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Food Stamps: Helpful or Hurtful?
The Effect of SNAP Participation on Obesity among US Latino Citizens
by
Vanessa Unglaub-Castaño
A Thesis Submitted in Partial Fulfillment of the Bachelor of Arts Requirements in
Interdisciplinary Studies (UGIS), The University of California, Berkeley
May 11th, 2014
Advisor: Bruce Newsome

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Table of Contents
Chapter Title Page
Title Page i
Table of Contents ii
1. Introduction 1
1.1 Scope 1
1.2 Objectives 2
1.3 Preview 4
2. Literature Review
2.1 Obesity: What is it? 4
2.2 Review of Federal Food Assistance Programs 5
2.3 History of SNAP 6
3. Theory Review 7
2.1 Acculturation Stress & Allostatic Load 8
2.2 Barriers to Physical Activity 10
2.3 Nutrition Theories 11
2.4 Cultural Differences 12
2.5 Food Environment 13
2.6 Alternative theories 14
2.7 Food Stamps and Obesity Associations 16
2.8 Hypothesis 20
2.6 Model 21
4. Methodology 21
4.1 My Methodology 21
4.2 Comparative Case-Study: San Joaquin/Santa Clara County 24
4.3 Results & Summary 27
5. Conclusion, Strengths/Limitations, Recommendations 29
6. Reference List 32
7. Bibliography 36

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I. Introduction
How can SNAP in the United States reduce obesity among the Latino community ?
1.1 Scope
It has been firmly established in the literature that there is a connection between what we
eat has a direct effect on our weight. “Comfort foods”, (usually foods high in fat, salt and /or
sugar), are absorbed quickly into the bloodstream when digested in the body, increasing insulin
production that, in turn, leads to fat storage. However a rather newer field of study has emerged
that studies how food purchasing habits depend much on socioeconomic status (SES). For too
many Americans, energy-dense, nutrient-poor (EDNP) foods are all that is affordable not to
mention what is most readily available (Togo et. al 2001, 1745; Kant 2000, 929). It has been
well-established in the literature that food insecurity which is defined as having an unreliable
access to nutritious, inexpensive foods is shown to increase the risk of obesity (Adams et. al
2003, 1070). The question that I will be asking and exploring is whether or not food stamps are
effective in their attempt to increase access to nutritious foods for low income families? Besides
alcohol and hot,prepared meals, there are no restrictions on what foods food stamps can buy.
Although the relationship between SNAP and health, especially as it pertains to obesity, is
disputed among researchers, I seek to improve and challenge the practice of federal food
assistance programs to implement a more culturally, socially, and economically-aware program
that understands and serves the unique situations of the diverse population they serve.
Obesity is a fairly new phenomenon in the United States. Obesity prevalence slowly rose
in the early to mid 20th century probably as a result of increased technology and the low cost of
EDNP foods. However it wasn’t until the 1980’s when obesity skyrocketed across all ethnicities.

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In 2004 32% of the US adult population were obese compared to 13 % between 1960-1962
(Finkelstein, Zickerman 2008, 5). If the current obesity trend in the United States continues,
“total health-care costs attributable to obesity/overweight would double every decade to
860.7–956.9 billion US dollars by 2030, accounting for 16–18% of total US health-care costs”,
which are then paid by the average taxpayer (Wang et al 2008, 2323). Obesity has become an
increasingly researched topic because of its dire effects on quality of life and its effect on heart
disease, the leading cause of death among women and men in the United States. For the purpose
of this paper what is of most importance is why and how obesity affects Latinos
disproportionately.
Objective
My research explores how SNAP is affecting obesity in the Latino community in both
unhealthy and healthy environments. SNAP is currently the largest domestic hunger safety net in
the United States organized by the US Department of Agriculture serving 1 out of 5 Americans
(Morin, 2013). Currently there are three camps of arguments that suggest that SNAP either
positively, neutrally, or negatively affects obesity. This paper will challenge these arguments by
suggesting that it is not SNAP alone that is causing obesity, it is in fact alternative factors that,
when coupled with SNAP participation, increase obesity in the Latino population. I hypothesize
that SNAP, in an environment with access to healthy food, would reduce obesity and, in an
environment without access to healthy food, would increase obesity among Latinos living in the
United States.
Why focus on the Latino population? According to Jerant et al and the Latino Coalition
for a Healthy California, the fastest growing ethnic group in California are Latinos. Between

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1998-2008 obesity remained highest among the Latinos compared to all the different ethnic
groups studied (Sharma et al 2009, 770). Latinos make up the largest minority group in the
United States and will soon become a majority ethnic group in our nation. Also I wanted to fill a
gap in the literature; there is insufficient research regarding the specific risk factors that are
making them more susceptible to obesity compared to other ethnic groups (Jerant et al 2008,
709) as well as how SNAP participation differentially affects the risk of obesity among different
ethnicities. However from the few studies that I have come across, Latinos are at greater risk for
dietary deficiencies; therefore given the unregulated structure of SNAP, they are more likely to
consume EDNP foods that contribute to obesity. Although I will not go into genetic
predisposition in this paper, research across the board has shown a higher propensity for Latinos
(especially women) to gain and hold onto excess weight; thus SNAP, I conclude is contributing
to the overall weight problem in this community. Because of this, I am seeking to improve policy
in this paper and make recommendations of where SNAP can be modified. I came across a study
published this year that showed that Latinos are at In a recent phone interview I conducted with
Dr. David Hayes Bautista, a leading expert on Latino health in the United States, he informed me
that the research methodologies that have been performed thus far on the topic of Latino health
are faulty. Given that taxpayers suffer when obesity rises as mentioned above, it is imperative for
the sake of all Americans that more research is done on Latino obesity in order to improve
current ineffective interventions and create innovative, culturally sensitive ones that will reduce
obese among Latino-Americans. My research suggests an integrated theory for why obesity
disproportionately affects Latinos in the United States combining theories from public health,
behavioral economics, anthropology, and nutrition.

