GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 1 Gender Inequality in Food Insecurity: An Examination of Single Adults
without Children in the United States
By
Megan Osborne
MPP Essay
Submitted to:
Oregon State University
In partial fulfillment of
The requirement for the degree of
Master of Public Policy
Presented November 16th, 2012
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 2 Master of Public Policy essay of Megan Osborne presented on November 16th, 2012
Approved:
_____________________________________________________________________________________ Mark Edwards, representing Sociology
_____________________________________________________________________________________ Sarah Henderson, representing Political Science
_____________________________________________________________________________________ Alison Johnston, representing Political Science
I understand that my essay will become part of the permanent collection of Oregon State
University Libraries. My signature below authorizes release of my thesis to any upon request.
Megan Osborne, Author
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 3 Acknowledgements
I would like to sincerely thank Mark Edwards, Sarah Henderson and Alison Johnston for
their support and feedback over the course of this project. Special thanks to Mark Edwards for
chairing this committee and for his continued interest in and enthusiasm for this project from its
conception to completion. I would also like to thank my friends and family for their everlasting
love, support, and encouragement throughout my time in this program, and beyond; I couldn’t
have done it without you.
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 4 Abstract
Using Current Population Survey data from 2008, 2009 and 2010 this paper explores the extent
to which there is gender inequality in food insecurity among employed single adults without
children. Gender inequality in the U.S. is well documented in a wide variety of spheres from the
home to the world economy and is built and reinforced through the institutions of marriage and
the family, work and the economy, politics, religion and many other cultural productions (Lorber
2010). This paper focuses on one kind of gender inequality of material hardship – food insecurity
– examining its links to unequal and segregated economic opportunity. This study is unique as it
examines how, when controlling for the influences of some of these structures ( e.g., marriage,
and the dynamics of family with children) there remains evidence of gender inequality in food
insecurity. Using ordinal logistic regression, results indicate a persistent presence of gender
inequality in food insecurity with women showing consistently higher likelihoods of being food
insecure when compared to men. This study both contributes to and expands on the existing
literature on both gender inequality and food insecurity, linking occupational sex segregation and
a gender income gap to higher likelihoods of food insecurity among women.
Keywords: food insecurity, gender inequality, occupational sex segregation, gender wage gap
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
Table of Contents
List of Tables and Figures…………………………………………………………….……..4
Introduction………………………………………………...…………………………………….…5
Literature Review………………………………………………………………………………..….7
Gender Inequality in Economic Opportunity and Achievement……………………………..7
Gender Inequality in Food Insecurity……………………………………………………….13
Central Variables for Understanding Gender Inequality in Food Insecurity………………….16
Expected Results……………………………………………………………………………..……..18
Data and Methods………………………………………………………………………………….20
Data…………………………………………………………………...…………………….20
Methods………………………………………………………………………………....…..24
Results……………………………………………………………………………………………….27
Descriptive and Bivariate Statistics…………………………………………………………27
Multivariate Ordinal Logistic Regression Results…………………………….…………….32
Interpretation of Results…………………………………………………………………………...39
Conclusions…………………………………………………………………..……………………..41
Appendices…………………………………………………………………...……………………..43
References……………………………………………………………………………….………….51
| 5 GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 6 List of Tables and Figures
Table 1: Food Security Status Distribution of Men and Women
Table 2: Predicted Likelihood of Food Security Status
Table 3.1: Predicted Likelihood of Food Security Status by Independent Variable Categories, Full Sample
Table3.2: Predicted Likelihood of Food Security Status by Occupation (income uncontrolled), Full
Sample
Table 4: Distribution of Men and Women among Independent Variable Categories
Table 5: Influences on the Likelihood of Food Insecurity
Table 6: Predicted Likelihood of Food Security Status for Men and Women by Income Level
Table 7: Predicted Likelihood of Food Security Status for Men and Women by Educational Attainment
Figure 1: Probability of Food Insecurity for Men and Women by Occupation
Table 8: Predicted Likelihood of Food Security Status for Men and Women by Occupation
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 7 Introduction
In spite of dramatic gains by women over the last several decades there remain substantial
differences in men’s and women’s economic opportunities. Some of the most well-known and
frequently cited gender inequalities in the workforce include occupational sex segregation and
the gender wage gap (Bielby & Baron 1986; Marini 1990; Reskin 1993; Naff 1994; Gronau
1998; Marini 1990; Tam 1997; England et al 2000; England 2005; Institute for Women’s Policy
Research 2011; American Association of University Women 2012), as well as the “glass ceiling”
(Marini 1990; Naff 1994; Federal Glass Ceiling Commission Report 1995; Blau&Kahn 2000;
Cotter et al 2001; Eagly&Karau 2002; Lorber p. 34 2011; Isaac et al 2012). Evidence of the
gender gap in wages appears in computations of women’s earnings as a percentage of men’s, or
in comparisons of average weekly earnings between the sexes. The U.S. Census Bureau’s
American Community Survey shows that in 2010 median earnings for women were seventyseven percent of men’s; $36,931 compared to $47,715 (DeNavas-Walt et al, 2011) 1. With
women now making up 47% of the 139 million person U.S. workforce (U.S. Department of
Labor; Employment and Earnings 2011) the implications for such a gap are many.
For example, 49.9% of unmarried women (including women who were never married,
divorced, separated and widowed) and 57.4% of married women (spouse present) were
employed in the civilian workforce in 2010 (Bureau of Labor Statistics 2011), providing sole or
supplemental income for themselves and their families. Although women’s participation in the
labor force has increased dramatically over the last several decades, they are still not afforded
fully equal opportunity in the workforce.
1
These computations are based solely on (hourly/weekly) earnings, not controlling for education and other human capital factors. The “actual” wage gap has been shown to be smaller when controlling for various human capital factors (Bielby & Baron 1986; Marini 1990; Reskin 1993; Naff 1994; Gronau 1998; Marini 1990; Tam 1997; England al 2000; England 2005). Further discussion presented on pg.7 GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 8 One potential consequence of gender inequality in economic opportunity and
achievement is gender inequality in material hardship. Material hardship is a concept that goes
beyond basic income to poverty, addressing overall well-being of individuals and their families
by focusing on the consumption of basic goods such as food, housing, and medical care (Beverly
2001). One common measure of material hardship is food insecurity. Food insecurity is defined
as the absence of a household’s “assured access of all people to enough food for a healthy and
active life” (Bartfeld and Duifon 2005). Food insecurity is closely tied to financial hardship (e.g.
poverty, unemployment, underemployment, etc.) (Taponga et al. 2004; LeBlanc et al 2005;
Edwards et al. 2006; Guo 2010; Coleman-Jenson et al 2011). Thus, inequality in economic
opportunity, such as evidenced by the presence of a gender wage gap, may contribute directly to
gender inequality in material hardship and to food insecurity specifically. This study examines
the degree to which gender inequality in food insecurity is present within the broader context of
gender inequality in the workforce by focusing only on single adults without children.
