2010 CURRENT POPULATION SURVEY FOOD SECURITY SUPPLEMENT:
CHARACTERISTICS OF CALIFORNIANS WHO ARE FOOD INSECURE
A Thesis
Presented to the faculty of the Department of Sociology
California State University, Sacramento
Submitted in partial satisfaction of
the requirements of the degree of
MASTER OF ARTS
in
Sociology
by
Charlene Rae Manning
FALL
2012
2010 CURRENT POPULATION SURVEY FOOD SECURITY SUPPLEMENT:
CHARACTERISTICS OF CALIFORNIANS WHO ARE FOOD INSECURE
A Thesis
by
Charlene Rae Manning
Approved by:
_____________________________________, Committee Chair
Ellen Berg, Ph.D.
_____________________________________, Second Reader
Jacqueline Carrigan, Ph.D.
____________________
Date
ii
Student: Charlene Rae Manning
I certify that this student has met the requirements for format contained in the University
format manual, and that this thesis is suitable for shelving in the Library and credit is to
be awarded for the thesis.
__________________________, Graduate Coordinator
Amy Qiaoming Liu, Ph.D.
Department of Sociology
iii
___________________
Date
Abstract
of
2010 CURRENT POPULATION SURVEY FOOD SECURITY SUPPLEMENT:
CHARACTERISTICS OF CALIFORNIANS WHO ARE FOOD INSECURE
by
Charlene Rae Manning
Hunger in the U.S. has historically been a problem with many root causes and
complicated solutions. There have been many studies on hunger in general, but few speak
to the unique characteristics of Californians who are hungry. The December 2010 Food
Security Survey is one part of the Current Population Survey (CPS) conducted by the
Census Bureau. The 2010 Food Security Survey measures US food security on a stateby-state basis. Logistic regression analysis of the 2010 CPS data for California reveals
specific demographic variables that are predictive of food insecurity among households.
The demographics of the heads of household who answered the questions of the survey
which are predicted to be food insecure are: age, education, black identification,
multiracial identification, Mexican Hispanic origin, non-Mexican Hispanic origin, those
looking for work, unemployed disabled people, those with a spouse
absent/divorced/separated, and never married. The demographic of the households that
participated in the survey that predicted food insecurity was income below 185% of the
poverty level. A model was ran to specify which demographic variables describe those
who use Supplemental Nutrition Assistance Program benefits and Women Infant and
iv
Children program benefits. Another model was ran to describe the demographic variables
of those who use free and reduced-cost lunch benefits at school, day-care, or Head-Start
program. Age, education, those below 185% of the poverty line, being Hispanic, being
unemployed, and those with a spouse absent/divorced/separated were significant factors
found in all regression analyses that predicted one’s odds of being food secure and one’s
odds of receiving food program benefits.
_______________________, Committee Chair
Ellen Berg, Ph.D.
_______________________
Date
v
ACKNOWLEDGEMENTS
Many thanks to my family and friends who helped, supported, and encouraged me
through this process. Knowing all of you were sure of my abilities whenever my
confidence wavered helped me to continue. Thanks to my parents for their patience and
trust in me. Thanks to Michelle, Michael, and Hilde-Marie for distracting me from my
work. Because of them I was able to visit beautiful places and have wonderful things to
reflect on during the long hours in front of a computer. I would also like to thank Ellen
Berg, Ph.D. and Jacqueline Carrigan, Ph.D for their guidance. I could not have done it
without your patience and understanding.
vi
TABLE OF CONTENTS
Page
Acknowledgements………………………………………………………………….vi
List of Tables………………………………………………………………………..ix
Chapter
1.
INTRODUCTION………………………………………………………………1
Research Question………………………………………………………….9
Research Significance……………………………………………………....10
2.
LITERATURE REVIEW…………………………………………………….....12
Nutrition…………………………………………………………………....12
Rural vs. Urban and Race/Ethnicity ………………………….…………....14
Poverty, Food Spending and Food Assistance……………………………..17
Research Gaps……………………………………………………………...23
3.
METHODS……………………………………………………………………..25
Research Design and Approach…………………………………………….25
Survey Population…………………………………………………………..25
Background………………………………………………………………....26
Dependent Variables………………………………………………………..27
Independent Variables……………………………………………………...29
Data Analysis Procedures…………………………………………………..31
4.
RESULTS………………………………………………………………………32
Model One Analysis: Being Food Secure….………...……………………..32
Model Two Analysis: Using Supplemental Food Programs……………….34
Model Three Analysis: Using Free Lunch Programs …………...………...36
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5. DISCUSSION…………………………………………………………………….39
Limitations……………………………………………………………...…...43
Areas of Further Research…………………………………………………..44
References………………………………………………………………………...….54
viii
LIST OF TABLES
Tables
Page
1.
Descriptive Statistics of Food Supplement Survey Participants in California…..45
2.
Logistic Regression Model 1-Describing those who are Food Secure………….48
3.
Logistic Regression Model 2- Describing those who Receive WIC and SNAP
Benefits……………………………………………………………………….…50
4.
Logistic Regression Model 3- Describing those who Receive Free Lunch at
School, Day Care, or Head Start Program……………………………………...52
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1
CHAPTER 1- INTRODUCTION
Hunger is an evolving global crisis that is shaped by the social and political
landscape. In the U.S “14.7% of households face food insecurity, (Nord et al. 2010) while
one billion people in the world are hungry everyday (Ore 2011: 689). Children are among
the most vulnerable to hunger and those under the age of five “comprise 18,000 of the
25,000 people per day who die of hunger totaling more than 6.5 million per year”
(Scanlan 2009: 294). These statistics show just a hint of the scale of the problem that
hunger represents, yet if we seek to eradicate hunger then we must dig deep to understand
how hunger works in our world system.
Global world food insecurity is tied to a multitude of other problems including
(but not necessarily limited to): poverty, inequality, economic downturns, market
fluctuations and trade, underdevelopment, power and politics and war and militarism,
population trends, and climate change. For us to focus on hunger alone would be to see
the issue in a smaller scope than the breadth of social factors it encompasses. On the
other hand, hunger can be a starting point to see how social inequality can be measured
from such basic human needs as food. These basic needs are “dependent on processes
that know no borders as food is commodified in a global economy that ironically
increases the overall supply with advances in agriculture, marketing and storage, and
transportation while doing little to guarantee that the world’s citizens are able to acquire
it” (Scanlan 2009: 297). Even with the technological advances in growing and
2
distributing food, not having access is still one of the main reasons for hunger in the
world. Scalan states, “the supermarket revolution in which the global citizenry relies on
large-scale operations to obtain their food can be devastating when global food prices
shut out large numbers of people from access to food” (2009:298). Economic and
political factors threaten food security as food pricing and obtainability influence whether
or not people eat.
The severity of hunger can be decreased both at home and through political and
legislative processes. The ease of getting more food on the table at home depends on a
decrease in military spending and an emphasis put on social gains such as education,
gender equality, and more basic resources provided to people (Jenkins et. al 2007:824). If
people have more political power they are less likely to be hungry, especially in less
developed countries. Priority is often put on protecting less developed countries’ interests
through war rather than investing in the social building blocks that increase food security.
Even when other countries step in to help with hunger, it has restrictions. Internationally,
“food aid is more influenced by the geopolitical and economic interests of the developed
countries than by food scarcity in less developed countries” (Jenkins et. al 2007:826). In
the U.S. we can get emergency food from charity organizations and sign up for
government programs to address hunger problems in our own home. With hunger aid in
place in the U.S. there is still a hunger problem, even with education, gender equality on
the rise, and democratic freedom. In the U.S. we also put a cap on domestic spending
since the military budget occupies a large share. It is the limited availability of resources
3
from organizations and government programs that keeps hunger a large-scale problem
both in the U.S. and internationally.
During the Great Depression many government programs were created to serve as
social safety nets. Food programs and agricultural relief programs were implemented to
eliminate hunger and bring about recovery to the nation. In 1932, the Roosevelt
Administration started to involve government in programs such as the “Federal Surplus
Relief Corporation, which is a temporary emergency measure to transfer agricultural
surpluses to the unemployed until the New Deal could bring recovery” (Whit 1995:157).
