Download View - OhioLINK Electronic Theses and Dissertations Center

Differences in Dietary Intakes of United State Adults from NHANES by Food Security
Status
Thesis
Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in
the Graduate School of The Ohio State University
By
Alayna Marie Markwordt, B.S.
Graduate Program in Allied Medicine
The Ohio State University
2014
Thesis Committee:
Dr. Christopher A. Taylor, Advisor
Dr. Colleen K. Spees
Dr. Neal Hooker
i
Copyright by
Alayna Marie Markwordt
2014
ii
ABSTRACT
Objective: To determine the patterns in nutrient intakes of the US Adult population by
food security status.
Design: A cross-sectional study of adults from the 2005-2010 National Health and
Nutrition Examines Survey
Setting: Dietary recall data and food security status were obtained in mobile exam
centers.
Participants: A total of 16,625 US Adults, aged 18 years and older
Variables Measured: Dietary intake data from 24-hour dietary recalls were used to
assess the sources and amounts of nutrients consumed. Food security status was used
to classify participants into food security groups.
Statistical analysis performed: The means, standard deviations, and percentages were
calculated to describe nutrient intakes obtained from domains and categories by food
security status was determined by linking individual food files to USDA What We Eat In
America Food Categories. Chi-square analysis by food security status was used to
determine the differences between nutrient intakes and food security groups. Total
nutrient intakes from each of the food groups will be aggregated per person for a total
intake from each group per person per day. Significant differences in the consumption
ii
of key nutrients obtained from domains were tested using one-way, ANOVA.
Significance established a priori at P<0.05.
Results: American adults obtained a large proportion of nutrients from mixed dishes,
protein foods, grains, snacks and sweets, and non-alcoholic beverages, and minimal
nutrients from fruits, vegetables, milk and dairy, fats and oils, condiments and sauces,
and sugars. Those who were more food insecure consumed foods with high-energydensity and of lower quality compared to those who were fully food secure.
Conclusions and Implications: US Adults who were more food insecure consumed
lower quality diets than those who were fully food secure. Dietary patterns are critical
to understanding the sources of food among food security groups and are paramount in
targeting interventions to help improve health outcomes of food insecure adults.
iii
VITA
November 18, 1989 ................................................................. Born – Baltimore, Maryland
June 2012 ................................................. B.S. Human Nutrition, The Ohio State University
2012-2014 ................................................................. Graduate Program in Allied Medicine
The Ohio State University
FIELD OF STUDY
Major Field:
Allied Medicine
Specialization:
Clinical Nutrition
iv
TABLE OF CONTENTS
Page
Abstract ................................................................................................................................ ii
Vita ...................................................................................................................................... iv
List of Tables ...................................................................................................................... vii
List of Figures .................................................................................................................... viii
Chapters:
1.
Introduction ...................................................................................................... 1
Research Question ...................................................................................... 2
List of Definitions ........................................................................................ 3
List of Abbreviations ................................................................................... 5
2.
Literature Review .............................................................................................. 6
Food Security and Insecurity in the United States ..................................... 6
Factors Related to Food Insecurity ............................................................ 9
US Adult and Household Income Dietary Patterns ................................... 11
Consequences of Food Insecurity ............................................................. 17
USDA Food and Nutrition Recommendations .......................................... 18
Diet Quality ............................................................................................... 24
Summary ................................................................................................... 25
3.
Methodology................................................................................................... 26
Study Overview ......................................................................................... 26
Research Question .................................................................................... 26
Overview of NHANES ................................................................................ 27
Data Collection ......................................................................................... 28
USDA Food Categories .............................................................................. 31
Data Preparation ....................................................................................... 33
Data Analysis ............................................................................................. 34
4.
Results and Discussion .................................................................................... 36
Study findings............................................................................................ 36
Discussion.................................................................................................. 41
v
5.
Page
Differences in Dietary Intakes of United States Adults From NHANES by Food
Security Status ................................................................................................ 49
Abstract ..................................................................................................... 49
Introduction .............................................................................................. 51
Methods .................................................................................................... 53
Results ....................................................................................................... 56
Discussion.................................................................................................. 59
Limitations................................................................................................. 63
Conclusions and Implications.................................................................... 64
Reference List.............................................................................................................. 66
Appendix A: Sums of grams by food domain and category and food security status
for US adults................................................................................................................ 70
Appendix B: Sums of kilocalories by food domain and category and food security
status for US adults ..................................................................................................... 73
Appendix C: Sums of fat (grams) by food domain and category and food security
status for US adults ..................................................................................................... 76
Appendix D: Sums of protein (grams) by food domain and category and food
security status for US adults ....................................................................................... 79
Appendix E: Sums of carbohydrate (grams) by food domain and category and food
security status for US adults ....................................................................................... 82
vi
LIST OF TABLES
Table
Page
1
Food Security Survey Module Questions ................................................................... 8
2
What We Eat in America USDA Food Categories 2001-2010 .................................. 32
3
Individual Food File Data ......................................................................................... 34
4
Totals Per Person Per Day From Domains and Categories ...................................... 34
5
What We Eat in America USDA Food Categories 2001-2010 ................................. 65
vii
LIST OF FIGURES
Figure
1
Page
Trends in Food Insecurity Over Time ...................................................................... 7
viii
Chapter One: Introduction
Background
In the United States, achieving national food security is an ongoing struggle.
Food security is the confidence one has in their ability to access adequate amounts of
nutritious food to meet their nutritional needs. When a person does not have the
confidence or capability to provide adequate food for their household, they are
considered food insecure. Food insecurity is when one experiences uncertainty in their
ability to provide adequate, nutritious food for themselves and/or household in a
socially acceptable manner. Nearly 15% of the United States population reported being
food insecure at some point last year. The percentage of food insecure US households
has increased throughout the past decade. Identifying the root cause of food insecurity
is difficult because many factors have been linked to the origin of the problem.
Addressing the problem and reducing the incidence in the United States is important
because food insecurity may have detrimental impacts on one’s overall health. Obesity
is one of the most overwhelming outcomes related to food insecurity (1).
Recent dietary trends in the US Adult population have revealed that food
insecure individuals are more likely to consume a lower quality diet compared to food
1
secure individuals. Patterns disclose that food insecure individuals are less likely to
consume fruits, vegetables, and whole grains compared to food secure individuals.
These dietary patterns do not comply with the most recent dietary guidelines from the
USDA. The relationship between food security status and macronutrient consumption
remains to be determined (1).
The U.S. Department of Agriculture (USDA) develops Dietary Guidelines for the
U.S. population every five years based on the most current research showing dietary
patterns that promote health and reduce risk for disease. The 2010 Dietary Guidelines
are the most recently updated version. Research shows the average American intake is
not in compliance with dietary guidelines. Excessive calories, sugar, sodium, and fat are
being consumed. These current dietary patterns are contributing to the obesity
epidemic. The USDA makes recommendations to help manage weight and reduce the
incidence of obesity.
Research Question
1. What are the patterns in nutrient intake of the US Adult Population by food
security status?
2
List of Definitions
Body Mass Index
A measurement of body fat based on body weight (kg)
divided by height (m) squared.
Dietary Guidelines
Recommendations that promote overall health and
accommodate food preference, ethnicities, and customs of
the United States population.
Dietary Patterns
Patterns used to identify typical consumption of food
among groups that may be associated with health
outcomes.
Energy density
The available dietary energy per unit of weight.
Healthy Eating Index
A tool used to measure total diet quality and evaluate
dietary compliance with USDA guidelines.
High Food Security
Households that have complete confidence in their ability
to access adequate foods on a consistent basis, in a
socially acceptable manner.
Low Food Security
Households that report a reduction in the quality and
variety of desirability, but the quantity of food intake was
not substantially affected.
3
Marginal Food Security
Households that have difficulties accessing nutritious, safe
food or experience anxiety about purchasing food at any
point in time, although the quality, variety, and quantity of
the food are not significantly reduced.
Nutrient Density
Foods that provide a high amount of nutrients in
proportion to total energy
Obese
Classified as having a BMI > 30 kg/m2.
Overweight
Classified as having a BMI between 25 and 29.9 kg/m2.
Poverty Line
The minimum level of income considered adequate.
US Department of
The US federal executive department responsible for
Agriculture
developing and implementing policy including food,
farming, agriculture, and forestry.
Very Low Food Security
Eating pattern of any member in a household is reduced
because of the lack of available resources and money.
4
List of Abbreviations
BMI
Body Mass Index
CAPI
Computer-assisted Personal Interview
CDC
Center for Disease Control and Prevention
DHHS
Department of Health and Human Services
FNDDS
Food and Nutrition Database for Dietary Studies
FSRG
Food Surveys Research Group
HEI
Healthy Eating Index
HFS
High Food Security
IFF
Individual Food Files
LFS
Low Food Security
MEC
Mobile Exam Center
MFS
Marginal Food Security
NCHS
National Center for Health Statistics
NHANES
Nations Heath and Nutrition Examination Survey
USDA
United States Department of Agriculture
USFMMS
United States Food Security Survey Module
VLFA
Very Low Food Security
WWEIA
What We Eat in America
5
Chapter Two: Review of Literature
Food Security and Insecurity in the United States
Many factors influence dietary patterns in the United States (2). Individual’s
access to resources to obtain food plays a critical role in individual dietary patterns.
Those who lack necessary resources to obtain adequate amounts of food are classified
as food insecure. Food insecurity is the uncertainty or anxiety households experience
when trying to acquire adequate food to meet the needs of every individual in a
household. The U.S. Department of Agriculture (USDA) defines food security as having
availability to nutritionally adequate and safe foods in a socially acceptable manner, for
all members of a household at all times, to engage in an active, healthy life.
Despite the growing number of resources the United States has to offer to help
reduce the percentage of food insecure individuals, a significant percent of the US
population continues to struggle with food insecurity. Millions of households struggle to
attain adequate amounts of foods each year. Even with the steps that are being taken as
a nation, the percentage of families struggling to provide adequate food to entire
households has increased over the past decade. Food Security in the US has decreased
over the past decade. During the year 2002, 88.9% of Americans were food secure,
decreasing to 85.49% in 2012. As seen in the graph below, food insecurity trends have
6
16
14
12
10
8
6
4
2
0
Food insecurity
Very low food security
Figure 1: Trends in Food Insecurity over Time
increased over time. The overall percentage of US population who is food insecure has
increased since 1995. The percentage of US households that were food insecure has
increased from 11.10% in 2002 to 14.51% in 2012.
The USDA uses the validated US Food Security Survey Module (US FSSM) to measure the
level of household food security (3). The Core Module for US Food Security
measurement is the standard measurement scale used to determine the severity of US
food insecurity and hunger. US FSSM is set up as a three-stage design with screeners
and measures household food security based on the responses. Households with
children are measured on 18 items, while households without children are measure on
10. The items used to measure US food security are present in the table below using
often, sometimes or never for responses. Affirmative responses are those often and
sometimes.
7
Food Security Survey Module Questions
Adult Questions
Worried run out of food
Food didn't last
Couldn't afford balanced meals
Adults cut size or skip meals
How often adults cut size/skip meals
Eat less than should
Hungry, but didn't eat
Lost weight, no money for food
Adults not eat whole day
How often adults not eat for day
Questions for those with children
Relied on low-cost food for child
Couldn't feed child balanced meal
Child not eating enough
Cut size of child meals
Child skip meals
How often child skip meals
Child hungry in last 12 months
Child not eat whole day
Table 1: Food Security Survey Module Questions
The Core Module covers a full range of severity of food insecurity based on
current conditions of US households with and without children. Each households overall
patterns from their responses classifies their food security status level. Four categories
based on the number of affirmative responses in the US FSSM are determined: high
food security (0 items); marginal food security (1-2); low food security (3-5 without
children, 3-7 with children); and very low food security (6-10 without children, 8-18 with
children).
High food security is when households have complete confidence in their ability
to access adequate foods on a consistent basis, in a socially acceptable manner (3). Their
quantity, variety, and quality of food intake are assured and nutritious, safe foods are
easy to access. Marginal food security is when households have difficulties accessing
nutritious, safe food or experience anxiety about purchasing food at any point in time,
8
although the quality, variety, and quantity of the food are not significantly reduced. Low
food security is when households report a reduction in the quality and variety of
desirability, but the quantity of food intake was not substantially affected. Very low food
security is when the eating pattern of any member in a household is reduced because of
the lack of available resources and money. An individual must report multiple situations
when eating patterns are disrupted and food intake is reduced.
Factors Related to Food Insecurity
The complexity of food insecurity and the numerous influencing factors makes it
difficult to analyze (4-8). Household income and economic stressors are two main
factors that impact food insecurity that need to be considered when analyzing food
insecurity.
Household Income
According to the most recent data from the census bureau report, over 15% of
Americans were living below the poverty line in 2011 and 2012 (3;5). Poverty is one of
the most significant factors predicting food insecurity. Many studies have found that
poverty levels are directly correlated to food insecurity (4;6-11). Food insecurity was
much more likely to occur in low-income families compared with those of higher income
(4;6;9-11). Households whose annual income fell below 185% the poverty line were four
times more probable to experience food insecurity (12). Similarly, those living in poverty
were 3.5 times more likely to experience food insecurity compared to those living above
the poverty threshold (7). Food insecurity is common in lower income households (8).
Those with income below 131% of the poverty line had a more difficult time sustaining
9
food security. Likewise, households that reported having “enough of the kinds of food
we want to eat”, classified as food secure, had household incomes 373% of the poverty
level (4). Households that reported having “enough but not always the kinds of food we
want to eat”, classified as mild insecurity, had household incomes 253% of the poverty
level. Households that reported having “sometimes not enough to eat”, classified as
moderate food insecurity, had households incomes 112% of the poverty level.
Households that reported having “often not enough to eat”, classified as severe food
insecurity, had household incomes 114% of the poverty level.
Economic Stressors
Even though numerous researchers have concluded that food insecurity is
strongly correlated with household incomes that fall below the poverty threshold,
households who are well above the poverty line have experienced food insecurity as
well as very low food insecurity, thus reducing the significance of household income as a
key factor of food insecurity (4;6-8;13). This usually occurs when various factors, such as
job loss, high housing and utility costs, divorce, excess medical bills, and transportation
costs, are present and financial stress takes place (12;13). Economic burdens can be a
factor that initiates food insecurity in a household very quickly (12). These stressors can
occur abruptly in a household, resulting in sparse money for food and triggering food
insecurity. Households are left to the decision of whether to purchase food or pay for
other needs discussed above.
Although the two are not synonymous, poverty and economic stressors can be
an indicator of hunger (4). Starvation and chronic undernutrition are not commonly
10
seen in the United States (6); yet, hunger and food insecurity can have many
consequences on the overall health of a considerable proportion of Americans (6;12).
While household income may be a strong predictor of food security status, it is not a
determinant; therefore we will specifically be analyzing food security status and nutrient
incomes in this study.
US Adult and Household Income Dietary Patterns
Dietary patterns are used to identify typical food consumption among groups
that may be associated with health outcomes. They can be of significant importance
when assessing trends among different populations (14). Current dietary patterns show
that diet quality is affected by household income level (6;8;14-16). A direct correlation
has been found with social affluence and consumption of a high quality diet (14). Higher
socioeconomic status has been associated with higher values of Healthy Eating Index
(HEI) and Diet Quality Index, while households of lower socioeconomic status are
associated with lower quality diets (6;12;14).
Fruits and Vegetables
A majority of Americans did not meet the minimum recommended amounts of
fruits and vegetables (2;17;18), consuming about half of the recommended amounts for
fruits and vegetables combined (17). USDA analysis of diet trends showed Americans
underconsumed the recommended amounts of vegetables and fruit by 41% and 58%
respectively (2). The average United States adult consumes an estimated 1.5 cups of
vegetables per day, 40% short of the recommendation. The consumption of fruits for
average United States Adult equaled 1.0 cup, 50% short of recommendation (2).
11
High socioeconomic status groups consume more fruits and vegetables than
those of low socioeconomic status (8;14-17;19-22). Income is directly related to fruit
and vegetable consumption (17). Significant increase in fruit and vegetable consumption
were noted once the income level reached 400% above poverty threshold. A higher
intake of vegetables was found in high socioeconomic status individuals measured by
education and income (17;22). Fruit consumption was higher in higher socioeconomic
status individuals when assessing occupation and income level (1004, 1020). Total
household income was positively correlated with fruit and vegetable consumption. A
low consumption of fruit and vegetables has been consistent by lower socioeconomic
status groups (14;17). When households face food insecurity, fruits and vegetables are
typically the initial food source to be sacrificed (12).
In low, middle, and high household income groups, fruit intake was significantly
greater in the highest household income group compared to the low and medium, while
vegetable intake was significantly greater in the middle and high household income
group (8). Low and middle household income group consumed an average of 1.1 cups
and 1.2 cups of fruit respectively, while the high group consumed an average of 1.5
cups. The low household income group consumed an average of 1.3 cups of vegetables,
while both the middle and high group consumed an average of 1.7 cups.
The frequency of fruit and vegetable consumption of food secure and insecure
younger (ages 29-59) and older adults (ages 60+) was analyzed (19). Overall, both
younger and older adults who were food secure consumed more fruits and vegetables
than the food insecure adults. On average, food insecure young adults consumed fruits
12
43.6 times per month and vegetables 75.5 times per moth, while food insecure young
adults consumed fruits on average 32.3 times per month and vegetables 69.1 times per
month. Food secure older adults consumed fruits an average of 58.6 times per month
and vegetables 87.9 times per month, while food insecure older adults consumed fruits
52.6 times per month and vegetables 85.1 times per month. Their findings resembled
findings of other studies that assessed intakes of fruits and vegetables among food
secure and insecure adults (16;19;21-23).
