This study examines the relative price of a standard market basket of food items and a market basket of healthier alternatives. Because people in low-income neighborhoods may have fewer grocery stores and transportation alternatives, the effects of store size and competition on the price of a market basket is estimated.Demand and Price Analysis, Food Consumption/Nutrition/Food Safety,

Cassady, Diana

Jetter, Karen M.

English

Research Papers in Economics

Explaining disparities in the cost of healthier food.
By
Karen M. Jetter, Agricultural Issues Center, University of California.
Diana L. Cassady, Center for Advanced Studies in Nutrition and Social
Marketing and Dept. of Epidemiology and Preventive Medicine, University of
California, Davis.
Selected Paper prepared for presentation at the American Agricultural Economics
Association Annual Meeting, Denver, Colorado, July 1-4, 2004
Abstract
This study examines the relative price of a standard market basket of food items
and a market basket of healthier alternatives.   Because people in low-income
neighborhoods may have fewer grocery stores and transportation alternatives,
the effects of store size and competition on the price of a market basket is
estimated.
Copyright 2004 by [authors].  All rights reserved.  Readers may make verbatim copies of
this document for non-commercial purposes by any means, provided that this copyright
notice appears on all such copies.Introduction
A higher incidence of chronic disease has been associated with diets that
are low in fiber, low in the consumption of fruits and vegetables, and high in fat,
especially saturated fat.   People in low-income neighborhoods tend to have
poorer diets, and a higher incidence of diabetes, heart disease and cancer.  There
is a growing consensus that the environment can support or discourage healthy
eating.  Neighborhood differences in the price and quality of food may partially
explain disparities in dietary behavior and chronic disease.   No studies have
documented the availability and price disparities between standard and healthier
food baskets in neighborhoods with different median incomes. The purpose of
this study is to determine:  1)  the relative price of a standard market basket of
food items and a market basket of healthier alternatives (i.e. white vs 100% whole
wheat bread, whole vs non-fat milk, etc.);   2) whether prices paid   for the
healthier market basket by people in low-income  neighborhoods is greater than
the amount paid by people in higher income neighborhoods; and 3) examine
how  neighborhood  characteristics  related  to  transportation  alternatives
(percentage car ownership, access to public transportation), store size and degree
of competition influence the prices paid for standard and healthier market
baskets in neighborhoods with different median incomes.
Disparities in obesity, disease, and diet
Low socioeconomic status (SES) is strongly associated with higher rates of
obesity and high rates of the leading causes of illness and death.  For instance,
results from the National Health Interview Survey show that adults with less
than a high school diploma are more likely to be overweight compared to thosewith a graduate degree (60.4% vs. 42.4%)  (Schoenbom et al, 2002).    Low SES
adults are more likely to have diabetes, cancer, heart disease, and hypertension
compared to those in with higher SES  (Mokdad et al., 2001; Paeratakul et al.,
2002).
  Diet may play an important mediating role in explaining socioeconomic
disparities in health status.   Analyses of data from the Continuing Survey of
Food Intakes of Individuals (CSFII) indicate that wealthier respondents eat more
fruits and vegetables, and eat a greater variety of foods, than their lower-income
counterparts (Haan et al, 2001).  Income appears to have a lesser effect on energy
intake compared to diet quality.
Higher  rates  of  obesity  also  are  associated  with  neighborhood-level
measures of SES.  For instance, researchers in Scotland documented significantly
higher body  mass  index among  residents of  the poorest neighborhoods in
Glasgow (Ellaway et al., 1997).  A similar graded relationship was found between
in poorer neighborhoods and higher body mass index a study in Holland (van
Lenthe, 2002).   This relationship could be due to a higher concentration of low-
income  residents  or  it  could  be  due  to  the  characteristics  of  low-income
neighborhoods.
Disparities in access to supermarkets
In a study on the distribution of supermarkets in 21 large U.S. cities,
Cotterill and Franklin (1995) discovered that, except for one city (Cleveland), a
supermarket gap existed in low-income neighborhoods.    Neighborhoods that
lacked supermarkets were also correlated with a large number of persons onpublic assistance and a large number of households without a car.   In Los