From 1939-41, the Department of Agriculture took over food assistance programs and
created a “food stamp policy” which served 4 million people (Whit 1995:158). In the
1960’s more specific food programs were created to target the hungry with the “WIC
program to provide women and mothers with small children with adequate healthcare and
food, as well as school lunch and senior nutrition programs” (Whit 1995:158). While
these programs are still in place today and even though the total quantity of food is
sufficient to feed the entire US population, since the late 1980’s people are still going
hungry.
With an increase in government aid helping hungry families in the 1940-60’s,
even aid to target women and young children, the actual relief of hunger in the past 30
years has not been very effective. There have been “reductions in child nutrition
programs (and)…elimination by the Reagan/Bush administrations of public and
subsidized housing programs” (Whit 1995:158). Rather than increasing funding for
4
programs that would provide access to food, money was redirected to defense spending
even as hunger rates were expanding in the 1980’s. Cutting taxes and decreasing
government involvement in social and domestic issues was seen as a way to boost the
economy. For the people in poverty and those who were hungry, the predicted benefits
from the ‘trickle down’ school of economic thought never materialized. The once
beneficial and ideologically progressive government programs, such as the Supplemental
Nutrition Assistance Program (SNAP) and WIC, were put on the back burner, and they
remain so today. Government policies have created an environment that nurtures
increased poverty, homelessness and unemployment while at the same time securing an
inadequate minimum wage. The decrease in minimum wage during the 1980’s has caused
“about 30 percent of the ensuing increase in wage inequality” (Partridge 1999:393). From
looking at the history of food programs, the correct political and social climate must
occur for these programs to effectively feed the hungry as they were designed.
There are several plausible theories covering the reasons why people remain
hungry when we have the technology to grow enough food to feed everyone. One of the
general theories regarding food inadequacy relates to the profit-driven food systems
wherein the system for feeding people is based on profits, and to give away food for less
money (or for free) does not generate the money and profits food manufacturers desire
(Whit 1995). Another theory concerns the tendency to provide food aid using food supply
surpluses but only with regards to satisfying specific political agendas favoring allies
foreign or domestic. Although it is nice that the U.S. may donate food to countries whose
5
alliance may benefit them politically, those donations could be used for our own domestic
needs. From these theories it is as if food is treated as a negotiable commodity and is
often used as a basis for profit and political strategies.
The conservative analysis of hunger derives from notions of world
overpopulation and that peasant values are the cause of people’s hunger. Some believe
that not every person should have food for every meal and that since there are a lot of
people on earth we don’t have enough food for everyone (Whit 1995). The consequence
of people dying from starvation would not be negative according to this analysis, since
the world is already ‘overpopulated’ and would thus benefit from deaths due to
starvation. The attitudes of peasants who work only to subsist and have an inability to
survive independently are a part of conservative rhetoric as explanations for hunger and
poverty. According to the theory a ‘culture of poverty’ is passed on from one generation
to the next because peasant values such as the “tendency to have large families, rural
families needing extra hands on the farm, and the need for children to help the elderly”
(Whit 1995:201). The ideology that one would only work to support what one currently
has along with no recognizable drive to become wealthy or have extra funds is seen as a
prescription for poverty and vulnerability to hunger. As many people need to have a large
family and a large labor pool in order to survive financially, this decision is often negated
as a poor choice and that large families deserve the hunger they experience. As we know
technology can help us meet our food demands there are still some that believe that food
is for those who meet specific requirements. Conservative analysis blames the victims of
6
poverty and malnutrition for their own demise.
Liberal analysis of hunger looks at the contradiction of having technology that can
provide the quantity of food necessary to feed everyone, but political choices keep food
from reaching everyone. Food production is capable of keeping up with demands as
“population growth itself stimulates agricultural innovation and leads to production
increases that more than keep up with population growth” (Whit 1995:202). With an
increasing number of generations that innovate and expand food production technology,
there is little reason to doubt our technological abilities. Access to food is hindered as the
liberal analysis sees food being used as a weapon. As countries make policy decisions
that the U.S. does not agree with or fails to encourage ‘development,’ food aid is often
removed or used as leverage (Whit 1995). Withholding food aid can be used as a strategy
to gain agreements that are beneficial to the U.S. without much real concern for hungry
people. Liberal theories of food inadequacy see how much food we have and how easily
it can be held captive at the expense of the hungry.
These theories are constantly seen throughout hunger relief efforts, where aid and
food programs have become a mainstay. Hunger is such a complex issue that people have
become dependent on food relief and have a difficult time providing every meal for their
family. For those in power, food is seen as a source of profit, a tool to address
overpopulation, and a source of political leverage used to gain and/or threaten allies and
adversaries. Although the task of understanding the root causes of hunger across the
globe are daunting, we can seek to gain a higher resolution understanding of those that
7
are hungry on a much smaller scale in our own state, city, and neighborhoods. With luck,
insights garnered from these smaller scale high resolution studies will find productive use
in addressing global hunger issues as well.
Since 1995 the U.S. Department of Agriculture has annually collected information
on food spending, food access and adequacy, and sources of food assistance for the U.S.
population. These data are recorded as a supplement to the Current Population Survey
(CPS). Within these data are three categories that define households and individuals
specifically with regards to food; these are i) food secure, ii) low food security, and iii)
very low food security. “Households classified as having low food security reported
multiple indications of food access problems, but typically have reported few, if any,
indications of reduced food intake. Those classified as having very low food security
have reported multiple indications of reduced food intake and disrupted eating patterns
due to inadequate resources for food” (Coleman-Jensen et. al 2010: 4). The food insecure
often avoid hunger by implementing different strategies such as eating less and
participating in federal food assistance programs as well as acquiring emergency food
from community food pantries, and/or emergency kitchens.
Household food spending, the use of federal and community food assistance
programs, and demographic variables of households are measured to account for food
insecurity. In the CPS survey, participants were asked about the amount of money their
households spent on food in the week prior to the interview and how much they usually
spend on food during a week. Their answers were calculated against the Thrifty Food
8
Plan, which is a national standard for nutritious low cost diets. Participants were asked if
they received benefits from nutrition programs such as the Supplemental Food Assistance
Program (SNAP), reduced-cost breakfast and lunches at school, daycare or Head Start
program, and the Women Infant and Children (WIC) program. Participants were also
asked if they used food pantries or emergency kitchens to help feed their household or
themselves. Since these programs assist in providing food resources, it is assumed that
they reduce the risk of hunger and aid households with food benefits. This in turn is
assumed to reduce hunger more than receiving no benefits at all. At the same time, it is
also assumed that those who participate in the assistance programs are also more likely to
have difficulty satisfying their nutrition needs, wherever the program benefits do not
close the gap to satisfy all of their hunger needs.
Rates of food insecurity were substantially higher than the national average
among several specific groups according to the CPS report, Household Food Security in
the United States, 2003.These groups include households with incomes below the official
poverty line, households with children, households headed by a single woman or a single
man, black households, and Hispanic households. In the 2003 CPS food report,
households with children reported food insecurity at more than double the rate for
households without children (16.7% vs. 8.2%). This is likely due to the fact that having
children presents an increased financial stress for people as their income must be
stretched even further to meet the increased demand for food spending each week.
Among households with children, those with married couple families showed the lowest
9
rate of food insecurity. These statistics clearly show that people are more vulnerable to
food insecurity when children enter the family or they are in a single parent household.
No government program can provide the equivalent financial security that married
couples are more likely to have. This survey shows that the choices one makes or the
situations one is handed are important factors to the kind of life an individual will have
with regards to food security. Life decisions that should not necessarily be considered
negative, such as being single and having children, are putting people at greater risk for
food insecurity. It is important to note that while these demographic identifiers may
describe those who were food insecure in 2003, the 2010 data may reveal different
factors, especially when examining hunger in California alone.
Research Question
The research questions addressed in the present study are the following: Which
demographic variables and characteristics of head of household are more likely to predict
food insecurity among California households in 2010? In addition, which demographic
variables among households describe those who participate in federal food assistance
programs such as SNAP or WIC?
The variables that will be examined as predictors of food insecurity are being
above or below 185% of the poverty line, age, marital status, sex, education, race,
Hispanic origin, citizenship status, and monthly labor force participation. Using the
USDA CPS 2010 Food Security Supplement data, these variables will be tested as
predictors of low food security and very low food security for households in California.