This oft-ignored group of Americans offers a unique opportunity to examine gender
inequity in food insecurity because they lack some of the important characteristics that seem to
make other households vulnerable. By only looking at single adults without children, this study
eliminates one of the major variables that has been cited to cause workforce inequalities; the
responsibility of women for childbearing. The decisions by employers that affect employment
opportunity for men and women may still exist for this population based on the (mostly truthful)
stereotype that women of a certain age are likely to bear children and thus need at least some
time out of the workforce to care for the family. However, by eliminating parents from the
sample, we minimize some of the “self-selection” or supply side decisions that women may
make with regards to employment choices. The effect of economic inequalities may still be
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 9 present in the work force of this sample, as they all exist in the larger social and economic
context that creates these inequalities. However, by examining single people without dependents
we can control for some of the known causes of occupational segregation. In an effort to gauge
whether inequality exists between men and women in this sample, food security status, a
common measure of material hardship and more dynamic measure than income, was chosen as
the dependent variable in this study.
Literature Review
Gender Inequality in Economic Opportunity and Achievement
The Institute for Women’s Policy Research (IWPR) and the American Association of University
Women (AAUW) both outline the contemporary situation of the gender wage gap and
occupational segregation (Institute for Women’s Policy Research 2011; American Association of
University Women 2012). They document occupational sex segregation with over 40% of
women employed in traditionally “female” occupations such as social work, nursing, and
teaching. Meanwhile, only 5% of men are in such jobs. Moreover, while 44% of men in the
workforce were employed in typically “male” jobs such as computer programming, engineering
and fire fighting; only 6% of women were in these jobs. Current labor statistics indicate that
women are more likely to be in professional, office and administrative support, sales and service
occupations while men are more likely to be employed in construction, maintenance, production,
and transportation occupations (U.S. Department of Labor; Employment and Earnings 2011).
This distribution of men and women in different occupations provides evidence of persisting
occupational sex segregation.
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 10 Further, the most recent data indicate that women’s median earnings are less than men’s
in nearly every occupation, regardless of whether they work in occupations dominated by men,
dominated by women, or in occupations that are relatively mixed between men and women
(Institute for Women’s Policy Research 2011; Kalantari 2012). For example, the top ten highest
paid occupations (with the highest median weekly earnings for full-time workers) are three times
more likely to be held by men than women, but the ten worst paid occupations with the lowest
median weekly earnings are twice as likely to be held by women. Evidence from these statistics
suggest that the gender earnings gap is as much due to pay differences within occupations as it is
due to pay differences between occupations, with women being disadvantaged in either scenario
(Institute for Women’s Policy Research, 2011). There are several theories that aim to explain
why men and women enter different occupations and why within those occupations they are
often paid unequal wages.
Two of the most prominent theories that aim to address the occupational segregation of
men and women in the workforce and the ensuing difference in compensation are the
devaluation hypothesis and the specialized human capital hypothesis. The devaluation
hypothesis stems from a sociological explanation of the segregation of men and women’s work
based on cultural transmissions that create differences in preferences, interest and aspiration
between males and females (England 2005). Rooted in theories of social construction and the
influence of patriarchy, the devaluation of women’s work can be seen as an outcome of Western
society’s construction of gender in which the characteristics associated with the male gender are
dominant and preferred over those of women (Marini 1990; Eagly&Karau 2002; Lorber 2011 pg.
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 11 245; Kalantari 2012)2. Through the social process of gender construction, women are influenced
to express traits such as affection, sympathy and kindness while men are encouraged to express
traits such as assertiveness, independence and competitiveness (Eagly&Karau 2002; Isaac et al
2012). These differences are then expressed by individual’s “doing gender” by acting out a role
to fit an ideal or image of one’s sex (West and Zimmeramn 1987; England 2005; Kalantari
2012). The traits typically ascribed to men are also those typically used to gain access to
positions of power and privilege, thus the use of these gender stereotypes further advances men
into more desirable positions in the workforce (Marini 1990).
Through the social process of gender differentiation these traits are then transferred into
the workforce, segregating men and women into different types of work. This duality of valuing
male traits over female’s, as well as valuing male’s work (typically associated with working
outside the home to make money) over women’s work (typically associated with the traditional
roles of unpaid housework and childcare) have the effect of sorting men and women into
different occupations, and within occupations, into differing levels of responsibility and
corresponding pay (Lorber 2011, Kalantari 2012). The devaluation hypothesis is thus rooted in
this understanding that due to a gender bias in popular culture, women’s jobs are led to be seen
to be worth less pay, i.e. a literal devaluation of women’s work. This then affects both men and
women. Regardless of what one’s gender is, if they work in a typically “female” occupation, the
compensation for such work will be less.
On the other hand, the specialized human capital hypothesis derives from economic
theory, claiming that jobs that require more human capital and specialized training pay more, and
women, because of the traditional responsibility of childrearing, are less likely to enter such jobs
2
There is a wealth of literature on the biological and social forces that differentiate men and women. It is beyond the scope of this paper to attempt a full summarization of these theories. For suggested reading on social gender construction, see Appendix A: “Suggested Reading”. GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 12 and have less overall job experience which sifts them into occupations that have less specialized
training and thus less compensation. Further, the specialized human capital hypothesis
rationalizes that because many women in the workforce plan for breaks in employment for
childrearing, they choose jobs that optimize lifetime earnings by finding jobs that have low
depreciation of human capital during years away from the job, thus a lower drop in wage when
they return to the workforce (Tam 1997)3. Although the specialized human capital hypothesis has
many critics (e.g. England 1982; England et al 2000) and could be argued to be out of fashion,
there are scholars who provide evidence for the cause of a gender wage gap and occupational
segregation to be based on rational choice supply and demand economics4 (Becker 1985; Tam
1997).
Studies attempting to explain the gender wage gap, occupational segregation, and limited
upward occupational mobility for women have struggled to find a complete model or
measurement tool to account for this inequality (Reskin 1993; Tam 1997; Preston 1999, Blau and
Kahn 2000; Eagly and Karau 2002; Baunach 2002; Shaumen 2006). Controlling for various
human capital, work effort, and family characteristics have partially explained the wage gap,
focusing on the inclusion of college major, occupation, hours worked, educational attainment,
marital status and number of children (Bielby & Baron 1986; Marini 1990; Reskin 1993; Naff
1994; Gronau 1998; Marini 1990; Tam 1997; England et al 2000; England 2005). However,
there has yet to be a full explanation for why women are still not compensated at an equal level
to men (Sorenson 1990; Wellington 1994; Blau&Kahn 2006). As a result, many researchers have
concluded that not all of the differences in occupation, pay, and promotion ability can be
3
Summarized by Reskin 1993; England et al 2000; England 2005. The use of this logic is applied to both the employer (demand) and employee (supply) side of employment; Women choose jobs with more flexibility and less pay and employers employ “statistical discrimination” by seeking men or non-­‐parent females for more permanent higher paying jobs. (Summarized by Preston 1999 and England 2005). 4
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 13 explained and have thus concluded that these may also be due to overt gender discrimination
(Bielby & Baron 1986; Reskin 1993; Naff 1994; Council of Economic Advisors 1998; Blau &
Kahn 2000; Baunach 2002; England 2005; Correll et al 2007; Kalantari 2012). Others explain
the differences in men’s and women’s wages by the gendered segregation of jobs and the effects
of women’s responsibility for childrearing.5 There is evidence to suggest that occupational
segregation is caused by both economic and social forces working in tandem to create our
current condition. Tam (1997) and England et.al. (2000) summarize the relative merits of these
two competing explanations of gender inequality in the public sphere.
