Record for a UF thesis. Title & abstract won't display until thesis is accessible after 2013-08-31.

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Record for a UF thesis. Title & abstract won't display until thesis is accessible after 2013-08-31.
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english
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Radford,Ally
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University of Florida
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Degree:
Master's ( M.S.)
Degree Grantor:
University of Florida
Degree Disciplines:
Food Science and Human Nutrition
Committee Chair:
Dahl, Wendy Joanne
Committee Members:
Langkamp-Henken, Bobbi
Christman, Mary C

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Food Science and Human Nutrition -- Dissertations, Academic -- UF
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Food Science and Human Nutrition thesis, M.S.
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Statement of Responsibility:
by Ally Radford.
Thesis:
Thesis (M.S.)--University of Florida, 2011.
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Adviser: Dahl, Wendy Joanne.
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INACCESSIBLE UNTIL 2013-08-31

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lcc - LD1780 2011
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UFE0043475:00001


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1 PROVISION OF WHOLE GRAINS TO MIDDLE SCHOOL STUDENTS ACHIEVES DIETARY GUIDELINES FOR AMERICANS AND MYPLATE RECOMMENDATIONS By ALLYSON RADFORD A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIA L FULFILLMENT OF THE REQUIREMENTS FOR THE DE GREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2011

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2 2011 Allyson Radford

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3 To my parents

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4 ACKNOWLEDGMENTS I thank my parents, family, friends, and mentors Dr. Dahl and Dr. Henken for guiding and supporting me through this process. The knowledge and experiences I have gained are life changing.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................. 4 LIST OF TABLES ............................................................................................................ 7 LIST OF FIGURES .......................................................................................................... 8 ABSTRACT ..................................................................................................................... 9 CHAPTER 1 LITERATURE REVIEW .......................................................................................... 11 Whole Grain ............................................................................................................ 11 Whole Grain Definition ..................................................................................... 11 Whole Grain Composition ................................................................................. 17 Whole Grain Processing ................................................................................... 21 Refined Grain Composition .............................................................................. 22 Whole Grain and Health .......................................................................................... 23 Whole Grain and Cardiovascular Disease ........................................................ 24 Whole Grain and Diabetes ............................................................................... 27 Whole Grain and Obesity ................................................................................. 28 Whole Grain and Cancer .................................................................................. 30 Whole Grain Recommendations ....................................................................... 32 Adolescent Whole Grain Consumption ............................................................. 33 Perceptions Regarding Whole-Grain Foods ..................................................... 36 Dietary Assessment ................................................................................................ 37 Dietary Assessment Methodology .......................................................................... 37 Diet Records ..................................................................................................... 38 24-Hour Diet Recall .......................................................................................... 39 Food Frequency ............................................................................................... 40 Brief Dietary Assessment Instruments ............................................................. 41 Diet History ....................................................................................................... 41 Dietary Assessment in Intervention Studies ............................................................ 42 Dietary Assessment in Children and Adolescents .................................................. 43 Issues in Dietary Assessment in Children and Adolescents ................................... 44 Validation of Diet Assessment Methods .................................................................. 47 Validity of the Multi-Pass 24-hour Diet Recall ......................................................... 48 Validation of Diet Assessment Tools Developed Specifically for Adolescents ........ 50 Future Dietary Assessment Methods ...................................................................... 54 2 PURPOSE .............................................................................................................. 57

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6 3 METHODS ................................ ................................ ................................ .............. 58 Study Design ................................ ................................ ................................ .......... 58 Inclusion / Exclusion Criteria after Obtaining Consent and Assent ......................... 58 Pre Baseline and Baseline ................................ ................................ ...................... 59 Randomization ................................ ................................ ................................ ........ 60 Treatment ................................ ................................ ................................ ............... 60 Oun ce Equivalents ................................ ................................ ................................ .. 61 Statistical Analyses ................................ ................................ ................................ 62 Daily and Weekly Measures ................................ ................................ ................... 62 Final Study Week ................................ ................................ ................................ .... 63 Incentives ................................ ................................ ................................ ................ 63 4 RESULTS ................................ ................................ ................................ ............... 71 Subject De mographics and Characteristics ................................ ............................ 71 Total Grain Intake ................................ ................................ ................................ ... 72 Refined Grain Intake ................................ ................................ ............................... 73 Whole Grain Intake ................................ ................................ ................................ 74 Fruit Intake ................................ ................................ ................................ .............. 75 Vegetable Intake ................................ ................................ ................................ ..... 76 5 DISCUSSION AND CONCLUSION ................................ ................................ ........ 92 APPENDIX: DOCUMENTS SUBMITTED TO THE INSTITUTIONAL REVIEW BOARD ................................ ................................ ................................ ................... 97 LIST OF REFERENCES ................................ ................................ ............................. 141 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 150

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7 LIST OF TABLES Table page 3 1 Foods provided during weeks 1 and 5 for subjects in wave 1, week 4 for wave 2 and week 3 for wave 3. ................................ ................................ .......... 65 3 2 Foods provided during weeks 2 and 6 for subjects in wave 1, weeks 1 and 5 for wave 2 and week 4 for wave 3. ................................ ................................ ..... 66 3 3 Foods provided during week 3 for subjects in wave 1, weeks 2 and 6 for wave 2 and weeks 1 and 5 for wave 3. ................................ ............................... 67 3 4 Foods pro vided during week 4 for subjects in wave 1, week 3 for wave 2 and weeks 2 and 6 for wave 3. ................................ ................................ .................. 68 3 5 Specific amounts that count as 1 ounce equivalent of grains towards daily recommended intake. ................................ ................................ ......................... 69 4 1 Subject characteristics and dietary intake data. ................................ .................. 77 4 2 The average number of targeted 24 hour recalls obtained during t he pre baseline and treatment periods for the intent to treat subjects ........................... 80 4 3 Average caloric, nutrient, and fiber content per ounce equivalent of whole grain and refined grain foods provided in the weekly food packages. ................ 80 4 4 The main effects of gender, group, study period, race/ethnicity, and their interactions on average daily intake of all grains. ................................ ............... 82 4 5 Tests of effect slices for group and race/ethnicity interaction. ............................ 85 4 6 Tests of effect slices for group and race/ethnicity interaction. ............................ 85 4 7 The main effects of gender, group, study period, race/ethnicity, and their interactions on average daily intake of refined grain. ................................ .......... 85 4 8 The main effects of gender, group, study period, race/ethnicity, and their interactions on average daily intake of whole grains. ................................ ......... 87 4 9 Tests of effect slices for group and race/ethnicity i nteraction. ............................ 89 4 10 Tests of effect slices for group and race/ethnicity interaction. ............................ 89 4 11 The main effects of gender, group, study period, race/ethnicity, and their interactions on average daily intake of fruit. ................................ ....................... 90 4 12 The main effects of g ender, group study pe riod race/ethnicity and their interactions on average daily intak e of vegetable ................................ .............. 91

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8 LIST OF FIGURES Figure page 3 1 Study design ................................ ................................ ................................ ....... 64 4 1 Fl ow chart of subject recruitment, allocation and analyses. ................................ 77 4 2 Ranking of most common refined grain package foods consumed. ................... 81 4 3 Ranking of most common whole grain package foods consumed. ..................... 81 4 4 The least squares means for the average daily intake of all grains by females and males across treatment groups and the p re baseline and treatment periods. ................................ ................................ ................................ ............... 82 4 5 The least squares means for the average daily intake of all grains by subjects in the refined grain or whole grain groups across the pre baseline and treatment periods. ................................ ................................ ............................... 83 4 6 The least squares means for the average daily intake of all grains by all subjects during the pre baseline and treatment periods across treatment groups. ................................ ................................ ................................ ............... 84 4 7 Total grain intake by treatment group across the pre baseline and treatment periods by subjects of different races and ethnicities randomized to the refined or whole grain groups. ................................ ................................ ........... 84 4 8 The least squares means for the average daily intake of refined grain (ounce equivalents) by females and males. ................................ ................................ ... 86 4 9 The least squares means for the average daily intake of refined grain by subjects in the refined grain or whole grain groups during the pre baseline and treatment periods. ................................ ................................ ........................ 87 4 10 The least squares means for th e average daily intake of whole grains by all subjects in the refined grain or whole grain groups during the pre baseline and treatment periods. ................................ ................................ ........................ 88 4 11 Whole g rain intake by treatment group a cross the pre baseline and treatment periods by subjects of different races and ethnicities. ................................ ........ 89 4 12 The least squares means for the average daily i ntake of fruit by gender and treatment group .. ................................ ................................ ................................ 90 4 13 The least squares means for the average daily intake of vegetables by gender.. ................................ ................................ ................................ .............. 91

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9 Abstract of Thesis Presented to the Graduate School of the Univers ity of Florida in Partial Fulfillment of the R equirements for the Degree of Master of Science PROVISION OF WHOLE GRAINS TO MIDDLE SCHOOL STUDENTS ACHIEVES DIETARY GUIDELINES FOR AMERICANS AND MYPLATE RECOMMENDATIONS By Allyson Radford A ugust 2011 Chair: Wendy Dahl Major: Food Science and Human Nutrition Middle school students should consume 5 to 6 oz equivalents/d (girls) and 6 7 oz equivalents (boys) of grains, with a t least half as whole grain according to the United States Departmen Current total intakes avera ge 5.3 oz equivalents/d, with whole grain intakes at 1.1 oz equivalents/d ay The aim of this study was to determine the e ffect of providing refined or whole grain foods to adolescents with encouragement to eat three different grain based food s per day, on total grain and whole grain intakes. Middle school students (n=83; 11 15 y) were recruited from Westwood Middle School, Gainesville FL, an d randomized to refined or whole grain food s for 6 weeks The adolescents and their families were provided with weekly grains (e.g. bread, pasta, and cereals), and participants were provided grain snacks at school. Two baseline and 6 intervention targeted 24 hr diet recalls were carried out, and in t akes in ounces were determined. Total grain intake for males increased when provided ref ined grains (6.00.5 to 7.2 0.4 o z equivalents/d; p<0.05), and whole grain foods (5.00.5 to 6.80.5 oz equivalents/d; p<0.001). Total grain intake for females did not change wi th either intervention. When whole grain foods were

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10 provided, whole grain intake increased for males (1.00.2 to 4.20.4 oz equivalents/d; p<0.0001) and females (0.90.3 to 3.50.3 oz equivalents/d; p<0.0001). In conclusion, providing adolesce nts with whole grain foods is an effective means of achieving recommendations.