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This thesis will challenge the USDA’s perception that federal nutrition assistance
programs, SNAP in particular, improve nutrition intake among low-income individuals hence
lowering obesity. There are many factors in the literature that suggest correlational relationships
to obesity; of these I will not research the effects of genetic predisposition nor will I separate the
effects of SNAP between the genders. Genetic predisposition will not be explored because I
explore mostly the social determinants of health. In addition given the limited time of a one
semester thesis I do not explore why there is a difference between males and females in obesity
prevalence.
Preview
The rest of this thesis will be divided into four sections: a literature review summarizing
the arguments regarding the relationships between food stamps and obesity; a theory review
covering alternative theories which explain my hypothesis for the causes of obesity in Latinos; a
test section explaining my methodologies and findings from testing my hypothesis; and lastly my
conclusion.
II. Knowledge Review
Before discussing the different theories regarding the role of food stamp participation
(FSP) in reducing the obesity epidemic, it is important to first understand what is obesity, who it
is affecting the most, and how it is quantified.
A. Obesity: What is it?
According to the Center for Disease Control, obesity is defined as having a body mass
index (BMI) of 30 kg/m​2​
or greater. A BMI is found by dividing one’s weight in kilograms by

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one’s height in meters squared. A normal BMI lies in the range of 18.5-24.9 kg/m​2​
. BMI
indicates extra body weight which if excessive, is classified as obesity leading to diseases such as
heart disease, diabetes, and other cardiovascular diseases (CDC, 2014). Obesity is not only
responsible for placing individuals at risk of these diseases but also can lead to psychological
issues such as depression and lower self-esteem, especially among children who are at higher
risk of being bullied at school (LCHC 2006; Finkelstein, Zickerman 2008, 5).
Obesity is a major risk factor for the leading cause of death for women and men in the
United States, heart disease (CDC 2014). To get a better sense of who obesity is unjustly
affecting and how burdensome it is, government data has revealed that between 1986-1998
obesity rose by more than “120 percent among African-Americans and Hispanic children
compared with 50 percent among Caucasians”. By 2004, Hispanic obesity rates reached roughly
35%. (Finkelstein, Zickerman 2008, 5-11). In order to address this growing epidemic, the
government has implemented several federal programs to increase access to nutritious food for
low income families who tend to be more food insecure and thus suffer from higher obesity
rates. There are specific programs that target children (i.e. the National School Lunch Program
(NSLP)), mothers and infants (i.e. Special Supplemental Nutrition Program for Women, Infants,
and Children (WIC)), and for low income individuals in general (i.e. Supplemental Nutrition
Assistance Program (SNAP)).
Review of Federal Food Assistance Programs
The National School Lunch Program (NSLP), which is run by the US Department of
Agriculture’s (USDA) Food and Nutrition Service (FNS), was designed to meet the nutritional

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needs of children in order for them to perform better at school. In order to receive a free or
reduced price lunch,
“household income must be at or below 130 percent of the federal poverty level; for reduced
price lunch, income must be between 130 percent and 185 percent of the poverty level.”
Congress decided to create this program after enacting the National School Lunch Act in 1946
“after an investigation into the health of young men rejected in the World War II draft showed a
connection between physical deficiencies and childhood malnutrition”. In 2011, $10.1 billion
dollars was spent on this program in the form of cash reimbursements per meal to schools for
preparing nutritious meals for children (FRAC 2010).
WIC, which is administered by the FNS, serves pregnant, postpartum, and breastfeeding
mothers, infants, and children up until the age of 5 with supplemental nutritious foods packages,
nutrition education/counseling including breastfeeding promotion and support, and health
screening and referrals to other health services. It was induced by a national public concern in
the 1960s for malnutrition in young mothers and children. It was officially introduced and
authorized as a federal program in 1972, by an amendment to the Child Nutrition Act of 1966.
Eligibility for this program is dependent on several factors such as income (between 100-185%
of the federal poverty guidelines) and nutrition risk which is a medically or diet-based condition
such as anemia or being underweight. In 2013, WIC benefitted 8.6 million women, infants, and
children per month. WIC operates on a federal, state, and local level which is principally
administered by the FNS. Each state is responsible for allocating food and services to eligible
residents. According to the USDA, Congress appropriated $6.522 billion for WIC in Fiscal Year
2013 (FNS 2014).

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History of SNAP
Lastly the program that I will focus on is SNAP. Food stamps, or as of 2008 known as
SNAP, have existed in the United States since the early 20th century and are funded by the
federal and state
governments. In 1933 the “Agricultural Adjustment Act introduced the first ‘farm bill’ [which]
established the New Deal mix of commodity-specific price and income support programs”
(Dimitri et.al 2005,9). Food stamps were initially distributed via coupons to people who were
making at or lower than an established income limit,which is 130% of the federal poverty line.
Since then, coupons have been replaced with Electronic Benefit Transfer (EBT) cards (Ver Ploeg
et al. 2008, 22). Because of the economic crisis at the time of the Great Depression, food stamps
were established to help farmers get rid of their excess produce supply by selling their produce at
a discounted price and distributing it to hunger relief agencies all throughout the country (USDA
Food and Nutrition Service, 2013). In other words, food stamps were created with the mission to
reduce hunger and malnutrition among food insecure individuals by increasing food purchasing
power in order for all eligible households to “obtain a more nutritious diet” (USDA 2004). In
1977, the American federal Farm Bill started to include food stamps The Farm Bill is a set of
policies that is reintroduced every 5 years which include topics such as food assistance, crop
support, and conservation. Eighty percent of the Farm Bill, which accounts for 2% of federal
expenditures, is spent on food assistance programs, mainly SNAP (House Committee on
Agriculture, 2012). Due to various policy reformations in the Farm Bill over the years, the
priority of food stamps, according to the USDA SNAP federal website, has shifted from reducing