10
To assess food assistance participation, usage of SNAP, participation in WIC benefits and
children receiving free or reduced lunch at school or food at a daycare or Head Start
program will be evaluated.
Research Significance
A survey of the literature reveals identifiable characteristics for those who are
most likely to be food insecure. Being single, having children, living in poverty, and
being a person of color are well cited descriptors for the hungry population in the U.S.
(Household Food Security in the United States, 2003). Where the literature is strong on
the national level, the literature covering state level analysis of food insecurity is lacking.
California-specific information from the Current Population Survey is a rich source for a
state-level analysis of food insecurity. California is a diverse state with many low-income
participants who benefit from food assistance. Unique features of the states’ racial and
ethnic characteristics and its variance of income level among urban/rural and
married/single populations throughout contribute to make an enhanced understanding of
California’s hungry population a valuable contribution to future research and policy
planning. Also having a large Hispanic immigrant population (with multiple generations
born in the U.S. as well as abroad) is unique to California. Further expanding the
potential scope of such analysis are the varying degrees of unemployment rates
throughout the state.
A higher resolution understanding of those who are the most at risk for hunger
will hopefully help to target and serve specific benefits capable of addressing the needs of
11
the hungry, and perhaps influence domestic food policies as well. Food supplement
programs have been unable to keep up with the needs of the hungry, as the monies
allocated to such programs are notoriously and regularly insufficient to satisfy the
demand for such programs. These government funded social safety nets are not achieving
their stated goal to be a temporary solution for people who are hungry. Such programs
were not intended to be used on a continuous basis and they were most certainly not
originally intended to receive less and less funding each year.
As discussed, hunger is a complex problem that isn’t just about having enough
money for social programs. There are powerful stakeholders who benefit from food
profits while funding for food programs are reduced. Low-income families of a variety of
demographic characteristics are struggling to make ends meet. Poverty is not a deliberate
choice, but is something we all have a stake in alleviating.
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CHAPTER 2- LITERATURE REVIEW
The literature on food security covers a range of topics. These include statistical
analyses using different models to compute food security, to nutritional effects of hunger,
and racial/ ethnic differences among the food insecure. There is also evidence on the
differences between urban and rural locations and married vs. single households having
an effect on one’s hunger status (Mammen et. al 2009). Food spending literature that
focuses on the increase in housing and rental costs in relation hunger also is well
documented (Fletcher, et. al 2009). Food assistance programs are studied to document
their effectiveness at alleviating hunger, and analyses reveal that government aid is often
underwhelming (Bitler, Gundersen, Marquis 2005). Resistance to hunger is also
occurring in a variety of ways as efforts to independently alleviate hunger and rejection
of unhealthy food options increase. Although the literature includes some studies
referencing California, there are few studies of California that specifically target the food
insecure population and its unique properties.
Nutrition
Corporations and government policy have together constructed a system that
separates us farther and farther from where our food is grown, how it is grown and how it
is processed. We are also watching as “food suppliers leave urban centers- largely
populated by marginalized communities- for more financially affluent suburban areas”
(Ore 2011: 690). This move of supermarkets to the fringes of city centers forces people to
travel farther to get high quality food, and creates a barrier for low-income people to get
13
the food they need in a low cost and efficient manner. The food choices that are most
likely to be offered in city centers are increasingly unhealthier options supplied by
convenience stores, liquor stores and dollar stores. These venues offer prepackaged food
and unsurprisingly “more than 92% of [these] retailers accept food stamps” (Ore
2011:690). These facts offer some perspective to the food insecure when the fact that a
great many of the food insecure live in cities and those that are food insecure are more
likely to live in poverty. Thusly the corporate strive for efficiency and profit are pushing
access to healthy foods even further out of reach among the most food vulnerable
populations.
Nutrition is a major concern of those who are food insecure not only in regards to
physical distance to healthy food options but also with regards to which substitutions are
being made for nutritious food. We need nutrients for the health and survival and without
them mental and cognitive functioning can be affected. In 2000, 18% of children in the
U.S. lived in food insecure households (ADA report 2002). California children with low
and very low food security had higher energy and fat intakes compared to children who
were food-secure (Rosas et. al 2009). The food children have access to when they have
limited resources for acquiring nutritious food items is not necessarily less food but rather
a replacement with unhealthy higher fat-content food. A lack of food also has serious
implications as “lacking food even at a level that does not approach severe deprivation
still has significant effects on physical and mental health….(but) the effects of household
food insufficiency may not be permanent if the food insufficiency is short term” (Siefert
14
et. al 2004:182). Alleviating hunger through a proper diet is important since neglecting
nutrition can spur possible long-term health issues.
Mental health and behavioral issues can be affected by food security, as well. A
study on the mental health of adolescent teens conducted by the authors Alaimo, Olson,
and Frongillo (2001) reported that “food-insufficient teens were more likely to (i) have
seen a psychologist (ii) have been suspended from school, and (iii) have difficulty getting
along with other children” (Ashiabi, O’Neal 2007:113). Food insecurity may be one
barrier capable of preventing teens from living healthy physical and mental lives,
however the causes of behavioral problems vary and behavioral issues can co-occur with
not having enough food to eat while not being directly caused by food insufficiency.
Parents are also negatively impacted by hunger as a 2007 study of 17 year olds has shown
“that heightened food insecurity was associated with an increase in parental emotional
distress and adolescents’ adjustment problems, and with diminished quality of parenting”
(Ashiabi, O’Neal 2007:126). These data suggest that teens and their family members can
have a difficult time coping with hunger related problems, and that these difficulties can
detrimentally impact and reduce positive interactions between family members.
Nutritional deficiencies negatively impact one’s health physically and socially, while
being even more unfavorable to those living in rural areas.
Rural vs. Urban and Race/Ethnicity
Where people live also helps predict the likelihood of becoming food-insecure.
Those with low incomes residing in rural areas experience nutritional issues more often
15
than people who live in urban areas as well as people who have higher incomes. Vitamin
A and C levels in people living in rural communities are depressed compared to
recommended standards (Molnar et. al 2001:187). “California’s northern rural counties
and San Joaquin Valley have the highest rates of food insecurity exceeding 30 % of low
income households in several northern counties ranging from 33 % to 41% in the San
Joaquin Valley” (Harrison et. al 2002:2). This goes to show that living situations have an
influence on the availability of food resources. Furthermore, this kind of insight cannot
always be resolved in broad national surveys that summarize the food insecurity
characteristics across the entire nation. State level food security research can resolve the
need for more localized information on people who are hungry.
Rural areas of the U.S. are more likely to have households that are food insecure
than in metropolitan areas. In 2005, “the rates of low food security varied from 6.4% in
North Dakota to 16.8% in New Mexico” (Mammen et. al 2009:154). There are clear
regional differences when it comes to hunger, as in the rural south where households
“particularly in Louisiana, were more likely to experience higher levels of food insecurity
than the nation as a whole, rural Blacks, and especially children in rural female-headed
households, were even more vulnerable” (Mammen et. al 2009:154). Region-specific
economic health, cultural history, and labor force participation rates have marked
influence over regional and state rates of food insecurity. California has its own ‘hunger
challenges’ having several metropolitan areas and its’ vast rural expanses as well.
A study of food insecurity in Los Angeles County gives some insight into the
16
importance of localized information with regards to specific demographics of the
population. In 2001, there were 22 million adults in California who were food insecure in
which a third of them lived in Los Angeles County (Furness, et. al 2004). What is unique
about the LA population of food insecure in 2001 is that 32.8% were African American,
28.4% Latino, 17.3% white, and 10.9% Asian (Furness, et. al 2004). The racial identities
of LA county residents of are important descriptors of the food insecure population since
a large percentage are non-white. Race and ethnic identity is vital information not only in
LA County to help describe food insecurity, but also in all food insecure populations as
diversity increases across the U.S.
