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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. 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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%)