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hunger in food-insecure communities to one focused on improving the nutrition of these
communities; however, I critique the realization of this priority shift in my theory review.
I have chosen to focus on SNAP because it is not only the largest and oldest of all of the
federal nutrition assistance programs in the country, but is also the most widely researched in
terms of its effects on health and most vulnerable to funding cuts (FRAC 2014). My subsequent
section will be divided into theories that explain why Latino-Americans suffer from higher rates
of obesity than White-Americans and theories that show how SNAP participation affects obesity
risks.
III.Theory Review
Latino obesity is a threatening issue that warrants much study and intervention. With
immigration on the rise and an already high percentage of Latinos in the United States, Latinos
are becoming central to the US economy. For example, without Latino immigrants, California
agriculture would not be the booming industry which is world renown (Diaz, Garza 2001, 5). In
order to improve the health of this population and stop incurring the high cost of obesity,
interdisciplinary research is needed to fully address the complex issue of obesity in regards to the
Latino population. First, I will review theories relating the effects of acculturation; cultural
differences; and food and physical environments to obesity. For the purpose of this thesis,
citizenship status and gender differences in obesity rates will be excluded from my scope but I
will investigate the difference in obesity rates between US-born vs. foreign-born Latinos. For
one, SNAP eligibility requires US citizenship status; therefore, looking at illegal residents is
irrelevant. In addition, adding a gender component adds another level of complexity that is out of
my expertise (i.e. gender differences could be explained by more biological/genetic and other

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confounding factors that require a higher level of obesity). My last subsections will be devoted
into investigating theories regarding the role of FSP on obesity.
Acculturation Stress, Allostatic Load, and obesity: a result of immigration
Acculturation stress (AS) is a phenomenon that has been observed in multiple immigrant
ethnic groups in the United States. For example, among Asian immigrants one study reported
that Koreans and Asian Indians experienced a high level of depression due to acculturation stress
caused by cultural alienation, confusion, and a loss of cultural identity when introduced to the
American, western culture (Oh et al 2010, 521). Although this has been studied across several
ethnic groups, the literature is most extensive regarding the effects of AS on Latinos in the US.
D’Alonzo et al argue that Latinos and other minorities tend to be more exposed to chronic
psychological and physiological stressors. In the literature, allostasis has been cited as one of the
biological onsets of obesity. Allostasis is a normal physical coping response to short term
physiological and psychological stress. AS triggers allostasis and is an independent risk factor
for the development of obesity which in turn is a major risk factor to heart disease which is the
leading cause of death in the United States. AS includes racism, discrimination, low
socioeconomic status (SES), separation from family, and fear of deportation. These factors
contribute to unhealthy behaviors such as sedentary lifestyle and higher consumption of
energy-dense, nutrient poor (EDNP) foods that increase the chances of becoming obese in the
Latino community.
The severity of acculturation stress is dependent on factors such as social support. No
matter what generation level, all Latinos are in one way or another affected by immigration

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either directly or indirectly via their parents or grandparents. Latino culture is very tight knit and
family-oriented; therefore, according to D’Alonzo et al., the decision to immigrate and leave
some family members behind is one major factor of acculturation stress, and thus obesity, among
Latino immigrants in the United States. Social networks serve as a “safety net” for Latinos who
may struggle from financial, psychological, and other stresses.
According to a study published by Thornton et al., informational and emotional support
were shown to be the most influential factors affecting the participant’s weight, eating, and
physical activity habits. In fact, geographic distance from female relatives and social support was
the primary reason for unhealthy behaviors. Separation from family results in social isolation
which causes a sense of reluctance and lack of motivation for Latinos to use communal places to
exercise. This lack of exercise increases their chances of weight gain and ultimately obesity
(D’Alonzo et al. 2012, 364,365,366,370). Recent Latino immigrants are similar to other ethnic
immigrants who have resided in the US for 10 years or less, in that they have been reported to
have a lower BMI compared to those who have lived in the US for longer. An average Latina
immigrant to the United States, whose height is roughly 5-feet 4-inches, gains an extra 9 pounds
compared to her counterpart who stayed in her home country, everything else controlled for
(Finkelstein,Zuckerman, 2008 16). Another study showed how participants’ husbands reinforced
a sense of holistic health (a belief in mind, body, spirit connection for true health and wellness)
in order to encourage their wives not to gain excess weight. This is yet another example of the
influence of family on perceptions of weight and weight control in the Latino culture.
Participants reported that they were more likely to maintain a healthy weight in order to please
their husbands. Thornton et al. illustrate the impact of family decisions and attitudes on food

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purchasing habits. For example, if a Latino husband and wife experienced financial difficulties,
Latina participants would often refuse to buy fruits and vegetables and instead buy meat that
would please their husbands. Consuming meats and other energy dense food which tend to be
more affordable for low SES groups instead of fruits and vegetables increases the risk of to
obesity (Drewnowski, Specter 2004, 11). In addition, when meals were home-cooked and a
specific schedule was set where husband and wife would eat together, healthy weight was
maintained because it was of high importance to the family bonding experience.
Barriers to Physical Activity: Social Support and Physical Environment
Public health experts have realized that simply educating the community on the amazing health
benefits of exercise is not enough to reverse the unhealthy trend towards a sedentary lifestyle.
Public health scholarship has investigated the relationship between barriers to physical activity
and obesity among the Latino community in the United States. One such barrier is the lack of
childcare. In Mexico, the home of the largest Latino subgroup in the United States (64.9%),
extended family serve as the main source of childcare while parents do their errands and other
physical activities (Motel, Patten 2012). However the lack of familial support in the United
States discouraged mothers to exercise. In addition, Latino parents report that barriers to their
children’s weight reduction include access to places where the family could exercise together;
the high cost of transporting and enrolling their children in extracurricular activities, and safety
concerns.
In addition to lack of social support, SES plays a major role in deciding what physical
environment Latinos reside in. Latinos are more prone to live in areas where crime, violence, and

