rural or urban designation. In general, 

food desert tracts tend to have smaller populations, and abandoned or vacant 

homes are more prevalent in these tracts than in their counterparts. Residents 

of food desert tracts also tend to have lower levels of education, to earn lower 

incomes, and to be unemployed. Some of these disadvantages are highlighted 

in figure 1, which illustrates mean characteristics for food deserts and all 

other tracts based on Census 2000 data. Such socioeconomic differences 

between food deserts and other areas suggest that demographics may play a 

role in determining food access.

Demographic Characteristics

In all 3 survey years of our analysis, census tracts categorized as food deserts 

have slightly smaller total populations: from 9 to 14 percent fewer people in 

rural food deserts than in other rural tracts (table 2) and 7 to 13 percent fewer 

people in urban food deserts than other urban tracts (table 3). 

In both rural and urban areas, food desert tracts also have different ethnic 

and racial compositions than all other tracts. Non-Hispanic Whites comprise

about 12 percentage points more of the population in non-food desert rural 

tracts relative to those that are food deserts. Food desert tracts have a greater 

concentration of all minorities, including Hispanics. In urban food deserts, 

Figure 1

Mean characteristics of food deserts versus other tracts, Census 2000

Source: USDA, Economic Research Service calculations based on data from U.S. Census 2000.

Unemployment

rate

 (16 yrs +) 

0

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

Poverty

 rate

Population

 receiving 

public

assistance 

Population

minority 

Population

w/ less than

 high school 

degree 

Percent of population or housing units in 2000 Census

Food desert in 2000

Non-food desert in 2000

Housing unit

 with no

vehicle

available
10

Characteristics and Influential Factors of Food Deserts / ERR-140

Economic Research Service/USDA

Table 2

Characteristics of rural tracts by food desert status: 1990 Census, 2000 Census, and 2005-09 American 

Community Survey—continued

1990 2000 2005-09

Variable

Food 

desert

Non-food 

desert

Percent 

difference

Food 

desert

Non-food 

desert

Percent 

difference

Food 

desert

Non-food 

desert

Percent 

difference

Demographic

Total population 3,538.66 3,890.52 -0.09 3,608.12 4,020.54 -0.10 3,556.99 4,143.12 -0.14

(1,878.267) (1,828.165) (1,858.598) (1,810.424) (1,984.479) (2,102.12)

Population density 0.59 0.59 0.00 0.56 0.48 0.15 N/A N/A N/A

(1.229) (3.211) (1.091) (1.078) N/A N/A

Percent of population

Non-Hispanic 

White

0.77 0.87 -0.12 0.74 0.84 -0.13 0.77 0.87 -0.11

(0.278) (0.19) (0.29) (0.213) (0.264) (0.167)

Non-Hispanic 

Black/AfricanAmerican

0.11 0.07 0.54 0.11 0.07 0.55 0.11 0.07 0.53

(0.206) (0.147) (0.211) (0.15) (0.211) (0.15)

Hispanic

0.06 0.04 0.70 0.08 0.05 0.53 0.09 0.07 0.38

(0.16) (0.107) (0.173) (0.122) (0.18) (0.134)

Minority 0.23 0.13 0.81 0.26 0.16 0.66 0.29 0.17 0.64

(0.278) (0.19) (0.29) (0.213) (0.291) (0.202)

Age > 25 w/ education less than highschool diploma

0.36 0.31 0.16 0.28 0.23 0.20 0.21 0.18 0.19

(0.122) (0.12) (0.112) (0.104) (0.107) (0.095)

Age > 25 w/ 

bachelor’s degree 

or higher

0.10 0.13 -0.20 0.12 0.15 -0.22 0.14 0.17 -0.20

(0.0619) (0.0778) (0.0683) (0.0886) (0.081) (0.098)

Economic

Median family 

income (dollars)

30,085.83 36,688.39 -0.18 33,281.30 40,698.43 -0.18 35,860.64 42,550.44 -0.16

(6,971.205) (9,265.964) (6,688.86) (10,407.65) (8,931.062) (11,301.7)

Percent

Population w/ 

income < poverty

0.24 0.16 0.46 0.21 0.14 0.50 0.20 0.15 0.34

(0.118) (0.093) (0.108) (0.08) (0.108) (0.083)

Households 

receiving public 

assistance

0.12 0.08 0.42 0.12 0.09 0.39 0.03 0.02 0.38

(0.078) (0.0533) (0.074) (0.054) (0.0436) (0.024)

Vacant housing 

units

0.19 0.14 0.28 0.18 0.14 0.30 0.22 0.17 0.31

(0.139) (0.132) (0.128) (0.12) (0.137) (0.125)

Population age 

16+ in civilian labor 

force and unemployed

0.09 0.07 0.32 0.08 0.06 0.37 0.05 0.04 0.13

(0.0579) (0.0401) (0.0571) (0.0383) (0.037) (0.025)

Transportation & 

Mobility

Occupied housing 

units w/o vehicle 

access

0.11 0.09 0.24 0.09 0.08 0.25 0.06 0.05 0.15

(0.075) (0.063) (0.0642) (0.0538) (0.0514) (0.0479)

Population age 16+ 

commuting < 25 

minutes to work

0.74 0.74 -0.01 0.67 0.70 -0.03 0.65 0.68 -0.03

(0.134) (0.124) (0.147) (0.132) (0.163) (0.143)

Population age 16+ 

commuting > 45 

minutes to work

0.10 0.10 0.06 0.14 0.13 0.11 0.15 0.13 0.10

(0.0691) (0.0629) (0.085) (0.072) (0.096) (0.081)

continued—
11

Characteristics and Influential Factors of Food Deserts / ERR-140

Economic Research Service/USDA

this difference was nearly 70 percent in 1990, approximately 60 percent in 

2000, and 53 percent in 2005-2009. The proportion of minorities in rural 

food desert tracts is around 65 percent greater than non-food desert tracts in 

the most recent two surveys, down from an 80-percent difference in 1990. 

The gap between rural food deserts and non-food deserts is of similar size for 

African Americans and Hispanics; the gap in the proportion of the population 

that is Hispanic appears to be diminishing more noticeably over the period. 

The percent of the population that is non-Hispanic Black is over twice as 

large in urban food deserts than in other urban areas. 

Residents of food desert tracts have lower levels of education than their 

counterparts in non-food desert tracts. In rural food desert tracts, the proportion of the population with at least a bachelor’s degree is 20 percent lower 

than in other rural areas; the difference is 47 percent for urban food deserts 

versus other urban tracts. 

Economic Characteristics

Economic disparities between food desert tracts and other tracts is prevalent 

and noted in differences in median family income, unemployment rates, 

poverty rates, and the proportion of households receiving public assistance. 

