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Choose a medical health concern that you’re interested in and write an introductory paragraph based on the research you find on the topic.

Body: (3 Paragraphs)

for the next two paragraphs find something from each one of the two readings that you can connect to cultural event you chose. Reference or quote what you find from each reading that connects to the cultural event in your two paragraphs. The two paragraphs should be about: 1- Immunology, 2- Nutrition, and you have to connect them to your medical health concern.

Use 3 online sources for your intro or body paragraphs. Provide the link for the online sources in the references sheet.



Reference 3 online sources you used for your essay.

Essay must be 4 paragraphs long and must follow the prompts above.

at SciVerse ScienceDirect

Social Science & Medicine 74 (2012) 1754e1764

Contents lists available

Social Science & Medicine

journal homepage: www.elsevier.com/locate/socscimed

Feeding her children, but risking her health: The intersection of gender,
household food insecurity and obesity

Molly A. Martin*, Adam M. Lippert
Pennsylvania State University, 211 Oswald Tower, University Park, PA 16802, United States

a r t i c l e i n f o

Article history:
Available online 20 December 2011

Food insecurity

* Corresponding author. Tel.: þ1 814 863 5508.
E-mail address: [email protected] (M.A. Mart

0277-9536/$ e see front matter ? 2012 Elsevier Ltd.

a b s t r a c t

This paper investigates one explanation for the consistent observation of a strong, negative correlation in the
United States between income and obesity among women, but not men. We argue that a key factor is the
gendered expectation that mothers are responsible for feeding their children. When income is limited and
households face food shortages, we predict that an enactment of these gendered norms places mothers at
greater risk for obesity relative to child-free women and all men. We adopt an indirect approach to study
these complex dynamics using data on men and women of childrearing age and who are household heads or
partners in the 1999e2003 waves of the Panel Study of Income Dynamics (PSID). We find support for our
prediction: Food insecure mothers are more likely than child-free men and women and food insecure fathers
to be overweight or obese and to gain more weight over four years. The risks are greater for single mothers
relative to mothers in married or cohabiting relationships. Supplemental models demonstrate that this
pattern cannot be attributed topost-pregnancy biological changes thatpredispose mothers toweight gain or
an evolutionary bias toward biological children. Further, results are unchanged with the inclusion of physical
activity, smoking, drinking, receipt of food stamps, or Women, Infants and Children (WIC) nutritional
program participation. Obesity, thus, offers a physical expression of the vulnerabilities that arise from the
intersection of gendered childcare expectations and poverty.

? 2012 Elsevier Ltd. All rights reserved.

Scholars argue that it takes money to maintain a healthy weight
in America’s obesogenic environment (Poston & Foreyt, 1999)
because healthy food is relatively expensive and calorie-dense,
nutrient-poor food is cheap (Drewnowski & Specter, 2004).
Although weight is a function of both caloric intake and expendi-
ture, materialist arguments focus on the costs of food and predict
greater caloric intake and consequent body fat among low versus
high income people (Glass & McAtee, 2006). In the U.S., there is
a strong, negative correlation between income and the likelihood of
being overweight or obese, but only among women; this is not
observed among men (for reviews, see McLaren, 2007; Sobal &
Stunkard, 1989). This sex difference is puzzling, particularly to
scholars who look beyond individual explanations to consider the
role of shared environments for health because the majority of men
and women live together (Casper & Bianchi, 2002) and share
socioeconomic resources and weight-related behaviors (French,
Story, & Jeffery, 2001; Mitchell et al., 2003). Given these common-
alities, one would expect greater similarity between the sexes.