Grains
Current diet trends show that the average American consumes 6.4 oz of grains
per day, and only 0.6 oz of that being whole grain (2). Nearly three-quarters (72%) of US
adults consumed less than 0.6 oz whole grains (24). More than 96.2% of the entire US
population was not meeting the minimum amount of recommended whole grains (18).
Similarly, 5.75% of the US population had consumed the recommended 3 servings of
whole grains (24). Americans consumed 15% of the recommended servings for whole
grains and consumed 200% of the recommended limit for refined grains (2).
Trends in the consumption of grains, refined and whole grain, between different
socioeconomic groups have also been observed (8;14;15;19;25). An international study
found that low socioeconomic status individuals consumed a higher amount of refined
grains, while high socioeconomic status individuals consumed whole grains more
regularly (14). Other professionals pointed out that lower socioeconomic groups
consume very limited amounts of whole grains, possibly relating to relatively higher
prices (15). In a comparison between household income groups and consumption of
13
whole grains, lower income adults consumed less whole grains than middle- and highhousehold income groups (8). Households 0%-130% of the poverty line consumed 0.7 oz
whole grain, while households 131%-350% and >350% of the poverty line consumed 0.9
oz and 1.0 oz of whole grains respectively. Low-income SNAP adult participants
consumed 39% fewer whole grains than non-participants (25). Over one-third (43.6%) of
SNAP participants reported low or very low food security during the year compared with
18.1% of nonparticipants. Participants were more likely to over-consume sweets and
bakery desserts (25).
Nutrient Trends
At least one-half of Americans fail to meet the Recommended Daily Allowances
for vitamin B-6, vitamin A, magnesium, calcium and zinc (26). Micronutrients trends
between varying socioeconomic state groups have been studied, although are not
completely understood (1;8;16;27). Understanding the degree of micronutrient
depletion in food insecure individuals may help explain the link between food insecurity
and health issues, such as obesity (1). A large proportion of food insecure individuals use
food pantries and other assistance programs for coping strategies (16). Food pantries
undersupplied specific micronutrients including, calcium, vitamin C, and vitamin A
(16;27). Higher household income groups consistently consumed greater amounts of
total fat, including saturated fat, monounsaturated and polyunsaturated fatty acids,
compared to lower household income groups (8). Those from higher household incomes
also had higher intakes of dietary fiber (1). The mean dietary fiber consumption from
low, medium and high-income households groups was 13.7 g, 15.6 g, and 17.4 g
14
respectively. More research is needed in this area. This is a gap we hope to help address
through this research study.
Food Price and Diet Quality Trends
Cost of food can play a significant role in the consumption of types of foods and
amount of energy and nutrients. It is important to understand the relationship between
food price trends and diet quality because it could have a major impact on the diet
quality of food insecure individuals. Patterns reveal that food costs tend to increase with
healthier foods, while unhealthier foods tend to be lower in cost
(6;12;14;15;17;19;20;28). Diet quality can be measured by looking at the dietary energy
density, which will be explained below (14). Food costs may explain food consumption
patterns between different socioeconomic groups (14;19;20). Food insecure individuals
are more likely to purchase less expensive food items that are energy-dense (15).
Energy-dense foods are associated with lower cost, while nutrient-dense foods are
associated with higher cost (6;12;14;15;17;19;20;28). Energy density, defined as
available dietary energy per unit of weight (14), can be a determinant of the amount of
energy consumed by an individual (1011). High-energy dense foods are associated with
overconsumption and reduced satiety and satisfaction (1011). Energy-dense foods
usually have little water content and higher amounts of added sugar, fat, and starch and
are more likely to have greater shelf stability (15). Examples of energy-dense foods
include potato chips, doughnuts, and chocolate (15).
Cost of food is inversely related to energy density; as food prices decrease,
energy density increases, and as food prices increase, energy density decreases (15).
15
Energy-dense foods are generally less costly than the nutrient-dense foods (15;19). One
example shows that the cost of cookies and potato, chips are almost one-fifth the cost
of fresh carrots (15). Another example compared cost of soft drinks to 100% fruit juice.
The cost of soft drinks were one-fifth that of 100% fruit juice. The study found that fats
and oils, sugar, refined grains, potatoes, and beans are several of the lowest cost
options. These foods provided significant sources of dietary energy for a very low cost
(15). In addition, shelf stable foods were typically less costly when compared to highly
perishable foods as such fresh produce, lean meats, and fish. The shelf stable foods had
greater energy density and a higher content of refined grains, added sugars, and
vegetable fats than the highly perishable and nutrient-dense foods. The inverse
relationship between high-energy dense foods and food price is a barrier for people
who are food insecure. Food insecure individuals may be more likely to purchase highenergy dense foods at a lower cost, which can promote consumption of unhealthy food
options with excess fat, sugar, and energy. This can be a risk factor for developing
noncommunicable diseases (15;19;20).
Complimentary evidence shows low energy dense foods are positively correlated
with increased food cost (14;15;17;19;20;28). Typically, low energy foods are higher in
nutrients, also known as nutrient-dense, and are associated with better health (14). Low
energy dense, nutrient-dense foods have high water content and help the consumer
feel more full and satisfied with lower calories (15). Examples include raw vegetables,
fresh fruit, whole grains, fish, and lean meats (14).
16
Fruits and vegetables are associated with lower energy density and high food
price (19). The mean cost of fruits was nearly $0.60 per 100 kcal and the mean energy
density about 70 kcal/ 100 g, while the cost of vegetables was nearly $0.70 per 100 kcal
and the mean energy density was about 80 kcal/100 g. The cost per calorie was about
four times more expensive when compared to sugars, sweets, beverages, and grains.
The fruits and vegetables had only 1/3 the amount of energy compared to sugars,
sweets, beverages, and grains. The cost of seven important nutrients, fiber, vitamin A, C,
and E, calcium, magnesium, and potassium were analyzed (19). The most expensive
diets had high intake of all seven nutrients. Those who spent an average of $13.43 per
day on food consumed an average of 99.4% of the daily value for all seven nutrients.
Those who spent an average of $5.70 per day on food consumed only 68.5% of the daily
value for all seven nutrients. The consumption of a more healthful diet is associated
with spending more money (17;19).
Higher income households spent more money on nutritious foods, such as highquality meats, fish, seafood, fruits and vegetables (15;28). Lower income households
spent a higher percentage of their income on food, particularly lower-cost items (19).
Consequences of Food Insecurity
Diet trends observed among the food insecure population result with negative
overall health consequences. The malnourished paradox explains the relationship
between food insecurity and increased risk for disease.
Malnourished Paradox
In the United States, overnutrition is a leading risk factor for disease and death
17
(29). Overnutrition is the consumption of too many calories. Poverty and food insecurity
have been linked with a state of overnutrition (1;30). Food insecure households have
the highest BMI, a trend especially seen in women (1;30-32). The lack of a diversified
diet results in obesity from inadequate consumption of recommended micronutrients
(1;32). Most typically in a food insecure environment, adequate and even a surplus of
energy is provided, yet overall diet quality is sacrificed from lack of micronutrients in
those foods. When diet quality is compromised from lack of resources for food, higher
intakes of energy-dense foods and high-fat foods are commonly supplemented, while
nutrient-density is minimal. Nutrient-dense foods have been found to be more
expensive, while energy-dense foods are typically less expensive. In a low-income
situation, it is more practical to purchase and consume energy-dense foods. Most of
these foods are have higher shelf stability and are more convenient to prepare. Studies
have found that an indirect relationship exists between energy dense food and cost.
The overwhelming link between inadequate nutrient consumption and increased
risk for disease is of major concern. The USDA provides nutrient recommendations for
the US population to assist health maintenance (2).
USDA Food and Nutrition Recommendations
The USDA revises key recommendations every five years based on the latest
research to assist American’s in establishing healthy diet patterns, known as the Dietary
Guidelines (2). The dietary guidelines are recommendations that promote overall health
and accommodate food preference, ethnicities, and customs of the United States
population. The USDA recommends the Americans pay attention to the nutrient
18
properties of foods and beverages for optimal health. A diet full of whole grains, fruits,
and vegetables from naturally occurring carbohydrates, and limited refined grains,
added fats, and sugar is one of high quality. More specifically, the USDA recommends
that individuals limit their intake of sodium, fat (saturated fat), calories from added fats
and added sugar, and refined grains.
The USDA recommends that sodium intake in limited to 2,300 mg/day (1,500 mg
per day for older adults over the age of 51, African Americans, individuals with
hypertension, chronic kidney disease, or diabetes) (2). Sodium is very readily available in
many food choices, which can make it difficult to meet the recommendations.
Processed foods contain large amounts of sodium, including prepackaged foods, mixed
dishes, fast food, processed meats and cheese, pizza, pasta dishes, etc. Excessive
sodium consumption can be detrimental to an individual’s health. Sodium can be a main
factor in developing hypertension. Limiting sodium in one’s diet can result in immediate
reduction in blood pressure.
Fat is an essential part to the human diet, although if too much of the wrong
kind of fat is consumed, it increases an individual’s risk for disease, specifically
cardiovascular disease (2). Overconsumption of solid fats, saturated or trans fat, can
lead to increased total cholesterol and LDL levels in the body. Elevated levels of
cholesterol and LDL can increase one’s risk for cardiovascular disease. The USDA
recommends the individuals reduce their intake of solid fats to less than 10% of their
caloric intake and replace them with oils, unsaturated fatty acids. Saturated fats are
commonly found in animal fats (except for seafood) and unsaturated fats are commonly
19
found in plant foods (except for coconut oil, palm kernel oil, and palm oil). Saturated
fats are commonly found in the US diet in regular cheese, pizza, desserts, chicken and
mixed chicken dishes, pork and beef, whole milk, eggs and egg dishes, candy, butter,
chips, and fried foods. Calories from solid fats should be limited. Solid fat consumption is
excessive in Americans and needs to be reduced. Americans are consuming an average
of 19% of their total daily calories from saturated fats. That is almost one-fifth of total
calorie intake that has no nutritional value. Limiting solid fats in the diet will result in
reduced calories and reduced risk for cardiovascular disease.
Sugars are naturally found in fruits and milk/milk products, although a majority
of Americans sugar intake is coming from added sugars in processed foods. Added
sugars contribute to additional calories in an individuals diet and often have limited
nutritional value. Added sugars are commonly found in sugar-sweetened beverages
such as soda, sports drinks, energy drinks, fruit drinks and dessert. An average of 16% of
total calories in American diets is from added sugar. By replacing high sugar beverages
with water or beverages without added sugars, Americans can reduce their total calorie
intake.
Refined grains are refined whole grains which are stripped of their natural
nutrients before being processed (2). They are then enriched with iron, thiamin,
riboflavin, niacin, and folic acid. This process returns some of their natural nutrients and
vitamins, but not all. Fiber and other vitamins and minerals are usually not added back
to refined grains and therefore do not contain as many nutrients as whole grains. In
addition, refined grains often have a high amount of solid fats and added sugars, making
20
them energy-dense. The USDA acknowledges that refined grains can be part of a healthy
diet if consumed in moderation, although can be a source of excess calories if consumed
in abundance. The USDA recommends that Americans consume no more than 3 ounces
of refined grains per day. This will help reduce the total calories in one’s diet from added
fat and sugar.
The USDA recommends that Americans increase their intake of fruits and
vegetables (2). Fruits and vegetables are a main source of micronutrients and vitamins
and are under consumed in the United States, including dietary fiber, folate, potassium,
vitamins A, C, and K, and magnesium. They are low in fat and calories, which can help to
maintain a healthy weight. Current recommendations vary depending on age, sex, and
activity level. Adult men’s average daily recommendations are 2 cups of fruit and 2.8
cups of vegetables. Adult women’s average daily recommendations are 1.7 cups of fruit
and 2.3 cups of vegetables. They are an important part of a healthy diet because they
can help maintain a healthy weight and can protect against chronic disease by
consuming at least 2.5 cups total per day. The USDA also recommends that Americans
eat a variety of fruits and vegetables to maximize intake of vitamins and nutrients.
The USDA recommends that Americans increase the amount of whole grains in
their diet (2). There is an abundance of grain-based food options available to American
consumers. A majority of these options are refined grains. The USDA encourages the
consumption of whole grains because of their nutrient-dense properties. Whole grain
products contain the entire grain seed and are a good source of iron, magnesium,
dietary fiber, and B vitamins. These nutrients are essential to the human health. Dietary
21
fiber is one of the main nutrients essential for health. It helps provide the feeling of
fullness and is very important to healthy digestion. Consumption of whole grains has
been associated with a lower body weight and reduced risk for cardiovascular disease.
The USDA recommends that Americans consume 6.0 oz of grains per day, with at least
half (3.0 oz) being whole grain.
The USDA has reviewed research on high quality eating patterns from the United
States and around the world. Dietary intakes throughout America have been studied for
patterns and health outcomes. No single eating pattern has been established in
America, although trends show that dietary intake has little similarity to current
recommendations, nor do they resemble the high quality eating patterns (2;18). In highincome countries, such as the United States, diets usually consist of excess calories,
saturated fats, salt, and sugar (29). Analysis of these dietary trends can help explain the
health outcomes. The USDA has reviewed the quality of the diet patterns that maximize
health and are related to increased risk of disease. Several diets will be discussed in
correlation with health outcomes.
DASH Diet
The DASH diet emphasizes high quality foods with limited sodium consumption.
It highlights the consumption of fruits, vegetables, low-fat milk and milk products, and
includes whole grains, poultry, seafood, and nuts (2). It limits sodium, red and processed
meats, sweats, and sugar-sweetened beverages. Eating patterns similar to DASH has
been associated with lower risk of cardiovascular disease, reduced blood pressure,
improved blood lipids, and lowered mortality.
22
Additional dietary patterns have emerged to represent a healthier pattern of
eating, especially related to various chronic diseases. The Mediterranean Diet is
commonly seen in the Mediterranean region and has recently been growing in
popularity throughout the United States because of the health benefits that has been
associated.
Mediterranean Diet
The Mediterranean-style eating pattern is another diet that has been studied for
diet quality. This style of eating is popular in the Mediterranean region. The high quality
dietary patterns emphasize the consumption of vegetables, fruits, nuts, olive oil,
legumes, fish, and whole grains, with limited amounts of meats and high-fat milk and
milk products (2). These eating patterns have been associated with lower risk of
cardiovascular disease risk factors, reduced cardiovascular disease, and lowered
mortality rates. Vegetarian diets are also commonly recognized for their increased
protection against disease.
Vegetarian Diet
Vegetarian eating patterns have been studied for its quality and health benefits.
Many different types of vegetarian diets are seen throughout the United States (2).
Overall, vegetarian diets emphasize large consumptions of fruits and vegetables. They
typically consume more fiber, potassium, and vitamin C and a lower proportion of
calories from fat (especially saturated fats) when compared to non-vegetarians.
Vegetarian eating patterns have been associated with lowered BMI, lower
cardiovascular disease, and lower total mortality.
23
Western Diet
The Western Diet began evolving from the beginning of the use of foodprocessing methods and agricultural growth (26). Prior to this development, primary
intakes included wild plant and animal foods and minimally processed foods. These
advancements in methods have fundamentally altered the intake and nutritional
characteristics of the western civilization. In the United States today, nearly threefourths of American’s total daily energy is composed of dairy products, cereals, refined
sugars, refined vegetable oils, and alcohol. Processed foods, such as cookies, cake,
baked goods, bagels, rolls, muffins, crackers, chips, pizza, soft drinks, candy, and ice
cream, are ubiquitous and predominant in the westernized diet. The Western diet has
the potential risk of vitamin and mineral deficiencies. The high percentage of calories
from refined sugars and refined vegetable oils reduces the nutrient density of the diet.
These diet patterns may incline chronic disease rates in the modern population. Chronic
diseases in the Western civilization may be a result from the nutritional qualities of
distinctive food patterns.
Diet Quality
The Healthy Eating Index (HEI) is the tool used to measure total diet quality and
evaluate dietary compliance with USDA guidelines (33). The HEI is a scoring metric that
determines the diet quality of foods, patterns, and menus. The HEI-2005 was revised in
2010. The current HEI-2010 is similar to the 2005 version. Both versions have 9
adequacy and 3 moderate components. They set standard using a density approach.
Recommendations that vary by energy level, sex, and/or age employ are employed by
24
least-resistive standards. Revisions have been made to reflect changes in the 2010
Dietary Guidelines for Americans. Several food categories have been changed and
added to emphasize and capture new recommendations.
HEI uses 10 components on a 100-point scale to rate the quality of a diet (15).
The first 5 components evaluate the compliance to the recommendations made by the
federal government (15;34). The other 5 components measure the variety in the diet
and the consumption items to be modified (15). A score of 80 points means the diet
quality is high, a score between 50 and 80 means the diet quality needs improvement,
and a score less than 51 means the diet quality is low (15).
Summary
There prove to be differences between nutrient intake and food security status.
More information is needed to understand the dietary patterns that support the
differences in dietary intake. The purpose of this study is to describe the dietary
patterns across food security levels.
25
Chapter 3: Methods
Study Overview
The data for this study will come from the 2005-2010 NHANES. Data from US
Adults will be observed to determine the relationship between food security and dietary
trends. Public use files will be accessed and the information will be converted to
produce data relevant to this current study. A total of 16,625 subjects with dietary
intake data will be classified into full food security, marginal food security, low food
security, and very low food security. The study included 12,007 (72.2%) participants who
were fully food secure, 1,698 (10.2%) marginally food secure, 1,886 (11.3%) low food
secure, and 1034 (6.2%) very low food secure. Food security status groups will be used
to compare the nutrient intake of grams, kcals, total fat, protein, and carbohydrate.