Median family income is around 18 percent lower in rural food deserts than 

in non-food desert rural tracts.11 Data from the 2000 Census show a difference of less than 50 percent in the share of the population with income below 

the Federal poverty line from rural food deserts to all other rural tracts. 

Accordingly, a higher percentage of households receives some form of public 

assistance in rural tracts identified as food deserts than in other rural tracts. 

These trends persist throughout the three surveys. The gap between median 

family income in food deserts and non-food deserts is even larger in urban 

tracts than in rural areas. Likewise, poverty is more prevalent in tracts designated as food deserts, and a larger proportion of these households receive 

11This difference appears smaller, 

at 15.7 percent, in the ACS data. 

ACS income and poverty data are not 

directly comparable to income and 

poverty data provided by the Census, 

however. While the Census measures 

income-related variables using the 

calendar year, ACS data are calculated 

based on the last 12 months. ACS data 

is adjusted for the month for which the 

data are provided. A study conducted 

by the Census Bureau found only few 

statistically significant differences between State-by-State poverty rates from 

the ACS compared with poverty rates 

from the Census data, and the statistically significant differences were not 

necessarily economically significant. 

As our discussion highlights differences 

between geographic areas, we discuss 

ACS income-related data along with 

Census data.

Table 2

Characteristics of rural tracts by food desert status: 1990 Census, 2000 Census, and 2005-09 American 

Community Survey—continued

1990 2000 2005-09

Variable

Food 

desert

Non-food 

desert

Percent 

difference

Food 

desert

Non-food 

desert

Percent 

difference

Food 

desert

Non-food 

desert

Percent 

difference

Population commuting to work by 

private vehicle

0.85 0.89 -0.04 0.88 0.91 -0.03 0.88 0.90 -0.03

(0.098) (0.073) (0.084) (0.059) (0.088) (0.069)

Population commuting to work by 

public transport

0.01 0.01 0.22 0.01 0.01 0.19 0.01 0.01 0.05

(0.0122) (0.0174) (0.0115) (0.0103) (0.0199) (0.0161)

Population commuting to work by 

foot/bike/other 

0.08 0.06 0.31 0.06 0.04 0.35 0.11 0.09 0.29

(0.0575) (0.0504) (0.0502) (0.0431) (0.086) (0.066)

Number of tracts 2,211 11,476 2,204 11,472 2,202 11,451

N/A = A variable was not available for that data year. Standard errors are in parentheses. 

Source: U.S. Department of Commerce, U.S. Census Bureau, Census of the Population, 1990 and 2000; and 2005-09 American Community 

Survey; authors’ calculations of percentage differences. 
12

Characteristics and Influential Factors of Food Deserts / ERR-140

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Table 3

Characteristics of urban tracts by food desert status: 1990 Census, 2000 Census, and 2005-09 American 

Community Survey —continued

1990 2000 2005-09

Variable

Food 

desert

Non-food 

desert

Percent 

difference

Food 

desert

Non-food 

desert

Percent 

difference

Food 

desert

Non-food 

desert

Percent 

difference

Demographic

Total population 4,679.15 5,082.05 -0.08 4,111.47 4,447.19 -0.08 4,204.80 4,834.18 -0.13

(3,154.111) (3,459.29) (2,161.978) (2,186.521) (2,605.649) (2,986.424)

Population density 4.19 7.73 -0.46 3.51 6.87 -0.49 N/A N/A N/A

(6) (15.163) (3.261) (13.786) N/A N/A

Percent of population

Non-Hispanic 

White

0.57 0.75 -0.23 0.48 0.68 -0.29 0.56 0.72 -0.22

(0.329) (0.293) (0.322) (0.309) (0.299) (0.265)

Non-Hispanic 

Black/African 

American

0.29 0.12 1.37 0.32 0.14 1.27 0.31 0.14 1.19

(0.326) (0.233) (0.111) (0.164) (0.323) (0.236)

Hispanic

0.11 0.09 0.21 0.16 0.13 0.28 0.20 0.15 0.28

(0.201) (0.17) (0.232) (0.198) (0.249) (0.212)

Minority 0.43 0.25 0.69 0.52 0.32 0.60 0.56 0.36 0.53

(0.329) (0.293) (0.322) (0.309) (0.313) (0.308)

Age > 25 w/ education less than highschool diploma

0.35 0.23 0.49 0.30 0.19 0.57 0.24 0.15 0.60

(0.146) (0.151) (0.133) (0.143) (0.124) (0.125)

Age > 25 w/ 

bachelor’s degree 

or higher

0.12 0.22 -0.47 0.13 0.26 -0.51 0.15 0.30 -0.49

(0.102) (0.156) (0.106) (0.179) (0.116) (0.189)

Economic

Median family 

income (dollars)

33,770.05 52,655.01 -0.36 33,709.76 56,105.42 -0.40 34,250.95 58,328.22 -0.41

(11,418.21) (22,236.19) (9,849.384) (25,167.3) (12,809.35) (27,833.14)

Percent

Population w/ 

income < poverty

0.23 0.12 0.94 0.23 0.12 0.91 0.25 0.13 0.89

(0.147) (0.121) (0.124) (0.114) (0.136) (0.114)

Households 

receiving public 

assistance

0.13 0.07 0.72 0.13 0.08 0.67 0.04 0.03 0.66

(0.096) (0.0855) (0.085) (0.083) (0.043) (0.0365)

Vacant housing 

units

0.11 0.08 0.42 0.10 0.07 0.52 0.15 0.10 0.53

(0.079) (0.0726) (0.077) (0.0673) (0.095) (0.0842)

Population age 

16+ in civilian labor 

force and unemployed

0.10 0.06 0.58 0.09 0.06 0.57 0.07 0.05 0.45

(0.064) (0.0531) (0.06) (0.0539) (0.043) (0.0323)

Transportation & 

Mobility

Occupied housing 

units w/o vehicle 

access

0.17 0.12 0.38 0.16 0.12 0.33 0.11 0.09 0.24

(0.137) (0.161) (0.118) (0.151) (0.0879) (0.1257)

Population age 16+ 

commuting < 25 

minutes to work

0.69 0.62 0.12 0.65 0.59 0.11 0.65 0.57 0.13

(0.138) (0.16) (0.145) (0.162) (0.157) (0.171)

Population age 16+ 

commuting > 45 

minutes to work

0.10 0.13 -0.27 0.13 0.16 -0.21 0.12 0.16 -0.23

(0.074) (0.1056) (0.0855) (0.1118) (0.0941) (0.118)

continued—
13

Characteristics and Influential Factors of Food Deserts / ERR-140

Economic Research Service/USDA

public assistance income. This gap between urban food deserts and other 

urban tracts appears to narrow slightly over the time period. All 3 survey 

years show persistently higher incidences of poverty in the population of 

food deserts, ranging from 94 percent higher in 1990 to 89 percent higher in 

the most recent survey.