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11 CHAPTER 1 LITERATURE REVIEW Whole Grain Whole Grain Definition Whole grains have been a part of the human diet for about 10,000 years ( 1). In opulation has relied on whole grains as a main component of the diet. In the United States, 66 75% of the total grain consumed is from wheat ( 2). Whole wheat, oatmeal, maize, brown rice, whole grain barley, whole rye, and millet are all examples of whole g rains grown and consumed around the world ( 2). The definition of a whole grain is currently a disputed topic in the scientific community. In the United States, a uniform definition of what constitutes a whole grain is established, however internationally, there is no accepted definition of whole grain. The U.S. Food and Drug Administration (FDA) defines a whole grain as consisting of the intact, ground, cracked, or flaked kernel (also known as the caryopsis, seed or fruit), which includes the bran, the germ and the inner most part of the kernel (the endosperm). This definition has been adapted from the American Association of Cereal Chemists (AACC). The Dietary Guidelines for Americans 2010 describe a whole grain as consisting of the entire grain seed, usua lly called the kernel. They define the kernel as consisting of three components: the bran, germ, and endosperm. If the kernel has must retain the same relative proport ions of the previously listed components, as they exist in the intact grain. Another definition comes from the American Whole Grain and naturally occurring nutrients of the entire grain seed. If the grain has been

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12 processed (e.g. cracked, crushed, rolled, extruded, and/or cooked), the food product should deliver approximately the same rich balance of nutrients that are found in the ons are similar in that they define a whole grain based on composition (consisting of the bran, germ, and wheat) and the raw material of the grain (ground, cracked, or flaked) ( 3). As of 2010, the definition of a whole grain is different all around the wor ld. Many researchers agree that one, strict and uniform definition of whole grain has not been established or accepted internationally and is urgently needed ( 4, 5). Cummings et al. ( 5) suggest that, the term whole grain be more clearly defined, concentrat ing on the role of intact versus milled grains. Some definitions are very broad, for example the AACC and FDA definition in the United States includes 22 cereals and pseudocereals, while a Danish Task Force ( 4) defines whole grain as intact, ground, cracke d, or flaked kernels after removal of the husks which only includes nine cereals as whole grain. Denmark, Sweden, and Norway agreed upon a definition of whole grain to include intact and processed products where endosperm, germ, and bran are present in the same proportion as in the intact grain. The definition goes on to describe that if fractions were to be separated under processing, they should be added back so that the final product has the same proportions of the three parts as in the intact grain. Som e whole grains that fall under this definition include whole grain cereals: wheat, rye, oats, barley, maize, rice millet and sorghum while omitting wild rice, quinoa, amaranth, and buckwheat ( 4). Depending on the definition, anywhere from 7 to 22 different grains may be included. De Moura et al. ( 6) explain that using the FDA definition of whole grain as a selection measure is limiting due to the fact that the majority of existing studies often

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13 use an even broader meaning to define whole grain. In a review of studies on the association of whole grain intake and incidence of cardiovascular disease (CVD), only four of the 204 articles evaluated conformed to the FDA definition of whole grain. Most of the scientific literature uses a broader concept of whole gr ain, such as looking at just the effects of bran to draw conclusions about whole grains ( 6). In 2010, Frolich et al. ( 4) explain the need for a universally agreed upon definition of whole grain. This has proven to be difficult due to the diversity of whol e grain composition in terms of macronutrients, micronutrients, and phytochemicals. The author goes on to explain that only those grains which have similar nutrient content should be included as a whole grain. Much of the issue surrounds which type of seed should be included in the definition ( 4). group is cereals, a member of the grass family. Cereals produce dry, one seeded fruits (caryopsis), which are commonly known as th e kernel or grain. All cereals have generally similar compositions made up of the bran, germ, and endosperm. Examples of cereals include wheat, rice, oats, and barley. Next is the pseudocereal group, which is not a member of the grass family. These plants have high starch content in their seeds and so are used in cereal like products. Some examples of pseudocereals are amaranth, quinoa, and buckwheat. Last, is the pulse or grain legume group, which is not often regarded as whole grain, but because of their high starch content, may fall into the definition of a whole grain ( 4). Frolich et al. ( 4) suggest that a definition for whole grain be formulated using two steps: first, by agreeing on a definition regarding the raw and dry materials (milled,

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14 cracked, cru shed, rolled, or flaked) and secondly, agreeing on a definition in terms of the preparation process (thermal, enzymatic, baking, malting, and fermentation). Okarter et al. ( 7) suggest defining whole grain based on the composition. The author explains that a whole grain can have its original composition of the bran, germ, and endosperm intact or can be a reconstituted whole grain product in which the original components are recombined to the same proportion as the naturally occurring grain kernel. Taking the se suggestions from the authors into consideration, the grain in question can then be tested for health effects and defined as a whole grain ( 4). Using a universal definition for whole grain is important because much of the existing literature cites a rela tionship between whole grain consumption and health benefits. Unfortunately, the lack of a general definition of whole grain for dietary assessment raises the question of validity and accuracy concerning the amount of whole grain consumed in research studi es. Some studies include products containing added bran and germ, so called pseudocereals, partial whole grain products, and starch rich seeds. In conclusion, Frolich et al. argue that finding an applicable definition of whole grain will be helpful for ind ividual consumers to facilitate their choice of healthy food alternatives; the scientific community, to establish a uniform dietary factor to study in relation to health; the authorities, to allow them to make recommendations; or the food industry, to p rod uce new whole grain products ( 4). Under the current FDA, WGC, and AACC definitions of whole grain, the following cereals and pseudeocereals are considered whole grain: amaranth, barley, buckwheat, corn (including whole cornmeal and popcorn), millet, oats, including oatmeal and quinoa, rice (both brown rice and colored rice), rye, sorghum, teff, triticale, wheat

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15 (including varieties such as spelt, emmer, faro, einkorn, kamut, durum, and forms such as bulgur, cracked wheat and wheatberries), wild rice, canary montina, and fonio. Under the whole grain definitions in the United States, oilseeds and legumes are not considered whole grain ( 4). The FDA allows health claims on products, which have scientific backing, to help the consumer make bett er food choices. In order for a product to bear the whole grain claim, the FDA requires that the food contain 51% or more whole grain ingredients by weight per reference amount customarily consumed (RACC). In order to assess compliance of a product with th e FDA regulation it should be compared to the dietary fiber level of whole wheat, since whole wheat is the predominant grain in the U.S. For example, since whole wheat contains 11 grams of dietary fiber per 100 grams, the eligible amount of dietary fiber r equired for a food to bear the whole grain claim could be determined by the formula: 11 grams x 51% x RACC/100 ( 8). Currently, the FDA has not defined any claims concerning the grain content of foods. However, they recommend looking at the food label and i ngredient list to The FDA also acknowledges that there are no standards of identity for products made from whole grains, however there are standards of identity for whole wheat bread, rolls, buns, and whole wheat macaroni products. This means that for bread, rolls and buns, the dough is made from whole wheat flour, brominated whole wheat flo ur, or a combination of these and no other type of flour is used. In terms of label statements about whole grains that are currently permitted on food products, the FDA allows

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16 manufacturers to make factual statements. These statements include labels such a and do not include statements which imply that a particular level of the ingredient are ( 9). In order to help consumers choose whole grain prod ucts, the FDA has allowed the stamp is allowed on food products that provide 8 grams or more whole grain per serving (contain at least half a serving of whole grain ingr edients). These products may contain provide at least 16 g rams or more of whole grain per serving. For these products, all of the grain in the ingredient list is from whole grain. The United States Department of Agriculture (USDA) recommends consumers read the ingredient list of the food in question and chose foods that have whole grain listed first in the ingredient list. Many foods contain whole and refined grains. If other non whole grains are listed in the ingredient list, it may be assumed that the product is a partial whole grain product. Determining if a product is truly whole grain is becoming difficult because a growing number of partial whole grain products are enter ing the marketplace. If a product lists multiple whole grain ingredients, they should appear near the beginning of the ingredient list to ensure that they make up most of the product. Jonnalagadda et al. ( 10) recommend only counting products whole grain if every grain listed in the ingredient label is whole. Due to the lack of detailed information about the quantity of whole and non whole grain ingredients in partial whole grain products, this is a simple option to determine if a product is 100% whole grai n. Harris et al. ( 11) add that terms such as