Dietary intake measurements will be used to distinguish patterns that may explain the
relationship between food security status and quality of diet.
Research Question
1. What are the patterns in nutrient intake of the US Adult Population by food security
status?
26
Overview of NHANES
The Center for Disease Control and Prevention (CDC) began consistently
measuring the health status of individuals in the United States in the early 1960’s. The
National Center for Health Statistics’ (NCHS), part of the CDC, has the responsibility of
producing critical health statistics for the nation. NCHS uses The National Health and
Nutrition Examination Survey (NHANES) for extensive, recurrent data collection.
NHANES is a program of studies created to examine the health and nutritional status of
the United States population. NHANES is extensive health and nutrition information. In
1999, NHANES began continuous data collection of a variety of health and nutrition
measurements. Every two years NHANES produces national data from the
measurements.
The initial main objective of NHANES was to monitor the health status of the US
population. As emerging needs have become of greater importance, NHANES objectives
have expanded and there is a transforming focus on a multitude of health and nutrition
measurements. Each year, NHANES examines a sample of approximately 5,000 persons.
These persons are dispersed across the country and make up a sample to represent the
nation. Questions related to demographic, socioeconomic, dietary, and health are
included in the interviews. A medical, dental, and physiological examination is
conducted as well.
Results are used to establish the prevalence of major disease and risk factors
associated for those diseases. Health promotion and disease prevention strategies are
27
associated with the nutritional status assessment. Health science research uses this data
to create policies, health programs and services, and education for the Nation.
Data Collection
The NHANES data utilized for this study is collected using three different
methods: in-home interview, physical examination during a mobile exam center (MEC)
visit and questionnaires. A Computer-Assisted Personal Interview (CAPI) technology
trained interviewer begins data collection in each individual household selected for
NHANES with an interviewer-assisted questionnaire. CAPI technology is a hand-held
computer device that collects and transmits data. Within one to two weeks of the initial
in-home interview, a physical exam typically occurs. The physical exams occur in the
MEC and are conducting by a survey team. The survey team includes a physician,
medical and health technicians, and dietary and health interviewers. The MEC travels
across the U.S. to survey locations. The physical exam lasts approximately 3 ½ hours.
Additional CAPI questionnaires, including a dietary questionnaire, are completed at this
time. Food frequency questionnaires are completed with dietary questionnaires.
Data used for this study will come from all three methods: in-home interview,
physical examination in the MEC including the 24-hour dietary recall interview, and
questionnaires.
Food Security Status
Food security status was collected during household interviews. Components
pertinent to this research include household food security and individual food security.
Household food security status was collected using the US FSSM. There are 18 items for
28
households with children under the age of 18 years old and 10 items for households
without children. Questions asked refer to all members of the household. Overall food
security was divided into three categories: food security status for the entire household,
the adults in the household, and the children in the household. This study will focus on
the food security of entire households and adults.
Individual food security questions were asked to all survey participants in the
households that confirmed any FSSM item during the household interview. Individuallevel food security questions were asked after the 24-hour dietary recall in the Mobile
Examination Center (MEC). Responses were collected using an Audio Computer-Assisted
Self Interview (ACASI) system. Data were provided as 4 levels of food insecurity: FFS,
MFS, LFS, VLFS based on the number of affirmative items.
Dietary Interview
Detailed dietary intake information was acquired in the MEC using an in-person
24-hour dietary recall. The collected data are used to estimate the intakes of energy,
nutrients, and other food components from the food and beverages during the
midnight-to-midnight 24-hour period prior to the interview. Beginning in 2005-2006,
consumption of all types of water was collected during the initial 24-hour dietary recall.
Following the initial interview, participants are asked about their salt consumption,
whether their intake from the previous day was usual or unusual, and whether or not
they follow any special diet. NHANES participants are eligible for two 24-hour recall
interviews.
29
Analysis of the data from the dietary interview is partnered with the USDA and
US Department of Health and Human Services (DHHS). The National Center for Health
Standards (NCHS) is responsible for designing the sample and collecting the data. The
USDA’s Food Survey Research Group (FSRG) is responsible for the collection
methodology, maintenance of the coding and data processing database, and the data
review and processing.
All NHANES examinees are eligible for the dietary interview. Individual Food Files
(IFF) and Total Nutrient Intake Files were produced using the information collected from
the dietary interviews. IFF contain information regarding the number of days of
complete intake obtained from the participant, day of the week of the intake, time of
eating occasion when the food was eaten, eating occasion name, food, water, or
beverage identified by a USDA food code, amount of food, water, and beverage
consumed, in grams, whether the food was eating in combination with other foods,
whether the food was eaten at home or not, where the food was obtained, amounts of
energy and 63 nutrients/food components from each food, calculated using USDA’s
Food and Nutrient Database for Dietary Studies (FNDDS) 3.0, and whether nutrients
were calculated directly from the food as identified in FNDDS or in the FNDDS item was
modified by adjusting recipe ingredients.
Total Nutrient Intake Files were created for each participant. These files include
whether or not the daily total energy and nutrient intake from foods and beverages and
whether the amount of food consumed was usual, much more than usual, or much less
than usual. These files also include information on salt use and current special diets.
30
Each total intake record contains the number of days of complete intake obtained from
participant, day of the week of intake, daily aggregates of food energy and 63
nutrients/food components from all foods calculated from the USDA’s FNDDS 3.0, daily
aggregates of water (moisture), total amount of water consumption, total number of
food reported for that participant for the day’s intake, whether the amount of food
consumed was usually, more than usual, or much less than usual, type of salt used and
how often added at the table and in food preparation, and whether the participant is on
any special diet.
Interview data files were imported into Survey Net. This is a computer-assisted
food coding and data management system developed by USDA. The intakes were
processed using the USDA’s FNDDS 3.0. Comprehensive information assists in coding
individual foods and portions sizes from participant reports. Nutrient values for FNDDS
3.0 were based on values in USDA National Nutrient Database for Standard Reference.
Coders participated in initial training and then were required to pass a certification test.
Routine monitoring took place to ensure high quality. Multiple reviews were initiated to
confirm the quality of the data.
USDA Food Categories
The USDA has established The What We Eat In America (WWEIA) Food
Categories. The WWEIA Food Categories allow for researchers to interpret and analyze
food consumption patterns in the United States. The food categories classify the foods
and beverages consumed in America into approximately 150 mutually exclusive
categories.
31
Domains
Milk and dairy
Protein foods
Mixed dishes
Grains
Snacks and sweets
Fruit
Vegetables
Beverages, nonalcoholic
Alcoholic beverages
Water
Fats and oils
Condiments and sauces
Sugars
Infant formula
& baby food
Categories
Milk
Flavored Milk
Dairy Drinks and Substitutes
Cheese
Yogurt
Meats
Poultry
Seafood
Eggs
Cured Meats/Poultry
Plant-based Protein Foods
Meat, Poultry, Seafood Pizza
Grain-based
Sandwiches (single code)
Asian
Mixed Dishes – Soups
Mexican
Cooked Grains
Breads, Rolls, Tortillas
Quick Breads and Bread Products
Ready-to-Eat Cereals
Cooked Cereals
Savory Snacks
Crackers
Snack/Meal Bars
Sweet Bakery Products
Candy
Other Desserts
Fruits
Vegetables, excluding Potatoes
White Potatoes
100% Juice
Diet Beverages
Sweetened Beverages
Coffee and Tea
Alcoholic Beverages
Plain Water
Flavored or Enhanced Water
Fats and Oils
Condiments and Sauces
Sugars
Baby Foods
Baby Beverages
Infant Formulas
Table 2: What We Eat in America USDA Food Categories 2001-2010
32
Each food code from the FNDDS is sorted into a WWEIA category. Each category
is designated a 4-digit number and description, and then linked to a unique category
that contains a separate food item. Domains, categories, and subcategories are used to
differentiate where a food or beverage item is placed. The current WWEIA Food
Categories contains 14 domains: milk and dairy, protein foods, mixed dishes, grains,
snacks and sweets, fruit, vegetables, nonalcoholic beverages, alcoholic beverages,
water, fats and oils, condiments and sauces, sugars, and infant formula and baby food.
Within each domain, the food or beverage item is designated to a specific category.
There are approximately 46 categories. Finally, within each category, the food or
beverage is further more designated to a specific subcategory. There are approximately
150 subcategories. For example, skim milk would be placed in the domain titled “Milk
and Dairy”, category titled “Milk”, and subcategory titled “milk nonfat”.
WWEIA Food Categories are designed to partner with dietary intake data from
WWEIA, NHANES, and the USDA FNDDS. An updated version of the WWEIA is produced
every two years with the release of WWEIA, NHANES, and FNDDS. Productions of data
tables are anticipated to summarize food and beverage intake of the U.S. population.
Data preparation
To evaluate the food group sources of key nutrients, foods reported in the IFF
were linked to the USDA Food Categories described above. Key nutrients used in these
will include grams, calories, total fat, protein, and carbohydrate. Total nutrient intakes
from each of the food groups will be aggregated per person for a total intake from each
group per person per day.
33
Subject
1
1
1
1
2
2…
n
Food
1
2
3
4
1
2
n
nutrients
X.X
X.X
X.X
X.X
X.X
X.X
X.X
Food Domain
Milk
Fruit
…
Food Category
Yogurt
Fruit Juice
…
Table 3: Individual Food File Data
Subjec
t
nutrient1_domain
1
nutrient1_domain
2
nutrient1_category
1
1
2
3
4…
n
∑
∑
∑
∑
N
∑
∑
∑
∑
N
∑
∑
∑
∑
N
nutrient1
_ category
2
∑
∑
∑
∑
N
Table 4: Totals Per Person Per Day From Domains and Categories
To identify the proportion of individuals who consume food from each of the
domains and categories, those with total gram consumption >0 will be classified as
consumers.
Data Analysis
To evaluate the proportion of individuals that consumed food from the domains,
chi square analyses will be conducted by food security status and income.
Means and standard deviations will be generated to describe nutrient intakes
obtained from domains and categories by food security. Significant differences in the
34
consumption of key nutrients obtains from domains will be tested using one-way,
ANOVA. Significance established a priori at P<0.05.
SPSS Complex Samples (version 21.0) will be used to perform analysis of the
NHANES sample. This software permits the correction of over-sampling of hard-to-reach
populations, which results in a nationally representative sample. SPSS Complex Samples
is also necessary to provide appropriate standard errors for statistical analyses when the
sample is increased to a national size.
35
Chapter 4: Results and Discussion
Source of Nutrients in American Adults
Foods were categorized into fifteen domains based on What We Eat in America:
Food Categories 2001-2010 from the USDA Agricultural Research Service. To assess
patterns in the amount and consumption of foods from domains, proportions of total
food grams, calories, fat, protein, and carbohydrate were calculated. Few foods were
reported from infant formula and other domain; therefore, the specific nutrients
consumed from these domains will not be discussed herein. These data may present a
greater likelihood of providing inaccurate national representations when divided into
subgroup analyses due to statistical concerns regarding the sampling weight
methodology.
Means of Nutrients within Categories and Subcategories between Food Security Status
Groups
Mean intakes of key nutrients among food security status groups for grams,
calories, fat, protein, and carbohydrate consumed from food domains and categories
are presented in Appendices A through E, respectively. Significant differences were
calculated for nutrient intakes between each food security status group and food
domain.
36
Mixed Dishes
Mixed dishes were one of the top food sources of grams, calories, fat, protein,
and carbohydrate for American adults, regardless of food security status. Amounts
(grams) of mixed dishes consumed were lower in those who were more food secure;
VLFS adults consumed greater amounts (grams) of mixed dishes and FFS presented with
the lowest intakes of mixed dishes. For all individuals, a large proportion of mixed dishes
consumed were from meat/poultry, grain-based, and pizza dishes, although VLFS
consumed the greatest amounts from each subcategory and FFS presented with the
lowest intakes from each subcategory. Overall, mixed dishes contributed 20% of the
daily energy intakes and 23% to 36% of the daily fat intakes, and were also leading
contributor to protein and carbohydrate intakes. VLFS adults had the highest daily
percentages of calories and fat from mixed dishes. MFS adults consumed significantly
more calories (P=0.03) and fat (P=0.035) from mixed dishes than FFS adults. MFS
consumed the largest amounts of calories and fat from meat/poultry, grain-based,
Mexican, and pizza dishes among all groups. LFS and VLFS consumed a large proportion
of calories and fat of mixed dishes from meat/poultry, grain-based, pizza, and sandwich
dishes. FFS adults consumed the most from grain-based and pizza dishes and had the
lowest intakes from these subcategories among all groups.
Protein Foods
On top of the nearly one-third of total protein intakes (32-36%), Protein foods
accounted for 15-17% of total caloric intakes and 25-27% of total fat intakes, regardless
of FS status. LFS adults consumed the most grams, calories, fat, and protein from
37
protein foods, which were primarily consumed from meats, poultry, and cured
meats/poultry. FFS adults consumed the second highest amount (grams), calories, and
fat from protein foods, although consumed more calories and fat from plant-based
protein foods than any other group. FFS adults consumed a wider variety and balance of
subcategories of protein foods, including less meat and poultry, and more seafood and
plant-based protein foods. VLFS adults consumed slightly less grams, calories, and fat
from protein foods than FFS adults, although the food subcategories were noticeably
different. VLFS adults consumed the most grams, calories, and fat from poultry. VLFS
adults also consumed a large proportion of calories and fat from meats and cured
meats. The MFS group consumed the least amount of grams, calories, and fat from
protein foods, with meat, poultry, and cured meats as the primary sources of energy
and fat from protein foods.
Grains
Grains accounted for roughly 12-15% of the total daily energy, 11% of total
protein, 20% of total carbohydrate, and 7.5% of the total fat intakes. FFS and LFS adults
consumed significantly more grams from grains than VLFS adults (P=0.038), although LFS
adults consumed significantly more calories from grains than both FFS and VLFS adults
(P=0.013). A majority of grain consumption was attributed to breads, rolls, and tortillas
and cooked grains for all FS groups. LFS adults consumed the most of breads, rolls, and
tortillas (67.7 grams), nearly 10% of their total caloric intake, while VLFS consumed the
least amount from breads, rolls, and tortillas (54.5 grams), 7.4% of their total energy
intakes. FFS adults consumed a wider variety of categories from grains, including a
38
higher intake of cooked cereals and ready-to-eat cereals than any other group. MFS
adults obtained a moderate amount of energy from grains compared to the other
groups, but also received a majority of nutrients from breads, rolls, and tortillas.
FFS adults had the highest overall intakes of protein from grains (8.5 grams);
significantly more than MFS (7.7 grams) and VLFS (7.3 grams) adults, while LFS (8.4
grams) consumed significantly more protein than VLFS adults (P=<0.001).
Snacks and Sweets
The amount (grams) consumed from snacks and sweets were a minimal
percentage of the overall diet, accounting for roughly 3% of the daily intakes, although
they contributed to a considerable percentage to daily caloric (14%), fat (16.5%), protein
(6.5%), and carbohydrate (15.7%) totals.
There was a U-shape pattern of grams, calories, fat, protein and carbohydrate
consumed from snacks and sweets among food security groups. FFS adults consumed
significantly more grams (P=0.004), calories (P=0.005), protein (P=<0.001), fat (P=0.024),
and carbohydrate (P=0.004) than MFS, and significantly more grams, protein, and fat
than LFS. Sweet bakery products and savory snacks contributed to a large proportion of
the calories, fat and carbohydrate from snacks and sweets, although FFS and VLFS adults
consumed a larger amounts of these subcategories compared to MFS and LFS adults
Non-Alcoholic Beverages
Non-alcoholic beverages were a large contributor to energy and carbohydrates
in the diet, accounting for 8%-13% of the total energy intakes. VLFS adults consumed
significantly more grams than FFS and MFS adults (P=0.016). MFS, LFS, and VLFS adults
39
consumed a considerable amount of sweetened beverages, which contributed
noticeably to calorie and carbohydrate totals. MFS, LFS, and VLFS consumed significantly
more energy and carbohydrates from non-alcoholic beverages than did FFS (P=<0.001).
Nearly 10% of energy intakes and 17% of carbohydrate intakes for MFS, LFS, and VLFS
was attributed to sweetened beverages, while FFS only consumed 5.7% and 10.6% of
energy and carbohydrates, respectively, from sweetened beverages. LFS and VLFS adults
also consumed more of 100% fruit juice than FFS and MFS adults. FFS consumed a
majority of grams from coffee and tea, which is not a large contributor of calories or
carbohydrate.
Milk and Dairy
Milk and dairy accounted for less than 10% of the total caloric, fat, and
carbohydrate intakes among all groups, and slightly over 10% of the total protein
intakes. Only protein intakes from milk and dairy were significantly different among FS
groups. FFS adults consumed significantly more protein from milk and dairy products
than MFS and LFS (P=<0.001). There is a U-shape pattern in amounts (grams) and energy
consumed from milk and dairy, with FFS and VLFS consuming the largest amounts. Both
FFS and VLFS adults consumed a majority of milk and dairy nutrients from milk and
cheese, yet FFS adults consumed more of yogurt, while VLFS consumed more of flavored
milk. FFS adults consumed more grams from milk than VLFS adults, 139.6 grams
compared to 137.0 grams, respectively, VLFS adults consumed more calories (69.0 vs
64.8 kcals) and fat (2.8 vs. 2.2 grams) from milk than FFS adults. MFS consumed the least
40
amount of grams and calories from milk and dairy, including the least amount of milk
and cheese, yet consumed more yogurt than LFS and VLFS adults.