Angeles,  Sloane  et  al.  (2002)  found  that  convenience  stores  were  highly
concentrated in low income compared to higher income census tracts. Moreland,
in her study including four counties in the eastern U.S., found an inverse
relationship between neighborhood income and supermarkets.  She also found a
significant inverse relationship between neighborhood racial segregation (greater
proportion of African American residents) and fewer supermarkets (Morland et
al., 2002).
The food store industry has also undergone significant change in the type
of food store available to shoppers.  Since the 1980s there has been a substantial
increase in the number of warehouse and supercenter stores have offer a variety
of services at relatively low-prices (Connor).  Studies have also shown that the
rise in the number of low-priced warehouse and supercenter food stores has
largely bypassed low-income neighborhoods (Troutt 1993; Crockett et al. 1992;
Kaufman et al, 1999).  These stores are more likely to be found in middle income
urban neighborhoods or in suburbs.
A grocery gap in low-income neighborhoods could result in a poor diet, as
some  research  suggests  that  access  to  healthier  foods  is  associated  with
consumption of healthy foods.  For instance, one study found that people who
live  near  supermarkets  that  sell  low-fat  milk  and  whole  wheat  bread  are
significantly more likely to purchase those healthy choices (Cheadle et al., 1993).
Conversely, people who live father from supermarkets are likely to consume
fewer  servings  of  fruits  and  vegetables  (Morland  et  al.,  2002).  In  a  study
examining  the welfare effects to food stamp recipients of increasing access to
supermarkets that accept food stamps, the change in consumer welfare waspositive and significant for those groups which lacked transportation (Feather
2003).
Important store attributes to consumers picking which store to shop in are
cleanliness, fresh fruits and vegetables, fresh meats, low prices and friendly
service (Food Marketing Institute 2004). While most consumers are satisfied with
their primary food store, many low-income consumers are dissatisfied with the
food store choices available to them.  In research completed by the authors of this
proposal, of 25 stores surveyed in the Sacramento and Los Angeles areas, three
stores are places the surveyors (Do you mean, the survey responders?) would not
frequent due to a lack of cleanliness and poor quality fruits and vegetables.  All
of these stores are located in low-income neighborhoods.
Does price influence the selection of healthier foods?
Public health researchers have just begun to investigate the role of food
prices on the selection of foods.  One study suggests that price is a significantly
stronger influence on healthy food choice compared to labeling healthy foods
(French, 2003).  In an experiment manipulating prices and labels on foods sold in
vending machines, the authors found that price reductions of 10%, 25% and 50%
on  lower  fat  snacks  resulted  in  an  increase  in  sales  of  9%,  39%  and  93%,
respectively, compared with usual price conditions.
A  recent  study  suggests  that  the  low  price  of  energy  dense  foods
encourages low-income consumers to make unhealthy choices (Drewnowski,
2004).  The author used linear programming models to generate a low-cost diet
to meet caloric, but not health, requirements.  The result was a diet low in fruitand vegetables, whole grains, and lean meats, and similar to a diet eaten by
lower income consumers.
In addition to these important issues, the relationship between retail food
prices, and firm conduct and market structure are of special interest.   In the
United States in 2000, supermarket sales were $337 billion compared with $73
billion for small grocery stores, and $49 billion for convenience stores.  Thus, of
total grocery store earnings of 458 billion, approximately 74, 10, and 16 percent,
respectively, went to these three types of stores. Compare this with the situation
twenty years earlier when supermarkets earned $157 billion and small grocery
stores and convenience stores earned $30 billion and $19 billion, respectively,
and it is interesting to note that while total food retail dollars earnings have more
than doubled the relationship between small and large store shares of that total
has not changed much.   What has changed over this time period has been a
decline  in  the  number  of  firms  collecting  those  dollars.   Acquisitions  and
consolidations are commonplace in the retail food industry.  Between 1997 and
2000, some 4,100 supermarkets were acquired by another firm.  In 1992, the eight
largest supermarket chains accounted for roughly 25 percent of the food retail
market; today, the share of the top eight is more than 40 percent with the top
four firms accounting for nearly 30 percent of the total share alone (Kaufman,
2002).