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traffic are high and access to parks and recreational facilities are low. It has been well
documented in the environmental justice literature that a safe environment that is conducive to
physical activity lowers BMI. In addition, growing research shows that ethnic minorities
communities of lower SES are marginalized because they live in “obesogenic” neighborhoods
where physical activity is very limited. One study shows that Los Angeles minority
communities have lower per capita park area compared to white communities (Cutts et al 2009,
1315). Other literature argues that it is not a lack of recreational facilities that contributes to
inactivity but rather hectic and conflicting parents‘ work schedules and children's’ schedules that
prevent parents to monitor and engage in active lifestyles with their children (Morales 36).
Whatever the reasons may be, it is evident that physical environment determines Latinos’
likelihood of becoming obese.
Nutrition theories
Acculturation stress has physical manifestations by way of the diet that immigrants adopt
as they migrate to the US. This is because when Latino immigrants leave their home country
where they are used to eating a diet that is low calorie, low fat, and high in fruits/vegetables to
migrate to the United States, most of them lose their traditional diet and adopt the American
cuisine which is notoriously EDNP (Kant 2000, 930). This transition in nutritional value is
known as the nutrition transition theory. This phenomenon is now seen in many parts of the
developing world such as in Brazil and India where the lowest income quartile are the most
obese partly due to the high accessibility of cheap fats and high fructose corn syrup (Candib
2007, 550).

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Another theory known as the mismatch theory​ ​explains that if children in their home
country experience nutritional deficits, then they are more likely to gain excessive weight after
immigration to the United States by consuming EDNP foods as a result of stressful changes in
social and economic environment (D’Alonzo et al 2012, 369). The obesogenic environment that
is common in many affluent societies around the world promotes the excessive weight by
encouraging higher EDNP food expenditures (Gluckman et al. 2009, 1654).
In addition to physical health, obesity plays a toll on the mental health of children,
especially for children who are already more prone to be bullied at school (such as those of lower
SES and minority groups). One study showed that quality of life (QoL) scores were less for
obese children than for those with cancer and more morbid diseases. In addition psychosocial
pressures such as bullying,lower self-esteem, and body image as well as physical consequences
such as asthma and joint pain are the reasons for this low QoL reporting (Boudreau et al, S252).
Cultural Differences
How do Latinos think about their health? It turn out that self-reported health is a major
determinant of whether individuals will seek help for managing their weight. Public health
scholarship stresses that policies and interventions that seek to reduce obesity in the Latino
community need to understand how the body is constructed mentally in the Latino culture and
how different levels of acculturation play into this construction (Finch et. al. 2002, 758). The
dominant conventional medical model, implemented in American health care systems, imposes
their own view of a healthy weight and body on Latinos by focusing on individual behavior and
choice, called in the literature “blaming the victim”. Contrary to what the American medical

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model may say about Latinos weight status, literature from 2000-2007 suggests that Latino
parents “do not perceive their children to be overweight and are not concerned about their health
risks.” In fact Latina mothers believed that a young child who was moderately overweight, was
in their perspective, healthy and happy. In addition, a thin child was seen as being at risk of
health problems due to the mother’s experience growing up in a developing Latin American
country where undernourishment was prevalent (Olvera et al 2011, 93; Ward 2008,410). One
study by Agne et. al. noted that marriage and family life made it easier for Latina participants to
live a more sedentary life since they stayed mostly in the household. Since family bonding is
key in the Latino culture, the lack of access and time to prepare fresh meals every day and
maintain regular familial meal schedules has proven to be detrimental to Latino health with
respect to obesity. Most women in this study worked and reported having very short breaks
which only gave them time to eat a quick highly processed meal. Also the move to the United
States decreased their physical activity that they were used to in their home country where they
could freely walk daily to the market to buy fresh foods inexpensively (Agne et al 2012, 1069).
Food Environment
In addition to walkability and access to safe daily physical activity, the food environment
directly affects nutrition and food consumption in the Latino community. According to the
USDA, the food environment includes factors such as “store/restaurant proximity, food prices,
food and nutrition assistance programs, and community characteristics” (USDA, 2014). Latinos
are more likely to live in low SES neighborhoods referred to as as “food deserts,” or regions
lacking the provision of fresh fruits, vegetables, and other fresh produce usually caused by a lack

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of grocery stores, farmers’ markets, and other healthy food providers (Gallagher,​ ​2010). The
number of food deserts is positively correlated with obesity rates among Latino adults (Han et al
2012, 1877). In California alone, 48% of Latinos live farther than a one-half mile walking
distance to a supermarket. This makes it extremely cumbersome and time consuming for those
that do not have a private vehicle to reach their nearest supermarket/grocery store,decreasing
their chances of consuming daily recommended amounts of fresh fruits/vegetables, whole grains,
and other healthier options compared to convenience/corner stores. (LCHC 2006, 2-3).
Alternative theories
In contrast, other literature argues that although Latinos in the United States have lower
socioeconomic status (SES) and higher morbidity rates compared to Caucasians, they actually
generally have lower mortality rates from “chronic diseases associated with obesity”. This is
otherwise known in
the literature as the “Hispanic paradox”(HP) or the “epidemiological paradox” (D’Alonzo et al
2012,365; Hao, Kim 2009, 240).
The HP is categorized into three subtheories: the “healthy immigrant effect”, the
“salmon-bias effect”, and the “cultural buffering effect.” The “healthy immigrant effect”
explains that foreign diets and lifestyles are generally healthier than those of Americans and thus
immigrants are initially “protected” because they have favorable body compositions when they
arrive to the United States. The salmon-bias effect explains that healthier Latinos tend to
self-select for migration when they feel healthy and when they reach a period of unhealthiness in
a host country they tend to return to their home country to die peacefully in the comfort of their