We hypothesize that the key distinction is not between all
women and all men, but between mothers and non-mothers. We


All rights reserved.

argue that the confluence of two factors e the experience of food
insecurity and the gendered nature of childcare e intersect and
contribute to the observed sex differences in the association of
income and body weight. Food insecurity is highly correlated with
poverty (Sarlio-Lähteenkorva & Lahelma, 2001) and occurs when
a household faces budgetary constraints that limit the quantity or
quality of food they can purchase (Wunderlich & Norwood, 2006).
Yet food insecurity is a “managed process” (Radimer, 1990),
meaning that families strategize and diligently work to avoid
hunger. That responsibility, however, falls more heavily on women
given traditional discourses about family life and “women’s work”
that place greater expectations on women for feeding and
nurturing their family, especially when children are present
(DeVault, 1991). Given that food insecurity is correlated with poor
dietary behavior and obesity (for a review, see Institute of Medicine,
2011), we assert that food insecurity mediates the association
between income and weight, but that the management of food
insecurity intersects with gender to create differential risks for
obesity between mothers and non-mothers.

To investigate these dynamics, we study men and women of
childrearing ages (i.e., 18e55) who are heads or partners of U.S.
households in the 1999, 2001 and 2003 waves of the Panel Study of
Income Dynamics (PSID). We test whether the association between

M.A. Martin, A.M. Lippert / Social Science & Medicine 74 (2012) 1754e1764 1755

household food insecurity and the likelihood of being overweight
or obese differs across groups defined by sex and parenthood in
cross-sectional models of weight status and longitudinal models of
weight change. We also examine how partner co-residence further
moderates these processes due to the gendered norms about
parental custody (Coltrane & Adams, 2003) and the greater prev-
alence of food insecurity among single parents (Rose, Gundersen, &
Oliveira, 1998).

Food insecurity and weight

Household food security exists along a continuum but can be
categorized into a four-point ordered scale: food secure, food
insufficiency, low food security, and very low food security (Bickel,
Nord, Price, Hamilton, & Cook, 2000; Wunderlich & Norwood,
2006). Most Americans are food secure, but some face food insuf-
ficiency, meaning, they worry about having enough money to buy
food for the month, but actually make no or few changes to their
diet (Wunderlich & Norwood, 2006). Food insecurity occurs when
those fears become a reality. Low food security, or not having the
means to buy the kinds of food desired, reduces the quality and
variety of people’s diets (Wunderlich & Norwood, 2006). Very low
food security occurs when people do not have the means to buy the
quantity of food needed and leads people to skip meals and reduce
their food intake (Wunderlich & Norwood, 2006). Those with either
“low food security” or “very low food security” are considered “food
insecure” (Wunderlich & Norwood, 2006). In 2009, 14.7% of U.S.
households were food insecure (Nord, Coleman-Jensen, Andrews, &
Carlson, 2010), while in 2003, the year corresponding to our study,
the prevalence was 11.2% (Nord, Andrews, & Carlson, 2004).

Because poverty predicts food insecurity (Sarlio-Lähteenkorva &
Lahelma, 2001), there are several parallels found in research on the
roleof food security for body weight. Keyamong them are consistent
sex differences, such that low food security is linked to being over-
weight (Adams, Grummer-Strawn, & Chavez, 2003; Dinour, Bergen,
& Yeh, 2007; Lyons, Park, & Nelson, 2008; Townsend, Peerson, Love,
Achterberg, & Murphy, 2001) and gaining 5 pounds or more in one
year (Wilde & Peterman, 2006), but only among women. Very low
food security is associated with being underweight, but again only
for women (Wilde & Peterman, 2006).

Several studies suggest that food insecurity is linked to over-
weight and obesity due to management strategies people adopt in
the face of economic constraints. Food insecure individuals are
more likely to consume high-calorie but nutritionally-poor food to
avoid feelings of hunger (Dixon, Winkleby, & Radimer, 2001;
Drewnowski & Specter, 2004; Kirkpatrick & Tarasuk, 2008), eat
irregular meals or skip breakfast (Kempson, Keenan, Sadani, Ridlen,
& Rosato, 2002; Ma et al., 2003), and consume less milk, fruit and
vegetables, especially later in the month (Tarasuk, McIntyre, & Li,
2007). According to public health and nutrition research, these
dietary practices are associated with being overweight (Ledikwe
et al., 2006; Ma et al., 2003) and weight gain (Berkey, Rockett,
Gillman, Field, & Colditz, 2003). In the next section, we detail
how the management of food insecurity is gendered.