As the studies alluded to above suggest, the relationship between food
prices and nutrition is an important one.  Therefore, because of ever increasing
consolidation, it is especially important to consider the relationship between the
structure (including size, number, and location) of firms in a given market and
the  competitiveness  of  food  prices.   One  issue  of  particular  importance  iswhether or not, because of geographic concentration or firm location, poor
people pay more for food.
What an empirical analysis will tell us.
The empirical analysis that we propose is adapted from methods used by
Alvarez et al. (2000) on imperfect competition in a spatial market setting and an
analysis  performed  by  Cotterill  (1986)  on  supermarket  concentration  and
imperfect competition.  Specifically, we seek to determine how the price level of
particular food retail establishments are related to local and regional measures of
market structure such as firm locations, ownership structure, cost and quality
factors, and measures of concentration, while taking into account consumer
attributes such as population density and demographics including local per-
capita income, race, and ethnicity.
The  analysis  to  estimate  whether  food  stores  located  in  low-income
neighborhoods are imperfectly competitive will include variables to account for
concentration, distance of food stores from each other, number of competitors
within a specified radius of each food store, store size, access to stores as
measured by percentage car ownership and the number of public transportation
lines  from  which  a  store  may  be  reasonably  accessed,  and  neighborhood
demographic  variables.   Concentration  will  be  measured  by  creating  a
Herfindahl-type index based on square footage, as we do not have access to sales
data.  Square footage is a reasonable measure to use in place of the sales data as
sales volume would be correlated with floor space.  Distance of food stores from
each other and the number of competitors within a specified radius of each food
store will be obtained using geographic information system (GIS) mapping.  TheInformation Center for the Environment (ICE) will complete the GIS mapping.
Data on square footage for supermarkets, and large and small grocery stores are
available from county tax assessors.   The data on car ownership and other
neighborhood demographic variables can be gathered from the Census Bureau’s
census tract statistics.  The data on public transportation lines are easily gathered
from public transportation maps.
RESEARCH METHODS
Most people tend to shop for food within five miles of their residences.  To
evaluate whether low-income neighborhoods have imperfectly competitive food
stores, we will compare the price of the Thrifty Food plan and measures of
imperfect competition between a core low-income area, and an area of five-mile
radius around the core areas.
Market Basket survey: The items included in the survey are
taken from the Thrifty Food Plan.  (USDA 1999; Andrews et al. 2001).   The items
on the list make up the basic market basket food items for which we obtained
prices, availability and nutrition information where applicable.  For example, we
collected data on the percentage fat for each type of ground beef sold in each
store.   The standard market basket of food items contains the less healthy
alternative and the healthy market basket, the healthier alternative.  For example,
the standard market basket has white bread, the healthier alternative 100% whole
wheat bread.  The standard market basket has whole milk, and the healthier non-
fat milk.  The lowest price per unit was recorded for each food item.  Thirteen
stores in Sacramento, CA and 12 stores in Los Angeles, CA were surveyed.  Tocontrol for quality, the accuracy of the surveys were verified by having a second
surveyor do an in-store check of the recorded prices.
Identification and verification of food stores: A geocoded dataset was
obtained from a marketing firm that includee North American Industrial
Classification (NAIC) codes to identify supermarkets, grocery stores, and
specialty stores such as butcher shops, vegetable markets, and ethnic markets.
The dataset was be augmented by an internet search of current listings for each
city. After eliminating duplicates, we also verified the stores on the list using a
phone survey.  Finally, for stores that were non-respondents to the phone survey
a drive-by survey was completed.   The stores were coded as a supermarket,
large grocery store, small grocery store, warehouse, convenience store or
specialty market based on the availability and variety of individual food items.
Conclusions
Appropriate policies to address the unique needs of the low-income
population regarding access to an affordable and healthier diet can only come
about through a thorough understanding of the food environment in low-income