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family. This selective in and out-migration process ensures a disproportionately healthier Latino
population in the United States, thus decreasing their mortality rates. Lastly, the cultural
buffering effect notes that first-generation immigrants maintain cultural ideologies and habits
from their homeland, thus delaying the acculturation process and slowing the erosion of the
individuals’ initial body advantage (Hao, Kim 2009 244).
After analyzing both sides of the argument, I have concluded that the first set of
arguments explaining that Latinos have higher mortality because of obesity-related diseases is a
more valid argument than the HP for several reasons. One criticism of the salmon-bias effect is
that it does not apply to all Latino sub-groups. For example Cubans can not return to their home
countries as easily as Mexicans and possibly other Latino populations for legal reasons
(Abraido-Lanza 1999, 1544). Also the salmon effect does not account for the differences
between US-born versus foreign-born Latinos. US-born Latinos were reported to have stronger
familial ties in the United States thus decreasing their odds of returning to their home countries.
They would not have a lower mortality than native born white Americans since their
obesity-related mortality risk would be higher; even if US born Latinos were healthier than their
white counterparts it would not be attributable to the salmon effect. Lastly the salmon effect does
not explain why in some cases there is a higher mortality rate among foreign-born Latino
immigrants in the United States compared to US-born Latinos due to factors such as decreased
access to stable and effective health care for foreign-born immigrants because of their legal
status in this country as well as lack of English language skills (Abraido-Lanza 1999, 1544).

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Whether mental, physical, emotional, or social stress, the immigrant experience has led to
negative modifications in diet and lifestyle which increase Latinos’ risk of obesity and
obesit-related diseases in the United States.
Independent of the effects of immigration and assimilation into American culture, Latino
and White culture have fundamentally different perceptions on what a healthy body image
should look like. This next section addresses these opposite ideologies and how they contribute
to Latino obesity
D. Food Stamps and Obesity: are there associations?
One argument in the literature argues that SNAP is successfully fulfilling its intended
role to provide nutrition assistance and thus lower obesity among low-income families who may
suffer from higher food insecurity. However there is another camp that emphasizes that the
weight gap between FSP and non-FSP is vanishing thus there is no difference in obesity between
the two groups. A third camp of thought stresses that SNAP perpetuates the obesity epidemic by
providing the monetary means for food insecure individuals to keep making unhealthy food
choices because the bottom line issues which include price and access to healthy food are not
addressed.
Negative Association between FSP and Obesity
Another camp of literature suggests that FSP lowers food insecurity. Multiple studies
have found that for every dollar of SNAP benefits spent, participants spend between $0.17 and
$0.47 more on food purchases which may minimize the probability of food insecurity (Hilmers
et. al. 2014, 44). In addition, Jones et al. found in their study that food insecure girls who

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participated in food assistance programs are at reduced risk of becoming obese compared to
eligible nonparticipating
households who are food insecure. This was studied by researching a sample population that was
determined by their income status. This study is not sufficient evidence for this claim because
they only researched girls at school age and did not consider boys or both genders jointly. Also,
factors such as years enrolled in the food assistance programs were not taken into account. In
addition, although the effects of SNAP,WIC, and NSLP participation were studied jointly,
specific findings to SNAP were not specified. Also this study looks at weighted average per
capita census data from 1996 which do not reflect current poverty thresholds ($7,995 vs.
$11,670) respectively. Therefore currently more people would qualify for SNAP compared to
1996, altering SNAP’s effect on obesity prevalence. Lastly, Jones et. al. do not reveal the
ethnicities of the sample studied which is of key importance because there is ample evidence
regarding ethnic differentiations of obesity.
No association between FSP and obesity
Ver Ploeg, an economist for the Food Assistance Branch of the USDA, and collaborators argue
that over time there is no direct correlation between food stamp participation and significant
weight gain. This article argues that non-FS participants are actually catching up to FS
participants in terms of weight gain. Both FS recipients and non-FS recipient Americans suffer
from a lower intake of fruits and vegetables than what is recommended. In addition, the authors
note that many studies on the relationship between FSP and obesity are faulty because they are
based only on a “single-period of cross-sectional data and [therefore] unable to explain dynamic
changes in both participation and weight gain” (Ver Ploeg et al, 23).

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Positive Association between FSP and Obesity
The current SNAP still operates under a nearly half-century old objective of increasing food
consumption in order to fight child hunger which was the issue of the last century in the United
States. However America’s main concern is no longer under-consumption (hunger), it is
over-consumption of EDNP (energy-dense, nutrient-poor) foods (You et al, 863; Besharov,
B01). In order for SNAP to be more effective in targeting the nutritional issues of today, the
socioeconomic, cultural, and environmental contexts of SNAP beneficiaries need to be explored
further.
A. Diet
Guthrie et. al. claim that FSP were less likely to follow the 2005 recommended Dietary
Guidelines for Americans and USDA’s MyPyramid. They report that the average FS
participant’s saturated fat and sodium intake was much higher while milks, fruits, and vegetable
were much lower than recommended. However this article’s findings were quite inconclusive.
They report that although there is research that suggests a positive association between FSP and
obesity, the most recent data shows a vanishing weight gap between FSP and non-FSP (Guthrie
et al 2007,2). First Guthrie et al note that cross-sectional studies suggesting a positive
correlation between the two variables is insufficient evidence to support causation since
temporality is not accounted for; obesity is a condition that takes years to develop and the effects
of SNAP on it can not be explained for in one snapshot in time. However the study concludes
that “ it is clear that not consuming enough fruits and vegetables is a major dietary problem for
Americans, especially for those who receive food stamps” (Guthrie et al 2007, 2).