Fruits and Vegetables
Overall, fruits and vegetable consumption accounted for a small proportion of
the dietary grams, energy, or protein. FFS adults consumed significantly more grams and
calories from fruit than MFS, LFS, and VLFS adults (P=<0.001) and significantly more
grams (P=<0.001), calories (P=0.029), and protein (P=<0.001) from vegetables than LFS.
VLFS adults had the lowest intakes of grams and calories from fruit. There is a U-shape
pattern of grams, calories, and protein from vegetables (excluding potatoes) among the
food security groups, while FFS and MFS adults consumed more white potatoes than LFS
and VLFS.
Fats and Oils/Condiments/Sugars
After combining totals for fats and oils, condiments, and sugars, mean intakes
accounted for approximately 5% of overall caloric intake. Fats and oils contributed
roughly 6-9% of total daily fat intakes. FFS adults consumed significantly more calories
and fat from fats and oils than all other groups (p=<0.001). Apart from the total fat
percentage from fats and oils, these domains have a minimal role in total nutrients of
the intake.
Discussion
Dietary patterns among food insecure adults are not well established in
the literature, but rather collectively have been generalized to state that food insecure
adults consume lower quality diets without informative details. The need for an outline
41
of dietary patterns has been acknowledged as an area of high-importance to further
promote and target appropriate interventions for specific groups (12). These data
support dietary quality differences among food security groups regarding the
understanding that those who are food insecure consume lower-quality diets, but also
describe the dietary patterns contributing to macronutrient from specific food domains
among food security status groups.
Diet Quality
The lower intakes of fruit and vegetables, higher intakes of sugar
sweetened beverages, high-fat protein foods and milk and dairy products, and energydense grains among LFS and VLFS adults is consistent with the findings that those who
are less food secure consume a lower quality diet (20;35). Findings that indicated diet
quality is compromised due to food insecurity and results in higher intake of energy
from foods that are higher in fat and carbohydrate is supported by our findings of higher
fat and carbohydrate intakes from mixed dishes and protein foods, specifically poultry
and cured meats, among those who were very low food secure (1). The lower intakes of
fruits and vegetables among LFS and VLFS adults are consistent with the findings that
fruits and vegetables are initially sacrificed when approaching food insecurity (36),
potentially due to the higher food prices of fruits and vegetables (15).
Energy Density and Food price
Intakes of fruits, vegetables, snacks and sweets, and sweetened
beverages among those who are food insecure and the association to food price has
been well-established in the literature and is supported by our results that indicated
42
VLFS adults consumed nearly 10% from sweetened beverages, 14% from snacks and
sweets, which are concentrated sources of energy, while only 2% from fruits, 5% from
vegetables, and 7% from milk and dairy, which tend to have lower energy density
(6;14;15;28). Energy density and food price have been thought to take priority over
quality of nutrients for individuals during a time of food insecurity and is consistent with
our findings that indicated VLFS adults consumed less grams from milk than FFS adults,
yet more energy and fat, supporting the findings that high-fat, energy-dense diets may
be related to a reduction of diet costs (15). VLFS adults had the second highest intakes
from snacks and sweets, which the literature attributes to the high-energy density, high
satiety, less preparation time, and convenience for disadvantaged populations (14;15).In
contrary to findings that indicate food insecure individuals consume more energy dense
foods, our results indicated that overall, FFS adults consumed the most total energy and
fat from snacks and sweets among all groups, which may be due to the high palatability
and enjoyment associated with foods with added fat and sugar, rather than a need for
more energy-density per dollar (15).
Our study provided additional insight of patterns that have not been recognized
in the literature that further support the relationship observed between energy-density
and energy-cost and intakes among those who are food insecure. The overall large
proportion of nutrients from mixed dishes, protein foods, and grains demonstrate highimportance among food security groups, but also revealed patterns that support
findings of compromised diet quality due to food insecurity (1). Mixed dishes collectively
contributed to one-fifth of the total energy, yet contributed to more nutrients and a
43
larger proportion of the overall diet for those who were more food insecure, in addition
to abundant macronutrients, such as carbohydrate and fat, which is indicated as a
common finding during periods of food insecurity (1). Mixed dishes seem to be of high
importance to those who were more food insecure in order to obtain adequate energy
for a lowered cost, which again, is very well stated in the literature (1;15;20).
The overall intakes of protein foods among FS groups were not drastically
different, yet VLFS adults consumed greater amounts of calories, fat, and carbohydrate
from poultry, indicating consumption of breaded or fried chicken, thus consuming a
high-energy density, while FFS adults consumed similar amounts (grams) of poultry but
less calories, fat, and carbohydrates, indicating they consumed leaner sources of
poultry. This is consistent with other findings that quality of food choices becomes of
lower importance when facing food insecurity, and quantity of energy per dollar
becomes the highest concern (1). Further supporting this evidence, FFS adults also had a
more balanced intake of protein foods, including higher intakes from fish and plantbased foods, while MFS, LFS, and VLFS adults had higher intakes from meats, and cured
meat.
LFS adults consumed a similar amount (grams) of grains as FFS adults, yet LFS
adults consumed significantly more calories than FFS adults, which indicated that LFS
adults consumed lower-quality grains with added sugar and fat and less fiber, which
supports findings that sugar, refined grains, and added fats represent some of the
lowest-cost options and provide dietary energy at low costs (15).
44
In sum, the patterns among food security groups regarding food domain,
category, and macronutrient intakes that are established in our results support a
hypothesis proposed by Drewnowski and Spectar that documents, “selection of energydense foods by food insecure individuals may represent a deliberate strategy to save
money” (15), thus resulting in a lower quality diet for those who are more food
insecure.
Food Assistance
Food assistance programs have been established as an important resource for
those who are more food insecure, which is consistent with our results that show the Ushape patterns of intakes among food security groups observed from milk and dairy,
protein foods, and fruit domains (12;23). While food assistance programs have been
shown to improve diet quality in those who are food insecure and are imperative
aspects to interventions, food supplies may only last three days to one week, thus
having little effect in improving food security in those who are VLFS (12). The little
impact food assistance programs have on LFS and VLFS adult’s food security status
further supports our discussion on why food insecure individuals may predominately
rely on energy-dense foods, such as mixed dishes, to supply adequate energy (12;15).
Health Literacy
Individuals with lower health literacy have consistently been associated with
households of lower-incomes, which are more likely to be food insecure, and lower HEI
scores (37;38). The higher intakes of sugar sweetened beverages among those who
were more food insecure from our study are congruent to the findings that documented
45
with every one point increase in health literacy score was associated with thirty-four
fewer kcal per day from sugar sweetened beverages (37). More studies are needed to
assess health literacy among those who are food insecure and dietary quality (37).
Implications: The Hunger-Obesity Paradox
The relationship between increased risk of obesity and food insecurity has been
well established in the literature, and was supported by the dietary patterns outlined in
this study, which showed those who were more food insecure consumed lower quality
diets compared to those who were fully food secure (1;12;20;39;40). Understanding the
dietary patterns among food security groups is vital to decreasing the numerous health
outcomes associated with those who are food insecure.
Interventions and Future Application
Interventions and studies have overwhelmingly targeted reduction of snacks and
sweets, beverages, fat and oils, and increased intakes of fruits and vegetables for
reducing obesity by dietary choices (1011, 1036, 1032}, which have been documented as
important measures in our study as well, but may not be realistic for those who are
more food insecure and cannot afford to lose one-fourth of their daily energy (snacks
and sweets and sweetened beverages) and replace fully with low-energy density fruits
and vegetables. Interventions as such are likely to be ineffective in which high-risk
groups are not exclusively accounted (14).
The substantial contribution of calories to the diet from mixed dishes, protein
foods, and grains observed in this study indicate that these domains may be of higher
46
importance and have a greater impact during planned interventions for food insecure
individuals.
These data should assist in developing targeted interventions that focus on
promoting realistic and appropriate dietary options, education, and assistance to the
intended population. Our understanding is in congruence with the literature that argues
the need for promotion of planned dietary interventions that address behaviors
regarding the specific population and options that are reasonable with their given
resources (12;14).
The data from the present study have specific limitations that must be
considered in the interpretation of the findings. It is important to reiterate the
limitations related to 24-hour dietary recall; under- and overreporting of food intakes
may occur and intakes may be somewhat flawed. Also, food insecurity is assessed based
on episodes during a year. Individuals may experience acute or chronic periods of food
insecurity, therefore dietary intakes may have been taken during a time of food security
and provide an inaccurate representation of intakes during food insecure periods.
Conclusions and Implications
This study demonstrates that food insecure individuals consumed higher energy
density and low quality food sources from mixed dishes, protein foods, grains, snacks
and sweets, and non-alcoholic beverages than those who are more food insecure. In
effort to reduce the overweight, obesity, and chronic disease rates in those who are
food insecure, nutrition interventions may need to focus on the food domains that
contribute majority of nutrients in a method that is realistic for the targeted audience.
47
Future research involving analysis of additional nutrients among food domains and
categories is needed to better understand the dietary patterns and nutrient quality of
energy.
48
Chapter 5: Differences in Dietary Intakes of United States Adults from NHANES by
Food Security Status
ABSTRACT
Objective: To determine the patterns in nutrient intakes of the US Adult population by
food security status.
Design: A cross-sectional study of adults from the 2005-2010 National Health and
Nutrition Examines Survey
Setting: Dietary recall data and food security status were obtained in mobile exam
centers.
Participants: A total of 16,625 US Adults, aged 18 years and older
Variables Measured: Dietary intake data from 24-hour dietary recalls were used to
assess the sources and amounts of nutrients consumed. Food security status was used
to classify participants into food security groups.
Statistical analysis performed: The means, standard deviations, and percentages were
calculated to describe nutrient intakes obtained from domains and categories by food
security status was determined by linking individual food files to USDA What We Eat In
America Food Categories. Chi-square analysis by food security status was used to
determine the differences between nutrient intakes and food security groups. Total
49
nutrient intakes from each of the food groups will be aggregated per person for a total
intake from each group per person per day. Significant differences in the consumption
of key nutrients obtained from domains were tested using one-way, ANOVA.
Significance established a priori at P<0.05.
Results: American adults obtained a large proportion of nutrients from mixed dishes,
protein foods, grains, snacks and sweets, and non-alcoholic beverages, and minimal
nutrients from fruits, vegetables, milk and dairy, fats and oils, condiments and sauces,
and sugars. Those who were more food insecure consumed foods with high-energydensity and of lower quality compared to those who were fully food secure.
Conclusions and Implications: US Adults who were more food insecure consumed
lower quality diets than those who were fully food secure. Dietary patterns are critical
to understanding the sources of food among food security groups and are paramount in
targeting interventions to help improve health outcomes of food insecure adults.
50
Introduction
Food insecurity continues to affect millions of households across the United
States (3;13). The overall percentage of US population who are food insecure has
increased since 1995 (3). The percentage of US households that were food insecure has
increased from 11.1% in 2002 to 14.5% in 2012 (3). It has been well documented that
food security status is a major predictor of diet quality (35), with those who were more
food insecure being associated with consumption lower quality diets (6;20;35). Zizza et
al documented that there were no differences in the energy intakes between food
secure and food insecure adults, yet the meal and snack behaviors differed (41); food
insecure individuals were more likely to have inadequate intakes of key nutrients (41).
Bhattacharya et al also suggested that food insecure individuals don’t consume too
much energy, but too much of the wrong sort of calories (6). Specific patterns have been
the focus of recent research and interventions, such as intakes of fruits, vegetables,
snacks and sweets, sweetened beverages, but actual dietary intakes are not well
established (20;30;42). Our results determine the actual intakes from each food security
groups to further understand the dietary patterns and have determined new findings
that have not been recognized in the literature.
The relationship between energy density and food price is one that will be
discussed for the purpose of understanding the factors influencing the patterns we
observed. This relationship is important when considering interventions targeted
towards specific populations due to the impact food cost have on consumer’s dietary
choices. Relationships have been well documented between energy density and food
51
price, where higher energy density foods are available at lowered price (14;15;19;42).
Energy-dense foods are commonly more palatable and composed of primarily refined
grains, added sugars, and fat, and have been referred to as “obesity-promoting”, while
low-energy-dense foods usually provide less energy and more nutrients but are more
expensive, and align more closely with the USDA Dietary Guidelines (2;15;42).
Drewnowski and Spectar indicated that “healthier diets cost more and are beyond the
reach of many low-income families,” (15), which are more likely to food insecure.
Interventions that focus on increasing fruits and vegetables may not be realistic for
those who are food insecure and must expand their dollar to receive the most calories
(12;15).
As a consequence of the relationship between food security status and diet
quality, food insecure individuals are at an increased risk for overweight (4), obesity
(6;20), and chronic disease (35). Individuals of food insecure households may be at an
increased risk due to consumption of diets that are deficient in particular food groups
and nutrients (6;14;15;20).
However, little has been documented on the specific dietary patterns across FI
groups. A deeper understanding of these patterns is paramount to explaining the
relationship between food insecurity and nutritional adequacy (12;32), which is vital to
creating successful interventions that specifically target food insecure individuals to
improve health outcomes (14;20). Lack of understanding of dietary patterns among food
security groups may result in ineffective interventions. Public health interventions
targeting obesity have not focused on high-risk groups, but rather have promoted
52
interventions that apply more directly to lower risk individuals (30), therefore having
little to no effect on high-risk groups (30). Darmon and Drewnowski (2008) examined an
intervention that promoted high-cost foods to low-income groups without taking food
costs into account, and noted that it had limited success rates (14). These data present
dietary patterns that may help to maximize the outcomes of dietary interventions for
food insecure individuals through targeting food domains and categories of high
importance.
Little data exists to describe the potential dietary patterns that produce the
differences in nutritional adequacy. This information may provide insight on dietary
patterns among food security groups and help to focus future nutrition intervention
efforts. The relationship among food insecurity, low diet quality, obesity, and chronic
disease is likely to remain without proper intervention (30). Food insecure individuals
are at an increased risk for poor health outcomes due to consumption of a low quality
diet, thus the purpose of this study was to determine the patterns in nutrient intakes of
the US Adult population by food security status.
Methods
Data from NHANES 2005-2010 were obtained to identify food security status and
food sources of American adults. NHANES assesses the health and nutritional status of
US adults and children by using a series of surveys, interviews and physical
examinations. Demographic, socioeconomic, dietary, and health related questions are
asked during the interviews, while medical, dental, physiological, and anthropometric
53
measurements and laboratory tests are administered by highly trained personnel during
the physical examination.
Dietary Assessment
Detailed dietary intake information was acquired in the MEC using an in-person
24-hour dietary recall using a trained interviewer. The collected data are used to
estimate the intakes of energy, nutrients, and other food components from the food
and beverages consumed during the midnight-to-midnight 24-hour period prior to the
interview.
Individual foods files (IFF) were produced using the information collected from
the dietary interviews. IFF contain information regarding food, water, or beverage
identified by a USDA food code, amount of food, water, beverage consumed, in grams,
and amounts of energy and 63 nutrients/food components from each food, calculated
using USDA’s FNDDS.
Food Security Status
Food Security Status was collected during household interviews. The US FSSM
was used to collect household food security status among adults. There are 18 items for
households with children under the age of 18 years old and 10 items for household
without children. Questions asked refer to all members of the household. Overall food
security was divided into three categories: food security status for the entire household,
the adults in the household, and the children in the household. This study will focus on
the food security of entire households and adults.
54
Individual food security questions were asked to all survey participants in the
households that confirmed any FSSM item during the household interview. Individuallevel food security questions were asked after the 24-hour dietary recall in the Mobile
Examination Center (MEC). Data were provided as 4 levels of food insecurity: FFS, MFS,
LFS, and VLFS based on the number of affirmative items.
Data Preparation
The WWEIA Food Categories established by the USDA allow for researchers to
interpret and analyze food and beverage consumption patterns in the United States
(Table 5). To evaluate the food group sources of key nutrients, foods reported in the IFF
were linked to the USDA Food Categories described above. Key nutrients used in these
will include grams, calories, total fat, protein, and carbohydrate. Total nutrient intakes
from each of the food groups will be aggregated per person for a total intake from each
group per person per day.
To identify the proportion of individuals who consume food from each of the
domains and categories, those with total gram consumption >0 will be classified as
consumers.
Statistical Analysis
To evaluate the proportion of individuals that consumed food from the domains,
chi square analyses will be conducted by food security status and income.
Means and standard deviations will be generated to describe nutrient intakes
obtained from domains and categories by food security and income levels. Significant
55
differences in the consumption of key nutrients obtains from domains were tested using
one-way ANOVA. Significance established a priori at P<0.05.
Results
Study Participants
A total of 16,625 subjects with dietary intake data were included in the
study and classified as fully food secure (FFS), marginally food secure (MFS), low food
security (LFS), and very low food security (VLFS). The study included 12,007 (72.2%)
participants who were fully food secure, 1,698 (10.2%) marginally food secure, 1,886
(11.3%) low food secure, and 1034 (6.2%) very low food secure. Mean intakes of key
nutrients among food security status groups for grams, calories, fat, protein, and
carbohydrate consumed from food domains and categories are presented in Appendices
A through E, respectively. Significant differences were calculated for nutrient intakes
between each food security status group and food domain.
Participant Proportions by Food Security and Food Domain
Mixed dishes, protein foods, grains, snacks and sweets, and non-alcoholic
beverages were the main contributors of nutrients in the diet. VLFS adults consumed
greater amounts (grams) of mixed dishes and FFS presented with the lowest intakes of
mixed dishes. VLFS adults had the highest daily percentages of calories and fat from
mixed dishes. MFS adults consumed significantly more calories (P=0.03) and fat
(P=0.035) from mixed dishes than FFS adults. LFS and VLFS consumed a large proportion
of calories and fat of mixed dishes from meat/poultry, grain-based, pizza, and sandwich
dishes. MFS consumed the largest amounts of calories and fat from meat/poultry, grain56
based, Mexican, and pizza dishes among all groups. FFS adults consumed the most from
grain-based and pizza dishes and had the lowest intakes from these subcategories
among all groups.