Gender, childcare, and food insecurity management

Traditional discourses about “family” life and “women’s work”
since the industrial revolution include expectations that women
are responsible for caring for their family members and managing
household tasks (Rothman, 1978; Sokoloff, 1980). When children
are present in the home, those responsibilities multiply (Hays,
1998) and the gendered division of household labor becomes
more unequal (Coltrane, 2000). For example, there is greater
gender equity in the total number of hours spent on housework in

child-free cohabiting and married couples than among similar
couples with children (Sanchez & Thomson, 1997; South & Spitze,
1994). Therefore, mothers are more likely to be subjected to,
internalize, and reflect traditional gender expectations about their
roles and responsibilities than child-free women.

A key feminine responsibility is “feeding the family,” which
requires a series of tasks: meal planning, monitoring the supply of
household provisions, shopping, cooking, and cleaning (DeVault,
1991). Beyond the practical goals, “feeding the family” also
sustains children’s emotional needs for love, support and security
(DeVault, 1991).

In food insecure homes, mothers work hard to prevent hunger
amongst their children. In a qualitative study with frequently food
insecure young mothers, all insisted that their children only expe-
rienced food insufficiency because they adopted several strategies
to protect them (Stevens, 2010), including prioritizing their chil-
dren’s needs over their own (McIntyre et al., 2003; Stevens, 2010). As
DeVault notes “[t]hese women seem to be expressing a heightened
sense of the more widespread notion that’s women’s own food is
less important than that prepared for others” (1991, p.199). As one
woman in a cash-strapped household noted: “If it gets down to it, we
buy to feed the kids” (DeVault, 1991, p.191).

To manage food insecurity, mothers adopt a variety of strategies.
Some strategies focus on grocery shopping, like buying in bulk,
shopping at different stores to get the best prices, or using coupons
(DeVault, 1991; Wiig & Smith, 2008). Other strategies involve
mothers’ food intake. Food insecure mothers skip meals, wait to eat
until later in the day, or eat less to spare their children from hunger
and nutritional deprivation (Badun, Evers, & Hooper,1995; DeVault,
1991; McIntyre, Connor, & Warren, 2000; McIntyre et al., 2003). As
a result, women in food insecure households are at risk of nutrient
deficiencies in Vitamin A, folate, iron, and magnesium (Tarasuk &
Beaton, 1999). We suspect that these behavioral patterns under-
gird the unexplained sex differences in the association between
food insecurity and weight (Adams et al., 2003; Dinour et al., 2007;
Lyons et al., 2008; Olson, 1999; Townsend et al., 2001; Wilde &
Peterman, 2006) and why food insecurity is typically not corre-
lated with children’s weight (Gundersen, Garasky, & Lohman, 2009;
Martin & Ferris, 2007), but for an exception see Gundersen and
Kreider (2009). Unfortunately we do not have direct measures on
people’s dietary behavior or food insecurity management practices
to fully explore this sequence, but we do have the requisite data to
test our primary hypothesis:

H1. There is a statistically significant association between food
insecurity and being overweight or obese for mothers, but not
child-free women or all men.