In addition to evidence of occupational sex segregation, previous research has also found
evidence of a “glass ceiling” effect for women. The glass ceiling is often described as an
artificial barrier to the advancement of women and minorities and refers specifically to labor
market discrimination. In practice, the measure of a glass ceiling is the residual difference due to
race or gender after controlling for education, experience, abilities, motivation and other job
related characteristics (Cotter et al 2001). The glass ceiling is usually observed in the upper most
rungs of the corporate ladder, preventing women from entering higher paid and more respected
positions of upper management, leadership and company control (Marini 1990; Naff 1994;
Federal Glass Ceiling Commission Report 1995; Blau&Kahn 2000; Cotter et al 2001;
Eagly&Karau 2002; Lorber 2011 pg. 24; Isaac et al 2012). This can be seen, for example, with
regards to the characteristic of leadership ability (a highly sought after character trait for those in
upper management and control positions). Leadership has typically been defined as a “male
characteristic” (Cotter et al 2001; Isaac et al 2012) leading the bias to favor men for positions of
5
Researchers attempting to explain these inequalities through the gendered segregation of jobs and women’s traditional responsibility for childrearing do not reject overt gender discrimination as a cause for inequality but have simply tried to go beyond that explanation to find the root cause for this inequity as all of those cited as acknowledging the potential of overt gender discrimination have also looked to the root causes for this occurrence ((Bielby & Baron 1986; Reskin 1993; Naff 1994; Council of Economic Advisors 1998; Blau & Kahn 2000; Baunach 2002; England 2005; Correll et al 2007; Kalantari 2012). GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 14 power and leadership and thus creating an artificial barrier for women into these positions based
on existing gender roles and stereotypes. However, regardless of the true mechanism that causes
these inequalities, most scholars working in this area agree that occupational segregation and the
gender wage gap are inexorably linked (Bielby&Baron 1986; Marini 1990; Preston 1999;
Kahn&Blau 2000; Baunach 2002; England 2005; Institute for Women’s Policy Research 2011;
Kalantari 2012; American Association of University Women 2012).
Existing literature linking these gender inequalities in the workforce to specific
inequalities in material hardship is scarce. However, following on the logic that inequality will
breed more inequality, it is important to look at how these gendered workforce inequalities may
lead to inequalities in other areas. For example, as with other forms of gender inequality, men
and women in the US have different levels of food insecurity (Coleman-Jenson et al 2011,
pg.11).
Gender Inequality in Food Insecurity
Since 1995 the U.S. Department of Agriculture (USDA) has collected information on food
spending, food access and adequacy, and sources of food assistance for the U.S. population. The
U.S. Household Food Security Survey (US-HFSS) attempts to understand the experiences of
households with food insecurity, not just the economic conditions that are likely to contribute to
it (Webb et al. 2006). Food insecurity can be experienced in spells or as a chronic condition over
the course of a year and is characterized by disrupted food intake patterns among one or more
members of a household due to a lack of money and other resources for food (Coleman-Jenson et
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 15 al 2010). Nationally, in 2010, 14.5 percent of US households experienced some degree of food
insecurity throughout the year (Coleman-Jenson et al 2011)6.
A number of factors affect the likelihood of an individual or household facing food
insecurity. These include income, unemployment (short versus prolonged), housing tenure
(renter/home owner), marital status, parental status and education level (Coleman-Jenson et al.
2010). Prior research has found several characteristics that identify “at risk” groups of people for
experiencing food insecurity. These populations include households with incomes near or below
the federal poverty level, households with children headed by a single parent, and Black and
Hispanic households (Rose et al. 1998; Taponga et al. 2004; Bartfeld and Duifon 2005; LeBlanc
et al 2005; Edwards et al. 2006; Coleman-Jenson et al 2011). Additional research has outlined a
number of other individual food insecurity indicators including, low education, lack of
homeownership, lack of savings, recent changes in income, unemployment, poor health and
social isolation (Rose et al. 1998; Taponga et al. 2004; Bartfeld and Duifon 2005; LeBlanc et al
2005; Edwards et al. 2006).
A majority of the existing literature on food insecurity and hunger focuses on households
comprised of families with children. When examining processes within these kinds of
households, gender plays a part in the experiences of families and the coping mechanisms of
families facing food insecurity. For example, within the household, men and women typically
hold different roles. Hanson et al. (2007) find that women, in their role as household food
manager, are tied uniquely to food insecurity-dilemmas. Hanson et al. (2007) describe how
women sometimes deprive themselves to feed others in the family, especially children. Further,
6
Because this study is including models run with combined 2008, 2009 and 2010 survey data, it is important to note that overall trends in food security rates at the national level have not seen a dramatic change over the years in question. For example in 2009, 14.7% of US households experienced some degree of food insecurity, up from 14.6% in 2008 (Nord et al 2009, Nord et al 2010). GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 16 women often establish food intake patterns that alternate between restriction in times of scarcity
and binging when food is plentiful. This technique, also referred to as “triage”, involves children
and men eating before women (Hanson et al. 2007; Lent et al. 2009; Mammen et al. 2009). This
disrupted eating pattern has often led to weight gain and obesity in women (Lent et al. 2009).
These tendencies provide evidence that women’s responses to food insecurity may differ from
men’s both behaviorally and physically (Townsend et al. 2001).
When looking at only single parent households, gender remains important to
understanding food security status. For example, single mothers have historically, and
consistently, been in one of the highest at risk categories for food insecurity. In 2010, 35% of
U.S. households headed by single females experienced some degree of food insecurity,
compared to 25.4 % of those headed by single males (Coleman-Jenson et al 2011). Because of
the complex set of processes that lead mothers to being single mothers, and that lead married
mothers to spend less time in the labor force, there is good reason to examine the link between
gender and food insecurity among single adults without children.
Single adults without children have lower rates of food insecurity than other adults, but
they are certainly not immune. In 2010 approximately 11.7% of this group experienced food
insecurity (Coleman-Jenson et al 2011). By examining this population we can control for some
of the known causes of occupational segregation, as well as some of the individual level
indicators of food insecurity.
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 17 The association between gender and food security status will be measured as:
Pr(yi = 1, 2, or 3│xi) = Λ [β1(Genderi) + ΣkβkXk,i + εi]
where Λ is the ordinal logit estimator: eβ/(1+eβ). Genderi is the gender of person i, ΣkβkXk,i is a
vector of controls influencing food security, as outlined below, and εi is the stochastic error term.
Based on existing literature, this study uses several additional controls to gauge gender inequality
in food insecurity; income, education, age and occupation.