LFS adults consumed the most grams, calories, fat, and protein from protein
foods; primarily from meats, poultry, and cured meats/poultry. FFS adults consumed a
wider variety and balance of subcategories of protein foods, including less meat and
poultry, and more seafood and plant-based protein foods. VLFS adults consumed slightly
less grams, calories, and fat from protein foods than FFS adults, although consumed the
most grams, calories, and fat from poultry, in addition to a large proportion from meats
and cured meats. The MFS group consumed the least amount of grams, calories, and fat
from protein foods, with meat, poultry, and cured meats as the primary sources of
energy and fat from protein foods.
FFS and LFS adults consumed significantly more grams from grains than VLFS
adults (P=0.038), although LFS adults consumed significantly more calories from grains
than both FFS and VLFS adults (P=0.013). LFS adults consumed the most of breads, rolls,
and tortillas (67.7 grams), nearly 10% of their total caloric intake, while FFS adults
consumed a wider variety, incorporating more cooked cereals and ready-to-eat cereals.
MFS adults obtained a moderate amount of energy from grains compared to the other
groups, but also received a majority of nutrients from breads, rolls, and tortillas.
There was a U-shaped pattern of grams, calories, fat, protein and carbohydrate
consumed from snacks and sweets among food security groups. FFS adults consumed
significantly more grams (P=0.004), calories (P=0.005), protein (P=<0.001), fat (P=0.024),
57
and carbohydrate (P=0.004) than MFS, and significantly more grams, protein, and fat
than LFS. Sweet bakery products and savory snacks contributed to a large proportion of
the calories, fat and carbohydrate from snacks and sweets, although FFS and VLFS adults
consumed a larger amounts of these subcategories compared to MFS and LFS adults.
MFS, LFS, and VLFS consumed significantly more energy and carbohydrates from
non-alcoholic beverages than did FFS (P=<0.001). Nearly 10% of energy intakes and 17%
of carbohydrate intakes for MFS, LFS, and VLFS was attributed to sweetened beverages,
while FFS only consumed 5.7% and 10.6% of energy and carbohydrates, respectively,
from sweetened beverages.
Milk and dairy, fruits and vegetables, fats and oils, condiments, and sugar
contributed minimal nutrients in the diet. There is a U-shape pattern in amounts (grams)
and energy consumed from milk and dairy, with FFS and VLFS consuming the largest
amounts. Milk and cheese were the most consumed categories for both groups. FFS
adults consumed more grams from milk than VLFS adults; however, VLFS adults
consumed more calories and fat from milk than FFS adults. FFS adults consumed more
of yogurt, while VLFS consumed more of flavored milk. MFS consumed the least amount
of grams and calories from milk and dairy.
FFS adults consumed significantly more grams and calories from fruit than MFS,
LFS, and VLFS adults (P=<0.001) and significantly more grams (P=<0.001), calories
(P=0.029), and protein (P=<0.001) from vegetables than LFS. VLFS adults had the lowest
intakes of grams and calories from fruit. There is a U-shape pattern of grams, calories,
and protein from vegetables (excluding potatoes) among the food security groups.
58
FFS adults consumed significantly more calories and fat from fats and oils than all
other groups (p=<0.001). Apart from the total fat percentage from fats and oils, fats and
oils, condiments, and sugars have a minimal role in total nutrients of the intake.
Discussion
Specific dietary patterns among food insecure adults are not thoroughly outlined
in the literature, but rather collectively generalized to state that food insecure adults
consume lower quality diets, without informative details. The need for an outline of
dietary patterns has been acknowledged as an area of high-importance to further
promote and target appropriate interventions for specific groups (12). These data
support dietary quality differences among food security groups regarding the
understanding that those who are food insecure consume lower-quality diets, but also
describe the dietary patterns contributing to macronutrient from specific food domains
among food security status groups.
Diet Quality
The 2010 USDA Dietary Guidelines were used as an indicator of diet
quality (2) for the dietary patterns observed in this study. The lower intakes of fruit and
vegetables, larger proportion of total energy, fat, and carbohydrate from mixed dishes,
energy-dense grains, greater intakes of high-fat protein food and milk and dairy
products, and higher intakes of sugar sweetened beverages among LFS and VLFS adults
is consistent with the findings that those who are less food secure consume a lower
quality diet than those who are fully food secure (20;35). Findings that indicated diet
quality is compromised due to food insecurity (6;35) and results in higher intake of
59
energy from foods that are higher in fat and carbohydrate (36) is supported by our
findings of higher fat and carbohydrate intakes from mixed dishes and protein foods,
specifically poultry and cured meats, among those who were very low food secure. The
lower intakes of fruits and vegetables among LFS and VLFS adults are consistent with the
findings that fruits and vegetables are initially sacrificed when approaching food
insecurity (12), potentially due to the higher food prices of fruits and vegetables (15).
Energy Density and Food Price
Higher intakes of snacks and sweets and sweetened beverages, and lower
intakes of fruits, vegetables, and low-fat milk and dairy products among those who are
food insecure due to food price (14;15;28) has been established in the literature, and is
supported by our results that indicated VLFS adults consumed nearly 14% of total
energy from snacks and sweets, 10% from sweetened beverages, while only 2% from
fruits, 5% from vegetables, and 7% from milk and dairy. Energy density and food price
have been thought to take priority over nutrient-density for individuals during a time of
food insecurity (28), and is consistent with our findings that indicated VLFS adults
consumed less grams from milk than FFS adults, yet more energy and fat, supporting the
findings that high-fat, energy-dense diets may be related to a reduction of food price
(15). VLFS adults had the second highest intakes from snacks and sweets, which the
literature attributes to the high-energy density and high satiety (15), and less
preparation time and convenience (14). Contrary to findings that indicate food insecure
individuals consume more energy dense foods, our results indicated that overall, FFS
adults consumed the most total energy and fat from snacks and sweets among all
60
groups, which may be due to the high palatability and enjoyment associated with foods
with added fat and sugar, rather than a need for more energy-density and reduced cost
(15).
Our study provided additional insight of patterns that have not been recognized
in the literature that further support the relationship observed between energy-density
and energy-cost and intakes among those who are food insecure. The overall large
proportion of nutrients from mixed dishes, protein foods, and grains demonstrate highimportance among food security groups, but also revealed patterns that support
findings of compromised diet quality due to food insecurity (35) and food price (15).
Mixed dishes collectively contributed to one-fifth of the total energy, yet contributed to
more nutrients and a larger proportion of the overall diet for those who were more food
insecure, in addition to abundant macronutrients, such as carbohydrate and fat, which is
indicated as a common theme during periods of food insecurity due to the concentrated
energy of mixed dishes (1). Mixed dishes seem to be of high importance for those who
were more food insecure, in order to obtain adequate energy for a lowered cost (15;20).
The overall intakes of protein foods among FS groups were not drastically
different, yet VLFS adults consumed greater amounts of calories, fat, and carbohydrate
from poultry, indicating consumption of breaded or fried chicken, thus consuming a
high-energy density, while FFS adults consumed similar amounts (grams) of poultry but
less calories, fat, and carbohydrates, indicating they consumed leaner sources of
poultry. This is consistent with other findings that quality of food choices becomes of
lower importance when facing food insecurity, and quantity of energy per dollar
61
becomes the highest concern (1). Further supporting this evidence, FFS adults also had
more balanced intakes of protein foods, including higher intakes from fish and plantbased foods, while MFS, LFS, and VLFS adults had higher intakes from meats, and cured
meat.
LFS adults consumed a similar amount (grams) of grains as FFS adults, yet LFS
adults consumed significantly more calories than FFS adults, which indicated that LFS
adults consumed lower-quality grains with added sugar and fat and less fiber, which
supports findings that sugar, refined grains, and added fats represent some of the
lowest-cost options and provide dietary energy at low costs (15).
In sum, the patterns among food security groups regarding food domain,
category, and macronutrient intakes that are established in our results support a
hypothesis proposed by Drewnowski and Spectar that documents, “selection of energydense foods by food insecure individuals may represent a deliberate strategy to save
money” (15), thus resulting in a lower quality diet for those who are more food
insecure.
Implications of Differences in Dietary Patterns
The lower quality dietary patterns of food insecure adults outlined in this
study support the relationship that has been recognized among increased risk of
overweight (4), obesity (1;6) and chronic disease (35) and food insecurity.
Understanding dietary patterns of those who were more food insecure may be vital to
improving the health outcomes in order to create effective and targeted dietary
interventions. Interventions have targeted reduction of snacks and sweets, beverages,
62
and increased intakes of fruits and vegetables for improving dietary quality of food
insecure individuals (15;16;30), which have also been documented as important dietary
patterns in our study; the substantial contribution of calories to the diet from mixed
dishes, protein foods, and grains observed in this study indicate that these domains may
be of higher importance and have a greater impact during planned interventions for
food insecure individuals.
Interventions that focus solely on increasing low-energy dense foods, such as
fruits and vegetables, and decreasing high-energy dense foods, such as snacks and
sweets, are likely to be ineffective in making significant dietary changes, because the
high-risk group’s resources and means are not exclusively accounted (14).
These data should assist in developing targeted interventions that focus on
promoting realistic and appropriate dietary options, education, and assistance to the
intended population. Our understanding is in congruence with the literature that argues
the need for promotion of planned dietary interventions that address behaviors
regarding the specific population and options that are reasonable with their given
resources (12;14).
The data from the present study have specific limitations that must be
considered in the interpretation of the findings. It is important to reiterate the
limitations related to 24-hour dietary recall; under- and overreporting of food intakes
may occur and intakes may be somewhat flawed. Food insecurity is assessed based on
episodes during a year. Individuals may experience acute or chronic periods of food
insecurity, therefore dietary intakes may have been taken during a time of food security
63
and provide an inaccurate representation of intakes during food insecure periods. We
also did not measure specific nutrients that are of high-importance to specific food
domains, such as fiber for grains, and could reveal more about the quality of domain
and category intakes. These nutrients should be considered for future research.
Conclusions and Implications
This study demonstrated that food insecure individuals consumed higher
energy density and lower quality foods from mixed dishes, protein foods, grains, snacks
and sweets, and non-alcoholic beverages than those who are more food secure. In
effort to reduce the overweight, obesity, and chronic disease rates in those who are
food insecure, nutrition interventions may need to focus on the food domains that
contribute majority of nutrients in a method that accounts for the targeted audience.
Future research involving analysis of additional nutrients among food domains and
categories is needed to better understand the dietary patterns and nutrient quality of
energy.
64
Domains
Milk and dairy
Protein foods
Mixed dishes
Grains
Snacks and sweets
Fruit
Vegetables
Beverages, nonalcoholic
Alcoholic beverages
Water
Fats and oils
Condiments and sauces
Sugars
Infant formula
& baby food
Categories
Milk
Flavored Milk
Dairy Drinks and Substitutes
Cheese
Yogurt
Meats
Poultry
Seafood
Eggs
Cured Meats/Poultry
Plant-based Protein Foods
Meat, Poultry, Seafood Pizza
Grain-based
Sandwiches (single code)
Asian
Mixed Dishes – Soups
Mexican
Cooked Grains
Breads, Rolls, Tortillas
Quick Breads and Bread Products
Ready-to-Eat Cereals
Cooked Cereals
Savory Snacks
Crackers
Snack/Meal Bars
Sweet Bakery Products
Candy
Other Desserts
Fruits
Vegetables, excluding Potatoes
White Potatoes
100% Juice
Diet Beverages
Sweetened Beverages
Coffee and Tea
Alcoholic Beverages
Plain Water
Flavored or Enhanced Water
Fats and Oils
Condiments and Sauces
Sugars
Baby Foods
Baby Beverages
Infant Formulas
Table 5: What We Eat in America USDA Food Categories 2001-2010
65
Reference List
1. Tanumihardjo SA, Anderson C, Kaufer-Horwitz M et al. Poverty, obesity, and
malnutrition: an international perspective recognizing the paradox. J Am Diet
Assoc 2007;107:1966-72.
2. U.S. Department of Agriculture and U.S. Department of Health and Human Services.
Dietary Guidelines for Americans, 2010. 7th Edition, Washington, DC: U.S.
Government Printing Office, December 2010.
3. US Department of Agriculture Economic Research Service. Food Security in the U.S.
Avaliable at: http://www.ers.usda.gov/topics/food-nutrition-assistance/foodsecurity-in-the-us/key-statistics-graphics.aspx Accessed: 15 April 2014.
4. Townsend MS, Peerson J, Love B, Achterberg C, Murphy SP. Food insecurity is
positively related to overweight in women. J Nutr 2001;131:1738-45.
5. US Census Bureau. State and County Quick Facts. Available at:
http://quickfacts.census.gov/qfd/index.html. Aceesed: 14 April 2014.
6. Bhattacharya J, Currie J, Haider S. Poverty, food insecurity, and nutritional outcomes
in children and adults. J Health Econ 2004;23:839-62.
7. Rose D. Economic determinants and dietary consequences of food insecurity in the
United States. J Nutr 1999;129:517S-20S.
8. Bowman S. Low economic status is associated with suboptimal intakes of nutritious
foods by adults in the National Health and Nutrition Examination Survey 19992002. Nutrition Research 2007;27:515-23.
9. Guthrie JF, Lin BH. Overview of the diets of lower- and higher-income elderly and
their food assistance options. J Nutr Educ Behav 2002;34 Suppl 1:S31-S41.
10. Nord M. How much does the Supplemental Nutrition Assistance Program alleviate
food insecurity? Evidence from recent programme leavers. Public Health Nutr
2012;15:811-7.
66
11. Furness BW, Simon PA, Wold CM, Asarian-Anderson J. Prevalence and predictors of
food insecurity among low-income households in Los Angeles County. Public
Health Nutr 2004;7:791-4.
12. Holben DH. Position of the American Dietetic Association: food insecurity in the
United States. J Am Diet Assoc 2010;110:1368-77.
13. Coleman-Jensen, Alisha, Mark Nord, and Anita Singh. Household Food Security in the
United States in 2012, ERR-155, U.S. Department of Agriculture, Economic
Research Service, September 2013.
14. Darmon N, Drewnowski A. Does social class predict diet quality? Am J Clin Nutr
2008;87:1107-17.
15. Drewnowski A, Specter SE. Poverty and obesity: the role of energy density and
energy costs. Am J Clin Nutr 2004;79:6-16.
16. Akobundu UO, Cohen NL, Laus MJ, Schulte MJ, Soussloff MN. Vitamins A and C,
calcium, fruit, and dairy products are limited in food pantries. J Am Diet Assoc
2004;104:811-3.
17. Middaugh AL, Fisk PS, Brunt A, Rhee YS. Few associations between income and fruit
and vegetable consumption. J Nutr Educ Behav 2012;44:196-203.
18. Krebs-Smith SM, Guenther PM, Subar AF, Kirkpatrick SI, Dodd KW. Americans do not
meet federal dietary recommendations. J Nutr 2010;140:1832-8.
19. Monsivais P, Aggarwal A, Drewnowski A. Are socio-economic disparities in diet
quality explained by diet cost? J Epidemiol Community Health 2012;66:530-5.
20. Pan L, Sherry B, Njai R, Blanck HM. Food insecurity is associated with obesity among
US adults in 12 states. J Acad Nutr Diet 2012;112:1403-9.
21. Dixon LB, Winkleby MA, Radimer KL. Dietary intakes and serum nutrients differ
between adults from food-insufficient and food-sufficient families: Third National
Health and Nutrition Examination Survey, 1988-1994. J Nutr 2001;131:1232-46.
22. Beydoun MA, Wang Y. How do socio-economic status, perceived economic barriers
and nutritional benefits affect quality of dietary intake among US adults? Eur J Clin
Nutr 2008;62:303-13.
23. Robaina KA, Martin KS. Food insecurity, poor diet quality, and obesity among food
pantry participants in Hartford, CT. J Nutr Educ Behav 2013;45:159-64.
67
24. O'Neil CE, Zanovec M, Cho SS, Nicklas TA. Whole grain and fiber consumption are
associated with lower body weight measures in US adults: National Health and
Nutrition Examination Survey 1999-2004. Nutr Res 2010;30:815-22.
25. Leung CW, Ding EL, Catalano PJ, Villamor E, Rimm EB, Willett WC. Dietary intake and
dietary quality of low-income adults in the Supplemental Nutrition Assistance
Program. Am J Clin Nutr 2012;96:977-88.
26. Cordain L, Eaton SB, Sebastian A et al. Origins and evolution of the Western diet:
health implications for the 21st century. Am J Clin Nutr 2005;81:341-54.
27. Rose D, Oliveira V. Nutrient intakes of individuals from food-insufficient households
in the United States. Am J Public Health 1997;87:1956-61.
28. Aggarwal A, Monsivais P, Cook AJ, Drewnowski A. Does diet cost mediate the
relation between socioeconomic position and diet quality? Eur J Clin Nutr
2011;65:1059-66.
29. Leathers HD. The world food problem toward ending undernutrition in the Third
World. Boulder: Lynne Rienner Publishers, 2009.
30. Crawford PB, Webb KL. Unraveling the paradox of concurrent food insecurity and
obesity. Am J Prev Med 2011;40:274-5.
31. Olson CM. Nutrition and health outcomes associated with food insecurity and
hunger. J Nutr 1999;129:521S-4S.