Unemployment rates also differ markedly between food desert tracts and 

other tracts. Unemployment among rural food desert residents is anywhere 

from 13 to 37 percent higher than in non-food desert tracts. The gap between 

unemployment rates in food deserts and in other tracts is even larger for 

urban areas than for rural: unemployment was about 60 percent higher in 

food deserts than other urban tracts in 2000. Also, the proportion of housing 

units that are vacant is higher in rural food desert tracts than in other rural 

areas. In conjunction with lower population numbers, this may reflect a 

general movement of population out of these tracts, leaving behind smaller 

populations and abandoned neighborhoods.

Transportation and Mobility Characteristics

Access to a private vehicle plays a large role in determining the ease of 

obtaining sufficient, healthy, and affordable food. Vehicle ownership rates 

are typically higher in rural areas than in urban areas as a result of the greater 

dispersion of residences, retailers, schools, and places of work in rural areas. 

Comparisons between food desert tracts and other areas suggest that the disadvantaged status of food deserts is also reflected in lower vehicle access rates. 

Data from the two decennial censuses suggest that 25 percent more of all occupied housing units report having no access to a vehicle in rural food deserts 

than in most rural tracts. The difference in vehicle access between rural food 

deserts and other rural tracts is smaller in the ACS data, at about 15 percent. 

For urban food deserts, the percentage of households without access to vehicles 

is anywhere from 24 to 38 percent higher than in other urban areas.

Table 3

Characteristics of urban tracts by food desert status: 1990 Census, 2000 Census, and 2005-09 American 

Community Survey —continued

1990 2000 2005-09

Variable

Food 

desert

Non-food 

desert

Percent 

difference

Food 

desert

Non-food 

desert

Percent 

difference

Food 

desert

Non-food 

desert

Percent 

difference

Population commuting to work by 

private vehicle

0.87 0.85 0.02 0.88 0.85 0.03 0.87 0.84 0.03

(0.111) (0.164) (0.099) (0.162) (0.111) (0.171)

Population commuting to work by 

public transport

0.05 0.07 -0.27 0.05 0.07 -0.30 0.05 0.07 -0.33

(0.0779) (0.1354) (0.0709) (0.1323) (0.0747) (0.138)

Population commuting to work by 

foot/bike/other 

0.06 0.05 0.25 0.05 0.04 0.22 0.08 0.08 -0.05

(0.067) (0.0607) (0.058) (0.0578) (0.077) (0.0715)

Number of tracts 4,197 46,331 4,175 46,316 4,166 46,320

N/A = A variable was not available for that data year. Standard errors are in parentheses. 

Source: U.S. Department of Commerce, U.S. Census Bureau, Census of the Population, 1990 and 2000; and 2005-09 American Community 

Survey; authors’ calculations of percentage differences. 
14

Characteristics and Influential Factors of Food Deserts / ERR-140

Economic Research Service/USDA

Time spent commuting between home and work, as well as the mode of 

transportation used for this commute, may also reveal the distance residents 

must travel from home to supermarket. A bigger share of the working population in rural food deserts has longer commutes (spends 45 minutes or more 

traveling to work) than in other rural tracts—around 10 percent greater in the 

most recent two surveys. Differences in work commute times between residents of rural food deserts and other rural areas could also reflect differences 

in modes of transportation used by workers. Private vehicles are used by a 

greater proportion of the working population in non-food desert rural tracts, 

while public transportation use is slightly higher in rural food desert tracts. 

Alternative methods of commuting (by foot, bicycle, or other) are substantially higher for residents of rural food desert tracts. Transportation patterns 

are reversed in urban areas: workers living in food deserts, despite lower 

access to private vehicles, report commuting to work by private vehicle in 

slightly greater proportion—a difference of 3 percent—than those in other 

urban areas. Meanwhile, residents of non-food desert tracts use public transportation in greater proportions than their food desert counterparts. This 

could be explained by a greater number of workers in food desert tracts using 

alternative forms of transportation, such as walking or biking, instead of 

private vehicles or mass public transit. Further, it could partly be responsible 

for the difference in commute times to work between food desert residents 

and other urban populations. A higher proportion of workers in urban food 

deserts has a short commute to work (less than 25 minutes) compared with 

workers in other urban tracts. The proportion of residents in urban food 

desert tracts with a commute to work shorter than 25 minutes is approximately 12 percent higher than in non-food desert urban tracts. 
15

Characteristics and Influential Factors of Food Deserts / ERR-140

Economic Research Service/USDA

Changes in Food Desert Tract Characteristics 

Over Time

The food desert tracts appear economically and socially disadvantaged relative to other tracts, and these differences seem to be relatively stable over 

time. Food desert tracts and other tracts change in many of the same ways 

throughout the period of study (table 4 for rural and table 5 for urban). Many 

of these changes reflect general trends in national socioeconomic composition, such as rising urban poverty as a result of multiple recessions since 

the year 2000. Interestingly, food desert tracts in both rural and urban areas 

show fewer statistically significant changes over the 30-year period than 

other tracts, and rural food desert tracts show fewer statistically significant 

changes than urban food desert tracts. This may reflect a relative stagnation 

in the characteristics of food desert tracts despite substantial changes in the 

economic climate, or it may simply be a manifestation of the smaller sample 

size of food desert tracts. Characteristics that did not change significantly 

across survey periods may be important in determining why certain tracts 

become food deserts and indicate tracts experiencing persistent deprivation.

Demographic Changes

Over the period surveyed, urban food desert areas experienced population

loss of 10 percent, while other urban areas experienced a loss of 4.8. Rural 

areas, however, experienced small growth in population overall—less than 1 

percent in food deserts and 6.8 percent in non-food deserts. Population loss 

is likely to discourage the entry of stores in an area and may contribute to 

the absence of stores. Population gain may indicate that a new store could 

be supported but that there is a lag in the development of such stores. Our

regression analysis will explore this further. 

Observing changes in racial and ethnic composition may help explain how

the populations of each area have shifted. The percent of the population 

reporting race as non-Hispanic White decreased in all urban tracts over the 

period, reflecting larger U.S. trends as minorities gained in number relative to 

the total population. Interestingly, the relative increase in minority population 

was larger in both rural and urban non-food desert tracts than in food desert 

tracts. However, in rural food deserts, the non-Hispanic White population 

increased very slightly.