Central Variables for Understanding Gender Inequality in Food Insecurity
Food insecurity is strongly associated with income (LeBlanc et al 2005,Guo 2010; ColemanJenson et al 2011). In 2010, 40.2 percent of households below the federal poverty line
experienced some degree of food insecurity, while only 7.4% of households with incomes above
185% of the federal poverty line experienced some degree of food insecurity (Coleman-Jenson et
al 2011). Additionally, as research points to a persistent gender wage gap, the percentage of men
and women with incomes at or below the federal poverty line may affect the degree to which
each sex is at risk for food insecurity. For example, the poverty rate for women in 2010 was
14.5%, 3.3 percentage points higher than it was for men (11.2%) (National Women’s Law Center
2011).
Income and education are also positively associated (Day and Newberger 2002; Shaumen
2007; Bobbit-Zeher 2007; American Association of University Women 2012), while education
and food insecurity are negatively associated (Rose et al 1998, Coleman-Jenson et al 2011).
Individuals with a high school degree or higher compared to those without are less likely to be
food insecure. As educational attainment increases, on average, risk of food insecurity decreases.
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 18 However, evidence suggests that although education is effective for increasing overall lifetime
earnings and human capital, it is not effective in leveling the pay gap between men and women
(Shaumen 2007; Bobbit-Zeher 2007; American Association of University Women 2012);
educational attainment has a disproportionate effect on men and women providing advantages to
both, but not to equal degrees.
Related to both income and education, employment status is also an essential component
of income and has shown to have a significant effect on the likelihood of food insecurity. Those
with intermittent, part time, or no employment are more likely than those who have steady
employment to experience food insecurity (LeBlanc et al 2005). This study focuses only on
employed workers so that occupation and earnings may be included, rather than confounding the
analysis with potentially different rates of unemployment between men and women.
Although there is less explicit research on the relationship between age and food
insecurity, two theories that support the importance of age in the explanation of income level
variation and material hardship for people as they progress through life are the affluencetrajectory hypothesis and the adequacy-gradient hypothesis. The affluence-trajectory hypothesis
suggests that economic hardship declines in successively older age groups up to late middle age
but then increases, while the adequacy-gradient hypothesis is supported by research finding that
economic hardship progressively declines for successively older age groups (Mirowsky and Ross
1999). With regards to food security specifically, traditionally, elderly households have had
lower than average rates of food insecurity, however there is a portion of this population that is
vulnerable to hunger if they are on fixed incomes living at or below the poverty line (Nord
2002,Coleman-Jenson 2011) . Age is an important variable in this study because the gender
wage gap has been shown to increase with age; differences in the wages of younger men and
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 19 women are significantly smaller than the difference in wages among older men and women
(American Association of University Women 2012). Because this study only includes employed
individuals, the sample is limited to those 18-65 years old.
Expected Results
Because of the pervasive and consistent evidence of gender inequality in the workplace, there is
good reason to believe that (a) there will be an initially observed gender difference in food
insecurity among single adults without children and (b) this difference should be at least partially
explained by workplace opportunity and achievement variables. Controlling for income and
occupational attainment should explain the anticipated gender difference in food insecurity
among non-parents. Controls for education and age will further clarify the degree to which
gender remains associated with food insecurity. However, despite the fact that most literature is
focused on gender inequality within the family context, there is reason to believe that gender
discrimination against women in the workforce will still be a barrier to achievement for women
without children. The devaluation hypothesis suggests that employers make decisions about
employees and potential employees based on women’s childbearing and rearing ability and
potential. Even women without children may face the same potential “effect” or stereotype as
women who do have children (or plan to have them in the future) as this method of segregation
and discrimination is now well build into our socio-economic system.
Additionally, consistent with existing literature, it is expected that income, education, and
age will all have a negative effect on an individual’s likelihood to experience food insecurity.
Based on what is known about the existence and effect of occupational sex segregation, it is also
expected that occupation will be significant in this model; individuals in typically higher paying
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 20 occupations will be less likely to experience food insecurity than those in lower paying minimum
wage sectors. There is also potential for occupation to have a different effect on men and
women’s likelihood of experiencing food insecurity if in fact women are paid less for the same
occupation as men.
Data and Methods
Data
The data used in this study was taken from the 2008, 2009 and 2010 U.S. Household Food
Security Survey(US-HFFS), part of the Bureau of Labor Statistic’s annual Current Population
Survey. The US-HFFS specifically measures food security in the United States and is
administered via a telephone survey every December to approximately 50,000 US households.
The initial food security survey consists of ten questions and asks one “reference person” (an
adult respondent) per household a series of questions about experiences and behaviors that
indicate the food security status of the household. Reference persons with children are asked an
additional eight questions specifically focused on their ability to feed their children. The
questions included in the first part of the survey include, “We worried about whether our food
would run out before we got money to buy more. Was that often, sometimes or never true for
you in the last 12 months?”, “In the last 12 months, were you ever hungry, but didn’t eat,
because there wasn’t enough money for food? (Yes/No)” and “In the last twelve months did you
or other adults in your household ever not eat for a whole day because there wasn’t enough
money for food? (Yes/No)” (Coleman-Jensen et al. 2011)7.
Households are rated as food secure if they answered “yes” to no more than two food
insecure conditions. They are rated as food insecure if they answered “yes” to three or more food
7
See Appendix B for complete US-­‐HFSS Questions GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 21 insecure questions. Food insecurity is further broken down into low food security and very low
food security (referred to in earlier USDA reports as “hunger”). If people answer “yes” to 3-6
questions they are qualified as having low food security, and if they answered “yes” to six or
more questions they are considered to have very low food security8.
The three annual samples were combined to generate a sufficiently large sample of
employed single adult non-parents in the United States. The resulting sample is comprised of
15,930 unmarried, childless individuals, down from the original 71,096 households with
complete US-HFS surveys in 2008, 2009 and 2010. The sample includes only individuals who
self-identified as living alone without a spouse or partner as well as those who did not have
children (either all together or still living in the household). Additionally, the sample only
includes 18-65 year olds who were reported as being employed9. Non-response households and
incomplete surveys were excluded from the sample. CPS data for five control variables were
consistently coded across years. Dummy variables for each year were used in a fixed effects
model to control for unobserved heterogeneity.10 The independent variables included are; sex,
yearly income, highest level of education, age, and occupation11.
8
For individuals without children in the household, 6 or more affirmative answers to the 10 question survey qualifies the household as having very low food security. For families with children in the household, 8 or more affirmative answers to the 18 question survey (8 additional questions are asked for families with children) qualifies the household as having very low food security (Coleman-­‐Jenson et al 2011, pg.4). 9
Work status (full or part) and hours worked is not specified. This sample simply includes individuals who were reported to be employed, restricted from: Unemployed; Not in Labor Force – Discouraged: Not in Labor Force -­‐ Other. It would be of interest to include a more specific measure such as hours worked in any additional research in this area. 10
By creating dichotomous dummy variables for the data collected in 2008, 2009 and 2010 I was able to measure if there were any statistically significant differences in trends over those three years, potentially creating skewed outcomes in my results. The effect of the independent variables on my dependent variable (food security status) was consistent over the years of 2008, 2009 and 2010. However, the effect of gender on food security status lost significance in some models using only 2010 data. To ensure a sufficient sample of this population the combined data from the three years was used, however it should be noted that this could potentially skew the outcome of the variable female to be shown as less significant than it would be if only 2008 and 2009 data was used. Although beyond the scope of this paper, it would be of interest to explore these changes between years in a future project. 11
See Appendix C for “Coding Key”. GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 22 The dependent variable, food security status (fss), was taken directly from the CPS data. It is a
12 month recall of food security status that identifies the condition of the household in the past
year. Food security status is measured on a three point ordinal scale; food secure (coding of 1),
low food security (coding of 2) and very low food security (coding of 3), and is determined by
the number of affirmative answers provided in the food security survey (Appendix B).