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17 confusion when choosing whole grain products. Lastly, the Dietary Guidelines for Americans 2010 recommend choosing whole grain produ cts based on fiber content ( 12). Whole Grain Composition As mentioned before, a whole grain is made up of three portions: the outer bran layer, the inner germ and endosperm. Whole grains are a good source of B vitamins, minerals, basic amino acids, and phy tochemicals ( 2). There is a great deal of variability among various whole grains in their content of macronutrients, micronutrients, and phytochemicals. The major nutrients and phytochemicals found in whole grains are as follows: protein, fat, carbohydrate dietary fiber, calcium, iron, magnesium, phosphorous, potassium, sodium, zinc, thiamin, riboflavin, vitamin B 6, niacin, folate, vitamin A, vitamin E, vitamin K, selenium, beta carotene, lignan, isoflavonoids, phenolic acids, and phenolic lipids ( 6). The most commonly consumed whole grain in the U.S. is whole wheat with composition as follows: 14% bran, 2.5% germ, 13% total dietary fiber (11.5% insoluble dietary fiber, 1.1% soluble dietary fiber), 14% protein, 2.7% fat, 70% starch and sugar, 1.8% total mi nerals, 7.5 milligrams/gram vitamin B 6, 32.8 micrograms/grams vitamin E, and 2.9 milligrams/gram phytate phosphorous ( 13). More specifically, the bran is a multi layered shell made up of nondigestible, mostly insoluble, low fermentable carbohydrates such as cellulose and hemicellulose ( 10). It also contains phenolic compounds along with vitamins and minerals ( 10). The bran functions as an outside shield to protect the inside germ and endosperm from damage, sunlight, pests, water, and disease ( 10). The star chy germ and endosperm contain viscous soluble fibers (found mostly in oats and barley), fermentable

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18 oligosaccharides, resistant starch, lignans, vitamins, minerals, polyphenols, oils, and many other phytonutrients ( 13). The endosperm is the largest portio n of the grain, rich with carbohydrates, protein, vitamins, and minerals to serve as a nutrient supply for the germ and the rest of the plant ( 13). The germ is the embryo of the grain and is where a new plant sprouts ( 10). It contains vitamins, some protei n, minerals and fat ( 10). The aforementioned components are thought to contribute to the hea lthfulness of whole grains. Whole grains are considered a functional food; this is because their components may provide health benefits. Functional foods are made u p of substances called phytochemicals, which may promote good health but are not considered nutrients because they are not essential for life. The beneficial elements of a whole grain are concentrated mostly in the bran and germ portion of the grain ( 14) Whole grains are also made up of essential macro and micronutrients. Adom et al. ( 15) explain that most of the beneficial phytochemicals and nutrients are found in the bran as well as the endosperm of the whole grain. Okarter et al. (16) list phenolics, carotenoids, vitamin E, dietary fiber, and beta glucan as the most important groups of whole grain phytochemicals. The most studied phytochemical, known as phenolic acids, provide chemical defense for the grain against pathogens, parasites, and predators. Specifically, in wheat kernels, a phenolic acid known as ferulic acid provides protection by employing physical and chemical barriers through cross linking with carbohydrates, antioxidant activity, and astringency that prevent s consumption by predators. Wh en a whole grain is ingested, the phenolic acids function as antioxidants by donating

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19 hydrogen atoms to free radicals. Of all the grains tested, corn is reported to have the highest phenolic acid content, followed by wheat, oats, and rice ( 16). Another ph enolic acid to note is alk(en)ylresorcinol, generally found in the bran layer of the grain. This compound is prominently found in barley, rye, and wheat. It has never been detected in corn, millet, oats, rice or sorghum. Alkylresorcinol is often used as a biomarker for whole grain intake assessment ( 7). Found in the germ and bran fraction of the grain is another type of phytochemical, carotenoids, these include lutein, zaexanthin, beta cryptoxanthin, beta carotene, and alpha carotene. These are most common ly known for giving the grain pigmentation and function in reproduction and protection while also providing some antioxidant activity ( 10). B vitamins such as thiamin, riboflavin, and niacin found in whole grain play a key role in metabolism. Vitamin E and its derivatives are mostly found in the germ fraction of whole grain and functions to maintain the integrity of the cellular membranes and also has a protective effect because of its antioxidant activity ( 7). Vitamin E is found in whole grains such as bar ley, bulgur, corn, rye, wheat, and wild rice ( 6). Minerals found in whole grain include iron, magnesium, and selenium ( 10). Another biologically important component of whole grain is fermentable carbohydrates. The content of fermentable carbohydrates varie s depending on the type of grain. Types found in whole grain include dietary fiber, resistant starch, and oligosaccharides. These are considered fermentable carbohydrates because they are undigested and once they reach the colon they can be fermented by in testinal microflora producing short chain fatty acids and gases. Short chain fatty acids such as

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20 butyrate, is a preferred fuel for the cells of the colonic mucosa ( 2). Slavin et al. ( 13) state that oats, rye, and barley only contain about one third soluble fiber while two thirds is made up of insoluble fiber. Furthermore, wheat is known to be lower in soluble fiber compared to other grains and rice contains close to no soluble fiber. The insoluble portion of the undigested carbohydrate helps to increase fec al weight and speed intestinal transit time. These functions have been known to provide health benefits ( 17). Insoluble fiber is mostly concentrated in wheat bran and corn bran ( 14). According to the AACC, dietary fiber is the edible parts of plants or ana logous carbohydrates that is resistant to digestion and absorption in the human small intestine and is completely or partially fermented in the large intestine ( 5). Some components of dietary fiber that are found in whole grain include lignin, hemicellulos e, cellulose, and beta glucan. Lignin is a compound found in the cell walls of plants and forms complexes with cellulose and hemicellulose, which is extremely resistant to degradation ( 18). Beta glucan is a dietary fiber mostly found in oat bran, oatmeal, oat flour, barley, and rye ( 14). Cummings et al. ( 5), state that another fiber found in whole grain known as resistant starch is the sum of starch and products of starch digestion that are not absorbed in the small bowel. Resistant starch I is mostly prese nt in whole grains and is a physically inaccessible starch such as partly milled grains. Thus, resistant starch I passes to the colon where it can be fermented by gut bacteria to produce short chain fatty acids and increase stool output ( 5). Oligosaccharid es, such as fructooilgosaccharides, are another type of fermentable carbohydrate found in whole grains that consist of linked monosaccharide units ( 5).

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21 Slavin et al. ( 17), describe oligosaccharides as having similar affects as soluble fibers in the human g ut in which portions that are undigested can serve as fuel for intestinal microflora. Cummings et al. ( 5), goes on to explain that oligosaccharides are a source of short chain fatty acids, which alter the balance of microflora. Van Loo ( 19) et al. estimate s that about 78% of the North American intake of oligosaccharides comes from wheat. Compounds called antinutrients are also found in whole grains. They may contribute to the overall protective effect that whole grains are known for by suppressing oxidativ e damage, thereby protecting the intestinal epithelium. A reduced risk of certain cancers has also been reported with the consumption of antinutrients found in whole grains ( 10). Some antinutrients include, phytic acid, hemagglutinins, tannins, and digesti ve enzymes (protease and amylase). They also function by interfering with the absorption of nutrients such as minerals. ( 2). Whole Grain Processing Processing of grains is common in developed countries and is often necessary in order to extend the shelf li fe of the food. Processing techniques include: milling, heat processing, and extrusion (puffing). These processing conditions prepare the grain for digestion and absorption in the body. Some research suggests that processing may positively affect the nutri tional quality of the grain by preserving the nutritive value of the grain. However, the milling process does remove many of the beneficial compounds found in the outer layers of the grain. Slavin et al. ( 1) describe the processing of grains and its effect on nutrition. The author reports that very few consumers actually eat the intact kernels of grain. This is helpful because the nutrients and phytochemicals in intact

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22 whole grain would not be as well digested and absorbed in the body as ground grains ( 1). Harris et al. ( 11) explain that processing grains may provide health benefits. More specifically, processing can improve the palatability and digestibility of whole grains and even increase antioxidant capacity. More specifically, a process known as extru sion interconversion between insoluble and viscous fiber ( 11). During milling, when the bran and germ are separated from the endosperm (to be ground into flour) the nutriti onal quality of the grain may be decreased but the loss of phytates and fiber increases the bioavailability of certain vitamins and minerals ( 1). Another processing technique known as grinding also increases bioavailability of all nutrients in the grain. I n fact, tightly bound phytochemicals may be released from the food matrix during processing ( 2). Thermal processing such as cooking the whole grain is known to release antioxidants from the bran into the endosperm, increase bioavailability of phytochemical s, and form resistant starch. The author concludes with the idea that understanding the synergistic and processing effects of whole grains on health are needed ( 11). Refined Grain Composition The majority of the U.S. population has only been consuming refi ned grains for the past 140 years ( 2). In 1873, a roller mill was introduced that could efficiently separate the bran and germ from the endosperm. Separating the germ was often necessary because it is high in unsaturated fat and could affect the shelf life of the food ( 1). The germ portion, rich with unsaturated fat, may become rancid over time in whole grains and is removed in refined grains and so contributes to its longer shelf life. Due to consumer demand of refined grain products, the use of the machin e became