We know of only one paper about food insecurity and obesity
that emphasizes parenthood. With a sample of parents (65% of
whom were single mothers), Martin and Ferris (2007) found
a positive association between food insecurity and obesity, but they
did not explore whether there was a differential association
between mothers and fathers. Therefore, the current analysis
makes a significant contribution by offering an initial test of this

The role of marriage and cohabitation

We predict that the living arrangements of heterosexual men
and women further condition the differences between mothers and
non-mothers. Prior research demonstrates that caretaking duties
among separated parents are largely performed by the custodial
parent, typically the mother (Furstenberg & Cherlin, 1994;
Marsiglio, Amato, Day, & Lamb, 2000). Therefore, the risks of
overweight due to food insecurity should be exacerbated among

M.A. Martin, A.M. Lippert / Social Science & Medicine 74 (2012) 1754e17641756

single mothers and relatively lower for mothers in co-residential
couple households. Likewise, single fathers should be at greater
risk of obesity when they are food insecure. Unfortunately, we have
too few single fathers in our data to fully explore this possibility
because most single parents are single mothers (Casper & Bianchi,
2002), reflecting a “community division of labor” (DeVault, 1991,
p.193) whereby women routinely have custody after parents
separate. Our second hypothesis is:

H2. The association between food insecurity and being over-
weight or obese is stronger for single mothers versus married or
cohabiting mothers.

It is important to note, however, that the causal relationships
between overweight, family formation, union dissolution, and
household food security are complex. In fact, the causal process
could work in the opposite direction: Overweight women may be
less likely to form unions and bear children given feminine beauty
ideals emphasizing thinness (Allon, 1982).

Alternative explanations

We predict that food insecurity and its management increases
the risks of overweight and obesity for mothers given the gendered
expectations of childrearing. We recognize, however, that there are
competing explanations and we do our best to address them.

First, one may agree with our prediction but disagree with our
interpretation. One may consider any observed risks for mothers as
reflecting, not childrearing, but biological risks of childbearing. If
metabolic changes related to pregnancy predispose birth mothers
to gain weight, then food insecure biological mothers would be at
greater risk of overweight and obesity than “social” mothers. Such
differences could also arise if, due to evolutionary pressures,
mothers are more protective of their biological children (Daly &
Wilson, 1980). To test whether the experience of pregnancy or
biological kinship creates unique risks, we conduct two supple-
mental analyses. First, we restrict our sample to only women living
with children (50% of the sample) and compare whether the risk of
obesity for food insecure mothers is lower among women living
with children they did not give birth to (i.e., they are adoptive, step,
or foster mothers), controlling for the number of children present.
Because most women live only with biological children, statistical
power issues may limit our ability to detect a significant difference.
Second, we restrict our sample to women who have ever given birth
by 2003 and examine whether the risks of household food inse-
curity increase as parity increases, regardless of whether their
children currently live with her and controlling for her age and
other demographic characteristics. Because 89% of the women in
our sample have given birth by 2003, power is less of a problem in
these analyses. If metabolic changes associated with pregnancy
undergird our findings, then one would expect those risks to
accumulate with each birth and, thus, translate into a statistically
significant interaction between parity and food insecurity among
biological mothers.

Second, one might argue that the statistical association between
food insecurity and overweight is a function of other sociodemo-
graphic factors besides income. Thus, we control for status char-
acteristics, like age, education and race/ethnicity in all models.

Third, one might expect that other mediating factors explain
these patterns, especially given that we do not have self-reported
measures of energy intake or, even better, data from doubly-
labeled water tests to measure their energy intake (Schoeller,
1990). We test several alternative mechanisms. Because food
insecure mothers may have fewer opportunities for recreational
physical activity, we test whether differences in self-reported
physical activity reduce the association between food insecurity

and weight among mothers. We also test whether the consumption
of alcohol or smoking cigarettes explains the observed patterns.
Because of the stresses associated with poverty and food insecurity
(Huddleston-Casas, Charnigo, & Simmons, 2009), which would
likely feel more threatening to parents, food insecure parents could
be more likely to self-soothe themselves with alcohol and nicotine.
Yet these behaviors are associated with being overweight (Mokdad
et al., 2003; Slattery et al., 1992). Lastly, given the longstanding
debate about whether receiving food stamps (now officially the
Supplemental Nutrition Assistance Program) increases the risks for
overweight and obesity (Borjas, 2004; Gibson, 2003; Institute of
Medicine, 2011), we test whether our results change with the
inclusion of food stamps receipt. We also include a measure of
participation in the Women, Infants and Children (WIC) nutritional