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One consistent finding in the food assistance literature has been SNAP’s effect on
increasing sugar-sweetened beverages (SSB) consumption among FS recipients (Watt et. al
2013, 517). For psychological and other factors addressed later in the thesis, Hispanic mothers,
who are more likely to be on SNAP compared to whites, were more likely to feed their toddlers
SSB and fast food compared to white mothers (Watt 2013, 514;LCHC 2006, 2).
B. Economic factors
Given that SNAP beneficiaries are of lower SES, the price of food is one factor that
influences their nutritional, caloric intake and is thus a driver of obesity. Meat, dairy, and
products containing high fructose corn syrup (HFCS) are less expensive than fruits and
vegetables because the government subsidizes meat and dairy products as well as cash crops like
corn to engineer cheaper products like HFCS which are less nutrient dense. In fact, a “2003
survey found that 41% of Latinos [in California] agree that fruits and vegetables are too
expensive” (LCHC 2006, 4). Research has shown that subsidizing fruits and vegetables would
serve as an incentive for Latinos to buy these foods because they would be more affordable; this
is a step towards decreasing the obesity epidemic because fruits and vegetable consumption
would lower BMI (Guthrie et al 2007, 2-4; DeBono et al 2012, 748).
Although the 2008 Farm Bill has created a SNAP nutrition education program
(SNAP-ED) to promote “healthy eating habits among participants”, education programs alone
“do not bring consistent improvements in diet quality” (You et al., 853). The “moral hazard
problem” in which “recipients can spend their SNAP benefits on whatever food they wish
[usually resulting in major EDNP consumption] without SNAP managers knowing”, calls for

23. 23
economic incentive mechanisms or contracts to “align the incentives of individuals with SNAP’s
healthy eating goal (You et al. 2012, 854). Behavioral economics explain that restricting
purchase of EDNP foods bought with SNAP benefits and incentivizing beneficiaries into buying
healthier foods would reduce obesity trends. You et. al. analyzed two proposed modifications to
the SNAP program, the restricted contract and the incentive contract, designed to provide “more
financial incentives to those who want to eat more healthily (You et al., 863). According to
behavioral economics, these modified programs would be more effective than the current SNAP
because they would provide extra compensation needed to motivate desired behavior.
“Food Stamp cycle”
The Food Stamp Cycle is a theory that was proposed to explain the energy imbalance
among FS participants. The food stamp cycle explains food purchasing behavior following
receipt of food stamps: initial periods of binge eating followed by dramatic decrease in food
consumption. These cycles of binge eating followed by caloric deprivation “can alter metabolism
in ways that promote fat storage and accumulation” It is an evolutionary adaptation to the human
genetic code since the Paleolithic era where the human body stores more fat in times of famine.
Unfortunately, this gene has been passed down as it was beneficial during times of food
insecurity and increased chances of survival, according to social darwinian theory (DeBono et.
al, 752).
Hypothesis
After review of the difference camps of thought in the literature, I conclude that there is
not enough evidence in the literature to conclude that SNAP any direct correlation with obesity
among Latinos. As mentioned above, most studies showing a correlation between the two are

24. 24
based on inconclusive evidence from cross-sectional data that does not look at temporality. In
addition many researchers (Guthrie et. al. and Ver Ploeg et. al.) seem to agree that excessive
weight gain is an issue affecting the general population regardless of SES. However, indirectly I
do believe that SNAP plays a role in obesity risk. My literature review and tests both reinforce
my theory: SNAP, given a healthy food and physical environment, would reduce obesity and in
an environment without a healthy food and physical environment, would help increase obesity
among Latinos living in the United States. My theory fills the gap in the literature by addressing
obesity in Latino-Americans using an interdisciplinary theoretical approach from the fields of
environmental justice, behavioral economics, public health, and sociology.
E. Model
My model below demonstrates that there is a positive relationship between my
independent variable (socioeconomic status) and two of of my mediators (access to grocery
stores and access to healthy food) which in turn have negative relationships with obesity (my
dependent variable). However SES has a negative relationship with SNAP participation which in
turn moderates the influence of SES on obesity. The following image models what I will be
testing in my methodology section:
(+) food environment status↘
Socioeconomic status​ ↗→(+) physical environment status→(-) ​Obesity
↘ (-) SNAP participation(+/-)↗

25. 25
IV. Methodology
My Methodology
I chose against performing surveys for my methodology based on the unreliability of this
method for this particular research question. For example, one study that used the 2007 Adult
California Health Interview Survey, a telephone based questionnaire to study the association
between participation in food assistance programmes with obesity in California adults showed
that women participants tended to underreport their weight (Leung, Villamor 2010 650). In
addition, given the limited time allotted for a one semester thesis and my lack of statistical
analysis skills, I was not able to perform my own surveys, experiments, nor analyze historical
research showing temporal trends in BMI change to test my hypothesis.
I am going to operationalize the relationships between the following endogenous
variables: SES, food environment, physical environment, and obesity by analyzing two case
studies: Santa Clara County and San Joaquin County. Before I do this, there are some definitions
that will be need to be set beforehand. The term “Latino” is defined as “a person of Cuban,
Mexican, Puerto Rican, South or Central American, or other Spanish culture or origin regardless
of race” (Humes et al 2010, 2). SNAP participation requires having an income at or below 130%
of the federal poverty line (FNS 2013). In 2010, which is the year I chose to calculate the
percentage of FSP participants in my test, this number was $11,139/capita. Socioeconomic status
is a composite measure that incorporates three indicators: income, level of education, and work
status (CDC, 2014). I also define a food environment status to be a composite measure taking
into account the number of convenience stores, grocery stores, and farmers’ markets accepting
SNAP. I define physical environment status to be the number of recreational facilities/1,000