Race has been shown to be a significant predictor of food insecurity. One
demonstration of this is found among people of color who are of a poor socioeconomic
status as this group is more food-insecure than white non-Hispanics with low or poor
incomes. The highest food insecurity rates are found among low income American
Indians, Alaska natives, African Americans, and Latinos (Harrison et. al 2002). Nutrition
among these groups is irregular as well. Children living in poverty are greatly affected by
the nature of their food and its quality; this is especially true among Blacks and Hispanics
compared to whites when measuring nutrient serum levels (Bhattacharya et. al 2004). In a
California study in the San Joaquin Valley, 19.5% of Hispanics were food-insecure,
living within a sample area of mostly farm worker families of low income (Rosas et. al
2009). These examples demonstrate that race descriptors are a significant predictive
characteristic for those who are more likely to be food insecure.
17
Between 2000 and 2010, the U.S. Hispanic population increased by 15.2 million,
making them the fastest growing population in the nation (Ennis et. al 2011). Poverty
disproportionately affects this group as “21.5% of all Hispanics live at or below the
poverty level, with close to 30% of Hispanic youth (under the age of 18) living in poverty
as compared to 18% of all U.S. children (Gorman 2011:153). Of further note, “Hispanics
are the only formally recognized ethnic group to be decreasing in median household
income” (Gorman 2011:153). This decreasing household income speaks to the fact that
over one-quarter of Hispanic households report high food insecurity (26.9%) compared to
the national percentage of 14.7% (Gorman 2011). These data show that Hispanics are at a
greater disadvantage economically, and that this factor (among others) leads to this group
having a statistically higher probability to be unable to provide food for themselves when
compared to non-Hispanic households (Gorman 2011). Focusing on California displays
the diversity of the food insecure as it encompasses a broad spectrum of racial and ethnic
identities. While race and ethnicity is just one aspect of food insecure populations, the
level of poverty people experience, how money is spent on food, and the use of food
assistance are also essential aspects of describing hungry people.
Poverty, Food Spending and Food Assistance
Food-insecure households spend 20% less on food than households that are foodsecure even when household composition, state, age, race, gender, and education are
controlled (Borjas 2004). Their dollar is being stretched so thin that, especially in an
economic depression, budgets for rent or mortgage or other expenses become
18
compromised. Health is also affected as needed hospital visits are avoided when food
resources are scarce. A nationally representative study of low-income adults has shown
that housing instability and food insecurity are linked to difficulty accessing health care
(Kushel et. al 2005). Conversely, spikes in expenses such as “energy costs, food prices,
medical expenses” increase the risk of food insecurity for low-income families (Fletcher
2009:90). These data indicate that food insecure people have to make compromising
decisions when it comes to affording bills, health, and buying food.
A large proportion of low income earner’s wages is spent on food and housing.
Between 2001 and 2005, “among U.S. households…the average annual housing
expenditure increased more than 10% from $6834 to $7529 while the share of
expenditures for housing rose from 36.2% to 39.4%. During the same time period, the
expenditure share spent on food declined from 17.3% to 15.9%” (Bureau of Labor
Statistics 2003, 2007) (Fletcher, et. al 2009:81). Not only is food spending declining as
more money is put towards housing but there is a disproportionate negative effect on lowincome people. For higher income households, even though their housing costs went up
during the same study period, there was “no change in the expenditure share spent on
food” (Fletcher et. al 2009:81). The consequence of this on families is that “their ability
to afford adequate food may be curtailed if they are required to make a trade off between
housing and food” (Mammen et. al 2009:164).
Living in regions with extreme winter weather, also requires that a substantial
amount of money be spent on heating, further diverting funds away from providing an
19
adequate food budget. Lack of home ownership also contributes to housing costs that
affect food spending. This effect is particularly pronounced in California where
“California’s low home ownership rate appears to substantially increase the hunger rate
to a level above the national average; hence, California’s hunger rate might be much
lower under different housing market conditions” (Edwards et. al 2007:592). The fact that
many people in California are renting means that a substantial proportion of the
California population is perilously susceptible to swings in housing costs, which in turn
can affect their ability to feed themselves. Not only does having a low income affect
hunger, but one’s marital status also predicts one’s ability to have enough food.
Marital status also affects food security, as being married is a favorable advantage
as one is less likely to be hungry with more resources in a family. Those who are
divorced or separated are vulnerable to food insecurity (Hason et. al 2007). Having a low
income that is not combined with a second person’s makes it more difficult to gather food
resources. This is compounded when there are children in the household who have their
own food requirements, raising the minimum food burden relative to the individual’s
income. Food Stamp Program (FSP) benefits those who are in need of food resources,
however “among potentially eligible, unmarried female households, [only] 35%
participate in FSP. The factors that determine FSP participation are family structure and
the food stamp benefit level, as well as the labor market opportunities measured through
the predicted wage” (Huffman, Jensen 2008:110). The lack of participation among single
women could be due to a number a factors including: lack of time, stigma of participating
20
in a government program, an inconvenience, or are unknowledgeable about the program.
Not having the financial support to have enough food and also not having the support to
reach out for assistance can be challenging for single people.
While food assistance programs are instrumental in helping the food insecure
obtain food, there is no guarantee that those benefiting from such programs will become
food secure. When looking at the impact of the 1996 welfare reform on food insecurity,
eligibility restrictions reduced welfare recipients by 10%and increased the food insecure
by 5% (Borjas 2004). Although not a huge increase we can see that government aid does
indeed that help people cover their food costs and manage their nutritional needs. Those
who receive WIC supplemental food are “equally likely to be food insufficient across all
categories with two exceptions: children and infants receiving WIC and Medicaid are
more likely to be food insufficient than those receiving only Medicaid” (Bitler,
Gundersen, Marquis 2005:437). This follows the trends among the most likely to be
food-insecure as female, low-income with children. Those enrolled in assistance
programs are already among the most vulnerable in the general population. Often it is the
case that even with such aid individuals remain locked out of the fully food secure
category.
One high note in all of this is school lunch programs which do seem to work well
to provide food to children during the months in which school is in session. Of course
there is the caveat in that during the non-school summer months the rates of hunger go
up. This seasonal effect is noted by Nord and Romig who state that “among low income
21
(below 185% of the poverty line) households, the seasonal difference in the prevalence of
food insecurity with hunger (higher in the summer) was substantially greater in
households with school-age children than in other households” (2006:154). Many
families depend on school lunch programs as a means to help them partially feed their
children in a way that does not impact the food budget for the rest of the family. The
literature clearly shows that when school is not in session, the missing supplement to the
family’s food supply creates a gap in food for their children that is difficult to fill and
often is not filled adequately. Between 1995-2001, “the prevalence of food insecurity
with hunger (measured over the 30 days prior to the survey) was, on average, 1.13
percentage points higher in the August/September surveys (6.47%) than in the in April
surveys (5.72 %), corresponding to an odds ratio (summer to April) of 1.14” (Nord,
Romig 2006:150). Implied from these data is that were food to be available at schools
during the summer for these same children, perhaps the rates of food insecurity would be
lessened during these months.
People use several means to cope with hunger. Food assistance from government
programs is not always a preferred or first choice. Some families use government
programs as the last ‘food management strategy’ they opt for as they would rather
“depend on themselves…extended family and friends, and finally on local community
groups before they turned to the federal government” (Mammen et. al 2009:165). From
this follows the implication that there is less negative social stigma attached to receiving
food from people we know than there is from receiving aid from the government. This is
22
indeed unfortunate as government aid programs have the potential to be a more of stable
and consistent resource than are friends and family. A caveat to this is that government
assistance also has the potential to be more of a burden to a family than it is beneficial
due to the logistics of receiving benefits when families do qualify. The time and energy
required to apply for benefits, receive transportation, using the benefits and providing
qualifications can prove difficult for the family to justify in order to get a supplement to
their monthly food budget. Receiving benefits is one way to avoid hunger, while finding
ways to grow one’s own food is an alternative many are trying to achieve.
Although the current state of food access may be intimidating, farmers and
communities are using their resources to demand what they feel is a basic human right:
having a stake in what they eat. Urban farmer’s agency is shown through their
negotiation with the structures that produce and deliver food to market. These farmers are
“challenging the government’s capacity to provide safe and clean food; to provide
culturally appropriate information about healthy food and demanding the right to control
the local food security movement” (Ore 2011:691). Not only is access to food important,
nutrition education as well as leadership in where and how our food grows is what we can
demand for healthier lives. Community gardens “can serve as examples of how groups of
typically marginalized citizens-immigrants and people living on low incomes- use their
neighborhoods as a means of resistance, asserting their identity to reclaim space and
engage in projects of citizenship” (Ore 2011:693). While abundance in food availability
and access are circumstances many are fortunate enough to take for granted, for those
23
who lack access and/or are low income, food availability can become a point of serious
political and economic struggle for which many are willing to fight.