Over the course of the 20-year period studied, educational attainment appears

to have increased, with a growing percentage of the population age 25 and 

older having obtained at least a bachelor’s degree. This proportion increased 

from 11.8 percent to 15 percent of the urban food desert population over 

the period, and from 22.4 percent to 29.6 percent of the non-food desert 

urban population. In rural food desert tracts and non-food desert tracts, the 

proportion of the population with at least a college degree grew from 10.2 

to 14 percent and from 12.7 to 17.4 percent, respectively, between 1990 and 

2005/2009. Concomitantly, the proportion of the same population having 

completed less than a full high school education has dropped.
16

Characteristics and Influential Factors of Food Deserts / ERR-140

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Table 4

Changes in characteristics of rural tracts by food desert status, 1990 to 2005-09—continued 

Food desert Non-food desert

1990-2000 2000-09 1990-2009 1990-2000 2000-09 1990-2009

Variable

Level 

change

Percent 

change

Level 

change

Percent 

change

Level 

change

Percent 

change

Level 

change

Percent 

change

Level 

change

Percent 

change

Level 

change

Percent 

change

Demographic

Total 

population 64.12 1.8 -44.76 -1.2 20.64 0.6 143.01 3.7 118.49 2.9 262.86 6.8 

Population 

density -0.04 -6.4 N/A N/A N/A N/A -0.10 -17.2 N/A N/A N/A N/A

Percent of population

Non-Hispanic 

White -0.03 -4.2 0.04 4.8 0.00 0.4 -0.03 -3.4 0.02 2.1 -0.01 -0.9 

Non-Hispanic 

Black/

African 

American 0.01 6.3 0.00 -1.5 0.00 4.3 0.00 5.9 0.00 -1.1 0.00 5.5 

Hispanic 0.02 28.5 0.01 14.1 0.03 47.1 0.02 43.9 0.01 24.6 0.03 82.0 

Minority 0.03 14.0 0.02 8.4 0.05 23.4 0.03 22.8 0.02 16.2 0.05 39.9 

Age > 25 w/ 

education 

less than 

high-school 

diploma -0.08 -23.2 -0.06 -22.1 -0.14 -40.2 -0.08 -25.4 -0.05 -22.0 -0.13 -41.8 

Age > 25 w/ 

bachelor’s 

degree or 

higher 0.02 18.2 0.02 15.7 0.04 36.9 0.03 21.4 0.02 13.1 0.05 37.4 

Economic

Median 

family 

income

(dollars) 3,209.36 10.7 2,540.86 7.6 5,739.83 19.1 4,074.95 11.1 1,417.03 3.4 5,742.10 15.6 

Percent

Individuals 

w/ income < 

poverty -0.03 -12.6 0.00 -1.9 -0.03 -14.3 -0.02 -14.7 0.01 9.4 -0.01 -6.6 

Households 

receiving 

public 

assistance 0.00 -0.9 -0.09 -71.7 -0.09 -72.0 0.00 1.9 -0.06 -71.9 -0.06 -71.2 

Vacant 

housing 

units 0.00 -1.4 0.03 18.6 0.03 16.7 0.00 -2.7 0.02 17.6 0.02 14.6 

Population 

age 16+ in 

civilian labor 

force and 

unemployed -0.01 -11.7 -0.03 -40.5 -0.04 -47.4 -0.01 -15.0 -0.02 -28.5 -0.03 -38.8 

Transportation & Mobility

Occupied 

housing 

units w/o 

vehicle 

access -0.01 -12.5 -0.03 -34.1 -0.05 -42.4 -0.01 -12.6 -0.02 -27.6 -0.03 -37.2 

continued—
17

Characteristics and Influential Factors of Food Deserts / ERR-140

Economic Research Service/USDA

Economic Changes

In rural food deserts, the proportion of the population that is poor fell from 

24 percent to 20 percent; in urban food deserts, it grew by 2 percentage 

points, from 23 percent to 25 percent.12 At the same time, the percent of 

households receiving public assistance also decreased over the period for 

all tracts, rural and urban. The universality of the latter trend may reflect 

lower cash assistance caseloads and stricter standards enacted during welfare 

reform in the 1990s. Combined with rising urban poverty rates, lower public 

assistance may compound food access issues in cities and other urban areas 

during this period.

Patterns in unemployment rates between 1990 and 2009 do not directly reflect 

the general economic downturn. For all areas—food desert and non-food desert, 

rural and urban—the unemployment rate has actually dropped over the period. In 

rural food deserts, the apparent decrease in unemployment is the largest, having 

fallen 47.4 percent from 1990 to 2009. This reduction in unemployment rates 

may not lead to accurate conclusions about economic health, though. The change 

in labor force participation may be a much more accurate indicator of economic 

well-being, as unemployment numbers will drop when discouraged workers 

cease searching for jobs and thus are no longer counted in the civilian labor force. 

12Income and poverty estimates 

are calculated differently by the ACS 

than by the Current Population Survey 

(CPS): CPS uses a calendar year reference period, while ACS uses a rolling 

12-month reference period. Because of 

this difference, direct comparison of 

poverty and income estimates between 

the Census and the ACS are inaccurate. 

We present changes over the entire period, as opposed to only those between 

the 2 Census years in order to capture 

the dramatic changes in national economic welfare that occurred between 

2000 and 2009.

Table 4

Changes in characteristics of rural tracts by food desert status, 1990 to 2005-09—continued 

Food desert Non-food desert

1990-2000 2000-09 1990-2009 1990-2000 2000-09 1990-2009

Variable

Level 

change

Percent 

change

Level 

change

Percent 

change

Level 

change

Percent 

change

Level 

change

Percent 

change

Level 

change

Percent 

change

Level 

change

Percent 

change

Population 

age 16+ 

commuting < 

25 minutes 

to work -0.06 -8.3 -0.02 -3.1 -0.08 -11.1 -0.05 -6.4 -0.02 -2.8 -0.07 -9.0 

Population 

age 16+ 

commuting > 

45 minutes 

to work 0.04 36.9 0.01 3.7 0.04 41.6 0.03 31.1 0.00 3.6 0.03 35.9 

Population 

commuting 

to work 

by private 

vehicle 0.03 3.6 0.00 -0.2 0.03 3.3 0.02 2.4 -0.01 -0.6 0.02 1.8 

Population 

commuting 

to work by 

public 

transport 0.00 -10.1 0.00 -14.3 0.00 -17.8 0.00 -3.5 0.00 3.0 0.00 -1.4

Population 

commuting 

to work by 

foot/bike/

other -0.02 -24.4 0.06 95.8 0.04 48.5 -0.02 -26.5 0.05 103.7 0.03 50.9 

N/A = A variable was not available for that data year. Standard errors are in parentheses. 

