An Economic Analysis of Fresh Fruit and Vegetable Consumption: Implications for Overweight and Obesity among Higher- and Lower-Income Consumers

and contrast the purchasing behaviors of the two income groups for these commodities. Many
studies have hypothesized that cost is a major determinant of fruit and vegetable consumption
and therefore another objective of this research is to determine if prices are more constraining on
the purchasing behavior of lower-income consumers. That is, do higher- and lower-income
consumers have different price elasticities of demand? To the extent that constraints are
identified and they lead to poor diets and subsequent costs that are borne by all of society, then
these findings could have important policy implications.

Data and Demographic Information

Data used in this study were obtained from a national supermarket chain in the
Columbus, Ohio Metropolitan Area. These data were collected at the store level and obviously
there are shoppers with varying levels of income at every store at any time period. To try and
control for income variation, two sets of stores were selected: (1) three stores from inner-city
locations where the majority of surrounding residents have low to moderate incomes; and (2)
three stores from suburban locations where the majority of surrounding residents have moderate
to high incomes. And since studies suggest that people shop within close proximity of their
residence, it seems reasonable to conclude that these stores represent two distinct income groups.

Some specific characteristics of the six stores that segment them into two income groups
are: (1) twelve percent of the households within a three-mile radius of the three inner-city stores
have incomes below $10,000, as compared to 4.2 percent of the households within a three-mile
radius of the suburban stores; and (2) just 12 percent of the households within a three-mile radius
of the three inner-city stores have incomes above $75,000 as compared to 34.1 percent of the
households within a three-mile radius of the suburban stores. Further, given the usual positive
correlation between income and education, educational levels also support the identification of

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