Research Gaps
The research on food insecurity focuses on the demographics of those who are
food-insecure, food spending among food-insecure populations and the effectiveness of
food assistance programs in relieving hunger. There has also been some interest in
studying how food-insecure people are affected nutritionally, how resident location
affects hunger, and how racial/ethnic identities predict food security. Poverty, food
spending, and food assistance are also topics often covered in food security research.
Limited studies have been published focusing on specific states, however, especially
California, in regards to food insecurity and regional variables within the state.
There are three gaps in the literature that my research will work to fill. First, I
have found the California specific demographic variables that help predict low food
security. The variables that are used to describe Californians are: sex, age, education,
poverty level, race, Hispanic origin, citizenship, labor force participation, and marital
status. Previously there has been a lack of specific research using these identifiers from
the population of one state to help understand to complexities of hunger. Second, I have
addressed the California use of supplemental food programs: SNAP and WIC, which are
two programs that are studied alone, but not always in combination. This information
gained from those who use these programs will help better identify the factors that
influence and affect hunger the most. The third gap that my research will work to fill is
24
the lack of California-specific research on the use of lunch programs for low-income
children. California’s participation of free and reduced cost lunch programs at school,
day-care, or Head Start Program is covered in my research and describes those who use
these supplemental food benefits. California’s diversity and great number of people in
poverty lends itself to a rich resource of information for studying hunger. Through
studying the demographics and the use of food assistance programs in the state, we can
get a better look at hunger with a different lens than has been used previously.
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CHAPTER 3- METHODS
Research Design and Approach
The aim of this study is to identify the demographic characteristics of the
participants of the California Current Population Survey who live in low or very-low
food-security households. The study identified the participants who used benefits from
the Supplemental Nutrition Assistance Program (SNAP), the Women Infant and Children
program (WIC), and received free or reduced cost lunch at school, daycare or Head Start
program to supplement themselves or their household. Data from the 2010 CPS will be
used to measure head of household and household members’ food- security status in
California during the past 12 months.
Survey Population
The CPS sample is based on U.S. Census information from the year 2000 in
which, “Approximately 72,000 housing units [were] assigned for interview each month,
of which 60,000 [were] occupied and thus eligible for interview. The remainder [were]
units found to be destroyed, vacant, converted to nonresidential use, containing persons
whose usual place of residence is elsewhere, or ineligible for other reasons. Of the 60,000
occupied housing units, approximately 108,000 persons [were] 15 years old and over,
approximately 27,000 [were] children 0-14 years old, and about 450 [were] Armed
Forces members living with civilians either on or off base within these households”
(CPS, Dec 2010 Food Security Supplement file, Technical documentation 2-2). The CPS
sample meets reliability criteria nationally, for each of the 50 states, and the District of
Columbia. .
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The December 2010 Food Security Survey was conducted by Census Bureau staff
as a supplement to the CPS. Previous collections of data for this supplement were
conducted yearly since 1995, with the collection consistently in December since 2001.
The food security questions were asked of all interviewed households, as appropriate.
“Items S1A through S8 dealt with food expenditures. Items S8B through S8D dealt with
minimum food spending needed. Items S9 through SP9 dealt with food program
participation. Items SS1 through SSHM5 dealt with concerns about food sufficiency. The
last series of questions, SC1 through SCM4 dealt with ways of coping with not having
enough food. Measures that combine information from multiple items (HRFS12M1 and
following) are generally considered to be more reliable measures of food security and
food insecurity” (CPS, Dec 2010 Food Security Supplement file, Technical
documentation 3-1).
Background
Although it is important to understand who comprises the household of the food
insecure, it is difficult to assume all individuals of the household are affected by food
insecurity in similar ways. The CPS Food Security Survey is designed to measure food
insecurity at the household level. The reference person is the one person who generally
responds for all eligible members of the household. This person is usually the person who
either owns or rents the housing unit. If the reference person is not knowledgeable about
the employment status of the others in the households, attempts are made to contact those
individuals directly.
27
To measure food security, questions are asked to target the household, the adults
in the household, and if there are children present in the household (CPS, Dec 2010 Food
Security Supplement file, Technical documentation 5-1). If there are children present
then some questions regarding food insecurity are asked specifically of households with
children. This includes whether or not they receive free or reduced cost breakfast (or
lunch) at a school or daycare and if they participant in the WIC program. Those who are
eligible to answer questions regarding children and supplemental food programs are
analyzed for their demographic information as well as their food insecurity status.
Although individuals can answer the survey on their own, they may often answer
for others in their household or have someone else answer for them. It may be difficult to
see the importance of gaining demographic information from the individual answering
for the household, but there may be some usefulness from this information since the
reference person usually pays rent or owns the home. The respondents also report the
demographic information of the members of the household or those other members may
report their own information (CPS, Dec 2010 Food Security Supplement file, Technical
documentation 5-1). The following independent variables can be considered significant
identifiers typically related to the head of household: age, marital status, sex, education,
race, Hispanic status, citizenship, and monthly labor force participation.
Dependent Variables
The significant measure of food insecurity summarizes the participant’s answers
to several food insecurity specific questions from the survey over the 12-month period.
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The summary identifies participants of the survey who are food-secure or food-insecure.
For analytical purposes, the categories of food security status were combined as “Food
Secure High or Marginal Food Security” and “Low Food Security or Very Low Food
Security”. Those with low or very low food security status will be considered food
insecure and those with high or marginal food security will be considered food secure.
This summary measurement is the dependent variable for Model 1 and will be referred to
as “Food Security”.
To describe participants who receive supplemental food benefits, the following
variables were used as an overall measure of food benefit participation: (1) whether or
not the participant received benefits from the Supplemental Nutrition Assistance Program
(SNAP) within the last year, as well as (2) whether they received benefits from the
Women Infant and Children program (WIC) within the last 30 days. Those who received
both were coded as “receiving benefits” for the variable “SNAP and WIC participation.”
SNAP is a benefit program that is provisioned for anyone who qualifies based on income,
whereas WIC benefits only women who are pregnant or families with children under 5.
Model 2 is constructed to include the participants who confirm they receive both SNAP
and WIC benefits.
Food supplement programs offering a free lunch benefit are examined in Model
3. The dependent variable consists of measurements that assess whether or not children in
the household received free or reduced cost lunches at school or day-care or Head Start
program within the past 30 days. This dependent variable is referred to as “children
29
receiving free lunch” This model was constructed to include participants who received
free lunch benefits either at school or day care or Head Start programs. For a participant
to receive benefits from any of these food related programs, either from SNAP, WIC, or
free lunch at school, day care or Head Start program, they must enroll in each program
separately as there is a unique set of qualifications for each.
Independent Variables
Independent variables included in this study are a range of demographic questions
aimed at highlighting specific characteristics relevant to food security in the population
surveyed. The independent variables describe poverty level above or below 185%, labor
status, the characteristics of the household family composition and the more specific
demographic information that describes the age, sex, race, and education, which are
typically those of the reference person of the household.
To determine family income and labor status of those who are food insecure, two
measures are included: poverty level and employment status. Poverty level qualification
is included in the analysis to determine whether or not participants fall in the income
range below 185% of the poverty line or above 185% of the poverty line. The reference
category for poverty level is above 185% of the poverty line. Status of the household’s
monthly labor force participation is also taken into account as a factor of income, where it
was recoded to include the following categories: 1) employed- at work 2) unemployedlooking 3) not in labor force- retired 4) not in labor force- disabled 5) not in labor forceother. The reference category for monthly labor force participation is employed at work.
30
To describe the household’s family composition one measure is used. Marital
status is used to describe the household and was recoded and reduced to 4 categories: 1)
Married-spouse present 2) never married 3) widowed 4) other marital status (spouse
absent/divorced/separated). The reference category for marital status is married with
spouse present.