neighborhoods.   If the dispersion of food stores does results in areas of imperfect
competition, then policies developed to expand access would be appropriate.
For example, policies to encourage the use of supermarket shuttles to transport
people from supermarkets to low-income neighborhoods, and expand the areas
of competition may be a viable policy option.REFERENCES
Alvarez, Antonio M., Eduardo G. Fidalgo, Richard J. Sexton and Mingxia Zhang.
“Oligopsony power with uniform spatial pricing: theory and application
to milk processing in Spain”.   European Review of Agricultural Economics.
2000. 27:347-364.
Andrews, Margaret, Linda Scott Kantor, Mark Lino, and David Ripplinger.
“Using  USDA’s  Thrifty  Food  Plan  to  Assess  Food  Availability  and
Affordability.”   Food Review.  United States Department of Agriculture.
Washington, DC.  2001.  24:45-53.
Cheadle A, Psaty B, Curry S, Wagner E, Diehr P, Koepsell T, Kristal, A.   Can
Measures  of  the  Grocery  Store  Environment  be  Used  to  Track
Community-level Dietary Changes? Preventive Medicine. 1993.  22:361-
372.
Connor, J.M. “Evolving Research on Price Competiion in the Grocery Retailing
Industry: An Appraisal.” Agricultural and Resource Economics Review. 1999.
28:119-127.
Cotterill, R.W. (1986): “Market Power in the Retail Food Industry: Evidence from
Vermont.” Review of Economics and Statistics 68: 379-386.
Cotterill, R.W. and Andrew W. Franklin.  The Urban Grocery Store Gap.  Food
Marketing Policy Issue Paper No. 8.   Food Marketing Policy Center,
Department  of  Agricultural  and  Resource  Economics,  University  of
Connecticut.  April 1995.  79 pages.Crockett, Elizabeth D., Katherine L. Clancy, and Jean Bowering.  “Comparing the
Cost of a Thrifty Food Plan Market Basket in Three Areas of New York
State.”  Society for Nutrition Education.  1992.  24:71S-77S
Drewnowski A, Specter SE.  “Poverty and obesity:  The role of energy density
and energy costs”. Am J Clin Nutr.  2002;79:6-16.
Ellaway A, Anderson A, MacIntyre S.  Does area of residence affect body size
and shape?  International Journal of Obesity.  1997;21:304-308.
Feather, Peter M.  “Valuing Food Store Access: Policy Implications for the Food
Stamp Program”.  American Journal of Agricultural Economics.  2003.  85:162-
172.
Flegal KM, Carroll MD, Ogden CL, Johnson CI. Prevalence and trends in obesity
among US adults 1999–2000. JAMA 2002;288:1723–7.
Food Marketing Institute. Trends in the United States: Consumer Attitudes & the
Supermarket 2004.  2004.
http://www.fmi.org/media/mediatext.cfm?id=631
French SA.  Pricing effects on food choices. J Nutr.  (2003). 133(3):841S-843S.
Hann CS, Rock CL, King I, Drewnowski A. Validation of the Healthy Eating
Index using plasma biomarkers in a clinical sample of adult females. Am J
Clin Nutr. 2001;74:479–86.
Hayes, L.R. (1999). “Are Prices Higher for the Poor in New York City?” Princeton
Industrial Relations Section Working Paper 423 (September).
Kaufman, P.R. (2002). “Food Retailing.” U.S. Food Marketing System, 2002. USDA,
Agricultural Economic Report No. 811: 21-33Kaufman, P.R., J.M. MacDonald, S.M. Lutz, and D.M. Smallwood (1999). “Do the
Poor Pay More for Food?” Item Selection and Price Differences Affect Low-
Income  Household  Food  Costs.  Food  and  Rural  Economics  Division,
Economics Research Service, USDA, Agricultural Economic Report No.
759.
Mokdad AH, Ford ES, Bowman BA, et al. Prevalence of obesity, diabetes, and
obesity-related health risk factors, 2001. JAMA.  2003;289:76–9.
Morland K, Wing S,  Diez Roux A,  Poole C.   Neighborhood characteristics
associated with the location of food stores and food service places.  Am J
Prev Med. 2002;22:23-9.
Morland K, Wing S, Diez Roux A.  The contextual effect of the local food environment
on residents' diets: the atherosclerosis risk in communities study. Am J Public
Health. 2002 Nov;92(11):1761-7.
Paeratakul S,  Lovejoy  JC,  Ryan  DH, Bray  GA. The  relation of  gender,  race and
socioeconomic status to obesity and obesity comorbidities in a sample of U. S.
adults Int J Obes Relat Metab Disord 2002;26:1205–10.
Schoenborn CA, Adams PF, Barnes PM. Body weight status of adults: United States,
1997–98. Adv Data 2002;330:1–15.
Sloane DC, Diamant AL, Lewis LB, Yancey AK, Flynn G, Nascimento LM,
McCarthy  WJ, Guinyard JJ, Cousineau MR; REACH Coalition of the
African American Building a Legacy of Health Project.   Improving the
nutritional resource environment for healthy living through community-
based  participatory  research.   Journal  of  General  Internal  Medicine.
2003;18:568-575. United States Department of Agriculture., Center forNutrition Policy and Promotion. The Thrifty Food Plan, 1999. CNPP-7A.
Washington, DC August 2000. 14 pages.
van Lenthe FJ, Mackenbach JP. Neighbourhood deprivation and overweight: the
GLOBE study. Int J Obes Relat Metab Disord.  2002;26:234-40.