Source: U.S. Department of Commerce, U.S. Census Bureau, Census of the Population, 1990 and 2000; and 2005-09 American Community 

Survey; authors’ calculations of percentage differences.
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Table 5

Changes in characteristics of urban tracts by food desert status, 1990 to 2005-09—continued

Food desert Non-food desert

1990-2000 2000-09 1990-2009 1990-2000 2000-09 1990-2009

Variable

Level 

change

Percent 

change Variable

Level 

change

Percent 

change Variable

Level 

change Variable

Level 

change

Percent 

change Variable

Percent 

change

Demographic

Total 

population -566.23 -12.1 92.91 2.3 -479.93 -10.2 -632.02 387.32 8.7 -245.33 -4.8 

Population 

density -0.69 -16.4 N/A N/A N/A N/A -0.86 N/A N/A N/A N/A

Percent of population

Non-Hispanic 

White -0.09 -15.8 0.07 15.4 -0.02 -3.0 -0.07 -9.5 0.04 6.0 -0.03 -4.0 

Non-Hispanic 

Black/African 

American 0.03 11.2 0.00 -1.5 0.03 9.6 0.02 16.1 0.00 2.4 0.02 19.1 

Hispanic 0.05 44.8 0.03 20.1 0.08 74.1 0.03 37.3 0.02 19.2 0.06 63.9 

Minority 0.09 21.3 0.04 7.9 0.13 31.1 0.07 28.3 0.04 13.5 0.11 45.8 

Age > 25 w/ 

education 

less than 

high-school 

diploma -0.05 -13.2 -0.06 -19.1 -0.10 -29.7 -0.04 -17.7 -0.04 -20.5 -0.08 -34.5 

Age > 25 w/ 

bachelor’s 

degree or 

higher 0.01 9.8 0.02 15.8 0.03 27.2 0.04 18.2 0.03 12.0 0.07 32.3 

Economic

Median 

family 

income

(dollars) -45.99 -0.1 321.94 1.0 352.46 1.0 3,436.46 6.5 2,015.88 3.6 5,466.73 10.3 

Percent

Individuals 

w/ income < 

poverty 0.00 -0.6 0.02 8.8 0.02 7.8 0.00 0.8 0.01 9.8 0.01 10.7 

Households 

receiving 

public 

assistance 0.01 5.6 -0.09 -67.4 -0.08 -65.5 0.01 8.7 -0.05 -67.2 -0.05 -64.3 

Vacant 

housing 

units -0.01 -8.0 0.05 45.4 0.04 33.2 -0.01 -13.9 0.03 44.4 0.02 24.2 

Population 

age 16+ in 

civilian labor 

force and 

unemployed -0.01 -7.4 -0.02 -25.6 -0.03 -31.2 0.00 -7.0 -0.01 -19.6 -0.02 -25.1 

Transportation & Mobility

Occupied 

housing 

units w/o 

vehicle 

access -0.01 -6.3 -0.04 -26.1 -0.05 -31.0 0.00 -3.0 -0.03 -21.5 -0.03 -24.0 

continued—
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An increasing number of vacant housing units seems at odds with a growing 

population in rural tracts but may imply families moving in with one another 

to ease financial stress. Growth in vacant housing units may also reflect 

market conditions: overproduction during the housing boom in the late 1990s 

and early 2000s left many units vacant in high-growth areas after the real 

estate bubble popped. These additional unoccupied housing units would be 

reflected in the later data years. 

Transportation and Mobility Changes

Despite these indications of declining economic conditions, data suggests 

that vehicle access for housing units has improved. The proportion of households with no access to a vehicle decreased from 10.8 percent to 6.2 percent 

for rural food deserts and from 16.6 percent to 11.5 percent in urban food 

deserts over the period. These statistics reflect documented increases in 

vehicle ownership by low-income and single female-headed families over the 

past decade as public assistance programs have relaxed vehicle ownership 

rules (Baum and Owens, 2010; Hurst and Ziliak, 2004; and Sullivan, 2004)

and the Earned Income Tax Credit has expanded (Goodman-Bacon and 

McGranahan, 2008; Romich and Weisner, 2000; and Smeeding et al., 2000).

Table 5

Changes in characteristics of urban tracts by food desert status, 1990 to 2005-09—continued

Food desert Non-food desert

1990-2000 2000-09 1990-2009 1990-2000 2000-09 1990-2009

Variable

Level 

change

Percent 

change Variable

Level 

change

Percent 

change Variable

Level 

change Variable

Level 

change

Percent 

change Variable

Percent 

change

Population 

age 16+ 

commuting < 

25 minutes 

to work -0.04 -5.7 -0.01 -0.9 -0.04 -6.5 -0.03 -5.3 -0.01 -2.3 -0.05 -7.5 

Population 

age 16+ 

commuting > 

45 minutes 

to work 0.03 28.9 0.00 -1.3 0.03 26.8 0.03 19.5 0.00 1.0 0.03 20.8 

Population 

commuting 

to work 

by private 

vehicle 0.01 1.3 -0.01 -1.0 0.00 0.2 0.00 0.4 -0.01 -1.5 -0.01 -1.1 

Population 

commuting 

to work by 

public 

transport 0.00 -5.0 0.00 -1.7 0.00 -7.1 0.00 -1.9 0.00 2.4 0.00 0.4 

Population 

commuting 

to work by 

foot/bike/

other -0.01 -16.6 0.03 55.5 0.02 29.8 -0.01 -14.8 0.04 96.9 0.03 67.7 

N/A = A variable was not available for that data year. Standard errors are in parentheses.

Source: U.S. Department of Commerce, U.S. Census Bureau, Census of the Population, 1990 and 2000; and 2005-09 American Community 

Survey; authors’ calculations of percentage differences.
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Data from the two censuses and the ACS show a growing number of workers 

with longer commute times (45 minutes or more). In 1990, 9.7 percent of 

workers in urban food deserts spent at least 45 minutes commuting to work, 

compared to 12.4 percent in 2005/2009; in other urban tracts, this proportion 

grew from 13.3 percent to 16 percent. In rural food desert tracts, the average 

proportion of workers commuting longer than 45 minutes expanded from 

10.3 percent to 14.6 percent; in other rural areas, from 9.7 percent to 13.2 

percent. The increase is larger for rural workers than for urban workers, but 

these shifts in commuting patterns are consistent over all tracts, regardless 

of food desert status. Working residents of both urban and rural food deserts 

increasingly rely on active or alternative commutes, as opposed to public 

transit or private vehicles. Changes in the proportion of workers using public 

transportation to commute to work are generally small and not statistically 

significant, while fewer urban non-food desert residents are using private 

vehicles and all workers in rural areas are barely increasing their use of 

privately owned cars, trucks, and vans. 
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Regression Analysis: Methodology 

The descriptive statistics in tables 1-5 illustrate broadly how food desert 

tracts differ economically and demographically from other areas. They do 

not, however, allow us to draw any conclusions regarding what characteristics most strongly distinguish food desert tracts from other low-income 

tracts. The census tract food desert definition only includes tracts that meet 

low-income criteria as possible food deserts. To better understand what 

distinguishes food desert tracts from other low-income tracts, we estimate 

logistic regressions of the probability that a low-income census tract is a food 

desert. Our analysis focuses on characteristics as of the year 2000, as well as

changes from the 1990 Census to the 2000 Census. The regression analysis 

includes these years because we are interested in determining what characteristics and changes in tracts may have influenced conditions prior to the 

designation of food desert status based on 2000 Census data. The outcome 

of interest is binomial with a value of 1 if the area is a food desert and 0 if 

otherwise. The regression analysis only examines the food desert status of the 

census tracts that are classified as low income as defined earlier, because low 

income is a criterion for defining a food desert. Examining only low-income 

tracts allows us to isolate the characteristics that distinguish tracts with low 

income and low access from other low-access tracts.