32. Mello JA, Gans KM, Risica PM, Kirtania U, Strolla LO, Fournier L. How is food
insecurity associated with dietary behaviors? An analysis with low-income,
ethnically diverse participants in a nutrition intervention study. J Am Diet Assoc
2010;110:1906-11.
33. Guenther PM, Casavale KO, Reedy J, Kirkpatrick SI, Hiza HAB, Kuczynski KJ, Kahle LL,
Krebs-Smith SM, Update of the Healthy Eating Index: HEI-2010, Journal of the
Academy of Nutrition and Dietetics 2013 Feb 13. pii: S2212-2672(12)02049-7. doi:
10.1016/j.jand.2012.12.016. [Epub ahead of print]
34. Centers for Disease Control and Prevention (CDC). National Center for Health
Statistics (NCHS). National Health and Nutrition Examination Survey Data.
Hyattsville, MD: U.S. Department of Health and Human Services, Centers for
Disease Control and Prevention, 2005-2010.
http://www.cdc.gov/nchs/nhanes.htm.
68
35. Champagne CM, Casey PH, Connell CL et al. Poverty and food intake in rural
America: diet quality is lower in food insecure adults in the Mississippi Delta. J Am
Diet Assoc 2007;107:1886-94.
36. Drewnowski A. Obesity and the food environment: dietary energy density and diet
costs. Am J Prev Med 2004;27:154-62.
37. Zoellner J, You W, Connell C et al. Health literacy is associated with healthy eating
index scores and sugar-sweetened beverage intake: findings from the rural Lower
Mississippi Delta. J Am Diet Assoc 2011;111:1012-20.
38. Zoellner J, Chen Y, Davy B et al. Talking Health, A pragmatic randomized-controlled
health literacy trial targeting sugar-sweetened beverage consumption among
adults: rationale, design & methods. Contemp Clin Trials 2014;37:43-57.
39. Scheier LM. What is the hunger-obesity paradox? J Am Diet Assoc 2005;105:883-4,
886.
40. Weber JA. Talking about hunger in a land of plenty. J Am Diet Assoc 2006;106:804-7.
41. Zizza CA, Duffy PA, Gerrior SA. Food insecurity is not associated with lower energy
intakes. Obesity (Silver Spring) 2008;16:1908-13.
42. Ledikwe JH, Blanck HM, Khan LK et al. Low-energy-density diets are associated with
high diet quality in adults in the United States. J Am Diet Assoc 2006;106:1172-80.
69
Appendix A: Sums of grams by food domain and category and food security status for US
adults
Food Group
Milk and Dairy
Milk
Flavored Milk
Dairy Drinks and
substitutes
Cheese
Yogurt
Protein Foods
Meats
Poultry
Seafood
Eggs
Cured
Meats/Poultry
Plant-based
Protein Foods
Mixed Dishes
Meat/Poultry/
Seafood
Grain-based
Asian
Fully Food
Secure
(n=12007)
191.7 ± 5.4
(5.8%)
139.6 ± 4.9
(4.3%)
8.8 ± 1
(0.3%)
10.8 ± 0.8
(0.3%)
18.9 ± 0.6
(0.6%)
13.5 ± 0.8
(0.4%)
153.6 ± 2.3
(4.7%)
31.2 ± 1.1
(0.9%)
33.2 ± 1.2
(1%)
15.8 ± 0.9
(0.5%)
21.9 ± 0.8
(0.7%)
28 ± 0.9
(0.9%)
23.4 ± 1.1
(0.7%)
262.4 ± 5.3
(8.1%)
57.7 ± 2.2
(1.8%)
55 ± 2.2
(1.7%)
21.7 ± 1.4
(0.6%)
Marginally
Food Secure
(n=1698)
164.2 ± 9.7
(5.2%)
117.7 ± 7.5
(3.8%)
11.2 ± 1.9
(0.3%)
10.3 ± 2
(0.3%)
15.2 ± 1.3
(0.5%)
9.7 ± 1.5
(0.3%)
149.5 ± 6.4
(5.1%)
35 ± 3.5
(1.2%)
32 ± 2
(1.1%)
10.9 ± 1.4
(0.4%)
25.5 ± 2.3
(0.8%)
25 ± 2.6
(0.8%)
21.1 ± 1.4
(0.7%)
275.3 ± 12.3
(8.7%)
66.9 ± 6.4
(2%)
58.5 ± 4.5
(1.8%)
18.5 ± 2.9
(0.6%)
70
Low Food
Secure
(n=1886)
176.6 ± 11.8
(5.3%)
134.0 ± 9.8
(4%)
13.4 ± 5
(0.4%)
10.3 ± 2
(0.3%)
15 ± 1
(0.5%)
3.8 ± 1.1
(0.1%)
164.4 ± 5
(5.6%)
34.9 ± 1.9
(1.2%)
35.4 ± 2.8
(1.3%)
13.4 ± 2.1
(0.5%)
24.1 ± 2
(0.8%)
29 ± 2
(0.9%)
27.6 ± 2.7
(0.9%)
281.1 ± 10.6
(9.3%)
62.9 ± 7.4
(2%)
57.2 ± 4.8
(2%)
14.9 ± 2.3
(0.5%)
Very Low Food
Secure
(n=1034)
182.9 ± 13.5
(5.5%)
137 ± 13.4
(4.1%)
13.7 ± 4.8
(0.4%)
10.8 ± 4.3
(0.3%)
16.2 ± 1.4
(0.5%)
5.1 ± 0.9
(0.2%)
151.4 ± 6.9
(4.9%)
29.1 ± 2.4
(0.9%)
37 ± 3.3
(1.2%)
12.8 ± 1.9
(0.4%)
19 ± 2.2
(0.6%)
28.8 ± 3.1
(1%)
24.7 ± 3.2
(0.8%)
296.7 ± 16.3
(9.2%)
72.5 ± 10.9
(2.2%)
61.5 ± 7.8
(1.9%)
17.8 ± 3.9
(0.5%)
Food Group
Mexican
Pizza
Sandwich (single
code)
Soup
Grains
Cooked Grains
Breads, Rolls,
Tortillas
Quick breads and
Bread products
Ready-to-eat
cereals
Cooked Cereals
Snacks and Sweets
Savory Snacks
Crackers
Snack/Meal bars
Sweet Bakery
Products
Candy
Other Desserts
Fruits
Vegetables
Vegetables (not
potatoes)
White potatoes
Fully Food
Secure
(n=12007)
19.7 ± 1.4
(0.6%)
29.5 ± 1.3
(0.9%)
26.3 ± 1.2
(0.9%)
52.3 ± 2.8
(1.6%)
124.2 ± 2.5
(4%)
22.6 ± 1.7
(0.7%)
55.1 ± 1
(1.8%)
14.1 ± 0.5
(0.4%)
12.2 ± 0.4
(0.4%)
20.2 ± 1.1
(0.6%)
97.6 ± 1.9
(3.1%)
14.3 ± 0.5
(0.5%)
4.7 ± 0.2
(0.2%)
2.8 ± 0.2
(0.1%)
36 ± 1
(1.1%)
10 ± 0.6
(0.3%)
29.9 ± 1.1
(1%)
110.6 ± 3.3
(3.4%)
140.5 ± 2.8
(4.3%)
96.8 ± 2.9
(2.9%)
43.7 ± 1.4
(1.4%)
Marginally
Food Secure
(n=1698)
31.1 ± 7.2
(0.8%)
30.7 ± 4.1
(0.9%)
27.9 ± 3.1
(1%)
41.7 ± 4.3
(1.5%)
118.4 ± 4
(4.2%)
21.5 ± 2.9
(0.7%)
56.5 ± 2.6
(2%)
14.7 ± 1.9
(0.5%)
10 ± 0.7
(0.4%)
15.8 ± 2.5
(0.5%)
84.2 ± 4.2
(3%)
13.1 ± 0.8
(0.4%)
3.4 ± 0.5
(0.1%)
1.7 ± 0.4
(0.1%)
31.6 ± 2.2
(1.1%)
8.4 ± 1.1
(0.3%)
26 ± 2.2
(0.9%)
90.2 ± 5.5
(3%)
122.5 ± 8.2
(4.1%)
77.5 ± 7.3
(2.5%)
45 ± 3.9
(1.5%)
71
Low Food
Secure
(n=1886)
22.6 ± 2.5
(0.7%)
30.8 ± 5.1
(0.9%)
34.8 ± 3
(1.3%)
57.9 ± 5.2
(1.9%)
129.7 ± 5.7
(4.5%)
26.1 ± 3.5
(1%)
67.7 ± 2.8
(2.3%)
13.3 ± 1.9
(0.4%)
9.2 ± 1
(0.3%)
13.3 ± 1.7
(0.4%)
84 ± 4.7
(2.8%)
14.2 ± 1.2
(0.5%)
2.9 ± 0.4
(0.1%)
0.8 ± 0.2
(0%)
31.7 ± 2.3
(1%)
9.9 ± 1.2
(0.3%)
24.4 ± 2.5
(0.8%)
82.7 ± 6.5
(2.6%)
99.1 ± 5.2
(3.4%)
62.3 ± 3.4
(2.1%)
36.8 ± 3.3
(1.3%)
Very Low Food
Secure
(n=1034)
24.5 ± 4.5
(0.7%)
32.4 ± 4.6
(0.9%)
28.5 ± 3.5
(1%)
59.4 ± 10
(1.9%)
110.9 ± 5.8
(3.7%)
20.4 ± 5.5
(0.7%)
54.5 ± 2.6
(1.9%)
12.4 ± 1.9
(0.4%)
10.2 ± 1.4
(0.3%)
13.5 ± 2.6
(0.4%)
90.7 ± 5.3
(2.9%)
17.9 ± 3.9
(0.5%)
4.5 ± 0.6
(0.2%)
1.5 ± 0.7
(0%)
33.8 ± 3
(1%)
7.6 ± 1
(0.3%)
25.5 ± 3.6
(0.9%)
76.5 ± 8.9
(2.5%)
114.9 ± 10.4
(3.6%)
79.8 ± 8.9
(2.4%)
35.1 ± 3.9
(1.1%)
Food Group
Non-alcoholic
beverages
100% juice
Diet beverages
Sweetened
beverages
Coffee and tea
Alcoholic beverages
Water
Plain water
Flavored on
Enhanced Water
Fats and Oils
Condiments and
Sauces
Sugars
Other
Fully Food
Secure
(n=12007)
1099.1 ± 19.1
(32.2%)
59.3 ± 2.4
(1.9%)
172 ± 6.6
(5%)
314.4 ± 10.4
(9.6%)
553.4 ± 14.7
(15.6%)
193.5 ± 8.7
(4.4%)
1106.4 ± 24.5
(28.3%)
1079.2 ± 23.5
(27.5%)
27.1 ± 2.9
(0.8%)
22.6 ± 0.7
(0.7%)
26 ± 0.9
(0.7%)
8.6 ± 0.3
(0.3%)
1.3 ± 0.2
(0%)
Marginally
Food Secure
(n=1698)
1066.7 ± 42.3
(34%)
56.3 ± 5.6
(1.9%)
109.5 ± 13.1
(3.4%)
503.4 ± 25.1
(16.5%)
397.5 ± 28.5
(12.2%)
207.6 ± 17.2
(5.1%)
1021.4 ± 49.8
(26.2%)
1004.6 ± 50.4
(25.6%)
16.7 ± 4.8
(0.5%)
15.7 ± 1.1
(0.5%)
20.4 ± 1.6
(0.6%)
8.5 ± 0.7
(0.3%)
1.3 ± 0.8
(0%)
72
Low Food
Secure
(n=1886)
1154.7 ± 45.5
(35.5%)
74.6 ± 6.6
(2.4%)
89.3 ± 16
(2.9%)
532.3 ± 30
(17.2%)
458.4 ± 30.4
(13.1%)
187 ± 18.1
(4.4%)
950.9 ± 43.8
(25.2%)
939.5 ± 43.9
(24.9%)
11.4 ± 4.3
(0.3%)
15.4 ± 1
(0.5%)
19.4 ± 1.2
(0.6%)
9.6 ± 0.9
(0.3%)
1 ± 0.4
(0%)
Very Low Food
Secure
(n=1034)
1282.4 ± 56.1
(36.7%)
79.7 ± 8.9
(2.5%)
120.5 ± 24.2
(3.3%)
548.6 ± 37.7
(16.8%)
533.7 ± 43
(14.1%)
279.4 ± 77.8
(5.7%)
925.2 ± 55.8
(23.8%)
892.6 ± 55.9
(22.8%)
32.6 ± 12.6
(1%)
16.4 ± 1.2
(0.5%)
20.7 ± 2.1
(0.6%)
10 ± 1.1
(0.3%)
0.3 ± 0.1
(0%)
Appendix B: Sums of kilocalories by food domain and category and food security status
for US adults
Food Group
Milk and Dairy
Milk
Flavored Milk
Dairy Drinks and
substitutes
Cheese
Yogurt
Protein Foods
Meats
Poultry
Seafood
Eggs
Cured
Meats/Poultry
Plant-based Protein
Foods
Mixed Dishes
Meat/Poultry/
Seafood
Grain-based
Asian
Fully Food
Secure
(n=12007)
149.8 ± 3.6
(7.1%)
64.8 ± 2.1
(3.1%)
6.7 ± 0.7
(0.3%)
7.5 ± 0.6
(0.3%)
58.9 ± 2.1
(2.7%)
11.9 ± 0.7
(0.6%)
352.8 ± 5.2
(16.4%)
75.1 ± 2.6
(3.4%)
76.2 ± 2.8
(3.6%)
27.7 ± 1.7
(1.3%)
37.8 ± 1.4
(1.8%)
66.1 ± 2.2
(3%)
69.9 ± 2.8
(3.2%)
418.8 ± 8.7
(19%)
79.2 ± 3.1
(3.9%)
83.3 ± 3.3
(3.9%)
33.2 ± 2.2
(1.5%)
Marginally
Food Secure
(n=1698)
136.2 ± 7
(6.3%)
62.2 ± 4.2
(3%)
8.8 ± 1.4
(0.4%)
7.7 ± 2.3
(0.3%)
48.3 ± 4.3
(2.2%)
9.1 ± 1.5
(0.4%)
343.3 ± 16.4
(16.1%)
85.8 ± 9.6
(3.9%)
76.3 ± 4.9
(3.8%)
20.6 ± 2.7
(1.1%)
43.3 ± 3.9
(2%)
64.2 ± 6.8
(2.9%)
53 ± 3.5
(2.3%)
472.7 ± 24.9
(20.1%)
95.3 ± 10.3
(4.4%)
92.4 ± 7.5
(4%)
30.1 ± 5.2
(1.4%)
73
Low Food
Secure
(n=1886)
141.6 ± 8.4
(6.2%)
69.6 ± 5.2
(3.1%)
10.7 ± 3.9
(0.4%)
8.8 ± 2.3
(0.4%)
48.7 ± 3.4
(2.2%)
3.8 ± 1.1
(0.2%)
364.7 ± 11.6
(17.1%)
86.9 ± 5
(4.1%)
85.3 ± 7.3
(4.1%)
22.9 ± 3.8
(1.1%)
43.1 ± 3.6
(2%)
65.7 ± 5
(3.1%)
60.9 ± 5.9
(2.6%)
458.1 ± 20.6
(19.9%)
90.8 ± 11.7
(4.1%)
83.4 ± 7
(3.9%)
22.6 ± 3.5
(1.1%)
Very Low
Food Secure
(n=1034)
145.8 ± 7.9
(6.8%)
69 ± 5.7
(3.4%)
11 ± 3.9
(0.4%)
7.6 ± 2.5
(0.3%)
53.5 ± 4.3
(2.4%)
4.7 ± 0.8