The variables of income, education and age were recoded and condensed for ease of
interpretation. Income is defined as the combined income of the individual during the last 12
months and includes; money from jobs, net income from business, farm or rent, pensions,
dividends, interest Social Security payments and any other money income received by the
individual. Income was recoded to include a total of 10 categories as opposed to the original 16.
These categories were recoded to compare those approximately at or below the federal poverty
level for a single adult and increasing from there by intervals of $10,000/year up to $75,000, and
then intervals of $25,000 and $50,000/year up to the income level of $150,000+12. This approach
allows for more detailed distinctions to be made among individuals in lower income brackets
while using wide income ranges for upper income individuals among whom food insecurity is
likely to be uncommon.
Education is defined as the highest level of education completed by the respondent. It was also
condensed and recoded to a total of four categories representing educational thresholds that are
likely to have an impact on occupational attainment and earnings. Those who have not
completed high school (coding of 1) are compared with high graduates (coding of 2), college
12
Income coded as follows: $0-­‐14,999 coding of 1; $15,000-­‐24,999 coding of 2; $25,000-­‐34,999 coding of 3; $35,000-­‐44,999 coding of 4; $45,000-­‐54,999 coding of 5; $55,000-­‐65,999 coding of 6; $65,000-­‐74,999 coding of 7; $75,000-­‐99,999 coding of 8; $100,000-­‐149,999 coding of 9; $150,000+ coding of 10. GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 23 graduates (coding of 3), and those with advanced or professional degrees (coding of 4). This
categorization also makes this study comparable with earlier research examining causes of food
insecurity (Bernell et al 2006; Mammen et al 2008). Additionally, condensing the education
variable into four categories, as opposed to 16, allows for a more balanced distribution of the
sample across education categories13.
Age is defined as the age of the respondent in years at the time of their last birthday. Age was
recoded into five categories (18-24 coding of 1; 25-34 coding of 2; 35-44 coding of 3; 45-54
coding of 4; 55-65 coding of 5). This approach permits easier interpretation and allows for
comparisons among the sample population by allowing for clearer distinctions between age
groups to be made as opposed to comparing single year age differences.
Occupation consists of five broad categories; management, sales and office, service,
construction, and transportation and production. Armed Forces and Farming, Fishing and
Forestry occupations were dropped due to an extremely small sample of individuals working in
these occupations14. The occupation categories were taken directly from the CPS dataset which
had condensed them from their original 52 different industry categories. Broader categories were
chosen for ease of interpretation15. Included in the five occupational categories are: management
(includes the occupations of chief executive, education administrators, human resource managers
and social and community service managers), sales and office (includes the occupations of
13
Distribution of sample by educational attainment; Less than HS 6%; HS Diploma/GED 46%; College Degree 36%; Advanced/Professional Degree 12%. 14
Approximately 0.65% of total sample was employed in Farming, Fishing and Forestry occupations; approximately 0.02% of total sample was employed in Armed Services occupations. 15
If this study were to be expanded on, it would be of interest to use more specific occupation and industry categories to catch the more nuanced differences between occupations. GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 24 supervisor and manager of retail sales workers, cashier, teller, receptionist and sales
representative), service (includes the occupations of food preparations worker, bartender,
waiter/waitress and host/hostess, and fast food worker), construction and maintenance (includes
the occupations of carpenter, construction worker, roofer, electrician, janitor, maid and
housecleaner), and transportation and production (includes the occupations of bus driver,
industrial truck driver, assembler, rail road conductor, machinist and service station attendant).
The occupation variables are dichotomous dummy variables with transportation and production
used as the baseline occupational category.
Methods
Descriptive statistics for each of the variables were computed to establish a base of the
distribution of this sample among the variables included in the model. Probability testing was
also conducted to see where men and women had significantly different, or higher or lower rates
of falling into specific income, education, age, and occupation brackets. After examining
univariate patterns and bivariate associations, the association of gender and food insecurity is
measured controlling simultaneously for income, education, age, and occupation1617. To do this
we use multivariate ordinal logistic regression (ologit)18. Ordinal logistic regression permits us to
gauge whether the likelihood of falling into each of the three categories of food security (food
16
Model specification assumptions were determined to be met through the use of AIC/BIC outputs, and Pseudo R2. Although these tests are less conclusive when used for ordinal logistic regression, they do provide some basis for analysis. Output tables for these tests are included in Appendix D. 17
To ensure these models did not suffer from (perfect) multicollinearity, pairwise correlation coefficients were run on all independent variables. Although there is significant correlation among some of the independent variables, none of them reach a critical point of concern, often ranging from a low of 0.50 to a high level of concern at 0.75-­‐
0.80. Pairwise correlation coefficient table presented in Appendix E. 18
Although heteroskedasticity is often of little concern in ologit models due to the fact that errors of Pr(Yi =1) exhibit standard logit distribution (as opposed to probit models in which errors exhibit a standard normal distribution), all models were run using Robust Standard Errors as a preventative control for the presence of heteroskedasticity. Robust Standard Errors generally produce a larger standard error thus decreasing the chance that results will be incorrectly interpreted towards a false negative result. GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 25 secure, low food security and very low food security) is different between men and women.
Ologit is unique as this form of regression analysis allows for a more specific distinction within
the dependent variable.
To ensure that ologit was appropriate for this model and that the model did not suffer
from an over or underrepresentation of dependent variable categories, all models were run using
logistic regression and a hunger dummy variable19. Results from the logistic regression output
were shown to be similar to that of the ologit results. Signage and significance of the coefficients
did not change and the magnitude of effect of each variable was similar when using logistic
regression. Because there were no significant differences, the use of ologit was continued to
measure the three category dependent variable, food security status.
To determine whether the use of odds ratios could be used to interpret the results from
these ologit models, a Brant test was conducted on the complete model (all variables included) to
measure the proportional odds ratio of each variable. This model failed the Brant test which
indicated that the use of odds ratios in the interpretation of results cannot be used20. To ensure
interpretation was not corrupted by this failure, results were “checked” using stereotype logistic
regression (slogit) which relaxes the proportional odds assumption. All betas maintained original
signs when run in slogit when compared to those in the ologit model, thus ologit was deemed
appropriate for continued use, withholding interpretation through odds ratios. Due to the failure
of the proportional odds assumption, interpretation of results must be done using log odds in
which general trends can be determined by the significance and signage of the coefficients. To
draw more specific conclusions about the relationships between gender, food insecurity and the
19
Logisitc regression results shown in Appendix F. Proportional Odds Ratios tests presented in Appendix G. 20
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 26 other independent variables included, additional explanatory tests were used and will be
discussed in tandem with the ologit output.