Selection of Independent Variables

We expect food desert status to be influenced by population characteristics, 

economic and employment characteristics, population density, and commuter 

and travel patterns, and by trends in these characteristics over time. All of 

the tract-level characteristics included in the descriptive analysis above were 

considered for inclusion in the logistic regressions. However, after considering correlation matrices of these variables, we eliminate some of the variables because they were too highly correlated with other variables. Instead, 

we considered the demographic, economic, and other geographic variables 

for which supermarket access may be most affected and considered findings 

from previous research. For example, areas with greater population density 

are likely to support a greater number of grocery stores and more likely to 

have stores close by. And even among low-income areas, those with higher 

levels of poverty, lower incomes in general, and more vacant housing units 

may not be able to support as many stores. Previous studies have emphasized the role of race and ethnicity as well. Changes in these variables (for 

example, population loss or decreasing incomes) may also reflect a community’s food retail prospects as firms consider where to locate and whether to 

improve or eliminate poorly performing stores. Regional dummy variables 

were included to control for broad differences in geographic characteristics. We use food desert status as the dependent variable in three different 

specifications. The first regression, which is our basic model, includes static 

measures of census tract demographic and economic characteristics, along 

with regional indicator variables: 

•	median family income in thousands of dollars;

•	percent of housing units vacant;

•	percent of population of minority race/ethnicity;
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•	percent of population age 16 or older that is unemployed;

•	percent of the population with income below the Federal poverty line;

•	indicator variables for each of the four Census regions of the United

States; and

•	population density, measured as thousands per square mile.

We next test the effect of adding variables to reflect changes in demographics. The second model includes the above regressors, as well as 

indicator variables for an increase in population greater than 10 percent; a 

decrease in population greater than 10 percent; an increase in the minority 

percent of the population greater than one standard deviation of the change 

in percent minority; and a corresponding variable for decrease in percent 

minority population. For very dense urban areas, we replace the variables for 

significant increase and significant decrease in the percent of the population 

that is of minority race/ethnicity with an indicator for any significant change, 

regardless of direction, in percent minority. A change in percent minority 

with an absolute value of at least 10 percent is considered significant in 

defining this variable. 

The third specification tests the effects of variables indicating tract-level 

economic changes between 1990 and 2000 in the regression. Variables for an 

increase in the poverty rate greater than one standard deviation of the average 

change in poverty rate across all tracts, and a corresponding variable for a 

decrease in the poverty rate of the same scale are added. 

We run an initial regression on the set of all tracts, both rural and urban, that 

qualify as low income, using the following independent variables: 

•	median family income in thousands of dollars;

•	percent of vacant housing units;

•	percent of population of minority race/ethnicity (percent non-Hispanic

White); 

•	percent of population age 16 or older that is unemployed;

•	percent of population with income below the Federal poverty line;

•	indicator variables for each of the four Census regions of the United

States (Northeast is omitted); and

•	a variable to indicate whether each tract is rural or urban.

To determine whether separate regressions should be run for urban and 

rural tracts, we fully interact the model using the binary urban indicator and 

perform a Chow test to determine whether these interaction terms are jointly 

significantly different from zero. The Chow test results in a chi-squared value 

of 540.01 and a p-value of 0.000, confirming that the socioeconomic factors 

above interact differently with food desert status depending on whether a 

tract is rural or urban. As a result, we run separate models for rural tracts and 

for urban tracts. 

The variety of tracts that fall into the urban category varies widely—from 

very dense central city tracts, to suburban tracts, to small city and large 
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town tracts. Retail development, population density, and other area characteristics could be very different in densely populated tracts than in the 

less dense urban areas. We also consider the possibility that the factors that 

affect food desert status in very dense urban areas differ from those in less 

dense urban areas. We define very dense urban areas as those in which the 

population per square mile (in 1,000s) is at or above the 90th percentile of 

population density for all urban tracts. We perform a similar Chow test to 

determine whether all urban areas should be grouped together for purposes 

of the regression or if very dense areas should be estimated separately from 

less dense urban areas. This test produces a chi-squared value of 370.50 and 

a p-value of 0.000. Therefore, we create separate data sets for urban areas 

with high population density (“very dense”) and all other (“less dense”) 

urban tracts. There are 6,519 rural low-income tracts in our sample. The total 

sample of urban tracts is 17,940, of which 14,385 tracts are considered less 

dense and 3,555 tracts fall into our dense category, with population density in 

the 90th percentile or higher.

For each set of rural tracts, very dense urban tracts, and less dense urban 

tracts, we perform three logistic regressions based on the models outlined 

above. To further control for differences among less dense urban tracts, we 

add a variable for population density—thousands of people per square mile. 

Regression Results

For both urban and rural regressions, minority population, poverty rates, and 

region of the country are consistently significant predictors of food desert 

status. We now discuss the most consistent and policy-relevant results, while 

detailed results are presented in tables 6 and 7. 

In rural areas, the percent of vacant housing units within a tract is a significant predictor of food desert status with a consistently large odds ratio. 

The percent of the tract population that is poor is also a consistently strong 

predictor of food desert status; tracts with higher poverty rates are more 

likely to be food deserts than otherwise similar low-income tracts. As some 

of the previous studies have found, we also find that the racial/ethnic composition of a tract is correlated with food desert status. The percent of the tract 

population that is minority is a consistently positive predictor of food desert 

status. Unexpectedly, higher rates of unemployment decrease the odds a 

tract fits the definition of a food desert. This result, while counterintuitive, is 

robust across specifications. Rural tracts located in the West, Midwest, and 

South are also much more likely to be food deserts than rural tracts located 

in the Northeast. This might reflect the relative proximity of rural tracts in

the Northeast to urban tracts (that contain grocery stores), compared with the

more sparsely populated rural areas in the South, Midwest, and West. 