Six measurements are used to determine the demographic characteristics of the
reference person of the household, which includes: age, sex, education, race, Hispanic
origin, and citizenship status. Age describes the age of the person as the end of the survey
week and represents ages 15-85+. Sex is represented as 0) male and 1) female where the
reference category is male. Education was measured as the highest level of school
completed and is represented as 1) less than 1st grade 2) 1st, 2nd, 3rd or 4th grade 3) 5th or
6th grade 4) 7th or 8th grade 5) 9th grade 6) 10th grade 7) 11th grade 8) 12th grade no
diploma 9) high school graduate diploma or G.E.D. 10) some college but no degree
11) associate degree-vocational 12) associate degree-academic 13) bachelor’s degree
14) master’s degree 15) professional school degree 16) doctorate degree.
Race is used to describe the participants and was recoded into 4 categories as
represented by: 1) White only 2) Black only 3) Asian Only 4) multiracial. White only is
the reference category used for race. The origin group of those who identified as Hispanic
was also measured and is represented as 1) Non- Hispanic 2) Mexican 3) other Hispanic
origin. The reference category for Hispanic origin is Non- Hispanic. Citizenship status is
represented as 1) Native, Born in the United States, Puerto Rico 2) Foreign Born, U.S.
31
Citizen by naturalization 3) Foreign Born, Not a Citizen of the U.S. The reference
category for citizenship status is native born in U.S., Puerto Rico.
Data Analysis Procedures
Descriptive statistics were performed on all variables including measuring central
tendency, variance, and standard deviation where appropriate (see Table 1 page 45).
Logistic regression was used for analyzing the independent effects of the independent
variables on the dependent variables “food security”, “SNAP and WIC participation”,
and “children receiving free lunch at school.” Odds ratios were calculated, which
describes the odds of groups being food secure, as well as describing the participation in
food programs. SPSS version 20 was used to run all analyses.
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CHAPTER 4- RESULTS
Table 1 (see page 45) reports descriptive statistics for the sample. The sample is
48.5% female. The mean age of the sample is 49.6 years of old. Of the Californians in the
sample, 12.3% are of low and very low food security in 2010. Of the 814 participants
who qualify for SNAP and WIC in the sample, 32.2% use these benefits. Of the 465
participants who qualify for free lunch for children at school, daycare or Head Start
program in the sample, 59.9% use these benefits. Of those sampled, 53.1% are above
185% of the poverty line, while 26.4% are below 185% of the poverty line. The highest
education obtained spreads from 21.4% having a high school diploma to 21.5% having a
bachelor’s degree, but 13.9% have an 11th grade education or less. The racial
identification of this sample ranges from the majority as white only (79.2%), black only
(6.5%), and as Asian only (11.3%). At the time of the survey, 57.1% of respondents were
employed, but 6.5% were looking for work. A significant amount are retired individuals,
unemployed disabled people, or unemployed because of other reasons, which all of these
groups make up (33.5%) of the labor force. A great number of people are married
(49.7%) while 21.8% have never married and 14.3% are divorced. These demographic
data show the majority are food secure, have at least a high school diploma, identify as
white, are employed and married. The vulnerable food insecure population is on the
fringes with a smaller percentage of people in each demographic category.
Model One Analysis: Being Food Secure
Model 1 (see Table 2, page 48) describes the characteristics that significantly
33
predict food security which are age, education, income below 185% of the poverty level,
black identification, multiracial identification, Mexican Hispanic origin, non-Mexican
Hispanic origin, looking for work, being unemployed and disabled, as well as being
unmarried. The Nagelkerke R square for Model 1 indicates that 23.9% of the variance in
food security is explained by the independent demographic variables. The number of
cases included in analysis is 3,179.
Age, education and level of poverty stand out as key demographics when
predicting the odds of food security. A one year increase in age is associated with a 2.3%
increase in predicted odds of being food secure. A one level increase in education (on the
education scale, see Table 1) is associated with a 11.4% increase in predicted odds of
being food secure. Compared to those who are above 185% of the poverty line, there is
62.5% decrease in odds of being food secure for those who are below 185% of the
poverty line. Poverty qualification is an important marker of initial access or inability to
meet food security status. Increases in age and education are beneficial to maintaining
food security.
Racial identification and Hispanic origin from this sample matter as demographic
characteristics that predict one’s odds of food security as seen in Table 2. For blacks there
is a 41.6% decrease in odds of being food secure when compared to whites. For those
who are multiracial there is a 44.4% decrease in odds of being food secure when
compared to whites. For those of Mexican Hispanic origin there is a 32.8% decrease in
odds of being food secure compared to those of non-Hispanic origin. For those who are
34
of other Hispanic origin there is a 49.1% decrease in odds of being food secure compared
to those of non-Hispanic origin. Compared to whites in the sample, black, multiracial,
and Hispanic people have a decrease in odds of being food secure according to this
sample.
Unemployment and marital status are other characteristics that have a significant
impact on food security as seen in Table 2. For those who are looking for work there is a
50.6% decrease in odds of being food secure compared to those who are employed.
Compared to those who are employed, unemployed disabled people have a 66.8%
decrease in odds of being food secure. Compared to those who are married, those with a
spouse absent/ divorced/separated have a 59.3% decrease in odds of being food secure
and those who were never married have a 25.3% decrease in odds of being food secure.
Clearly employment and marriage contribute positively to food security.
Model Two Analysis: Using Supplemental Food Programs
Model 2 (see Table 3, page 50) describes the characteristics that significantly
predict those who use food supplement programs- WIC and SNAP- which are age,
education, income below 185% of the poverty level, black-only racial identification,
Mexican Hispanic origin, non-Mexican Hispanic origin, being a foreign born non-US
citizen, looking for work, being retired, unemployed and disabled, or being unemployed
for other reasons. Those who are divorced/separated or have an absent spouse for other
reasons are also more likely to use supplemental food programs compared to those who
are married. The Nagelkerke R square for model 2 indicates that 28.3% of the variance of
35
WIC and SNAP participation is explained by the independent demographic variables.
The number of cases included in the analysis is 814.
The demographics that are important indicators to predicting one’s of receipt of
supplemental food benefits are age, education, and poverty level. A one year increase in
age for head of household is associated with a 4.6% decrease in predicted odds of
receiving WIC and SNAP benefits. A one level increase in education (on the education
scale, see Table 1) is associated with a 8.7% decrease in predicted odds of receiving WIC
and SNAP benefits. Compared to those who are above 185% of the poverty line, there is
146.8% increase in odds of receiving WIC and SNAP benefits for those who are below
185% of the poverty line. Being above 185% of the poverty line, older and more
educated are characteristics that decrease one’s odds of receiving WIC and SNAP
benefits.
Racial identification, Hispanic origin, and citizenship status, are also significant in
predicting WIC and SNAP use in model 2 (Table 3). Compared to whites, there is a
129.1% increase in odds of receiving WIC and SNAP benefits for blacks in this sample.
Compared to non-Hispanics, those of Mexican Hispanic origin have a 94.3% increase in
odds of receiving WIC and SNAP benefits. Those of non-Mexican Hispanic origin have a
150.3% increase in odds of receiving WIC and SNAP benefits compared to nonHispanics. Compared to those who are native, born in the U.S., Puerto Rico, or abroad,
those who are foreign born non-US citizens have a 116.4% increase in odds of receiving
WIC and SNAP benefits. Each one of these demographic variables increases one’s odds
36
of receiving these benefits to a great degree.
Employment and marital status also matter when describing those who receive
WIC and SNAP benefits as shown in Table 3. Compared to employed individuals, those
who are looking for work have a 147.1% increase in odds of receiving WIC and SNAP
benefits. Retired individuals have a 851.8% increase in odds of receiving WIC and SNAP
benefits compared to those who are employed. Unemployed disabled people have a
254.7% increase in odds of receiving WIC and SNAP benefits, compared to those who
are employed. Unemployed people for other reasons have a 131% increase in odds of
receiving WIC and SNAP benefits, compared to those who are employed. For those of
with a spouse absent/divorced/separated there is a 147.4% increase in odds of receiving
WIC and SNAP benefits compared to those who are married. Each of these independent
variables significantly affects the odds of receiving these benefits.