Results
Descriptive and Bivariate Statistics
Women comprise 47% of the 15,930 individuals who were identified as being employed, single
adults, with no dependents. Table 1 shows the actual distribution of food security status reported
by men and women in this sample. Eighty-eight percent of respondents were reported as food
secure; 86% of women and 89% of men. Six percent of all respondents reported low food
security; 7% of women, 6% of men and six percent of all respondents reported very low food
security; 7% of women and 5% of men.
Table 1: Food Security Status Distribution of Men and Women Food Security Status
Food Secure
Low Food Security
Very Low Food Security
Males
89% (7,514)
6% (487)
5% (435)
Females
86% (6,454)
7% (545)
7% (495)
Difference
-3%
+1%
+2%
Table 2 shows the predicted likelihood of food security status among men and women holding
income, education, age and occupation constant at the mean. Table 2 indicates that women are
more likely than men to experience both low food security and very low food security and thus
less likely to be food secure. Although the magnitude of this difference is small (women are
1.8% more likely to be food insecure than their male counterparts), it is statistically significant at
the .05 level.
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 27 Table 2: Predicted Likelihood of Food Security Status
Table 3.1 shows the predicted likelihood of food security status within the independent variable
categories.
Table 3.1: Predicted Likelihood of Food Security Status by Independent Variable Categories, Full
Sample
General trends shown in Table 3.1 indicate that an individual’s likelihood of being food insecure
decreases as income, education and age increase. For example, those with incomes of $0-14,999
per year have a 26.8% predicted likelihood of being food insecure (13.6% predicted likelihood of
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 28 having low food security and a 13.2% predicted likelihood of having very low food security),
while those with incomes between $100,000-149,999 per year have a 1.7% predicted likelihood
of being food insecure (1% predicted likelihood of low food security and a 0.7% predicted
likelihood of experiencing very low food security). Similarly, individuals who have not
completed high school have a 12.7% predicted likelihood of being food insecure (7% predicted
likelihood of experiencing low food security and a 5.7% predicted likelihood of experiencing
very low food security), compared to a 6.1% predicted likelihood of being food insecure (3.5%
predicted likelihood of low food security and 2.6% predicted likelihood of very low food
security) for those with advanced or professional degrees. The variation between age categories
is less dramatic than in income and education but Table 3.1 shows that generally, as age
increases, an individual’s likelihood of being food insecure decreases. However, Table 3.1 also
indicates that there is almost no variation in food security status among occupations21.
To more accurately gauge the differences in the predicted likelihood of food security status
among the occupation categories Table 3.2 shows the likelihood of food security status when
income is not held constant. When income is not controlled, those in management occupations
have the highest likelihood of being food secure, while those in transportation and production
occupations have the lowest likelihood of being food secure22. For example, individuals who
work in transportation and production occupations have a 13.3% predicted likelihood of being
21
Table 3.1 shows the predicted likelihood of food security status within each of the independent variable categories while holding all other independent variables constant at their mean. It is likely that due to income’s strong association with food security status and the correlation between income and occupation, when income is held constant at its mean, any potential variation in food security status by occupation is “hidden” by the effect of income. 22
Correlation coefficients between income and the occupation variables indicate a significantly positive association between income and the management occupation (shown in Appendix G). Additionally, individuals who work in management positions are generally distributed into higher income categories than those in all other occupations further indicating an association between income and occupation (Table not shown). Due to this association, by removing income, food security status by occupation can be seen more clearly. GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 29 food insecure (7.1% predicted likelihood of experiencing low food security and 6.2% predicted
likelihood of experiencing very low food security), while those who work in management and
professional occupations have a 9.9% predicted likelihood of being food insecure (5.4%
predicted likelihood of low food security and a 4.5% predicted likelihood of very low food
security).
Table 3.2: Predicted Likelihood of Food Security Status by Occupation (income uncontrolled), Full
Sample
Table 4 shows the distribution of men and women among the independent variable categories.
Overall, distribution trends show that a higher percent of women compared to men fall into the
lower two income brackets ($0-14,999 and $15,000-24,999) and a higher percent of men than
women fall into all income categories above $24,000/year. Thus overall, men make up a majority
of the individuals who fall in income brackets above $24,999/year.
The education distribution is divided into four categories, measuring the highest level of
education attainment for all individuals in the sample. Overall, women in this sample have
achieved higher educational attainment than men. Of those with less than a high school diploma,
62% are men. Of those with an advanced/professional degree, 56% are women. Consistent with
this pattern, 58% of women in the sample have obtained a college degree or higher compared to
only 48% of men.
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
Table 4: Distribution of Men and Women among Independent Variable Categories
| 30 GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 31 The distribution of men and women into the five occupation categories indicates a general
pattern of occupational sex segregation, specifically in the occupations of
construction/maintenance and production/transportation (typical “male” jobs). Men in this
sample make up 97% of individuals in construction/maintenance and 80% of those in
construction/transportation. Nearly half of all women in the sample (49%) are in the occupation
of management/professional. Of those in service, 55% are women; of those in sales and office
occupations 60% are women. Based on these occupational distributions there is clear evidence of
occupational segregation between men and women, consistent with existing literature.
Multivariate Ordinal Logistic Regression Results
Table 5 shows in log odds the “effect” of gender on an individual’s likelihood of experiencing
food insecurity, using a combination of the control variables which include income, education,
age, and occupation. The results are presented in log odds as these models failed the proportional
odds test. For interpretation purposes, general conclusions about trends and higher and lower
likelihoods of falling into each of the three food security categories must be used; positive
coefficients indicate a higher likelihood of falling into the lower categories of food security (low
food security, coding of 2 and very low food security, coding of 3). Negative coefficients
indicate a lower likelihood of falling into these categories i.e. negative coefficients have a
negative effect on food insecurity, meaning they reduce the likelihood of being food insecure
(experiencing low or very low food security). The significance of each coefficient is indicated
within the table. Both the Pseudo R2 and the WaldChi statistic are presented at the bottom of the
table to indicate the significant and variation in food security status explained by each model.
Although R2s cannot be accurately interpreted in ologit, they are presented for consistency.
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 32 Table 5 shows that gender is a significant determinant of food security status in all models;
women are slightly more likely than men to experience food insecurity when controlling for
other variables. Model1 indicates that when no other variables are controlled, women are
significantly more likely than men to experience low or very low food security.
Table 5: Influences on the Likelihood of Food Insecurity
When controlling for income in Model 2, gender remains significant though is less strongly
associated with food insecurity. This is consistent with income’s negative relationship with food
insecurity and the negative relationship between income and being female (with “female” coded
as “1”). As expected, the significant negative income effect appears in Model 2. Furthermore,
although the effect of increased income on food security status is the same for both men and
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 33 women (higher income equates to a lower overall likelihood of being food insecure), the degree
to which increased income affects men and women’s food security status is not the same.