(0.3%)
350.5 ± 14.9
(15.6%)
72 ± 6.4
(3.1%)
91.2 ± 8.3
(3.8%)
24.5 ± 3.6
(1.1%)
34 ± 4
(1.6%)
73.3 ± 8.8
(3.3%)
55.6 ± 5.9
(2.6%)
468.1 ± 22.4
(20.6%)
95.5 ± 11.7
(4.4%)
92.9 ± 11.7
(4%)
25.3 ± 5.7
(1.1%)
Food Group
Mexican
Pizza
Sandwich (single
code)
Soup
Grains
Cooked Grains
Breads, Rolls,
Tortillas
Quick breads and
Bread products
Ready-to-eat
cereals
Cooked Cereals
Snacks and Sweets
Savory Snacks
Crackers
Snack/Meal bars
Sweet Bakery
Products
Candy
Other Desserts
Fruits
Vegetables
Vegetables (not
potatoes)
White potatoes
Fully Food
Secure
(n=12007)
45.7 ± 3.4
(1.8%)
82.9 ± 3.7
(3.2%)
64.6 ± 3.1
(3%)
29.8 ± 1.7
(1.6%)
287.6 ± 4.1
(14.3%)
30 ± 2.2
(1.6%)
154.2 ± 2.8
(7.6%)
42.5 ± 1.5
(1.9%)
44.7 ± 1.4
(2.3%)
16.1 ± 0.9
(0.9%)
331.8 ± 6.1
(15.1%)
71.3 ± 2.3
(3.3%)
21.5 ± 0.9
(1.1%)
11.6 ± 0.8
(0.6%)
131 ± 3.2
(5.7%)
45.4 ± 2.6
(2.1%)
51.1 ± 1.9
(2.4%)
64.6 ± 1.9
(3.5%)
122.1 ± 2.6
(5.9%)
46 ± 1.6
(2.4%)
76.1 ± 2.2
(3.5%)
Marginally
Food Secure
(n=1698)
72.7 ± 17.5
(2.5%)
87.8 ± 11.7
(3.2%)
70.1 ± 7.9
(3.3%)
24.3 ± 2.8
(1.4%)
274.6 ± 7.2
(14.2%)
28.7 ± 3.9
(1.6%)
154.4 ± 7.2
(7.7%)
42 ± 5.6
(2.3%)
36.9 ± 2.7
(1.9%)
12.5 ± 1.9
(0.7%)
291.7 ± 11.9
(13.7%)
66.6 ± 4
(2.9%)
15.6 ± 2.3
(0.9%)
6.8 ± 1.5
(0.4%)
117.6 ± 7.9
(5.5%)
38 ± 4.5
(1.8%)
47 ± 3.8
(2.3%)
51 ± 2.9
(2.9%)
113.8 ± 7.8
(5.3%)
38.7 ± 4.5
(2%)
75.1 ± 5.9
(3.3%)
74
Low Food
Secure
(n=1886)
53 ± 6.1
(2.1%)
86.2 ± 13.5
(3.1%)
87.7 ± 7.7
(3.8%)
34.4 ± 3.4
(1.9%)
302.4 ± 10.9
(15.2%)
34.7 ± 4.7
(2.2%)
183.6 ± 7.6
(9%)
38.4 ± 5.4
(1.8%)
34.2 ± 3.4
(1.6%)
11.4 ± 1.5
(0.6%)
296.5 ± 14.4
(12.8%)
70.8 ± 5.5
(3%)
13.4 ± 2.1
(0.7%)
3.4 ± 0.9
(0.2%)
119.5 ± 8.1
(5.1%)
44.9 ± 5
(1.9%)
44.4 ± 4.9
(2%)
44.4 ± 2.8
(2.4%)
97.5 ± 7.3
(4.8%)
30.9 ± 2.2
(1.6%)
66.6 ± 6.6
(3.1%)
Very Low
Food Secure
(n=1034)
55 ± 10.3
(2.5%)
89.3 ± 12.3
(3.3%)
75.4 ± 9.3
(3.3%)
34.8 ± 5.1
(2.1%)
262.8 ± 10.2
(12.8%)
26.9 ± 7.1
(1.3%)
149.5 ± 7.2
(7.4%)
37.2 ± 5.8
(1.6%)
38.2 ± 5.3
(1.9%)
10.9 ± 2.3
(0.6%)
321.5 ± 17.9
(13.8%)
88.2 ± 17.4
(3.7%)
20.7 ± 2.7
(1.1%)
6.2 ± 2.7
(0.3%)
129.1 ± 11.1
(5.2%)
33.1 ± 4.3
(1.5%)
44.2 ± 6.4
(1.9%)
42.9 ± 4.6
(2.3%)
111.3 ± 9
(5.1%)
45.4 ± 6.2
(2.3%)
65.9 ± 6.6
(2.9%)
Food Group
Non-alcoholic
beverages
100% juice
Diet beverages
Sweetened
beverages
Coffee and tea
Alcoholic beverages
Water
Plain water
Flavored on
Enhanced Water
Fats and Oils
Condiments and
Sauces
Sugars
Other
Fully Food
Secure
(n=12007)
184.9 ± 4.3
(8.5%)
27 ± 1.1
(1.3%)
2.7 ± 0.1
(0.1%)
126 ± 4.2
(5.7%)
29.2 ± 1.5
(1.4%)
100.2 ± 4.4
(4%)
1.9 ± 0.2
(0.1%)
0±0
(0%)
1.9 ± 0.2
(0.1%)
79 ± 2.1
(3.7%)
21.9 ± 1.1
(1%)
26.1 ± 0.7
(1.2%)
4.7 ± 0.7
(0.2%)
Marginally
Food Secure
(n=1698)
260.8 ± 10.3
(12.2%)
26 ± 2.7
(1.3%)
1.7 ± 0.2
(0.1%)
201.5 ± 9.7
(9.2%)
31.6 ± 4.2
(1.6%)
101.7 ± 7.9
(4%)
1.2 ± 0.4
(0.1%)
0±0
(0%)
1.2 ± 0.4
(0.1%)
57.4 ± 3.7
(2.8%)
17.9 ± 1.9
(0.8%)
26.9 ± 2
(1.3%)
5.1 ± 3.1
(0.2%)
75
Low Food
Secure
(n=1886)
282.8 ± 11.9
(13.2%)
35 ± 3.2
(1.6%)
1.3 ± 0.3
(0.1%)
214.5 ± 11.7
(9.9%)
31.9 ± 3.3
(1.6%)
83.1 ± 8.4
(3.3%)
1.4 ± 0.7
(0%)
0±0
(0%)
1.4 ± 0.7
(0%)
54.2 ± 3.7
(2.7%)
14.8 ± 1.1
(0.7%)
31.4 ± 2.7
(1.5%)
4.1 ± 1.6
(0.2%)
Very Low Food
Secure
(n=1034)
289.5 ± 14.6
(13.2%)
36.8 ± 4.4
(1.8%)
1.9 ± 0.4
(0.1%)
216.1 ± 14.2
(9.6%)
34.6 ± 5.5
(1.7%)
123.9 ± 23.9
(4.5%)
3.8 ± 2.1
(0.3%)
0±0
(0%)
3.8 ± 2.1
(0.3%)
59.2 ± 4.2
(2.7%)
16.6 ± 2.1
(0.7%)
33.9 ± 3.5
(1.6%)
1 ± 0.5
(0.1%)
Appendix C: Sums of fat (grams) by food domain and category and food security status
for US adults
Food Groups
Milk and Dairy
Milk
Flavored Milk
Dairy Drinks and
substitutes
Cheese
Yogurt
Protein Foods
Meats
Poultry
Seafood
Eggs
Cured
Meats/Poultry
Plant-based
Protein Foods
Mixed Dishes
Meat/Poultry/
Seafood
Grain-based
Asian
Fully Food
Secure
(n=12007)
7 ± 0.2
(8.9%)
2.2 ± 0.1
(2.9%)
0.2 ± 0
(0.2%)
0.2 ± 0
(0.3%)
4.3 ± 0.2
(5.2%)
0.1 ± 0
(0.2%)
21.6 ± 0.3
(25.5%)
4.2 ± 0.2
(5.1%)
3.8 ± 0.2
(4.8%)
1.2 ± 0.1
(1.6%)
2.8 ± 0.1
(3.3%)
4.7 ± 0.2
(5.2%)
4.8 ± 0.2
(5.5%)
18.4 ± 0.4
(22.6%)
3.7 ± 0.2
(4.9%)
3 ± 0.1
(4%)
1.4 ± 0.1
(1.8%)
Marginally
Food Secure
(n=1698)
6.9 ± 0.4
(8.9%)
2.7 ± 0.2
(3.8%)
0.2 ± 0
(0.3%)
0.2 ± 0.1
(0.2%)
3.6 ± 0.3
(4.4%)
0.1 ± 0
(0.2%)
21.3 ± 1.2
(26.3%)
4.9 ± 0.6
(6%)
4 ± 0.3
(5.7%)
1 ± 0.1
(1.4%)
3.2 ± 0.3
(4%)
4.9 ± 0.6
(5.5%)
3.3 ± 0.3
(3.7%)
21.3 ± 1.2
(24.8%)
4.6 ± 0.6
(5.7%)
3.4 ± 0.3
(3.9%)
1.3 ± 0.3
(1.9%)
76
Low Food
Secure
(n=1886)
7.3 ± 0.4
(9.3%)
2.9 ± 0.2
(3.9%)
0.3 ± 0.1
(0.4%)
0.3 ± 0.1
(0.4%)
3.7 ± 0.3
(4.5%)
0.1 ± 0
(0.1%)
21.8 ± 0.8
(27.3%)
5 ± 0.3
(6.5%)
4.6 ± 0.4
(6%)
1 ± 0.2
(1.5%)
3.2 ± 0.3
(3.9%)
4.6 ± 0.4
(5.6%)
3.5 ± 0.4
(3.8%)
20.1 ± 1
(24.4%)
4.1 ± 0.6
(5.1%)
2.7 ± 0.2
(3.8%)
0.9 ± 0.1
(1.3%)
Very Low Food
Secure
(n=1034)
7.4 ± 0.4
(9.7%)
2.8 ± 0.2
(4.1%)
0.3 ± 0.1
(0.3%)
0.2 ± 0.1
(0.3%)
4 ± 0.3
(4.8%)
0.1 ± 0
(0.2%)
21.5 ± 1
(25.5%)
4.2 ± 0.5
(5.1%)
4.9 ± 0.5
(5.8%)
1.2 ± 0.2
(1.7%)
2.6 ± 0.3
(3.1%)
5.4 ± 0.7
(6%)
3.1 ± 0.3
(3.9%)
20.4 ± 1
(25.9%)
4.3 ± 0.5
(5.8%)
3.2 ± 0.4
(4.2%)
0.9 ± 0.2
(1.2%)
Food Groups
Mexican
Pizza
Sandwich (single
code)
Soup
Grains
Cooked Grains
Breads, Rolls, Tortillas
Quick breads and
Bread products
Ready-to-eat cereals
Cooked Cereals
Snacks and Sweets
Savory Snacks
Crackers
Snack/Meal bars
Sweet Bakery
Products
Candy
Other Desserts
Fruits
Vegetables
Vegetables (not
potatoes)
White potatoes
Fully Food
Secure
(n=12007)
2.3 ± 0.2
(2.4%)
3.8 ± 0.2
(3.9%)
3.3 ± 0.2
(3.9%)
1.1 ± 0.1
(1.7%)
5.1 ± 0.1
(7.1%)
0.3 ± 0
(0.5%)
2.4 ± 0.1
(3.4%)
1.6 ± 0.1
(1.9%)
0.5 ± 0
(0.8%)
0.3 ± 0
(0.5%)
14.3 ± 0.3
(17.3%)
3.7 ± 0.1
(4.5%)
0.8 ± 0
(1.2%)
0.3 ± 0
(0.5%)
5.6 ± 0.1
(6.6%)
1.8 ± 0.1
(2.1%)
2.2 ± 0.1
(2.6%)
0.3 ± 0
(0.5%)
5.2 ± 0.1
(6.4%)
1.7 ± 0.1
(2.3%)
3.5 ± 0.1
(4.1%)
Marginally
Food Secure
(n=1698)
3.5 ± 0.8
(3.2%)
4 ± 0.5
(3.9%)
3.6 ± 0.4
(4.5%)
0.9 ± 0.1
(1.6%)
4.9 ± 0.2
(7.8%)
0.3 ± 0
(0.6%)
2.5 ± 0.1
(3.7%)
1.5 ± 0.2
(2.4%)
0.3 ± 0
(0.6%)
0.3 ± 0.1
(0.5%)
13 ± 0.5
(16.5%)
3.7 ± 0.2
(4.3%)
0.6 ± 0.1
(1%)
0.2 ± 0
(0.4%)
5 ± 0.3
(6.4%)
1.4 ± 0.2
(1.8%)
2.2 ± 0.2
(2.7%)
0.2 ± 0
(0.4%)
4.8 ± 0.4
(5.9%)
1.4 ± 0.2
(2%)
3.5 ± 0.3
(4%)
77
Low Food
Secure
(n=1886)
2.6 ± 0.3
(2.8%)
4 ± 0.6
(4%)
4.6 ± 0.4
(5.1%)
1.2 ± 0.1
(2.2%)
5.4 ± 0.3
(8.3%)
0.4 ± 0.1
(0.8%)
3.1 ± 0.2
(4.6%)
1.4 ± 0.2
(1.9%)
0.3 ± 0
(0.5%)
0.3 ± 0
(0.5%)
12.9 ± 0.6
(15.6%)
3.8 ± 0.3
(4.5%)
0.5 ± 0.1
(0.7%)
0.1 ± 0
(0.1%)
5 ± 0.3
(6%)
1.6 ± 0.2
(1.9%)
1.9 ± 0.2
(2.3%)
0.2 ± 0
(0.3%)
4.4 ± 0.4
(5.7%)
1.3 ± 0.1
(1.9%)
3.1 ± 0.3
(3.7%)
Very Low
Food Secure
(n=1034)
2.7 ± 0.5
(3.2%)
4.1 ± 0.5
(4.1%)
4 ± 0.5
(4.8%)
1.3 ± 0.2
(2.6%)
4.8 ± 0.3
(6.9%)
0.3 ± 0.1
(0.5%)
2.4 ± 0.2
(3.6%)
1.4 ± 0.2
(1.7%)
0.4 ± 0.1
(0.6%)
0.3 ± 0.1
(0.4%)
14 ± 0.7
(16.7%)
4.6 ± 0.8
(5.5%)
0.8 ± 0.1
(1.2%)
0.2 ± 0.1
(0.3%)
5.4 ± 0.4
(6.2%)
1.1 ± 0.2
(1.3%)
2 ± 0.3
(2.2%)
0.2 ± 0
(0.3%)
4.9 ± 0.5
(6.2%)
1.7 ± 0.4
(2.4%)
3.1 ± 0.3
(3.8%)
Food Groups
Non-alcoholic beverages
100% juice
Diet beverages
Sweetened beverages
Coffee and tea
Alcoholic beverages
Water
Plain water
Flavored on Enhanced
Water
Fats and Oils
Condiments and Sauces
Sugars
Other
Fully Food
Secure
(n=12007)
0.7 ± 0
(1.1%)
0.1 ± 0
(0.1%)
0±0
(0%)
0.2 ± 0
(0.4%)
0.3 ± 0
(0.4%)
0±0
(0%)
0±0
(0%)
0±0
(0%)
0±0
(0%)
7.8 ± 0.2
(9.1%)
1.2 ± 0.1
(1.3%)
0.1 ± 0
(0.1%)
0.1 ± 0
(0.1%)
Marginally
Food Secure
(n=1698)
0.7 ± 0.1
(1.2%)
0.1 ± 0
(0.1%)
0±0
(0%)
0.3 ± 0
(0.5%)
0.4 ± 0.1
(0.5%)
0±0
(0%)
0±0
(0%)
0±0
(0%)
0±0
(0%)
5.6 ± 0.4
(7%)
0.9 ± 0.1
(1%)
0±0
(0%)
0.1 ± 0.1
(0.1%)
78
Low Food
Secure
(n=1886)
0.8 ± 0.1
(1.3%)
0.1 ± 0
(0.2%)
0±0
(0%)
0.3 ± 0.1
(0.6%)
0.3 ± 0
(0.5%)
0±0
(0%)
0±0
(0%)
0±0
(0%)
0±0
(0%)
5.2 ± 0.4
(6.7%)
0.7 ± 0.1
(0.8%)
0±0
(0.1%)
0.1 ± 0.1
(0.1%)
Very Low
Food Secure
(n=1034)
0.6 ± 0.1
(1%)
0.1 ± 0
(0.2%)
0±0
(0%)
0.3 ± 0.1
(0.5%)
0.2 ± 0
(0.3%)
0±0
(0%)
0±0
(0%)
0±0
(0%)
0±0
(0%)
5.8 ± 0.4
(6.8%)
0.7 ± 0.2
(0.8%)
0±0
(0%)
0±0
(0.1%)
Appendix D: Sums of protein (grams) by food domain and category and food security
status for US adults
Food Groups
Milk and Dairy
Milk
Flavored Milk
Dairy Drinks and
substitutes
Cheese
Yogurt
Protein Foods
Meats
Poultry
Seafood
Eggs
Cured Meats/Poultry
Plant-based Protein
Foods
Mixed Dishes
Meat/Poultry/
Seafood
Grain-based
Asian
Fully Food
Secure
(n=12007)
9.8 ± 0.2
(11.9%)
4.6 ± 0.2
(5.6%)
0.3 ± 0
(0.4%)
0.2 ± 0
(0.3%)
4.1 ± 0.1
(4.8%)
0.6 ± 0
(0.8%)
30.4 ± 0.5
(33.7%)
8.4 ± 0.3
(8.7%)
8.3 ± 0.3
(9.1%)
3.2 ± 0.2
(3.3%)
2.7 ± 0.1
(3.2%)
5 ± 0.1
(6%)
2.9 ± 0.1
(3.5%)
22.7 ± 0.5
(26.8%)
6.3 ± 0.2
(7.3%)
3.3 ± 0.1
(4.3%)
1.9 ± 0.1
(2.2%)
Marginally