26. 26
people. Unfortunately, data on how many recreational facilities a county needs to be considered
healthy was not accessible so I will operationalize by comparing the numbers in both counties to
determine which one has a healthier physical environment. I define my dependent variable
(obesity) as having at least a Body Mass Index of 30 kg/m​2​
(CDC, 2014).
I have chosen to keep these variables (non-Latinos in Santa Clara and San Joaquin
County; citizenship status; and genetic predisposition) exogenous for several reasons. Many
studies in the literature have already proven a relationship between the effects of SNAP
participation on obesity among Americans as a whole. Therefore since there is very little
literature on the differences of this relationship among various ethnicities, I have chosen to focus
on Latinos because they make up the largest ethnic group in the United States and also in
California. Also I exclude citizenship status because I am assuming that SNAP recipients are
citizens based on the eligibility requirements. Lastly the research articles on obesity among
Latinos report almost unanimously a great genetic susceptibility to becoming obese (LCHC, 4)
compared to other ethnicities; therefore, I am assuming that this is true and will not be testing
that.
My process of county selection began by starting at the USDA’s Economic Research
Service website and searching for the Food Environment Atlas Map’s Data Access and
Documentation Downloads tab to select two sets of counties that both had relatively high SNAP
participation; one set had the top three obesity rates in California while the second set had the
bottom three obesity rates in the state. I selected these two sets of counties (six counties total) by
performing multiple functions on the excel sheet to filter through and select for data on FSP and
obesity rates in 2010. This excel sheet was quite comprehensive because it contained multiple

27. 27
important attributes that contribute to status of the food and physical environments for each
county in the United States . Some of these attributes per county included the percentage of the
poor population participating in FS, the percent of Latinos residing in the county, number of
grocery stores, number of Farmers Markets accepting SNAP benefits, and much more. In the
first set I chose Santa Clara, San Francisco, and San Mateo County. The second set included
Fresno, San Joaquin, and San Bernardino County. I chose these two sets of counties because
they had higher SNAP participation compared to many other counties in California such as
Alameda and Contra Costa County which I initially was going to use as my case studies for
convenience purposes but decided against it based on low participation rates. I chose high SNAP
participation rate selection for both sets of case studies initially in order to measure FSP’s true
effect on obesity; having a lower FSP would have meant that there would have been a higher
chance of other confounding factors influencing the obesity rates. Secondly, I chose two sets of
urban, high Latino density counties because social services such as SNAP are more likely to
serve ethnic minorities who typically are of lower SES than Caucasians in a metropolitan area
which contain governmental infrastructure in place to carry out social services. After looking at
these six counties I chose Santa Clara as my first case study as it had a relatively high FSP rate
but low rates of obesity and San Joaquin because of its high FSP rate and high obesity rate. My
goal in this test was to see if SNAP, food environment, and physical environment influenced
obesity rates in these two counties which have very similar sociocultural, economic, physical,
and food environments. I choose to just look at adult obesity rates because children weight gain
is much more variable than adults because of constant growth spurts relative to adults. I used the
California Food Policy Advocates website to find FI rates for both counties in 2010. In order to

28. 28
find the percent of Latinos residing in each county, I averaged two percentages that separated
women and men Latino prevalence for 2010 based on data provided on the SNAP Data System
excel sheet.
The second two graphs were screenshotted from the California Center for Public Health
Advocacy’s website. They represent the distribution of retail food outlets in each county. Based
on the information provided, an RFEI or (Retail Food Environment Index) can be calculated for
each for each county which is the simple ratio of the sum of the number of fast food restaurants +
convenience stores over the sum of the number of supermarkets, produce stores, and farmers
markets. However since I am looking at locations that accept SNAP I ignore the number of fast
food restaurants since prepared foods of any kind not be bought with SNAP benefits.
B. Comparative Case Study: Santa Clara and San Joaquin County
Findings
Below is one table and two graphs of my findings for both counties:
Santa Clara San Joaquin
● Tot.Pop​: ~1.8 Ma (1,781,658)
● %Pov:​ 10%
● %FI*​: 33.5%
● % Latinos​: 26.9%
● Tot.Pop​: ~0.7 Ma (685,308)
● %Pov: ​16%
● %FI*​: 30.2%
● % Latinos​: 39.7%
● Obesity Rate: 25.6% ● Obesity Rate: 37.5%

29. 29
● %FSP/elig. population: 55%
● Total elig: ~124 K
● %FSP/elig. population: 83%
● Total elig: ~123 K
**Farmers’ markets (FM)/1 K pop: 10
****% FM accepting SNAP: ~42%
***Grocery stores/1 K people: 190
***Convenience stores/1K people:180
LI and LA: 1.27%
** Farmers’ markets (FM)/1 K pop:
10
****% FM accepting SNAP: 47%
***Grocery stores/1 K people: 240
***Convenience stores/1 K
people:230
LI and LA: 3.59%
***#Rec. facilities/1000 people: 120 ***#Rec. facilities/1000 people: 60
*Food Insecurity ** 2009 data ***2011 data ****2013 data

30. 30
Results
The table above implies several interesting points and clarifies where further research is
needed. For one, FI rates are basically the same between the two counties. I am postulating the
small differences between them may not be statistically significant. T​his supports my theory
because given similar insecurity, obesity is significantly different; therefore, the environment
appears to be a stronger influence on obesity rates.​.
Also I noted that Santa Clara and San Joaquin counties seem to have almost the same
amount of SNAP eligible individuals. Being that San Joaquin has a smaller population than
Santa Clara and that there is a ​higher proportion of those eligible receiving SNAP benefits, the
SNAP population is more concentrated in San Joaquin County. This higher concentration of
poverty and SNAP use, given a less healthy food and physical environment as San Joaquin