Are Prices Higher for the Poor in

Body weight status of adults: United States,

Can Measures of the Grocery Store Environment be Used to Track Community-level Dietary Changes? Preventive Medicine.

Coalition of the African American Building a Legacy of Health Project. Improving the nutritional resource environment for healthy living through communitybased participatory research.

Does area of residence affect body size and shape?

Evolving Research on Price Competiion in the Grocery Retailing Industry: An Appraisal.” Agricultural and Resource Economics Review.

Food Marketing Institute. Trends in the United States: Consumer Attitudes & the Supermarket

Food Retailing.” U.S. Food Marketing System,

Market Power in the Retail Food Industry: Evidence from

Neighborhood characteristics associated with the location of food stores and food service places.

Neighbourhood deprivation and overweight: the GLOBE study.

Obes Relat Metab Disord

Oligopsony power with uniform spatial pricing: theory and application to milk processing in Spain”. European Review of Agricultural Economics.

Prevalence and trends in obesity among US adults 1999–2000.

Prevalence of obesity, diabetes, and obesity-related health risk factors,

The contextual effect of the local food environment on residents' diets: the atherosclerosis risk in communities study. Am J Public Health.

The Urban Grocery Store Gap. Food Marketing Policy Issue Paper No. 8. Food Marketing Policy Center,

Validation of the Healthy Eating Index using plasma biomarkers in a clinical sample of adult females.

Valuing Food Store Access: Policy Implications for the Food Stamp Program”.

EXPLAINING DISPARITIES IN THE COST OF HEALTHIER FOOD

EXPLAINING DISPARITIES IN THE COST OF HEALTHIER FOOD

Abstract

Similar works

Full text

Available Versions

Research Papers in Economics