In sum, we bridge several empirical literatures to develop a new
theoretical model about how gendered patterns of childcare
intersect with household economics to increase the risk of over-
weight among poor, food insecure mothers. We recognize that
there are several alternative explanations and, thus, do our best to
test them with the available data. Our aim is to provide an initial
examination of whether overweight and obesity are physical
expressions of the vulnerabilities that arise from the intersection of
gender, parenthood, and poverty.

Data and methods


We use data from the Panel Study of Income Dynamics (PSID)
because it is the only study that collects data on individuals’ weight,
income, household food insecurity, and household composition.
Unfortunately, PSID does not have information about individual’s
energy intake and food insecurity management.

PSID is a longitudinal household-based study that began col-
lecting data in 1968 for a nationally representative sample and an
oversample of low-income, Southern households (Hill, 1992). The
PSID contains longitudinal data for all individuals who were ever in
a PSID household, even if they move out (Hill, 1992). Interviews
since 1997 are conducted biennially. Given that the PSID has been
fielded for almost 50 years, sample attrition could pose a problem,
but several studies have found that attrition has not affected PSID’s
representativeness (Becketti, Gould, Lillard, & Welch, 1988;
Fitzgerald, Gottschalk, & Moffitt, 1998). PSID is not representative,
however, of immigrant groups arriving in the U.S. after 1968.

We make several restrictions to arrive at our analytic sample.
First, we must rely on data collected in 1999, 2001, and 2003, the
years in which PSID collected data on both weight and food inse-
curity. Second, we restrict our analysis to those who were either the
head of a PSID household or their marital or cohabiting partner in
1999, 2001, and 2003 (n ¼ 9935) because PSID only collects data on
body weight for those individuals. While this provides for
a consistent sample across the various models, it makes the sample
more selective with regard to family structure stability. Our
substantive findings are unchanged, however, in analyses where
the data are multiply imputed to include anyone who meets the
restrictions listed below and was ever in the PSID between 1999
and 2003, regardless of their relationship to the household head.
Third, we restrict the analysis to heads and partners between the
ages of 18 and 55 in 1999 (n ¼ 8151) to focus on adults most at risk
for living with minor children and, thus, the hypothesized patterns.
The next two restrictions eliminate outlier cases that would chal-
lenge the statistical homogeneity of our analysis. Fourth, we drop
those who report being foreign born (n ¼ 82) or who can be
reasonably assumed to be foreign born because they have five or

M.A. Martin, A.M. Lippert / Social Science & Medicine 74 (2012) 1754e1764 1757

fewer years of completed schooling (and the minimum age of
compulsory schooling in the United States is 16) (n ¼ 51). These
individuals are unique in both unobserved and observed ways (i.e.,
their means and correlations for food insecurity, number of chil-
dren, marital status and weight differ significantly) because the
PSID is not representative of immigrants. The absence of immi-
grants reduces the prevalence of food insecurity in the study
(Borjas, 2004). Fifth, we omit women who are pregnant at the time
of the 2003 interview (n ¼ 85). Specifically, we omit women
reporting a live birth in the PSID’s Childbirth and Adoption History
File within 9 months following their 2003 interview date. After
these restrictions, our sample is 7931 adults.