31. 31
shows, contributes to obesity increases which agrees with my theory.
One data point in the table that negates my theory is the number of grocery stores/1000
people in both counties. According to the USDA’s Food Environment Atlas, there were more
grocery stores per 1000 people in San Joaquin than in Santa Clara county which is contrary to
my expectations, given the other data presented which suggests that San Joaquin’s food
environment is unhealthier than Santa Clara’s. What warrants further research is who has access
to the grocery stores that are in each of these two counties; where are the counties located in
proximity to the Latinos who are on SNAP vs. non-SNAP beneficiaries.? Based on the Low
Income and Low Access index which is a composite measure that combines socioeconomic
status and proximity to the nearest grocery store, San Joaquin has a higher index meaning its
residents have less access to grocery stores which sell fresh produce and whole grains needed to
reduce obesity risk. Therefore, I postulate that perhaps most of the grocery stores in San Joaquin
county are located in cities or regions with lower Latino residence where the concentration of
SNAP recipients is lower.
Also a notable finding in my research shows the stark difference in th​e number of
recreational facilities between the two counties. Being that Santa Clara County has double the
amount of recreational facilities than does San Joaquin County seem to show that the overall
population of Santa Clara county may benefit from the larger number of rec facilities since they
have a lower obesity rate. However, more research is needed to investigate if if these facilities
are being used by Latino FS and eligible non-FS recipients in both counties.The data thus far
does not specify the demographics of the people using them. This data would better support my
claim because it would show if and how SNAP participation affects the correlation between

32. 32
physical environment and obesity among a low income Latino population.
Based on my findings I can conclude that a potential reasoning for San Joaquin’s higher
obesity rate is due to their higher FSP, more convenience stores per 1000 people, higher LI and
LA percentage (food desert metric), fewer recreational facilities per 1000 people, and a higher
poverty rate compared to Santa Clara.
Summary​:
The data does not support my hypothesis directly because there is insufficient data to
distinguish Latino SNAP recipients from other ethnic participants. Based on the high prevalence
of Latinos living in my two case counties, I postulate that the same effect occurred for them as
well.
V. Conclusion
For many years, minorities in this country have been victim to social and institutional
prejudices that shape every aspect of their lives, including their physical well being. In deciding
my research topic and scope for this paper, I realized that so much of human health is outside of
our individual control. From other courses that I have taken here at UC Berkeley in the
disciplines of Public Health, Medical Anthropology, and Global Poverty, a common denominator
has been revealed to me: the external social, cultural, political, physical, and environmental
context that one is in plays an important, if not, the most important role in influencing the
internal biochemical processes that constitute one’s health. For this reason I decided to research
how a political institutional, the US government, use their agency to make changes in the health

33. 33
status of their citizens. SNAP is one such way that the government may believe that their
altruistic benefit the nutritional status of their recipients but it isn’t until someone researches the
complex factors that affect obesity that positive changes in our policies can be made. I decided
to concentrate on the effects that this program has had on the Latino population because, being
Latina myself, I am interested to help my own culture. In addition, the Latino community is a
fast growing community which, in not too many years, will actually be the majority of our state’s
population given current growth trends. There is an economic incentive for the government to
fund research, policies, and other effective interventions to maximize the wellbeing of the fastest
growing minority in this country. They are the reason why California’s agriculture industry has
been such a huge world-reknown success and they fill the nation’s low wage jobs that I am sure
many “native” Americans would not be willing to do.
Give the complexity of the obesity epidemic in the United States, I tested my hypothesis
taking into account different attributes and indices to get a better sense of why obesity is
affecting Latinos more so than other races. My test proved that the physical environment, food
environment, and SNAP participation all affect obesity. My test failed to prove whether this was
specific for Latinos or SNAP recipients in general.
After looking through governmental websites, peer-reviewed journals and books, as well
as interviewing two professionals in the fields of Nutrition and Medical Sociology, I was able to
research my hypothesis and come up with the following main points:
1. Obesity was less prevalent in first generation US Latinos participating in SNAP
because these participants still look for those healthier foods that they were accustomed to back
home: fresh fruits and vegetables, beans, rice, etc. The later generations have assimilated more

34. 34
into the US culture which, unfortunately, includes eating more of our unhealthy fast foods and
junk foods.
2. Easier access to healthier food retails who accept SNAP benefits such as farmers’
markets and grocery stores had a lowers obesity among SNAP participants.
Strengths and Limitations
Of course as with any study, there are limitations to the accuracy of the findings. Due to
the lack of time, I was unable to study more counties that would have provided a more
comprehensive conclusion. I was unable to find out supporting information as to why Santa
Clara County had higher food insecurity than San Joaquin County. Despite ample research on
the effects of SNAP on obesity, there was limited research on the Latino community in particular
which was why I decided to focus on this ethnic group. In addition, health interview surveys
have indicated that women have a propensity to underreport their weight which skews BMI data
needed to conclude weight status.
Recommendations
After researching this topic, I have several recommendations on how SNAP could be
improved. I would highly recommend more stringent guidelines on what kinds of food could be
purchased with SNAP benefits. It already does not allow the purchase of liquor, cigarettes, or
prepared food. I would expand the restrictions to include processed food, soft drinks, and
desserts. In addition, I would make participation in SNAP-ED classes on nutrition, that
emphasize the health risks of obesity, mandatory before received these benefits. These programs

35. 35
should be made available in English, Spanish, and other dominant local languages (Mandarin,
Vietnamese, etc.). SNAP-ED cooking classes should be made available to instruct participants
on how to cook healthier and be culturally sensitive and tailored to the tastes of each ethnicity.
For example, during an interview with my Nutrition professor, she made the observation that
when she tried to get her Asian clients to consume brown rice instead of white rice; these clients
went away appalled, saying that brown rice was “disgusting”. White rice has been a basic staple
for Asians for centuries. In order to be more effective, SNAP-ED coordinators need to include
the different fundamental ingredients of the various ethnic cuisines of their clients.
Some suggestions for further research include looking into how SNAP affects Latinos in
particular- looking into subgroups of those who have lived here a long time versus recent
immigrants. Subsidies on the purchase of fresh fruits and vegetables would be a good way to
lower the cost of healthier food options and provide an incentive for SNAP participants to
purchase them. We owe it to the taxpayers who support this government program to make it as
effective as possible. In the long run, with a healthier population, health care costs will diminish
for everyone.

36. 36
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