Food Secure
(n=1698)
8.0 ± 0.4
(10.2%)
3.8 ± 0.2
(5%)
0.4 ± 0.1
(0.4%)
0.2 ± 0.1
(0.3%)
3.2 ± 0.3
(3.9%)
0.4 ± 0.1
(0.6%)
29 ± 1.4
(33.7%)
9.6 ± 1
(10%)
7.8 ± 0.5
(9.4%)
2.1 ± 0.3
(2.5%)
3 ± 0.3
(3.6%)
4.2 ± 0.4
(5.5%)
2.3 ± 0.1
(2.7%)
25.1 ± 1.3
(29.3%)
7.3 ± 0.8
(8.4%)
3.6 ± 0.3
(4.2%)
2.1 ± 0.4
(2.2%)
79
Low Food
Secure
(n=1886)
8.5 ± 0.5
(10%)
4.4 ± 0.3
(5.1%)
0.4 ± 0.2
(0.5%)
0.3 ± 0.1
(0.3%)
3.2 ± 0.2
(3.9%)
0.2 ± 0
(0.2%)
31.5 ± 0.9
(36.1%)
9.4 ± 0.5
(10.2%)
8.6 ± 0.7
(9.9%)
2.7 ± 0.4
(2.9%)
3 ± 0.2
(3.6%)
5.1 ± 0.3
(6.4%)
2.7 ± 0.2
(3.2%)
24.2 ± 1.1
(28.5%)
6.8 ± 0.8
(7.4%)
3.2 ± 0.3
(4.1%)
1.2 ± 0.2
(1.5%)
Very Low
Food Secure
(n=1034)
8.9 ± 0.5
(11%)
4.5 ± 0.4
(5.7%)
0.4 ± 0.2
(0.5%)
0.3 ± 0.1
(0.3%)
3.5 ± 0.3
(4%)
0.2 ± 0
(0.4%)
28.7 ± 1.3
(32.3%)
7.6 ± 0.6
(8.2%)
8.7 ± 0.8
(9.3%)
2.4 ± 0.4
(2.5%)
2.3 ± 0.3
(3%)
5 ± 0.6
(6%)
2.5 ± 0.3
(3.4%)
24.6 ± 1.3
(30.4%)
7.3 ± 1
(8%)
3.5 ± 0.4
(4.3%)
1.3 ± 0.3
(1.6%)
Food Groups
Mexican
Pizza
Sandwich (single
code)
Soup
Grains
Cooked Grains
Breads, Rolls, Tortillas
Quick breads and
Bread products
Ready-to-eat cereals
Cooked Cereals
Snacks and Sweets
Savory Snacks
Crackers
Snack/Meal bars
Sweet Bakery
Products
Candy
Other Desserts
Fruits
Vegetables
Vegetables (not
potatoes)
White potatoes
Fully Food
Secure
(n=12007)
2.4 ± 0.2
(2.6%)
3.5 ± 0.2
(3.9%)
3.4 ± 0.2
(4.2%)
1.9 ± 0.1
(2.4%)
8.5 ± 0.1
(11.3%)
0.7 ± 0
(0.9%)
5.3 ± 0.1
(7%)
0.9 ± 0
(1.2%)
1.1 ± 0
(1.5%)
0.5 ± 0
(0.8%)
4.9 ± 0.1
(6.8%)
1.1 ± 0
(1.5%)
0.4 ± 0
(0.6%)
0.3 ± 0
(0.4%)
1.6 ± 0
(2.2%)
0.5 ± 0
(0.7%)
1±0
(1.3%)
0.8 ± 0
(1.1%)
2.8 ± 0.1
(3.8%)
1.6 ± 0
(2.3%)
1.2 ± 0
(1.5%)
Marginally
Food Secure
(n=1698)
3.4 ± 0.8
(3.4%)
3.7 ± 0.5
(4%)
3.8 ± 0.4
(5%)
1.3 ± 0.2
(2%)
7.7 ± 0.2
(11.2%)
0.6 ± 0.1
(0.9%)
5 ± 0.2
(7%)
0.9 ± 0.1
(1.6%)
0.8 ± 0.1
(1.1%)
0.4 ± 0.1
(0.6%)
4.2 ± 0.2
(6.4%)
1 ± 0.1
(1.4%)
0.3 ± 0
(0.6%)
0.2 ± 0
(0.3%)
1.5 ± 0.1
(2.3%)
0.4 ± 0
(0.6%)
0.9 ± 0.1
(1.3%)
0.6 ± 0
(0.9%)
2.6 ± 0.2
(3.6%)
1.3 ± 0.2
(2%)
1.2 ± 0.1
(1.7%)
80
Low Food
Secure
(n=1886)
2.6 ± 0.3
(2.8%)
3.7 ± 0.6
(4.1%)
4.5 ± 0.4
(5.5%)
2.2 ± 0.3
(3.1%)
8.4 ± 0.3
(11.6%)
0.7 ± 0.1
(1.2%)
5.8 ± 0.2
(7.7%)
0.8 ± 0.1
(1.2%)
0.7 ± 0.1
(0.9%)
0.3 ± 0
(0.5%)
4.2 ± 0.2
(5.7%)
1 ± 0.1
(1.4%)
0.3 ± 0
(0.4%)
0.1 ± 0
(0.1%)
1.6 ± 0.1
(2.1%)
0.5 ± 0
(0.7%)
0.8 ± 0.1
(1%)
0.5 ± 0
(0.8%)
2 ± 0.1
(2.9%)
1 ± 0.1
(1.5%)
1 ± 0.1
(1.3%)
Very Low
Food Secure
(n=1034)
2.8 ± 0.6
(3.6%)
3.8 ± 0.5
(4.3%)
3.8 ± 0.5
(5.3%)
2 ± 0.4
(3.2%)
7.3 ± 0.3
(10.2%)
0.6 ± 0.2
(0.8%)
4.8 ± 0.2
(6.7%)
0.8 ± 0.1
(1.2%)
0.8 ± 0.1
(1%)
0.3 ± 0.1
(0.4%)
4.6 ± 0.4
(6.7%)
1.4 ± 0.3
(2.1%)
0.4 ± 0.1
(0.8%)
0.1 ± 0.1
(0.2%)
1.6 ± 0.1
(2.2%)
0.3 ± 0
(0.4%)
0.8 ± 0.1
(1%)
0.5 ± 0.1
(0.8%)
2.5 ± 0.3
(3.8%)
1.5 ± 0.2
(2.4%)
1 ± 0.1
(1.4%)
Food Groups
Non-alcoholic beverages
100% juice
Diet beverages
Sweetened
beverages
Coffee and tea
Alcoholic beverages
Water
Plain water
Flavored on
Enhanced Water
Fats and Oils
Condiments and Sauces
Sugars
Other
Fully Food
Secure
(n=12007)
1.6 ± 0.1
(2.3%)
0.3 ± 0
(0.4%)
0.2 ± 0
(0.2%)
0.5 ± 0
(0.7%)
0.7 ± 0
(0.9%)
0.6 ± 0
(0.7%)
0±0
(0%)
0±0
(0%)
0±0
(0%)
0.3 ± 0
(0.5%)
0.6 ± 0
(0.8%)
0±0
(0%)
0.4 ± 0.1
(0.4%)
Marginally
Food Secure
(n=1698)
1.5 ± 0.1
(2.4%)
0.3 ± 0
(0.4%)
0.1 ± 0
(0.2%)
0.6 ± 0.1
(0.9%)
0.6 ± 0.1
(0.9%)
0.7 ± 0.1
(0.9%)
0±0
(0%)
0±0
(0%)
0±0
(0%)
0.2 ± 0
(0.3%)
0.6 ± 0.1
(0.8%)
0±0
(0%)
0.4 ± 0.2
(0.2%)
81
Low Food
Secure
(n=1886)
1.6 ± 0.1
(2.5%)
0.3 ± 0
(0.4%)
0.1 ± 0
(0.2%)
0.6 ± 0.1
(0.9%)
0.6 ± 0.1
(1%)
0.7 ± 0.1
(0.8%)
0±0
(0%)
0±0
(0%)
0±0
(0%)
0.2 ± 0
(0.3%)
0.4 ± 0
(0.6%)
0±0
(0%)
0.3 ± 0.1
(0.2%)
Very Low
Food Secure
(n=1034)
1.6 ± 0.1
(2.6%)
0.3 ± 0.1
(0.5%)
0.1 ± 0
(0.2%)
0.5 ± 0.1
(0.9%)
0.6 ± 0.1
(1%)
0.8 ± 0.2
(1.2%)
0±0
(0%)
0±0
(0%)
0±0
(0%)
0.2 ± 0
(0.4%)
0.5 ± 0.1
(0.6%)
0±0
(0%)
0.1 ± 0
(0.1%)
Appendix E: Sums of carbohydrate (grams) by food domain and category and food
security status for US adults
Food Groups
Milk and Dairy
Milk
Flavored Milk
Dairy Drinks and
substitutes
Cheese
Yogurt
Protein Foods
Meats
Poultry
Seafood
Eggs
Cured Meats/Poultry
Plant-based Protein
Foods
Mixed Dishes
Meat/Poultry/
Seafood
Grain-based
Asian
Fully Food
Secure
(n=12007)
11.9 ± 0.3
(4.8%)
6.8 ± 0.2
(2.7%)
1 ± 0.1
(0.4%)
1.1 ± 0.1
(0.4%)
0.9 ± 0.1
(0.4%)
2.1 ± 0.1
(0.9%)
8.6 ± 0.2
(3.6%)
0.3 ± 0
(0.1%)
1.6 ± 0.1
(0.7%)
0.8 ± 0.1
(0.3%)
0.4 ± 0
(0.2%)
0.7 ± 0
(0.3%)
4.8 ± 0.2
(1.9%)
40.1 ± 0.8
(15.3%)
5.1 ± 0.2
(2.2%)
10.8 ± 0.4
(4.1%)
3.2 ± 0.2
(1.3%)
Marginally
Food Secure
(n=1698)
10.7 ± 0.8
(4%)
5.6 ± 0.4
(2.2%)
1.4 ± 0.2
(0.5%)
1.3 ± 0.4
(0.4%)
0.7 ± 0.1
(0.3%)
1.6 ± 0.3
(0.6%)
8.3 ± 0.3
(3.3%)
0.3 ± 0.1
(0.1%)
1.8 ± 0.2
(0.7%)
0.7 ± 0.1
(0.3%)
0.6 ± 0.1
(0.2%)
0.7 ± 0.1
(0.3%)
4.2 ± 0.3
(1.6%)
44.7 ± 2.4
(15.7%)
6.1 ± 0.6
(2.4%)
11.7 ± 0.9
(4.2%)
2.4 ± 0.5
(0.9%)
82
Low Food
Secure
(n=1886)
10.7 ± 0.9
(3.8%)
6.4 ± 0.5
(2.4%)
1.6 ± 0.6
(0.4%)
1.3 ± 0.3
(0.5%)
0.7 ± 0.1
(0.3%)
0.6 ± 0.2
(0.2%)
9.7 ± 0.7
(3.7%)
0.4 ± 0.1
(0.2%)
1.9 ± 0.2
(0.8%)
0.7 ± 0.2
(0.3%)
0.5 ± 0
(0.2%)
0.8 ± 0.1
(0.3%)
5.5 ± 0.5
(2%)
44.7 ± 2.1
(15.9%)
6.6 ± 0.9
(2.6%)
11.4 ± 1
(4.1%)
2.4 ± 0.5
(0.9%)
Very Low
Food Secure
(n=1034)
10.9 ± 0.8
(4.2%)
6.6 ± 0.7
(2.5%)
1.6 ± 0.6
(0.5%)
1.1 ± 0.3
(0.4%)
0.8 ± 0.1
(0.3%)
0.8 ± 0.1
(0.4%)
9.9 ± 0.8
(3.8%)
0.4 ± 0.2
(0.2%)
2.5 ± 0.3
(0.9%)
0.9 ± 0.2
(0.4%)
0.3 ± 0
(0.2%)
0.9 ± 0.1
(0.4%)
5 ± 0.6
(1.8%)
46.1 ± 2.4
(16.4%)
6.8 ± 1.2
(2.8%)
12.4 ± 1.6
(4.2%)
3.1 ± 0.8
(1%)
Food Groups
Mexican
Pizza
Sandwich (single
code)
Soup
Grains
Cooked Grains
Breads, Rolls, Tortillas
Quick breads and
Bread products
Ready-to-eat cereals
Cooked Cereals
Snacks and Sweets
Savory Snacks
Crackers
Snack/Meal bars
Sweet Bakery
Products
Candy
Other Desserts
Fruits
Vegetables
Vegetables (not
potatoes)
White potatoes
Fully Food
Secure
(n=12007)
3.9 ± 0.3
(1.4%)
8.6 ± 0.4
(2.8%)
5.2 ± 0.2
(2.2%)
3.2 ± 0.2
(1.4%)
52.6 ± 0.8
(21.4%)
6 ± 0.4
(2.4%)
27.7 ± 0.5
(11.6%)
6.2 ± 0.2
(2.4%)
9.8 ± 0.3
(3.8%)
2.8 ± 0.2
(1.2%)
47.4 ± 0.9
(17.8%)
8.7 ± 0.3
(3.4%)
3.1 ± 0.1
(1.4%)
1.9 ± 0.1
(0.8%)
19.3 ± 0.5
(6.8%)
7.2 ± 0.5
(2.7%)
7.2 ± 0.3
(2.8%)
16.4 ± 0.5
(6.9%)
17.4 ± 0.4
(7.4%)
7.2 ± 0.3
(3.3%)
10.2 ± 0.3
(4.1%)
Marginally
Food Secure
(n=1698)
6.9 ± 1.9
(1.9%)
9.3 ± 1.3
(2.8%)
5.5 ± 0.6
(2.3%)
2.9 ± 0.4
(1.2%)
50.2 ± 1.4
(20.6%)
5.7 ± 0.8
(2.4%)
28 ± 1.3
(11.5%)
6.2 ± 0.9
(2.6%)
8.2 ± 0.6
(3.1%)
2.1 ± 0.3
(1%)
40.8 ± 1.9
(15.3%)
7.8 ± 0.5
(2.8%)
2.2 ± 0.3
(1.1%)
1.1 ± 0.2
(0.6%)
17.2 ± 1.2
(6.3%)
6.2 ± 0.9
(2.1%)
6.2 ± 0.5
(2.4%)
12.9 ± 0.7
(5.4%)
16.2 ± 1
(6.4%)
6.1 ± 0.6
(2.7%)
10.1 ± 0.8
(3.7%)
83
Low Food
Secure
(n=1886)
4.8 ± 0.6
(1.5%)
8.9 ± 1.4
(2.5%)
7 ± 0.6
(2.6%)
3.7 ± 0.3
(1.6%)
55.4 ± 2
(21.6%)
6.9 ± 0.9
(3.1%)
33.3 ± 1.4
(13%)
5.7 ± 0.8
(2.1%)
7.6 ± 0.8
(2.7%)
1.9 ± 0.3
(0.8%)
42.2 ± 2.4
(14.3%)
8.5 ± 0.8
(2.8%)
1.9 ± 0.3
(0.8%)
0.6 ± 0.1
(0.2%)
17.7 ± 1.2
(5.8%)
7.3 ± 1
(2.4%)
6.3 ± 0.7
(2.2%)
11.3 ± 0.7
(4.5%)
13.5 ± 0.9
(5.8%)
4.5 ± 0.3
(2%)
8.9 ± 0.9
(3.7%)
Very Low
Food Secure
(n=1034)
4.8 ± 0.9
(1.8%)
9.3 ± 1.4
(2.8%)
5.9 ± 0.7
(2.2%)
3.9 ± 0.5
(1.7%)
47.9 ± 1.9
(18.5%)
5.4 ± 1.5
(1.9%)
27 ± 1.3
(11%)
5.4 ± 0.8
(1.9%)
8.3 ± 1.1
(3%)
1.9 ± 0.4
(0.8%)
45.9 ± 3
(15.6%)
10.8 ± 2.7
(3.6%)
3 ± 0.4
(1.3%)
1.1 ± 0.5
(0.4%)
19.2 ± 1.8
(6%)
5.7 ± 0.8
(2%)
6 ± 0.9
(2.2%)
10.9 ± 1.1
(4.3%)
15.5 ± 1.1
(5.9%)
6.9 ± 0.8
(2.7%)
8.6 ± 0.9
(3.1%)
Food Groups
Non-alcoholic beverages
100% juice
Diet beverages
Sweetened
beverages
Coffee and tea
Alcoholic beverages
Water
Plain water
Flavored on
Enhanced Water
Fats and Oils
Condiments and Sauces
Sugars
Other
Fully Food
Secure
(n=12007)
44.3 ± 1.1
(15.5%)
6.5 ± 0.3
(2.4%)
0.5 ± 0
(0.2%)
31.5 ± 1
(10.6%)
5.9 ± 0.3
(2.2%)
5.6 ± 0.3
(2.3%)
0.5 ± 0.1
(0.2%)
0±0
(0%)
0.5 ± 0.1
(0.2%)
2.3 ± 0.1
(1%)
2.5 ± 0.1
(1%)
6.7 ± 0.2
(2.5%)
0.6 ± 0.1
(0.2%)
Marginally
Food Secure
(n=1698)
64 ± 2.6
(22.2%)
6.3 ± 0.7
(2.3%)
0.3 ± 0
(0.2%)
50.9 ± 2.5
(17.1%)
6.5 ± 0.9
(2.6%)
6.1 ± 0.6
(2.4%)
0.3 ± 0.1
(0.2%)
0±0
(0%)
0.3 ± 0.1
(0.2%)
1.7 ± 0.2
(0.7%)
2.1 ± 0.2
(0.8%)
7 ± 0.5
(2.7%)
0.7 ± 0.4
(0.2%)
84
Low Food
Secure
(n=1886)
69.5 ± 3.1
(23.5%)
8.5 ± 0.8
(3%)
0.2 ± 0
(0.1%)
54 ± 3
(17.9%)
6.7 ± 0.8
(2.5%)
5.8 ± 0.6
(2.2%)
0.3 ± 0.2
(0.1%)
0±0
(0%)
0.3 ± 0.2
(0.1%)
1.8 ± 0.2
(0.8%)
2 ± 0.1
(0.8%)
8.1 ± 0.7
(2.8%)
0.5 ± 0.2
(0.1%)
Very Low
Food Secure
(n=1034)
71.4 ± 3.7
(23.4%)
8.9 ± 1.1
(3%)
0.3 ± 0.1
(0.2%)
54.6 ± 3.6
(17.6%)
7.6 ± 1.4
(2.7%)
6.9 ± 1.3
(2.8%)
0.9 ± 0.5
(0.4%)
0±0
(0%)
0.9 ± 0.5
(0.4%)
1.8 ± 0.1
(0.8%)
2.3 ± 0.2
(0.8%)
8.8 ± 0.9
(3.2%)
0.1 ± 0.1
(0.1%)