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23 widespread and consequently a dramatic decline in whole grain consumption was observed between 1870 and 1970 ( 2). A refined grain contains only the endosperm as the refining process removes the germ and bran The endosperm is then ground and made into flour, which can then be incorporated into foods. Consequently a majority of the fiber, vitamins, minerals, and phytochemicals are lost Whole grains contain about 80 % more fiber than refined grains and also have a higher content of antioxidant acti vity compared to refined grains. The refining process removes more of the insoluble fiber than soluble, however refined grains are low in total dietary fiber ( 10). Because refined grain mostly consists of endosperm, it has higher starch content than whole grains ( 13). Most r efined grains are enriched in order to replace the vitamins and other nutrients lost in the refining process ( 10). Whole Grain and Health The connection of whole grain consumption and health benefits were suggested long ago. During the 4 th century BC, the father of medicine, Hippocrates acknowledged the health benefits of whole grain bread. Later on, whole grains were recommended to prevent constipation by physicians and scientists ( 2). Today, whole grains have been linked to reducing the risk of cardiovascular disease (CVD), cancer, diabetes, and obesity. The additive and synergistic effects of all nutrients and phytochemicals found in whole grain are thought to be responsible for the health benefits associated with whole grain consumptio n ( 10). The basis of these findings is mainly derived from observational studies ( 18). Evidence based recommendations regarding whole grain intake and health is lacking and sometimes contradictory ( 4). E pid emiological studies have shown that a diet

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24 rich in whole grains is associated with reducing the risk of chronic diseases such as certain forms of cancer, CVD, and diabetes ( 20, 21, 22, 23). W hole grain consumption has also been related to weight maintenance, blood glucose levels, and all cause mortality ( 22). Therefore, it is assumed that whole grains are important for a health y lifestyle and it is recommended th at adequate amounts be consumed ( 24). A problem that comes along with observational data is that causality cannot be assigned. Therefore, it is un known whether a diet rich in whole grains is protective or if it is simply a marker of a healthy lifestyle. Also, different grains are made up of different compositions of macronutrients, micronutrients, and phytochemicals, therefore each may provide diffe rent effects that may be involved in decreasing the risk of certain diseases. For example, wheat is composed of more insoluble fiber while oats are known to be a good source of beta glucan and soluble fiber. Intervention studies are needed to provide evide nce of the health benefits of whole grain consumption ( 11). Whole Grain and Cardiovascular Disease Okarter et al. ( 7), describe the health benefits of whole grain phytochemicals in which the most recent observational studies that are associated with health benefits and whole grains are reviewed. One of the first studies reviewed, by Jacobs et al. ( 25), shows an inverse association between whole grain intake and ischemic (reduced blood for total dietary fiber intake. A few years later, Pietinen et al. ( 26), report that when whole grain products, mostly rye, were given to a study population, an inverse association was seen with coronary death. The next year, Liu et al. ( 27) reported resu Health Study. The researcher concluded that there was a strong inverse association between whole grain intake and the risk of coronary heart disease for women in the

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25 highest quintile (3 servings per day) for whole grain consumption whe n compared to the lowest. Interestingly, this association held true for both nonfatal coronary heart disease and fatal coronary heart disease. Consequently, increased consumption of whole grains may protect against CHD. That same year, Fraser et al. ( 20) l ooked at whole grain preference and the incidence of ischemic heart disease. The author reports that the preference for whole grain bread instead of preference for white bread was associated with reduced risk of ischemic heart disease. In 2000, Anderson et al. ( 28) reported findings on a meta analysis of studies that investigated the relationship between whole grain consumption and the risk of coronary heart disease (CHD). After an adjustment for primary (demographic data) and secondary (total energy intake body mass index, smoking, and blood pressure) risk factors, four of the twelve studies reviewed showed a significant inverse association between whole grain and whole wheat bread intake and risk of CHD. The results indicate a significant reduction of ris k of 26% on average for those consuming a regular intake of whole grain food (3 servings per day). Lastly, results from a case control study performed in Norway, reported by Lockheart et al., ( 29) showed an association between dietary patterns and the risk of first myocardial infarction. Once the researcher adjusted for family history of heart disease, smoking, energy intake, and other possible confounding factors, whole grain breakfast cereals, not whole grain bread, were inversely associated with risk of first myocardial infarction when comparing the group with the highest level of whole grain intake to the group with the lowest. The epidemiological data shows that the consumption of whole grains is associated with reduced risk of CVD.

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26 The previously descr ibed observational studies establish an association between CVD and whole grain intake. I n addition intervention studies are needed to prove causality. In 2010 Tighe et al. ( 30) performed an intervention study to determine the effect of increased consumpt ion of whole grain foods on blood pressure and other cardiovascular risk markers in healthy middle aged persons. The study assessed the effects of consuming three daily portions of whole grain foods (wheat or a mixture of wheat and oats) on markers (blood pressure, cholesterol and triglyceride measurements) of CVD in relatively high risk individuals. A total of 206 participants included in the study, started with a run in period consuming refined grains. Then were randomized into a control group (refined di et), wheat diet, or wheat and oats diet for 12 weeks. The researcher found, for the first time, that daily consumption of three portions of whole grain foods significantly decreased systolic blood pressure and pulse pressure in middle aged, otherwise healt hy, overweight men and women ( 30). Contrary to the findings described above, a randomized, controlled, dietary intervention found that the markers of cardiovascular risk are not changed by increased whole grain intake. In 2010, Brownlee et al. ( 31) reporte d findings of the WHOLEheart study, which included 316 participants between the ages of 18 and 65 years old. The participants were randomly assigned to three groups: control, intervention 1 (60 g WG/day for 16 weeks), and intervention 2 (60 g WG/day for 8 weeks followed by 120 g WG/day for 8 weeks). The researcher found no significant difference in any markers of CVD between groups ( 31). Compared to the intervention trial described previously, which used 6 blood pressure measurements on average, the WHOLEhe art study blood pressure results were averaged from only two consecutive measurements. The

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27 differences in findings illustrate the limitations of randomized, controlled, intervention trials among humans although clinical trials hold more credibility than ob servational studies ( 30). Whole Grain and Diabetes Modifications in lifestyle, such as changing eating habits, are major factors in the prevention and treatment of diabetes. In order to assess the effects of consuming whole grains on the risk of type II di abetes, numerous epidemiological studies have been performed. Starting in 2000, Liu et al. ( 32) investigated the relationship between whole grain and refined grain intake and the risk of type II diabetes. A positive association between refined grain intake and risk of type II diabetes was found when the highest quintile of refined grain intake was compared to the lowest quintile after adjusting for age and energy intake. When looking at whole grain intake and the risk of type II diabetes, a significant inve rse association was found. According to the author, the results provide supportive evidence that consumption of whole grains is associated with reduced risk of developing type II diabetes ( 33). Another study performed in 2000, Meyer et al. ( 34) also looked at the consumption of whole grains and type II diabetes. Whole grain consumption was found to be inversely associated with the risk of type II diabetes when comparing the highest quintile of whole grain intake to the lowest. A study performed in 2002, us ing data from the Health Professionals Follow up Study, found that the subjects who consumed diets high in refined grain remained positively associated with risk of type II diabetes ( 35). Later in 2002, Fung et al. ( 36) also used data from the Health Profe ssionals Follow up Study to investigate the association between whole grain intake and risk of type II diabetes. Whole grain consumption was inversely associated with the risk of type II diabetes after

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28 adjusting for fruit and vegetable intake and other con founding factors. In 2003, Monteonen et al. ( 37) looked at whole grain intake and the risk of type II diabetes using data from the Finnish Mobile Clinic Health Examination Survey. When compared to the highest quartile of whole grain consumption to the lowe st, and after adjusting for fruit, berry, and vegetable consumption and other confounding factors, whole grain consumption was inversely associated with the risk of type II diabetes. A more specific study by de Munter et al. ( 38), in 2007, investigated the association between whole Health Study. After adjusting for confounding factors such as physical activity and energy intake, the author found that whole grain and bran intake (2 serving per day increase) was inversely associated with risk of type II diabetes. This resulted in a 21% decrease in risk of type 2 diabetes. According to the observational data described here, an association between whole grain intake and type II diabetes has been established. Whole Grain and Obesity Epidemiological studies illustrate that consuming whole grains is associated with reduced risk of obesity and weight gain ( 10). To date, 14 cross sectional studies have been performed in order to i nvestigate the relationship between whole grain intake and weight management. All 14 of the studies found that higher intake of whole grains (a daily intake of 3 servings) are associated with lower BMI in adults ( 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51). In 2003, Liu et al. ( 41) investigated the association between whole grain consumption, body weight, and long term body weight changes consumed larger amounts of whole gr ain consistently weighed less than women who consumed smaller amounts of whole grain.