Women in the same income bracket as men, holding all else constant, still have higher
likelihoods of experiencing food insecurity than men (Details shown in Table 6).
Table 6: Predicted Likelihood of Food Security Status for Men and Women by Income Level
In Table 5 education is added to the regression in Model 3, using individuals whose highest
educational attainment is a high school diploma as the reference category. The likelihood of food
insecurity for individuals with less than a high school diploma is not statistically different from
those who do have a high school diploma. However, individuals with a college degree or
advanced professional degree are significantly less likely than those with only a high school
diploma to experience food insecurity.
In Table 5, Model4, age is added to the regression and the education dummies are replaced by an
ordinal interval education measure (less than HS, coding of 1; HS diploma, coding of 2; college
degree, coding of 3; professional degree, coding of 4). As age increases an adult’s likelihood of
experiencing food insecurity decreases. The magnitude of the effect of age on food security
status is relatively small but still significant. Further, when controlling for education, the gender
and income effect remains robust. Although the effect of educational attainment on food security
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 34 status is the same for both men and women (higher education equates to a lower overall
likelihood of being food insecure), the degree to which higher educational attainment affects men
and women’s food security status is not the same. Women with the same educational attainment
as men, holding all else constant, still have higher likelihoods of experiencing lower levels of
food security and a lower likelihood of being food secure (Details shown in Table 7).
Table 7: Predicted Likelihood of Food Security Status for Men and Women by Educational Attainment
Model5 in Table 5 adds occupation to the regression by using dichotomous occupation variables.
Due to the presence of multicollinearity between income and occupation, income was removed
from the regression in Model523. Model5 indicates that overall, individuals in management
occupations are significantly less likely than those in the reference category of transportation
and production to experience low and very low food security. Individuals in service occupations
are significantly more likely than those in the reference category to experience lower levels of
food security. Model5 also indicates that there are no significant differences in food security
23
Note conflict between multicollinearity and omitted variable; You cannot simultaneously correct for multicollinearity and an omitted variable bias in the same model. By omitting one of the correlated variables and running two separate models, multicollinearity can be corrected for but an omitted variable bias must be noted as well. When combined with both income and education, occupation is not a significant determinant of food security status, however when either income or education are left uncontrolled occupation is significant. Occupation’s significance when not combined with income or education is likely due to the effect of multicollinearity; occupation is correlated with both income and education. To control for multicollinearity, Model5 removes income from the model. GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 35 status among individuals who work in the occupations of sales and office, and construction and
maintenance to those in the reference category of transportation and production24.
To gauge whether these differences in the likelihood of food security status based on occupation
are the same for men and women, Figure 125 shows the likelihood of food insecurity between
men and women within each occupation controlling for education and age (income
uncontrolled).
Figure 1 shows that occupation does not have the same effect on food security status for women
as it does for men. Women in the same occupation as men have a higher likelihood of
experiencing lower levels of food security than their males counterparts when not controlling for
income, holding all else equal26.
24
Because there are no significant differences in the food security status of individuals in construction and maintenance and sales and office to those in the reference category we can infer that those in the management occupation are significantly less likely than those in all other occupations to experience food insecurity, while those in service occupations are significantly more likely than those in all other occupations to experience food insecurity. 25
This graph shows the likelihood of food insecurity among men and women in the five occupation categories. Using a hunger dummy variable, the likelihood of food insecurity is measured (low food security + very low food security). 26
Interpretation of this graph must be done carefully as the occupation variables are categorical and cannot be ranked. This graph merely shows that between men and women in the same occupation, their likelihood for being food secure is statistically different. GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 36 Figure 1: Probability of Food Insecurity for Men and Women by Occupation
Figure1 indicates that there is a statistically significant inequality between men and women in
the same occupation and their likelihood of being food insecure. Table 8 shows a more detailed
account of this difference.
Table 8: Predicted Likelihood of Food Security Status for Men and Women Working in the Same
Occupation
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 37 In all occupations, women’s likelihood of falling into the lower two food security categories is
significantly greater compared to men. This difference is most pronounced in the
production/transportation occupations (where women in this occupation are 5.7% less likely to
be food secure compared to men in this occupation) and the construction/maintenance
occupations (where women in this occupation are 5.3% less likely to be food secure compared to
men in this occupation). Based on the descriptive statistics presented previously, these are the
two occupation categories in which men make up a strong majority of workers. The smallest
difference is shown in management/professional occupations with a 4.4% difference in the
likelihood of food security between men and women.
Interpretation of Results
The results in this study generally confirm what was expected. Gender is a significant
determinant of food security status for single adult nonparents. Women are more likely to fall
into the lower two food security categories (low food security and very low food security) than
their male counterparts. When including the controls of income, education and age, gender
remains significant. The effects of income, education, and age on food security status are
consistent with existing literature. Occupation’s association with food security status is only
present when income is left uncontrolled. Individuals in occupations typically associated with
higher income rates, such as management positions, are less likely to be food insecure than those
in the other occupational categories.
There is evidence of both occupational sex segregation and gender inequality within
occupations in this sample. This indicates that even men and women without children or
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 38 spouses/partners are influenced by the same or similar forces that distribute men and women
with spouses/partners and children into specific occupations. Because these trends were found
among single adults without children we can see that gender inequalities in the workforce and in
relation to material hardship go beyond just women who have or plan to have children and seem
to permeate into the gender of workers themselves. Evidence of occupational sex segregation is
present in this sample based on the unequal distribution of men and women into each of the
occupational categories as shown in Table 4. Additionally, as shown in Figure 1 and Table 8,
men and women in the same occupation have an unequal likelihood of experiencing food
insecurity. When not controlling for income, women have a higher likelihood of low and very
low food security compared to men working in their same occupation. This provides evidence of
a gender wage gap within occupations as well as a gendered food security gap within
occupations. One logical explanation of this difference in food security status within occupations
by men and women is that if men and women are not paid the same, due to the strong association
between income and food security status, women’s ability to feed themselves is hindered by
unequal workplace conditions such as the debilitating gender wage gap27.
Further, when exploring the distribution of men and women into the different
independent variable categories (Table 4), several interesting patterns can be observed. Based on
the outputs presented in Table 3.2, men are distributed into the occupations that are shown have
a higher likelihood of food insecurity. However, Table 4 shows that they are also distributed into
higher income brackets than women, but also have lower overall educational attainment. The
distribution of men and women in the independent variable categories indicates a conflicting
trend when compared to what we know about the variables that increase or decrease an
27
It would be essential to control for hours worked before concluding that this entire disadvantage is caused by a gender wage gap. GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 39 individual’s likelihood of food insecurity. Although men are less educated and concentrated in
jobs with a higher likelihood of food insecurity, they are less likely to be food insecure than
women. A gender wage gap or a concentration of men in higher paid positions would account for
this type of distribution, leading back to the conclusion that workforce inequalities may be
associated with a higher likelihood of food insecurity for women.
Conclusions
This study both contributes to and expands on existing literature on food insecurity and gender
inequality within the workforce. By finding an existing inequality among single adult women
and men without children, it begs questions about some of the potentially discriminatory
practices that place men and women in different occupations with different corresponding pay.