Many of the same demographic factors are important predictors of food 

deserts in less dense urban areas as in rural areas, although some differences 

exist. Notable differences also exist between very dense and less dense urban

tracts (table 7). 
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Table 6

Logistic regression odds ratios and 95-percent confidence intervals for rural low-income tracts

Rural low-income tracts Basic model: all rural tracts

Basic model w/ demographic 

change: all rural tracts

Basic model w/ demographic 

& economic change: 

all rural tracts

Median family income 

0.99 0.991 0.992

(0.979 - 1.000) (0.981 - 1.001) (0.981 - 1.002)

Vacant housing units (percent)

14.152** 14.678** 14.187**

(8.532 - 19.773) (8.653 - 20.702) (8.346 - 20.028)

Population minority (percent)

2.351** 2.434** 2.361**

(1.816 - 2.886) (1.851 - 3.016) (1.786 - 2.936)

Population age 16+ in civilian 

labor force and unemployed 

(percent)

0.027** 0.028** 0.028**

(-0.006 - 0.060) (-0.006 - 0.063) (-0.006 - 0.062)

Individuals w/ income < poverty 

(percent)

3.312* 3.185* 3.224*

(0.628 - 5.997) (0.599 - 5.772) (0.514 - 5.934)

West Census region

2.574** 2.681** 2.648**

(2.046 - 3.101) (2.120 - 3.241) (2.094 - 3.202)

Midwest Census region

2.827** 2.863** 2.799**

(2.308 - 3.347) (2.336 - 3.390) (2.278 - 3.320)

South Census region

1.270* 1.303* 1.282*

(1.023 - 1.517) (1.048 - 1.559) (1.029 - 1.535)

Population density

0.981 0.983 0.983

(0.942 - 1.019) (0.944 - 1.022) (0.944 - 1.022)

Substantial increase in population

0.889 0.888

(0.794 - 0.983) (0.793 - 0.983)

Substantial decrease in 

population

1.009 1.006

(0.874 - 1.144) (0.872 - 1.141)

Substantial increase in percent 

minority

0.91 0.918

(0.796 - 1.025) (0.799 - 1.036)

Substantial decrease in percent 

minority

1.541* 1.512*

(1.057 - 2.025) (1.036 - 1.987)

Substantial increase in poverty 

rate

1.103

(0.902 - 1.303)

Substantial decrease in poverty 

rate

1.114

(0.998 - 1.230)

Observations 6,519 6,519 6,519

95-percent confidence intervals in parentheses. * significant at 5 percent. ** significant at 1 percent.

Low-income census tracts are those with: a poverty rate > 20 percent; median family income < 80 percent of statewide median family income 

(tracts outside metro areas) or median family income < 80 percent of the greater of statewide median family income (tracts outside metro areas) 

or the median family income of the metropolitan area.

Source: Regression output created using statistical software Stata, based on U.S. Department of Commerce, U.S. Census Bureau, Census 1990 

and Census 2000 data from National Change Database.
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Table 7

Logistic regression odds ratios and 95-percent confidence intervals for urban low-income tracts

Urban lowincome tracts: 

Odds ratios

Basic model: 

less dense 

urban tracts

Basic model: 

very dense 

urban tracts

Basic model w/ 

demographic 

change: less 

dense urban 

tracts

Basic model w/ 

demographic 

change: very 

dense urban 

tracts

Basic model w/ 

demographic 

& economic 

change: less 

dense urban 

tracts

Basic model w/ 

demographic 

& economic 

change: very 

dense urban 

tracts

Median family 

income 1.003 0.991 1.003 0.995 1.003 0.997

Vacant housing 

units (percent) 0.502* 44.846 0.545* 53.162 0.569* 17.749

Population minority 

(percent) 1.557** 0.332 1.534** 0.428 1.567** 0.419

Unemployed 

(percent) 0.357** 0.014 0.361** 0.02 0.364* 0.01

Individuals w/ 

income < poverty 

(percent) 0.853 29.813* 0.912 37.749* 0.903 82.138**

West Census 

region 0.737** 2.576* 0.745** 2.899* 0.746** 3.015**

Midwest Census 

region 1.028 2.904* 1.024 2.901* 1.036 2.141

South Census 

region 1.113 4.821** 1.117 4.965** 1.119 4.599**

Population density 0.817** Omitted 0.815** Omitted 0.815** Omitted

Substantial 

increase in 

population 

1990-2000 0.921 0.351* 0.923 0.340*

Substantial 

decrease in 

population 

1990-2000 0.987 0.543 0.989 0.532

† Substantial 

increase in percent 

minority 1990-2000 1.054 1.648 1.044 2.084*

Substantial 

decrease in percent 

minority 1990-2000 0.585** 0.596** Omitted

Observations 14,385 3,555 14,385 3,555 14,385 3,555

95-percent confidence intervals in parentheses; * significant at 5 percent; ** significant at 1 percent.

† Substantial change in either direction for very dense urban tracts.

Low-income census tracts are those with: a poverty rate > 20 percent; median family income < 80 percent of statewide median family income 

(tracts outside metro areas), or median family income < 80 percent of the greater of statewide median family income (tracts outside metro 

areas) or the median family income of the metropolitan area.

Source: Regression output created using statistical software Stata, based on U.S. Department of Commerce, U.S. Census Bureau, Census 

1990 and Census 2000 data from National Change Database.
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As is the case with rural tracts, the percent of the tract that is minority is a 

strong predictor of food desert status in the less dense urban tracts. In these 

tracts, a 1-percentage-point increase in the percent minority is associated 

with about a 50-percent increase in the odds of being a food desert. In less 

dense urban areas, the model that includes changes in demographic characteristics over time indicates that a large decrease in minority status also lowers 

the odds that a tract is a food desert in less dense urban areas. Interestingly, 

the percent of the population of minority race or ethnicity in a tract is not a 

significant predictor of food desert status in very dense urban tracts, nor are 

the variables for changes in the percentage minority between 1990 and 2000. 

The extent of poverty in very dense urban tracts is an important predictor 

of food deserts, but it is not a predictor of food desert status in less dense 

urban areas. The model that includes a measure of the change in poverty 

rates between census years shows that poverty changes in less dense urban 

areas are not related to the odds that a tract is a food desert. However, in very 

dense urban areas, a substantial decrease in a tract’s poverty rate increases 

the odds that a tract is a food desert. This result is counterintuitive. It is 

possible that the few very dense tracts with large swings in poverty rates may 

be in a state of flux with respect to residential and retail development. 

Among less dense urban tracts, those in the West are less likely to be food 

deserts than their counterparts in the Northeast. And as expected, higher

population density within the less dense areas reduces the odds of a food 

desert slightly. Dense urban areas located in the West, Midwest, and South 

are also more likely to be food deserts than dense areas in the Northeast. This

may reflect the difference between very dense cities in the Northeast (e.g.,

New York and Philadelphia) where few neighborhoods are more than 1 mile

from a supermarket and very dense urban tracts in other cities that may be 

surrounded by slightly less densely populated tracts and, thus, people and 

stores are more spread out. The characteristics that predict food desert status 

in less dense urban tracts are notably different than those that predict food 

desert status in dense urban areas. This may be partly due to the fact that less 

dense urban areas include a wide range of tracts, from suburbs to small cities 

to small towns, all of which may have very different characteristics. This 

variation in the socioeconomics of the tracts in the less dense urban areas 

may make difficult the detection of any meaningful links between economic 

and demographic characteristics and the existence of food deserts. Very 

dense urban tracts, however, are much more likely to resemble one another in 

terms of composition. In these areas, we find a strong link between poverty 

and the presence of food deserts. 