Missingdata dueto item non-response is relatively minor in these
data. There are actually no missing data for people’s sex, age, part-
nership status, the number of co-residential children, urbanicity, and
household income (because the PSID has imputed it). There is minor
item non-response on food insecurity (n1999 ¼ 9, n2001 ¼ 11,
n2003 ¼ 20), self-rated health (n2003 ¼ 86), race (n ¼ 129), and
women’s fertility histories (n ¼ 36). The items with the most missing
data are body mass index (n1999 ¼ 379 [4% of the original 9935
sample], n2001 ¼ 257 [3%], n2003 ¼ 305 [3%]) and education
(n2003 ¼ 596 [6%]). We utilize multiple imputation handle item non-
response, which replaces missing values with predictions from
information observed in the sample (Rubin, 1987). We use the
supplemental program “ice” within STATA 11.0 (Royston, 2005a,b) to
create five imputed data sets. The imputation models include all of
the variables and their interactions that are used in the empirical
models, as well as the respondent’s work status, occupation, and
region (all in 2003), the number of adults in the household (in 1999,
2001, 2003), whethertheylivewithayoungchild(ages0e5;in 2003)
and whether PSID imputed their income. We estimate the empirical
models for each imputed data set and then combine the results,
accounting for the variance within and between the imputed
samples to calculate the coefficients’ standard errors (Rubin, 1987).


Body weight
We determine people’s weight classification in three steps. First,

because PSID only has self-reported weight and because self-
reported weight is generally biased downward among women and
upward among men (Cawley & Burkhauser, 2006), we use the
Cawley (2004; Cawley & Burkhauser, 2006) adjustments to improve
the accuracy of our dependent variable. Specifically, we multiply
respondents’ self-reported weight by race- and sex-specific coeffi-
cients from Cawley’s regressions of measured weight on self-
reported weight. Second, we calculate their body mass index
(BMI) [weight (kg)/height2 (m2)] from their self-reported height and
their Cawley-adjusted self-reported weight. Third, we follow World
Health Organization (2000) guidelines to classify BMI into the
following weight categories: underweight (BMI < 18.5), normal
weight (18.5 ? BMI < 25), overweight (25 ? BMI < 30) and obese
(BMI ? 30). In the cross-sectional models, we predict whether
a person is (1) normal weight or underweight, (2) overweight, or (3)
obese in 2003. Because less than 2% of the sample is underweight,
we cannot model underweight as a separate category. For the
longitudinal models, we predict their weight change (in pounds)
between 1999 and 2003, simply calculated as their Cawley-adjusted
2003 weight minus their Cawley-adjusted 1999 weight.

Household food insecurity
We use the U.S. Department of Agriculture’s Food Security Scale

(Bickel et al., 2000). Respondents were asked a sequential series of
18 questions if they live with children and 10 questions if they do
not. The different series are made equivalent (and thus orthogonal

to the presence of children) in the final 10-point scale and cate-
gorical measure of food security. Following the USDA’s guidelines,
households are classified as food insecure (¼1) if they score a 2.2 or
higher on the Food Security Scale (Bickel et al., 2000). We measure
their household food insecurity in 2003 and create a longitudinal
measure that counts the survey years with reported household
food insecurity between 1999 and 2003 (values: 0, 1, 2, or 3).

Sex is a dichotomous indicator for whether the person is female

(1 ¼ yes) or male.

PSID participants report the number of children between the

ages of zero and 17 years currently in the household, regardless of
their biological relationship to the household head or their partner.
We create a dichotomous measure indicating children are present
(¼1) and a count of children present.

We use the PSID’s Childbirth and Adoption History (1985e2007)
data to create two variables. First, among those living with children
in 2003, we determine whether the woman gave birth to every
child present and create a dichotomous variable equal to one if she
did not. Because very few women live with a mix of biological and
non-biological children (N ¼ 14), the results primarily reflect
whether women who did not give birth to any of the children
present (N ¼ 307) are different. Second, we calculate the total
number of children a woman has ever borne.

In the longitudinal models, we use a variable that equals the
differencebetween thenumberofchildrenpresentin2003and 1999.