Eliminating two of the most prominent factors that have been shown to affect men’s and
women’s employment decisions, children and marital status, as well as controlling for other
known factors that are associated with food insecurity, reveals a persistent inequality between
men and women, providing further reason to explore the association between food insecurity and
gender. Finding that women have higher likelihoods of food insecurity when controlling for
income, education, and age shows us that there is something beyond these factors that
contributes to unequal food security status. It is possible there are other social conditions such as
social isolation, gender differences in the capacity to get food assistance, or gender differences in
the perceptions of food insecurity and ability to admit to insecurity, that could contribute to these
differences in measured food insecurity.
These findings provide a basis for further study of this subset of the American
population, looking first at more detailed measures of employment status and pay as well as at
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 40 the social factors that may not only segregate this part of the population into different
occupations but also potentially lead to different experiences of food security. Specifically, it
would be of interest to use more specific occupation categories as well as a more specific
employment measure, such as at hours worked. Additionally, it would of interest to more closely
examine the way men and women in similar circumstances may respond differently to the USHFSS. This study thus provides a basis for additional exploration of systemic inequality and how
inequalities within the workforce and economic opportunity may permeate into gendered
experiences of material hardship.
Specific policies that have been targeted at reducing the pay gap and broadening
women’s economic and workplace opportunities have been effective in reducing the pay gap and
providing precedent for more integrated and equal working conditions. However, it is clear that
there is still work to be done. Policies working to eliminate food insecurity have focused
predominantly on families with children. It would be of interest to see how these policies affect
single adults without children and whether their use of existing policies and programs such as the
Supplemental Nutrition Assistance Program (SNAP) and the Earned Income Tax Credit (EITC)
could be better utilized to provide more stability in income and food security.
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 41 Appendices
Appendix A: Suggested Reading on Social Construction of Gender:
1. Cameron, Deborah. 2007. The Myth of Mars and Venus: Do Men and Women Really Speak
Different Languages? New York: Oxford University Press.
2. Deutsch, Francine M. 2007. “Undoing Gender”. Gender and Society 21:106-127.
3. Lorber, Judith. 1994. Paradoxes of Gender. New Haven, CT. Yale University Press.
4. Lorber, Judith 2010. Gender Inequality: Feminist Theory and Politics. New York.
Oxford University Press.
5. West, Candace, and Don Zimmerman. 1987. “Doing Gender”. Gender and Society 1:125-151.
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 42 Appendix B: “Questions Used to Assess the Food Security of Households in the CPS Food Security
Survey”
1. “We worried whether our food would run out before we got money to buy
more.” Was that often, sometimes, or never true for you in the last 12 months?
2. “The food that we bought just didn’t last and we didn’t have money to get
more.” Was that often, sometimes, or never true for you in the last 12 months?
3. “We couldn’t afford to eat balanced meals.” Was that often, sometimes, or
never true for you in the last 12 months?
4. In the last 12 months, did you or other adults in the household ever cut the size
of your meals or skip meals because there wasn’t enough money for food?
(Yes/No)
5. (If yes to question 4) How often did this happen—almost every month, some
months but not every month, or in only 1 or 2 months?
6. In the last 12 months, did you ever eat less than you felt you should because
there wasn’t enough money for food? (Yes/No)
7. In the last 12 months, were you ever hungry, but didn’t eat, because there wasn’t
enough money for food? (Yes/No)
8. In the last 12 months, did you lose weight because there wasn’t enough money
for food? (Yes/No)
9. In the last 12 months did you or other adults in your household ever not eat for
a whole day because there wasn’t enough money for food? (Yes/No)
10. (If yes to question 9) How often did this happen—almost every month, some
months but not every month, or in only 1 or 2 months?
Coleman-Jensen, Alisha, Mark Nord, Margaret Andrews and Steven Carlson.(2010) Household
Food Security in the United States in 2010. Economic Research Report Number 125,
Economic Research Service. United States Department of Agriculture. Pg.3
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
Appendix C: Data Coding Key
Source of Data:
Current Population Survey, December 2008: Food Security Supplement [machine-readable
datafile]/conducted by the Bureau of the Census for the Bureau of Labor Statistics. Washington: U.S.
Census Bureau [producer and distributor], 2009.
Current Population Survey, December 2009: Food Security Supplement [machine-readable
datafile]/conducted by the Bureau of the Census for the Bureau of Labor Statistics. Washington: U.S.
Census Bureau [producer and distributor], 2010.
Current Population Survey, December 2010: Food Security Supplement [machine-readable
datafile]/conducted by the Bureau of the Census for the Bureau of Labor Statistics. Washington: U.S.
Census Bureau [producer and distributor], 2011.
Conditions:
(HRNUMHOU) Numhouse==1 (one person in household)
(PERRP) Singlestatus==2 (Single status; no dependents)
(PREMPNOT) Employment Status: Sample only includes those who are employed
Dependent Variable Coding:
(HRFS12M1) FSS (Food Security Status):
1= Food Secure
2 = Low Food Security
3 = Very Low Food Security
Independent Variable Coding:
(PESEX) Female:
1= Female
0=Male
(HUFAMINC) Income:
1 = $0-14,999
2 = $15,000-24,999
3= $25,000-34,999
4 = $35,000-44,999
5 = $45,000-54,999
6 = $55,000-64,999
7 = $65,000-74,999
8 = $75,000 – 99,999
9 = $100,000-149,999
10 = $150,000 +
(PEAGE) Age: Years 18-65
1= 18-24
2= 25-34
3= 35-44
4= 45-54
5= 55-65
| 43 GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
(PEEDUCA) Education:
1 = Less than 1st Grade – 12th Grade, No Diploma
2 = HS Diploma/GED/Equivalent/ Some College, No Degree
3 = College Degree: Associate’s/Vocational Degree/ Bachelor’s Degree (BA/BS)
4 = Professional Degree: Master’s Degree (MA, MS, MSW, MEd, MEng), Professional Degree (MD,
DDS,DVM), Doctorate Degree (PhD, EdD)
(Four Education dummies also included)
(PRMJOCGR) Occupation:
1 = Management, Professional and Related Occupation
2 = Service Occupation
3 = Sales and Office Occupation
4 = Construction and Maintenance Occupation
5 = Production and Transportation Occupation
(Five Occupation dummies also included)
| 44 GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
| 45 Appendix D: Model Specification Tests
AIC and BIC Measures of Fit
ologit fss female income education agecat occupation if livealone==2 & numhouse==1
ologit fss female income lessHS collegedegree profdegree agecat management sales construction
transportation if livealone==2 & numhouse==1
GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
Appendix E: Logistic Regression Output Comparison Using DV “HungerDummy”
| 46 GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
Appendix F: Proportional Odds Ratios Test
| 47 GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
Appendix G: Correlation Coefficients/Multicollinearity
| 48 GENDER INEQUALTIY IN FOOD INSECURITY: AN EXAMINATION OF SINGLE ADULTS WITHOUT CHILDREN IN THE U.S
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