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29 ( 43) reported the association between whole and refined grain breakfast cereal consumption and weight gain i n men. The results demonstrate that whole grain breakfast cereal consumption was inversely associated with risk of having a BMI greater than 25 and weight gain of more than 10 kg, 8 years after initial subject evaluation after adjusting for baseline BMI, p hysical activity, age, and other confounding factors. Few randomized, controlled, trials have been conducted to see the effect of whole grains on weight management. Of the few that have been done, whole grains did not facilitate weight loss. Nevertheless, more intervention studies are needed to learn the effects of a diet rich in whole grains on weight ( 11). A study to specifically test the hypothesis of whether whole grain consumption is associated with lower body mass index among adolescents was performed by Steffen at el ( 40). The study involved 285 adolescents between the ages of 13 and 15 years old. After adjusting for age, gender, race, Tanner stage, and energy intake, the mean BMI for adolescents consuming less than serving of whole grain foods per day was 23.6, while the mean BMI for adolescents consuming more than 1 servings per day was 21.9. The author concludes that whole grain intake is associated with lower BMI in adolescents, particularly for the heaviest children. A higher intake of whole g rain foods was also associated with a healthier dietary profile, consisting of greater intakes of fruit and vegetables, fiber, iron, zinc, calcium, folate, and vitamin E. Additionally, the results show that initiating diets rich in whole grains during the adolescent years would be beneficial for weight management ( 40).

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30 Whole Grain and Cancer Many epidemiological studies have been performed in order to determine if a relationship between whole grain intake and relative risk of certain cancers can be establis hed. The 4 th most common type of cancer, colorectal cancer, contributes to 53% of all gastrointestinal cancers ( 10). From 1995 2007, four studies looked at whole grain consumption and colorectal cancer. In 1995, Jacobs et al. ( 21) reported an inverse assoc iation between whole grain consumption and risk of colorectal cancer. Four years later, Pietnen et al. ( 26) used data from the Alpha Tocopherol, Beta Carotene Lung Cancer Prevention Study and reported no association between colorectal cancer and intake of various rye products. These findings do not agree with the assumption that increased intake of whole grains decreases the risk of cancer, specifically colorectal cancer. In 2005, Larsson et al. ( 52) used data from the Swedish Mammography Cohort in order to report the association between whole grain intake and incidence of colon cancer. The author found that whole grain consumption was inversely associated with risk of colon cancer after adjusting for red meat, fruit, and vegetable intake and other possible confounding factors. In agreement with Larsson et al. ( 52), in 2008, Schatzkin et al. ( 53) also found an inverse association between whole grain consumption and risk of colorectal cancer. Interestingly, the association was stronger for men than for women a nd the reduced risk of site specific tumors was strongest for the rectum ( 53). Other cancers have also been of interest. Nicodemus et al. ( 54) investigated whole grains and breast cancer. Women in the lowest quintile of whole grain intake had a lower risk of breast cancer incidence compared to women in the highest quintile. Other studies report that there is an unclear association between dietary fiber and risk of

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31 death from breast cancer ( 55). Currently, more research is needed to further understand the re lationship of whole grain and breast cancer. Kasum et al. ( endometrial cancer and whole grain intake. Findings suggest that for women who have never received hormone replacement therapy, whole gr ain consumption was inversely associated with risk of endometrial cancer. However, no association was found between whole grain consumption and risk of endometrial cancer for the rest of the women in the study when confounding factors were adjusted for. Ch an et al. ( 57) found a strong inverse association between the risk of pancreatic cancer and the highest quartile of whole grain consumption to the lowest. Data was collected from a large population based case control study on pancreatic cancer and adjusted for history of smoking, red meat, fruit, and vegetable intake (57). Currently, researchers agree that it is not possible to determine exactly which specific components in whole grain are responsible for reduced risk of disease. It is suggested by Frolich et al. ( 4) that there is most likely a combination of different components providing such an effect. The author goes on to explain that because whole grains are made up of individual components correlated in different ways to each other, it is near imposs ible to separate their effects ( 4). Jonnalagadda et al. ( 10) describe this point even further, stating that health benefits associated with whole grains may be from the additive and synergistic effects of these bioactive phytochemicals. Epidemiological dat a has formed a foundation for the Dietary Guidelines 2010 to recommend that Americans consume at least half of their grains as whole grains. In

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32 whole grain foods and o ther plant foods and low in total fat, saturated fat, and ( 8). Furthermore, the FDA claims that there is a body of scientific research that provides compelling evidence that whole grain con sumption among the US population would have a marked impact on public health by reducing risk for some types of cancer and CHD ( 8). Whole Grain Recommendations The United States Department of Agriculture reports that Americans are getting enough total grai ns, however most are coming from refined grains. F or the past 20 years the USDA has suggested that whole grains are an essenti al factor for a healthful diet ( 58) T Chronic Disease R isk also recommends the consumption of whole grains ( 59). A food guide for the general population was created by the USDA called ChooseMyPlate to provide nutrient adequacy information for individuals, depending on their age, sex, and activity level ( 60). A ccording to ChooseMyPlate at least half of the recommended total grain intake should be from 100% whole grains. For many, this would amount to consuming 3 ounce equivalents or more of 100% whole grains each day. A slice of bread is an example of 1 ounce e quivalent. The amount of grains needed per day depends on age, sex, and level of physical activity. More specifically they suggest that adolescent males require between 6 to 7 ounce equivalents of grains per day with at least half being whole and adolesce nt females require 5 to 6 ounce equivalents of grains per day with at least half being whole Health organizations along with the U.S. government recommend people to consume more whole grains in accordance with research that has shown a relationship betw een positive health

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33 outcomes and whole grain consumption. The key consumer message the USDA is trying to get across is to make at least half of the grain intake whole grain ( 61). To determine if people are consuming the recommended amount of whole grains p er day, diet information from large epidemiological studies is analyzed. According to published data, adolescents seem to be an age group that is consuming well below the recommended amount of whole grains per day ( 62, 63, 64). Meeting the recommendations during the adolescent years is very important for growth and health outcomes they may affect adulthood and beyond. Adolescent Whole Grain Consumption In order to determine the average grain intake for adolescents Harnack et al. ( 64) examined data from th e 1994 1996 Continuing Survey of Food Intakes by individuals. From the survey, the intake and food sources of whole grains among adolescents aged 2 to 18 years old (n=4,802) was determined. The participants provided 2 days of dietary recall da ta administer ed by using the Continuing Survey of Food Intakes b y Individuals (CSFII) method. The CSFII method consists of two nonconse cutive days of dietary data, collected using a one day, interview administered, recall. The major sources of whole grains indentified were ready to eat cereals, corn and other chips, and yeast breads T he average whole grain intake for the adolescents sa mpled was 1.0 serving per day according to serving size as defined by the Food Guide Pyramid. It is noted that an aggres sive public heal th intervention targeted to childre n and adolescents are required to implement whole grain recommendations. In conclusion, the reported low levels of whole grain consumption in adolescents demonstrate th at the recommended amount is not being met ( 64).

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34 Tren ds of whole grain consumption in adolescents have also been studied In 2010, Burgess Champoux et al. ( 63) reported 5 years (1999 2004) of longitudinal and secular trends in adolescent whole grain consumption. Data was collected from 996 males and 1 222 fe males who were part of Project EAT (Eating Among Teens). In 1999, only 11% of adolescent males and 13% of adole scent females consumed more than one serving of whole grains per day. No significant changes in whole grain consumption for either sex were seen over the 5 years. Overall the reported average da ily intake of whole grains was below the rec ommended amount, for both sexes. Some potential barriers were reported as reason for the low a mount of whole grains consumed, such as taste, appearance, cost, te xture, knowledge of health benefits, and ability to identify whole grain products at the grocery store ( 66). The findings suggest that efforts should be made to help adolescents incr ease their whole grain intake. The researchers advocate the development of an intervention in order to improve the whole grain intake among adolescents to the recommended amount ( 63). In 2010, Larson et al. ( 62) reported data from Project EAT II and also suggest that an intervention to provide adolescents with whole grains is ne eded in order to increase whole grain consumpti on to the recommended amount. It was found that mean daily intake of whole grains was lower than recommended among adolescents. The author suggests that young people need to be provided with opportunities to taste a variety of whole grains in order to enhance taste preferences and awar eness of whole grain products ( 62). Low intake of whole grain was confirmed in another study, which associated improved diet quality and nutrient intake in children and adolescen ts consuming whole

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35 ( 65) used data from the National Health and Nutrition Examination Survey for 1999 2004, and found that adolescents 6 12 years old consumed an average of 0.59 servings of whole grain per day and adolescents 13 18 yea rs old consumed 0.63 servings of whole grain per day. The data demonstrates that overall consumption of wh ole grain in adolescents is low These intakes are even less than previously reported averages of whole grain intake among adolescents. Although whole grain intake was low among adolescents, an increased consumption of whole grain was associated with improved diet quality and nutrient intake. The improved diet quality may have the potential to improve even more if daily recommendations of whole grain in take were met in adolescents (65). According to the Whole Grains Council, in 2000, there were 164 whole grain product launches Fast forward to 10 years later, and 3,272 new products have been launched. Additionally, the whole grain stamp is now on over 5,300 different products across 22 countries. The council also provides data on the rise in overall whole grain consumption over the years. Apparently, from 2005 to 2008, consumption rose 20% after remaining steady from 1998 to 2005 and in 2008, 60% of Am ericans consumed at least one whole grain product during a typical two week period. Moreover, 18 to 34 year olds increased their consumption the most from 2005 to 2008, rising 38%. In conclusion, the group goes on to explain that Americans are still not ea ting the recommended amount, with only 11% eating their grains as whole grains ( 67). Observational data has b een assessed in order to determine the current amount of whole grains being consumed by adolescents ( 64, 62, 63, 65). Overall, adolescents are cons uming below the USDA recommended amount. A study to reveal the impact of