Some common factors can be traced between the presence of rural food 

deserts and urban food deserts. Tracts that have larger representations from 

minority groups are more likely to be food deserts in rural, less dense urban, 

and dense urban areas. This is true even after controlling for income and 

other tract-level characteristics. High poverty rates are usually positive 

predictors of a food desert tract, and regions in the South, Midwest, and West 

tend to be more likely to be food deserts than tracts in the Northeast. Vacant

housing is also often important in increasing the probability of the existence 

of a food desert, although the predicted odds ratios for dense urban tracts are 

not statistically significant.
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Conclusion

Our study confirms poverty’s primary role in the evolution of food deserts.

Our statistical analyses build on previous research by examining the characteristics of food deserts, defined on a national level. The analyses also 

provide additional insight by investigating changes in these characteristics 

over time. Results from our descriptive analysis contrasting food desert 

tracts and other tracts support much of the previous research, concluding 

that minority status and poverty are more prevalent in areas with limited 

access to healthy and affordable food. Observation of three survey periods

also illuminates the persistence of low-access and low-income conditions in 

food deserts. As community development and infrastructure investment are 

neglected, residents remain in impoverished conditions.

While we find a number of characteristics that are associated with low access 

and low income, econometric analysis isolates only a few of these as strong, 

consistent predictors of food deserts. Different factors are more important in rural 

areas than in urban areas, and in very dense versus less dense urban areas. For 

both the descriptive and multivariate analysis, concentrated poverty is a significant predictor of low access. This is true even as our set of tracts is limited to 

those already designated as low income, implying that even among poor tracts, 

those areas with greater levels of poverty are more likely to be food deserts. The 

predictive strength of poverty rate is most strongly observed among the set of 

densely populated urban tracts, where other demographic factors are likely to 

be more uniform across tracts. As opposed to the poverty rate itself, changes in 

tract poverty rate are not statistically significant in most cases. When viewed in 

conjunction with the importance of the poverty rate at a single point in time, this 

insignificance provides further argument for the persistent effects of poverty: a 

tract with high poverty rates at a given point is much more likely to be a food 

desert despite any changes in the poverty rate over time. 

Another important factor affecting food desert status in rural and less dense 

urban areas is the percent of minority population in a tract. This finding 

partially corroborates the conclusions from the econometric analysis in 

Access to Affordable and Nutritious Food: Measuring and Understanding 

Food Deserts and Their Consequences—Report to Congress (USDA, 2009) 

and indicates that racial/ethnic aspects influence retail development across a 

wide range of neighborhoods. Food desert tracts have a greater concentration 

of all minorities, including Hispanics. In urban food deserts, this difference 

was nearly 70 percent in 1990, approximately 60 percent in 2000, and 53 

percent in 2005-09. The proportion of minorities in rural food desert tracts 

is around 65 percent greater than in non-food desert tracts in 2005-09 and in 

2000, down from an 80-percent difference in 1990.

Our findings also imply that low-income tracts in the Northeast are less

vulnerable to access problems than low-income tracts in other regions of 

the country. As described in the introduction of this report, the census-tract 

food desert definition is based upon distance from the nearest grocery store. 

This may translate into relatively fewer food deserts in the Northeast, where

development is more densely distributed. 

Identifying further characteristics that influence the development and 

persistence of food deserts across rural, urban, and very dense urban areas is 
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difficult. In less densely populated urban areas and in rural areas, economic 

and demographic heterogeneity from tract to tract obfuscates the most 

important causal factors of low access. For example, high vacant-housing 

rates affect the probability of a food desert differently in rural areas than 

in less dense urban areas, and they have a statistically insignificant effect 

in very dense urban areas. This suggests that abandoned property and 

movement of population is more detrimental to already dispersed rural 

populations. The insignificant impact of vacant-housing rates in very dense 

urban areas is likely a result of a still highly concentrated population. 

Concentrated poverty and minority populations emerge from our study as the 

critical factors in determining low access. As impoverished and minority 

populations are already more likely to have poor access to health care and fitness 

facilities, limited access to healthy food may compound the effects of this deprivation. These environments, plagued with low income, low education levels, 

and high unemployment, may well be unattractive markets for supermarkets and 

grocery stores. Difficulty in training and retaining staff from such a population, 

as well as low demand resulting from poverty, pose significant disincentives 

for retailers to operate in these areas (Food Marketing Institute, 1998). If profit 

potential to attract these retailers does not exist, effective policy may focus on 

lowering other barriers to access, such as providing better public transportation 

to enable access to retailers in surrounding areas or addressing education and 

employment shortcomings directly. It may also be feasible to encourage smaller 

stores in food deserts to carry healthier products. Policies that emphasize community development and infrastructure investment in areas of concentrated poverty 

may also be effective options to remove barriers to food retail development 

and to create healthier living environments in these areas. Tailoring solutions to 

specific communities may be more efficient than a one-size-fits-all approach, 

as different infrastructure failures are at fault in urban areas than rural areas, 

and even in very densely populated areas than in other areas. Recognizing these 

differences will be crucial to the success of any policy option.

Potential for future research exists in identifying connections between low access 

and poor health outcomes. Such a relationship is difficult to identify in a nationallevel study, as very little in the way of specific health data exists at such a level. 

Disentangling consumers’ preferences regarding location and diet from market 

forces can also help further shape effective policy in addressing access problems. 

This study considers supermarkets, supercenters, and large grocery stores in 

measuring access to healthful and affordable foods. We focus on these store 

types because they tend to carry a wide variety of food products at lower prices 

than many other food retailers. In addition, national data on these stores are 

readily available, while such data are less detailed for smaller outlets. But there 

are other outlets where fresh, healthy foods may be obtained, such as farmers’ 

markets, mobile markets, or corner stores with expanded healthy options. 

Further research accounting for other means of accessing nutritious food could 

provide a different perspective on food access. 

Food deserts have currently only been defined for one time period. ERS is planning 

to update the estimates of food desert census tracts using more recent population 

and store location data. Two estimates of food desert status will allow us to explore 

in more detail the determinants of food deserts and how food desert status is associated with changes in these characteristics over the two time periods. 
29

Characteristics and Influential Factors of Food Deserts / ERR-140

Economic Research Service/USDA

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