Model Three Analysis: Using Free Lunch Programs
Model 3 (see Table 4, page 52) describes the characteristics that significantly
predict those households with children who receive free lunch at school, day care, or their
Head Start program. Age, education, income below 185% of the poverty line, multiracial
identification, Mexican Hispanic origin, non-Mexican Hispanic origin, having a head of
household who is looking for work, or being unmarried are all significant factors in
predicting use of free lunch programs for children. A one year increase in age for head of
household is associated with a 2.9% decrease in predicted odds of children receiving free
lunch. A one level increase in education for the head of household (on the education
37
scale, see Table 1) is associated with a 18.5% decrease in predicted odds of children
receiving free lunch. Compared to those who are above 185% of the poverty line, there is
166.9% increase in odds of children receiving free lunch benefits for those who are below
185% of the poverty line. The Nagelkerke R square for model 3 indicates that 41.9% of
the variance of participation in free lunch at school, day care, or Head Start program is
explained by the independent demographic variables. There were 465 cases included in
the analysis.
Racial identification and Hispanic origin are key factors describing the head of
household whose children receive or don’t receive free lunch as seen in Table 4. For
those who are multiracial there is a 74.9% decrease in odds of children receiving free
lunch compared to whites. For those who are of Mexican Hispanic origin there is a
187.9% increase in odds of children receiving free lunch compared to non-Hispanics. For
those who are of non-Mexican Hispanic origin there is a 320.2% increase in odds of
children receiving free lunch compared to non-Hispanics. Being a race other than white
and being Hispanic puts the likelihood of children receiving free lunch at increased odds.
Unemployment and marital status contribute to the odds of children receiving free
lunch as seen in Table 4. For heads of household who are looking for work there is a
286.3% increase in odds of children receiving free lunch compared to those employed.
For those with a spouse absent/divorced/separated there is a 146.1% increase in odds of
children receiving free lunch compared to those who are married. For those who were
never married there is a 141.2% increase in odds of children receiving free lunch
38
compared to those who are married. It is more favorable to be employed and married if
one wants to decrease their odds for the need to sign up for free lunch benefits.
All three models share significant variables that describe those who are predicted
to be food secure and those who are likely to receive WIC and SNAP and free lunch for
children at school, day-care, or Head Start program. Increasing one’s age and education
level not only increases the odds of being food secure, but it also decreases the likelihood
of receiving food program benefits. For those below 185% of the poverty line, being in
this category decreases the odds of being food secure and increases the odds of receiving
food program benefits. People who are of Mexican Hispanic origin and of non-Mexican
Hispanic origin are at decreased odds of being food secure and at increased odds of
receiving food program benefits. Also those who are unemployed are at decreased odds
of being food secure and are at increased odds of receiving food program benefits. One’s
marital status as spouse absent/divorced/separated is another significant predictor of
decreasing one’s odds of being food secure, and increasing the odds of receiving food
benefits throughout all three models. Age, education, Hispanic origin, being unemployed,
and those with a spouse absent/divorced/separated are key factors in California when
predicting hunger and need for extra food resources.
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CHAPTER 5- DISCUSSION
The results of this research are similar to the findings of previous food security
studies with a few surprises. The significant variables in the analyses bring about several
descriptions of hungry people that are also common descriptors of many topics of
inequality. Having a low income, having little education, being a person of color, being
Hispanic, being single, and being unemployed are characteristics that give one a higher
chance of experiencing disparity. The use of food programs by demographic groups who
also tend to be food insecure is not a revelation, but it speaks to the programs’ inability to
permanently relieve hunger. The results show how complicated ending hunger can be
when so many demographic characteristics are entwined with each other.
Poor nutrition can influence learning challenges at school and with racial
inequality, getting out of poverty and eliminating hunger can be difficult. The previous
research on education and race influencing food security is validated by this study’s focus
on California. As education levels increase in this study, the odds of being food secure
increase as well. Nutrition levels that are inadequate not only affect one’s health, but
cognitive functioning important in academics negatively affects those who are hungry
(Ashiabi, O’Neal 2007). Even though being more educated is beneficial to avoiding
hunger, once one has already experienced hunger it can be a roadblock to achieving
academic success. Being a person of color, specifically black or multiracial, along with
being in poverty decreases one’s odds of being food secure. Hispanic children and teens
“have higher school dropout rates and lower high school completion rates” (Gorman et. al
40
2011: 153). In this study being of Mexican or other Hispanic origin increased one’s odds
of being food insecure compared to non-Hispanics. Poverty along with discrimination
and lack of access to food brings about a vicious cycle of inequality that is difficult to
break.
California’s diverse metropolitan cities and isolated rural areas make it difficult
for people to eat healthy food on a regular basis, especially for black, multiracial, and
Hispanic people. Previous studies have described groups at risk for food insecurity
including “Black and Hispanic households had rates of low and very low food security
that were well above the national average (Nord et al. 2005). Also considered particularly
susceptible to food insufficiency were families of migrant and seasonal farm workers”
(Mammen et. al 2008: 153). In this study, even though only 6.5% of the sample is black
and 1.7% is multiracial, the number of food insecure is not small at nearly 12% of the
state. Hispanics of Mexican origin are at 32.8% decreased odds of being food secure
when compared to non-Hispanics, furthering the evidence of the marginalization of
people of specific national origins and ethnicities as their likelihood for hunger increases.
Whether one is in the center of large city making it difficult to access larger food stores in
the suburbs, or in a rural area with even greater distance to a food store, California is not
easy to simplify in terms of where hungry people live. This study confirms that a person’s
race/ethnicity compounded with California’s unique variety of living situations
contributes to one’s odds of being food secure.
Poverty, income, and marital status are all important demographic variables that
41
are highly related to food insecurity in previous studies as well as this one. Poverty not
only has to do with the amount of money one has, but the proportion of it that is allocated
to food costs is often minimal (Fletcher et. al 2009). In this study those who are below
185% of the poverty line have a 62.5% decreased odds of being food secure compared to
those above 185% of the poverty line. This statistic is predictable as one of the main
factors that cause hunger. Marital status is another important component of poverty as
studies have shown that “Never married, cohabiting, separated and divorced men and
women, all reported lower levels of food security, with divorced and separated men and
women most likely to report very low food security (7%)” (Hanson et. al 2007:1461).
Those with a spouse absent/divorced/separated in this study were at much greater odds of
being food insecure than the married participants. Food resources of single people who
were once married do not compare to the great amount of money for food that married
people are more likely to have. Poverty when combined with other characteristics that
decreases one’s income has an insurmountable affect on food security.
Unemployment is just one demographic characteristic that describes many people
who are more likely to receive benefits from food programs such as SNAP, WIC, and
free lunch for children at school, day-care, or Head Start program. The effectiveness of
food supplement programs has been widely studied, but in this California sample only a
small amount were included as using these programs. The population eligible to receive
WIC is growing, but of those who can receive it, only 6 in 10 children do (Bitler et. al
2005). This study confirms that of those who are looking for work, 147.1% are at
42
increased odds of receiving WIC and SNAP compared to those who are employed. Even
though unemployment makes one a candidate for needing such programs, participation
does not always occur. School lunch programs are successful as meals offered during the
school year and in the summer decreased food insecurity in U.S. households (Nord and
Romig 2006). In this study, being unemployed as the head of household increased one’s
odds of children participating in a free lunch program by 286.3% when compared to
employed people. Although it is clear how lacking an income creates the need for free
food, there are free lunch programs that still do not have nearly the amount of participants
using it that are eligible.
The surprise from this study that fills previous gaps in food security literature is
that being of Mexican or other Hispanic origin is a significant descriptor of those who are
at decreased odds of being food secure and describing those who are at increased odds of
participating in food programs. It is shown in many hunger studies that increasing
education and avoiding unemployment are vital aspects of maintaining food security. In
all of the model analyses Hispanic origin, education, and unemployment either put one at
greater or lesser odds of being food secure. Hispanic origin stood out statistically perhaps
because of California’s large population of Hispanic people. Due to this ethnicity often
being tied to poverty and discrimination, it is likely that this group will have a more
difficult time avoiding hunger than their non-Hispanic counterparts.