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36 providing grain foods (e.g. cereals, breads, and pastas) to adolescents has n ever been conducted and is needed to determine if adolescents will consume the recommended amount of whole grains if it is provided to them Perceptions Regarding Whole Grain Foods The USDA has been recommending the consumption of whole grain foods for many years, however overall, adolescents are not incorporating these foods into their diets at the recommende d amount. Including whole grains in the diet and establishing healthful eating habits at a young age may carry over to adulthood, thereby reducing the risk of chronic diseases. Burgess Champoux et al. ( 66) report some common barriers exist that may be cont ributing to the low intakes of whole grain foods among adolescents. Some of the potential barriers are taste, appearance, cost, texture, consumer knowledge of health benefits, and ability to identify whole grain products. Perhaps learning about the percept ions of young people regarding whole grain foods could eliminate some of these barriers and increase overall consumption of whole grain. In 2006, a study was performed to explore perceptions of whole grain foods and factors influencing intake of children (n=40). Focus group interviews were arranged for children in grades ranging from K 6 th grade. During the interview, a series of discussion questions were asked while a variety of whole grain and non whole grain bread and cereal products were shown. Most of the participants (70%) indicated they always or often ate school lunch. Along with questions pertaining to individual factors such as physical and socioenvironmental factors including the availability of whole grain foods, sensory characteristic questions rating of whole grain foods. Most children indicated that they wanted to eat the whole grain cereal and a majority liked the appearance, taste, and texture of the product. This

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37 study provides insight into the perceptions and views of whole grains according to a small group of children, however more research is still needed to optimize ways to increase whole grain consumption to the recommended amount ( 66). Findings from Project EAT (Eating Among Teens) report a conceptual model of factors influencing whole grain intake in adolescents, which include sociodemographic factors (race/ethnicity), socioenvironmental factors (support for healthy eating), behavioral factors (meal frequency), and personal factors (taste preference) ( 62). Still, it is reported that little is known about the barriers to whole grain consumption in adolescents. Dietary Assessment Dietary assessment has increased in popularity since the link between diet and disease was established ( 68 ). More importantly, the accuracy of diet assessment has been an ongoing area of research since diet reporting can be so variable. This is needed in order to evaluate the diet precisely and validate findings. Dietary assessment is also a very valuable meas ure for clinical nutrition studies such as interventions, implementing new dietary guidelines or to see if guidelines are being followed. Measuring the diet of a specific population to determine if they are meeting recommendations requires some form of d ietary assessment. The United States diet assessments of the US population, among other things. Diet assessment strategies are very important for nutrition assessment, educ ation and research. Dietary Assessment Methodology The Nutrition in the Prevention and Treatment of Disease by the National Cancer Institute describes some commonly used methods for individual level diet assessment. These include dietary record, 24 hour di et recall, food frequency, brief dietary

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38 assessment instruments, diet history and blended instruments. These methods are all used to assess diet in a research setti ng ( 69). Diet Records A diet record is an approach in which the respondent records food and beverages and the amounts consumed over one or more days. It is suggested that foods and b everages be recorded shortly after they are consumed. Recording periods should last no more than 3 or 4 days in order to decrease the risk of respondent fatigue. Int ake has been known to be recorded using journals, dictation machines, computers, and self recording scales. In order for the respondent to accurately record their intake they must be trained at a level to en able them to report measurements of food and beve rag es ( 69). Using food records as a means to measure dietary intake has some advantages and disadvantages. Advantages for using food records include quantification of intake, the possibility of enhancing self monitoring for weight control or other behavior change, and not requiring the recall of foods eaten. However, some disadvantages include high investigator cost, high respondent burden, extensive respondent training and motivation, the need of many days to capture an g eating behavior (such as changing diet for ease of reporting), underreporting intake, and reports of intake decreasing with time ( 69). for dietary intake assessment (69). This is because many previous studies found that intake was underreported when using diet records compared to energy expenditure as measured by doubly labeled water ( 70, 71, 72, 73 74, 75). However, it

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39 omes to assessing diets for longer than 24 hours but no more than 3 to 4 consecutive days. ( 68). 24 Hour Diet Recall A 24 hour diet recall is a method used in which the respondent is required to give information about their dietary intake during a 24 hour peri od, typically the day prior. It 24 hour diet recall can be gathered by an in person interview, over the telephone, using a computerized interview, or using a pencil and paper form. In order for a 24 hour diet recall to be most accurate it is crucial that the interv iewer be well trained in food measurements and interview skills. The interviewer uses specific questions and statements in order to probe the respondent for details concer ning consumption. This has been known to help the respondent recall what was consumed in the past 24 hours. Interviewers are usually dietit ians or well trained interviewers that have an extensive knowledge of foods and beverages in the marketplace as well as measurements Currently, the most validated 24 hour diet recall used is one in which a multiple pa ss method is implemented ( 69). A 24 hour diet recall instrument has been standardized by the United States Department of Agriculture called the Autom ated Multiple Pass Method It is used in th e What We Eat in America survey a nationally representative dietary survey in the United recall and questions numerous times. Th e met hods consists of five passes: (i) an initial ) a forgotten foods list of 9 food categories commonly omitt ed in a 24 hour recall report (iii) time and occasion, (iv ) a detail pass with probing questions about portion size, eating occas ions and times and lastly, (v ) final review. For each recall the

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40 description of the food, amount of food consumed, additions to the food (cream in coffee), time eaten, name of eating occasion, where obtained, and whether it was eaten at home or not is reco rded. This method provides many advan tages for the researcher ( 69). Advantages for using the 24 hour diet recall method for dietary assessment includes, being able to quantify intake, being appropriate for most populations, having relatively low respondent burden, and not affe cting eating behavior. There are however some disadvantages, to include high investigator cost, many days needed to capture the individua ( 69). It has been reported that 2 4 hour diet recalls are most useful in population based studies. Depending on the number of days needed for dietary analysis, a 24 hour diet recall can be used in order to determine dietary patterns within a sample (68). Food Frequency Another approach f or dietary assessment described in the National Cancer Institute publication is called food frequency (69) Food frequency questionnaires (FFQ) are administered in order to sum the overall nutrient intake of an individual over the past week, month or even year. Questionnaires can be developed which target a specific population such as the diet of Native American Indians The main focus in the food frequency approach is to get a general ide a of the usual foods consumed. The respondent reports their usual co nsumpti on based from a list of foods. Generally, portion size is collected while more specific characteristics such as cooking methods or combination of foods in a me al are given in little detail. A typical FFQ consists of 100 individual items with additio nal portion size questions and may take up to 60 minutes to complete ( 69).

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41 Some adv antages for using an FFQ to collect diet information is that the usual individual intake is asked, information about total diet is obtained, there are low investigator costs and it does not affect eating behaviors. Moreover, some disadvantages in clude not being quantifiably pre cise, being a difficult cognitive task for the respondent and intake i s often misreported ( 69). Brief Dietary Assessment In struments Brief dietary as sessments are used in order to obtain crude information about the diet using a short screener. The screener may focus on one food group or incorporate multiple dimensions. For example, a fruit, vegetable, and dietary fiber screener may be used in order to study. Generally, 15 to 30 foods are used to estimate nutrient status. This enables large groups of people to be grouped such as those with low fiber intake. This can be helpful for resea rch criteria, to track changes in the diet or for directi on in nutrition education ( 69). Using brief instruments in order to assess dietary intake has its advantages. These include, low investigator costs, low respondent burden, not affecting eating behavi or and asking about the usual intake. Some disadvanta ges of using a brief instrument include, not being a quantifiably precise method, being a difficult cognitive task, and intake often being misreported. The authors suggest that brief instruments be used to assess dietary intake for specific food groups and not as a means for capturing an overall evalu ation of the diet ( 69). Diet History collection of information not only about the frequency of different foods but also about

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42 the typical composition of meals. Today, however, the term is used loosely to describe many assessments. The authors describe diet history as being most beneficial in in which many details about characteristics of foods as usually consumed are assessed in addition to the frequency and amount of food intake ( 69). The Burke diet history encompasses three parts: a detailed interview about usual pattern of eating (much like a 24 hour diet recall), a food list asking for amount and frequency usually eaten, and a 3 day diet record (69). These assessments are meant to ascertain the usual eating patterns for an extended period of time. Many other diet history methods have been f ormulated around th e original Burke diet history. Some advantages of the method i s that the usual intake is captured information on the total diet is obtained, information about foods consumed by meal is obtained, there can be low investigator costs, and it does not affect eating behavior. Some disadvantages of the diet history method are that it is not quantifiably precise, it has difficult cognitive tasks, the intake is often misreported, and it can have a high degree of investigator burden ( 69). Dietary Assessment in Intervention Studies During an intervention study, dietary assessment is necessary to evaluate changes in the diet that may be due to the intervention. Additionally, to determine effects that may be from the intervention, diet assessment nee ds to be performed before and during the intervention study. Studies have been done to determine which method of dietary assessment is most often used during small and large scale interventions. It has been reported that for small population studies, diet ary records, multiple 24 hour diet recalls, and diet history questionnaires are most commonly used.