Partner co-residence
To compare adults in different residential relationships, we

estimate models separately for those who are single and those who
are who are living with a romantic partner, whether married or

Alternative mediating variables
Supplemental models include the following variables, reported

in 2003: being a “current smoker” (¼1), the number of alcoholic
drinks consumed per day (0 ¼ none,1 ¼ less than one a day, 2 ¼ 1 to
2 per day, 3 ¼ 3 to 4 a day, and 4 ¼ 5 or more a day), bouts of
“heavy” physical activity during the last month (PSID-provided
examples include aerobics, running, swimming, strenuous house-
work), bouts of “light” physical activity during the last month
(PSID-provided examples include walking, golfing, gardening,
bowling), receipt of food stamps in 2001 (¼1), and receipt of WIC in
2002 (¼1).

Control variables
To control for confounding variables, we include age (in years),

education (in years of completed schooling), poor self-rated health
(0 ¼ “good,” “very good,” or “excellent,” 1 ¼ “poor” or “fair”),
disability status (1 ¼ at least one limitation in the Activities of Daily
Living Scale, 0 ¼ none), and metropolitan residence (0 ¼ non-
metropolitan area, 1 ¼ metropolitan area). Race is measured with
three dichotomous variables to compare (1) non-Hispanic African
Americans, (2) Hispanics, and (3) non-Hispanic other racial groups
to non-Hispanic Whites (the reference category).


For the cross-sectional analysis, we estimate several ordinal
logistic regression models in STATA (v. 11) to predict 2003 weight
categories. The results are substantively similar to those from
multinomial logistic regression models. (Results available upon

M.A. Martin, A.M. Lippert / Social Science & Medicine 74 (2012) 1754e17641758

request.) For the longitudinal models, we make an additional data
restriction. We omit people who report gaining (n ¼ 73 [averaged
across imputations]) or losing (n ¼ 50 [consistent across imputa-
tions]) at least 75 pounds in between 1999 and 2003 because such
dramatic changes likely reflect a reporting error in either year or
very unique weight-related experiences. We then use an OLS
regression to predict their change in weight (in pounds) between
1999 and 2003.

All models include PSID 2003 sampling weights to account for
the PSID’s attrition and oversampling of low-income Southern
households and, thereby, make the findings generalizable to the
2003 U.S.-born population. For ease of presentation, we present
results stratified by sex, but we estimate supplemental models
using a pooled sample of men and women to directly test whether
the interaction between food insecurity and the presence of chil-
dren is significantly different by sex.


Table 1 presents weighted descriptive statistics for our full
analytic sample and for men and women separately. Key among
these is that over 60% of the sample is overweight or obese in both
1999 and 2003. On average, women are more likely to be over-
weight or obese in both years and women gain more weight
between 1999 and 2003 (p < .01). In 1999, 6.8% of the sample was
food insecure, while only 4.8% of the sample was food insecure in
2003. These estimates are lower than the national averages for
these years, reflecting our restriction to U.S.-born individuals. As
such, our tests rely on the comparison of small subpopulations.
There are 174 food insecure men (101 are fathers) and 293 food
insecure women (196 are mothers). In 2003, the average sample
member was 39 years old, which partially accounts for the
observed decline in the proportion living with children between

Table 1
Sample means and percentages, weighted and adjusted for sampling design.

Full sample (N ¼ 7931)
1999 2003

Weight, Cawley-adjusted self-report
Body mass index 28.3 29.2
Weight classification
Underweight 1.1% 1.0%
Normal weight (reference) 34.7% 30.1%
Overweight 33.6% 33.6%
Obese 30.6% 35.3%

Weight change (in pounds), 1999e2003 5.3
Household food insecurity 6.8% 4.8%
Household income (in $1000s) e 79,892
Female (¼1) e 53.1%
Co-reside with children (¼1) 55.0% 49.9%
Number of children present 1.0 0.9
Relationship to co-residential children (among those living with children)
All borne by her e e
Some or all not borne by her e e

Number of children ever borne e e
Age (range: 18e55 in