Although food insecurity seems to be a difficult condition to overcome when
analyzing the data of vulnerable groups, it is something we can slowly try to achieve. We
43
need to recognize the inequalities that low income, unemployed, uneducated, people of
color face that the middle class, employed, educated, white people rarely encounter when
trying to feed themselves and their families. Once hunger enters a home, the negative
effects on one’s health encroach on other aspects of life. If food programs where more
readily available to people before they experienced hunger, the detrimental impacts
would lessen. Since food programs are tied to political means, it’s not a guarantee that
food budgets will expand. Some are already finding their own ways of gathering healthy
foods through city gardens, but this will not work for everyone. Poverty’s connection to
our other social statuses enables us to see how the overall investment in human rights and
equality will solve hunger problems and other social issues as well.
Limitations
The data from the Current Population Survey was beneficial as well as limiting.
Although the dataset provided large numbers for the sample size of California that were
surveyed for food security, the sample for those who used food supplemental programs
was much smaller. Model 2 provided 814 in the analysis and Model 3 provided 465 in the
analysis. Perhaps a data set that was more specific to measuring food programs would aid
this study. As for the weighting the data, the analyses were done unweighted. This was
due to the SPSS program that was available to me had issues with the data set and its
ability to weight it correctly, while other statistical software was not within my resources.
It is assumed that the results would be slightly different if weighted, but not dramatically
so. One variable, poverty level qualification was categorized within the data as
44
combining poverty level above 185% of the poverty line and income not reported. This
did not allow those who did not report income to be taken out of the analyses.
Areas of Further Research
Although the data provided a wealth of information on those who are food
insecure it only highlights the statistical story of Californian’s hunger. A follow up study
of a qualitative nature, including focus groups and interviews, would add to the
explanation of how and why people become hungry. Although hunger rates are recorded
and studied year after year using the CPS food security supplement survey, it does not
capture some of the localized and time specific events that could affect people’s food
consumption. This gap in information could be captured through open-ended interviews.
Questions could include: what do you do when you don’t have enough food? Is there an
event(s) that you can think of that compromised you or your family’s hunger in the past
year? Who is/are the member(s) of the family that will go hungry if there is not enough
food? Is it always the same person, if not who? What are your priorities when it comes to
your family’s funds? Do you feel comfortable reaching out for government help when it
comes to feeding your family? These are just some of the questions that would provide a
narrative to the lives of the hungry.
45
Table 1 Descriptive Statistics of Food Supplement Survey Participants in California
Variable
Percent
Summary Food Security Status
Not in Universe
20.5%
Food Secure High or Marginal Food Security
66.7%
Low Food Security
7.9%
Very Low Food Security
4.4%
Received SNAP and WIC Benefits
Yes
32.2%
No
67.8%
N= 814
Received free or reduced cost lunches at school, daycare, or Head Start Program
Yes
59.9%
No
40.1%
N= 465
Poverty level- above or below 185% of the poverty line
Below 185% poverty
26.4%
Above 185% poverty
53.1%
Highest level of school completed
Less than 1st grade – 11th grade
13.9%
12th grade no diploma
1.4%
High school grad diploma or GED
21.4%
Some college but no degree
20.2%
Associate degree- occupational/vocational
3.8%
Associate degree- academic program
5.2%
46
Table 1 Descriptive Statistics of Food Supplement Survey Participants in California
Continued
Variable
Percent
Highest level of school completed
Bachelor’s degree
21.5%
Master’s degree
8.6%
Professional school degree
1.8%
Doctorate degree
2.2%
White only
79.2%
Black only
6.5%
American Indian, Alaskan
.9%
Asian only
11.3%
Hawaiian/Pacific Islander only
.5%
Multiracial
1.7%
Race
Monthly Labor Force
Employed- at work
57.1%
Employed- absent
1.7%
Unemployed- on layoff
.8%
Unemployed- looking for work
6.5%
Not in labor force- retired
18.4%
Not in labor force- disabled
5.2%
Not in labor force- other reasons
9.9%
47
Table 1 Descriptive Statistics of Food Supplement Survey Participants in California
Continued
Variable
Percent
Marital Status
Married- spouse present
49.7%
Married- spouse absent
2%
Widowed
8.9%
Divorced
14.3%
Separated
3.2%
Never married
21.8%
48
Table 2 Logistic Regression Model 1-Describing those who are Food Secure
Variables
Exp(B)
Sex, Age, Education
Sex (male omitted) Female
.987
Age
1.023***
Highest level of School
1.114***
Income
Below 185% of the poverty line1
.375***
Race2
Black only race
.584**
Asian only race
1.103
Multiracial race
.556*
Hispanic Origin3
Mexican Hispanic Origin
.672**
Other Hispanic Origin
.509**
Citizenship4
Foreign Born U.S. Citizen
1.100
Foreign Born Not a Citizen
.868
Employment5
Unemployed Looking for Work
.494***
Not in Labor Force Retired
1.111
1
Reference category = above 185% poverty
Reference category= White only racial identification
3
Reference category= Non- Hispanic
4
Reference category= Native, born in US, Puerto Rico, or abroad
5
Reference category= Employed at work
2
49
Table 2 Logistic Regression Model 1-Describing those who are Food Secure Continued
Variables
Exp(B)
Employment Continued
Not in Labor Force Disabled
.332***
Not in Labor Force Other
.750
Marital Status6
Other Marital Status: Spouse Absent, Divorced, Separated
.407***
Widowed Marital Status
.728
Never Married Marital Status
.747*
N=4140 total, 3179 included in analysis
Nagelkerke R Square = .239
*p<.05, **p<.01, ***p<.001
6
Reference Category= Married spouse present
50
Table 3 Logistic Regression Model 2- Describing those who Receive WIC and SNAP
Benefits
Variables
Exp(B)
Sex, Age, Education
Sex (male omitted) Female
.894
Age
.954***
Highest level of School
.913**
Income
Below 185% of the poverty line7
2.468***
Race8
Black only race
2.291*
Asian only race
1.274
Multiracial race
1.938
Hispanic Origin9
Mexican Hispanic Origin
1.943**
Other Hispanic Origin
2.503**
Citizenship10
Foreign Born U.S. Citizen
1.294
Foreign Born Not a Citizen
2.164**
Employment11
Unemployed Looking for Work
2.471**
Not in Labor Force Retired
9.518***
7
Reference category= Above 185% poverty
Reference category= White only racial identification
9
Reference category= Non-Hispanic
10
Reference category= Native, born in US, Puerto Rico, or abroad
11
Reference category= Employed at work
8
51
Table 3 Logistic Regression Model 2- Describing those who Receive WIC and SNAP
Benefits Continued
Variables
Exp(B)
Employment Continued
Not in Labor Force Disabled
3.547**
Not in Labor Force Other
2.310***
Marital Status12
Other Marital Status: Spouse Absent, Divorced, Separated
2.474***
Widowed Marital Status
1.997
Never Married Marital Status
.965
N=4140 total, included in analysis= 814
Nagelkerke R Square= .283
*p<.05, **p<.01, ***p<.001
12
Reference Category= Married spouse present
52
Table 4 Logistic Regression Model 3- Describing those who Receive Free Lunch at
School, Day Care, or Head Start Program
Variables
Exp(B)
Sex, Age, Education
Sex (male omitted) Female
.686
Age
.971*
Highest level of School
.815***
Income
Below 185% of the poverty line13
2.669**
Race14
Black only race
2.223
Asian only race
1.710
Multiracial race
.251*
Hispanic Origin15
Mexican Hispanic Origin
2.879**
Other Hispanic Origin
4.202**
Citizenship16
Foreign Born U.S. Citizen
.676
Foreign Born Not a Citizen
1.518
Employment17
Unemployed Looking for Work
13
Reference category= Above 185% poverty
Reference category= White only racial identification
15
Reference category= Non-Hispanic
16
Reference category= Native, born in US, Puerto Rico, or abroad
17
Reference category= Employed at work
14
3.863**
53
Table 4 Logistic Regression Model 3- Describing those who Receive Free Lunch at
School, Day Care, or Head Start Program Continued
Variables
Exp(B)
Employment Continued
Not in Labor Force Retired
2.633
Not in Labor Force Disabled
2.576
Not in Labor Force Other
1.722
Marital Status18
Other Marital Status: Spouse Absent, Divorced, Separated
2.461**
Widowed Marital Status
1.737
Never Married Marital Status
2.412*
N=4140 total, included in analysis= 465
Nagelkerke R Square= .419
*p<.05, **p<.01, ***p<.001
18
Reference category= Married Spouse Present
54
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