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43 For larger scale studies, FFQs and brief instruments were used more frequently. Less precise measures of dietary assessment are generally used in larger st udies because of resource constraint ( 69). Dietary Assessment in Children and Adolescents Assessing the diets of children and adolescents has known to be more challenging compared to adults. In particular, there are reports that adolescents may be more wil ling to report, however their interest in giving accurate reports may be a problem. Furthermore, Rockett et al. ( record or remember their diets, as well as their limited knowledge of food and food preparation, there is an additional dimension of difficulty that must be addressed. Dietary assessment in children has been reviewed and many methods have been tested ( 68, 77, 76). It is suggested that dietary assessment in children and adolescents involv e blended instruments and other creative ways of engagement and motivation in order to retrieve the most accurate measure of intake ( 69). Rockett et al. ( 76), explains that the diets of young people have been evaluated using all of the previously mentioned methods and the development of these methods has been evolving since 1882. One of the first longitudinal studies, which looked at hour diet recalls. After the study began the investigators realized that me asures of quality control, such as protocols for interviewing and training of the interviewers, the use of food models and pictures, school lunch analysis, and duplicate recalls were necessary in order to obtain the most accurate data ( 77). These measures of quality control are still implemented today in many studies involving dietary assessment.

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44 Throughout the years, dietary assessment in children and adolescents has evolved from weighing food, to the development of the diet history, to standardized nutrit ion surveys and in the future, to computerized data collection programs. Rockett et al. ( 77) compare the validation of current methods and finds that dietary records, 24 hour recalls, and food frequency questionnaires all have their advantages and disadvan tages, as described before. Therefore, it is to the discretion of the scientist to re quires a lot of writing and food measurements from the subject, this can be difficult in an adolescent population. FFQs and 24 hour diet recalls may be more adolescent friendly because they both require less effort from the participant than diet records ( 7 6). Rockett et al. ( 68) describe that the main considerations, when it comes to choosing which dietary assessment tool to use in adolescents are : motivation, cognitive ability and literacy level of the participant, the size and location of the study popula tion, as well as the financial constraints and d etail of nutrient/food analysis Additionally, diet records should be used when a specific period of time needs to be accounted for (3 4 days), 24 hour diet recall should be used when an estimate of a populat year) ( 68). Issues in Dietary Assessment in Children and Adolescents The adolescent years are a time of growth and development, including changes that are biological, social, and psychological. Because of these changes, dietary patterns and cognitive abilities may be different than during childhood or adulthood.

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45 Understanding these patterns and abili ties is the key to developing an appropriate diet assessment strategy in adolescents ( 78). Livingstone et al. ( 79) describe the issues with dietary intake assessment of children and adolescents. More specifically, when it comes to the thought process of di report their food intake include their ability to estimate and indicate portion size and their knowledge of food. These problems have been indicated in children 12 years of age and young er. The author goes on to explain that by the ages of 8 10 years old children can reliably report their food intake, often as well as adults. When it comes to portion size estimations, adolescents as well as adults have been known to experience difficulty in reporting portion sizes and so one can conclude that the ability to estimate portion size is not age related. Earlier work suggests that the best way to improve portion size estimation is to train the respondent ( 79). In a study by Weber et al. (80) a 45 minute training exercise in portion size estimation improved the accuracy of estimated food portions in children ages 9 10 years old. Another issue related to dietary assessment in children is how they remember what they have eaten. Livingstone et al. ( 79) go on to describe the problem with how children remember, which can be one of the largest concerns when it comes to misreporting diet information. From previous work, the author describes that with all methods of diet assessment, there are problems wit h incorrect identification of foods and over and under reporting intake. Due to the lack of research, there is little known information ( 79). According to Baxter, et al. ( 81) in order to gain maximum recall from

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46 fourth grade children, non directive prompts and cues have been shown to be helpful, such as those used in the multi pass method of 24 hour diet recalls. The main problems with dietary assessment accuracy are error s due to omission (failure to report items actually eaten) and intrusion (report of something not eaten at all). These problems are commonly seen in children and adolescent populations. Domel et al. ( 82) looked at self reports of diet in order to describe how children remember what they have eaten. The author explains that learning how a child remembers what they have eaten may help in determining what kind of cue would be helpful in dietary assessment practices. The study involved 4 th grade students, with an average age of 10 years old. Researchers observed the children while they consumed their school lunch interviews were similar to the standard 24 hour diet recall method During their diet This response was then used in order to compose retrieval response categories. The categories are as follows: visual imagery, usual practice (habit), be havior chaining (linking item to other items or activities), preference, lunch menu, smell taste imagery, texture imagery, food related events, food label, expected inquiry (from parent or interviewer), completion (eating all of the meal), and other (does not fit into other categories). The authors believe the development and use of cues during dietary assessments are needed, which may help the respondent remember what they have eaten ( 82). A study was completed by Baxter et al. ( 83) to see the effects of s hortening the retention interval of 24 hour dietary recalls in fourth grade students. Over three school

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47 years, 374 fourth grade students were observed eating two school meals and then interviewed using the 24 hour diet recall method with three interview ti mes (prior 24 hour/morning, prior 24 hour/afternoon, and prior 24/evening). The researchers found that shortening the retention time of dietary recalls increases accuracy for reporting energy and macronutrients. In conclusion, when a researcher obtains the 24 hour diet recall is important for accuracy and needs to be considered when planning a study ( 83). Validation of Diet Assessment Methods Validation of dietary assessment is needed in order to determine the accuracy of the data obtained; this can be done using biomarkers or by comparing the tool in question to other diet assessment methods. The U.S. National Institutes of Health provides a dietary calibration/validation register for studies and their associated publications ( 84). In 1990, energy intake fr om dietary assessments was validated using a biomarker called doubly labeled water ( 79). Doubly labeled water is an isotope based method that meas ures the energy expenditure based on 2 isotopic labels in body water, 1 of hydrogen and 1 of oxygen. The doubl y labeled water method is based on the theory that total daily carbon dioxide production can be measured from the differential elimination of water labeled with stable isotopes of hydrogen and oxygen. The labeled hydrogen will be eliminated as water, while the labeled oxygen will be eliminated as carbon dioxide. Next, the difference between the elimination rates of the labeled oxygen and hydrogen is measured and the carbon dioxide rate can be calculated. The rates at which the isotopes are excreted in the u rine can be measured. This rate can then be converted into energy expenditure to be compared to energy intake recorded in dietary assessment methods. ( 85)

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48 An article by Burrows et al. ( 86) reviews the validity of dietary assessment methods in children whe n compared with the method of doubly labeled water. Between 1973 and 2009, a total of 15 articles were reviewed that used the doubly labeled water technique to validate reported energy intake by any other dietary assessment method. The gathered studies we re cross sectional in design and reported on a total of 664 children. The majority of the participants were white children aged 4 to 11 years old. The most commonly used dietary assessment tools of the 15 studies reviewed were 24 hour multiple pass recalls (n=4 studies) and estimated foods records (n=5 studies). Other methods included diet history, weighed food records, and FFQ. In most of the studies, both the child and one or two of the parents/caregivers reported dietary intake ( 86). Out of the 15 studi es reviewed, all concluded some degree of misreporting. It was found that food records were underreported by 19% to 41% while over reporting was associated with 24 hour recalls (7% to 11%), diet history (9% to 14%), and FFQ (2% to 59%). Overall, the author s suggest that the most accurate and convenient method for reporting energy intake in children aged 4 to 11 years old is the 24 hour multiple pass diet recall conducted over a 3 day period that includes weekdays and weekend days, using parents as the repor ter. Furthermore, additional research is needed to further validate the conclusions. ( 86). Validity of the Multi Pass 24 hour Diet Recall Since 1965, the USDA has been conducting n ationwide surveys on the diets consumed by people in America using the 24 ho ur dietary recall method. Recently a group known as the ARS Food Surveys Research Group (FSRG) improved the method, whic h is now known as the multiple pass method of 24 hour diet recall. This method

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49 uses the technique of guiding the participant through a 24 hour reference period of food intake more than one time, as previously described. Each pass probes for more detail and helps the subject recall information regarding their diet. Currently this method is being used for the dietary interview portion of th e What We Eat in America survey to collect statistical data about the current dietary intake and health of people in the United States. T has been reviewed and validated by many published articles ( 87, 88, 89). Revisions were made to the original method of 24 hour diet recall because of data showing that underreporting was common. The multiple pass method hopes to improve accuracy by keeping respondents interested and engaged in the interview process and to help them remember all foods they had consumed ( 90). The multiple pass method is thought to help respondents recall more foods they consumed by asking about their intakes in different ways. Moshfegh et al. ( 88) reported that the new method was tes ted in a nationwide pilot study of 800 individuals and showed that the average calorie intakes and the number of foods reported were higher than data from 1996, using the original recall method (without multiple passes). This indicates that perhaps the mul tiple pass method helps respondents remember and report more foods consumed than the original method ( 88). Furthermore, the USDA multiple pass method has also been evaluated by comparing reported energy intake with total energy expenditure using the doubl y labeled water technique. Five hundred twenty four participants, aged 30 69 years old, were included in a study in which doubly labeled water was dosed on the first day of the 2 week study period while three 24 hour diet recalls were collected using the m ultiple

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50 pass method. Overall, the multiple pass method accurately reported energy intakes, with approximately 78% of men and 74% of women classified as acceptable energy reporters ( 88). In conclusion, more research needs to be conducted to understand varia bility of the multiple pass 24 hour at the individual level, however data shows this method to be accurate for obtaining dietary information among populations of adult men and women. Validation of Diet Assessment Tools Developed Specifically for Adolescent s When it comes to gathering information about the diet, as previously described, adolescents have issues that need to be addressed. Measuring diet intake in adolescents is specifically complex because of issues with memory, portion size estimation, having variability in day to day intake and misreporting intake. Therefore, dietary assessments developed for adults need to be adapted for adolescents. Described here is some dietary assessment tools developed specifically for adolescents. Rockett et al. ( 77) d eveloped a Youth/Adolescent Food Frequency Questionnaire to be used to assess the diets of large populations of youths. The questionnaire is different than the standard FFQ for adults because the researchers refined the format and tried to make it relevant and simpler to complete. For instance, the Youth/Adolescent Food Frequency Questionnaire has a modified food list that reflects more of what adolescents consume. The validity of the Youth/Adolescent Food Frequency Questionnaire was tested with a sample of 261 adolescents, ages 9 to 18 over a one year time period. The researchers compared the average of three 24 hour diet recalls to the average of two Youth/Adolescent Food Frequency Questionnaires. The authors define the validity of a food frequency questio

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51 When nutrient intake was compared between the two methods, the Youth/Adolescent Food Frequency Questionnaire demonstrated to be an accurate me asure in order to ( 77). In 2001, a food checklist was validated as part of the Child and Adolescent Trial for Cardiovascular Health (CATCH). The food checklist is similar to a FFQ in that it was developed to p rovide a brief, inexpensive, and easily administered measure of the diet. More specifically, the food checklist was developed to target 3 nutrients: total fat, saturated fat, and sodium. It consists of 40 items including 30 foods, 2 beverages, and 8 condi ments. The criterion measure for validation was a 24 hour diet recall. Following extensive analysis, the researchers conclude that the food checklist is a reliable and valid assessment tool for measuring fat, saturated fat, and sodium in adolescents ( 91). Vereecken et al. ( computerized 24 hour diet recall designed for children and adolescents aged 11 years and older. The program consists of one 24 hour diet recall made up of six meal occasions, embedded questions, and a selection of over 400 food items. In order to validate the program, two studies were initiated with a total of 145 participants. Study one compared the program to a one day food record and study two compared the program with a 24 hour diet recall interview. Results indicate that the Young nutrient and energy intake when compared to the food record, however this was not

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52 Nutrition Assessment on computer may be a useful method for collecting dietary information from adolescents when interviews cannot be co mpleted ( 92). In 2007, an adolescent web based food frequency questionnaire was tested for validity and reproducibility. The questionnaire has been developed to be cost effective and easy to administer. The questionnaire contains 15 food groups including b everages, snacks, and sauces, among others. The participants were a selected group of 12 to 18 year olds (n= 104). The FFQ data was compared to 3 day estimated food records. The data suggests that most questions on the 15 food groups had acceptable reprodu cibility however, validation was only shown for select food groups: water, fruit, bread, and fish/eggs/meat. This indicates that further development and investigation is needed in order to establish a valid FFQ for an adolescent population ( 93). Cullen et al. ( 94) tested the reliability and validity of a Block Kids Questionnaire. The Block Kids Questionnaire is a self report of consumption based on 72 food/beverage items for a period of 7 days. The questionnaire uses 6 response categories, ranging from none to everyday. Additional questions were used in order to clarify response, such as cereal type. Visual aids were used for serving sizes on plates and bowls. Children and adolescents (n=83) aged 10 17 years old completed two 24 hour diet recalls by telephon e in order to compare dietary intake to the Block Kids Questionnaire. The results suggest, that in general, the Block Kids Questionnaire has validity for some nutrients and may be most beneficial for adolescents older than age 12 years ( 94). Foster et al. ( 95) developed and evaluated three different portion size assessment tools for use with children. This may be very helpful since previous work finds that

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53 portion size estimation is an issue with adolescent diet assessment ( 79). The aim of the study was to using three tools: child specific food photographs, food models and a novel interactive portion size assessment system. The study included 200 children, ages 4 16 years old. The child ren were provided with foods of known weights and each portion size tool was evaluated during a 24 hour diet recall. The authors found the food models to be the least accurate of the three. The interactive portion size assessment system and the food photog raphs were reported as having potential for use with children, however the with actual food intakes ( 95). In 2010, Ambrosini et al. ( 96) compared a standardized F FQ and a 3 day food diet over a long period of time and food records are known to generate in depth information about the diet over 3 4 days, a diet pattern association between the two methods was tested. In order to compare the data, each item that was recorded in the food record was matched with an FFQ item. The scientists found that the nutrient profiles of the dietary patterns between the two methods were similar. Two patterns were found when both methods of dietary assessment were used on adolescents diet patterns were found when both methods were used in adolescents, the authors conclude that these two dietary patterns are relatively valid in adolescents ( 96). A study by Kobayashi et al. ( 97) looked to validate a food frequency questionnaire (CFFQ) for estimating habitual intake in children and adolescents. The author notes that

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54 it is not feasible to conduct 24 habitual dietary intake. This may be due to difficultly in obtaining accurate dietary information because children are known to lack knowledge about foods and cook ing methods ( 97). Additionally, it has been reported that when FFQs are administered to adults, dietary intake is overestimated. The FFQ (CFFQ) developed for assessing the diets of children is a 75 item questionnaire which includes the average portion size consumed by 3 to 11 year olds and also individual foods as well as mixed dishes. In order to validate the CFFQ, it was compared to weighed dietary records and also to an adult FFQ. The participants were among two groups, 3 11 years old (YC) and 12 16 year s old (AD) for a total of 103 children. The questionnaires for the children in the YC groups were completed by their parent/guardian while the AD group self administered. The researchers found that the CFFQ may be a helpful tool for assessing habitual diet ary intake for the children in the YC group, however it was found to underestimate dietary intake in the AD group ( 97). Diet assessment methods have even been developed in order to analyze the intake of specific food groups. A FFQ was developed by Ross et al. (98) that specifically targets whole grain cereal intake. However, a food group FFQ specific for adolescents has not been found in the literature. Currently, methods are still being developed and validated in order to accurately measure the diets of ad olescents. Future Dietary Assessme nt Methods Technological advances have led to the development of diet assessment and evaluation tools on mobile devices (99). A group at Purdue University has developed an application for a smart phone, which provides a u nique vehicle for collecting dietary information. The diet assessment application uses an image analysis approach that

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55 involves the subject taking a picture, using the mobile device, of food before and after consumption. The researchers believe that this a pproach will lessen the burden of recalling intake that is necessary for traditional diet assessment methods and is known to be a limitation. The next step is to test the device for accuracy and subject proficiency ( 99). Previous results found that adolesc ents prefer technology based dietary assessment methods to traditional methods. It is known that adolescents tend to have less structured eating habits such as eating away from home, snacking a lot and problems with remembering what they consumed and so th eir burden of reporting diet intake may be greater than adults. Additionally, reporting serving sizes of foods and drinks consumed has also shown to be problematic for adolescents. In 2010, evidence based development of the mobile telephone food record was reported. Seventy eight adolescents taking part in a technological based summer camp were recruited to use the mobile telephone food record for one or two meals. The system, a mobile telephone with a built in camera, is used to capture images of food befo re and after consumption and sent to a server for evaluation. Next, the information from image analysis and volume estimation can be linked to a nutrient database in order to estimate energy and nutrients consumed, this information can then be sent to rese archers or dietitians to be further analyzed ( 100). In regard to ease of use, the majority of participants agreed that the software was easy to use. Moreover the majority of participants were able to save images that included all of the foods and beverage s in both before and after images for the first and

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56 image of everything consumed improved after the first use. In conclusion, the researcher states that results from this study will lend a hand in improving future diet assessment methods in adolescents ( 100).

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57 CHAPTER 2 PURPOSE Consuming adequate amounts of whole grain foods (at least 3 ounce servings per day) is important because the individual may acquire healthful benef its such as reducing the risk of developing chronic diseases and maintaining a healthy weight (2). Adolescents are a population known to under consume (<1 serving per day) whole grains (62). Thus, the current study will quantify the amount of grains consum ed by adolescents while receiving weekly groceries of whole or refined grain foods. For the research proposed here, targeted multi pass 24 hour diet recalls were administered to assess the effects of providing grain foods to middle school children. It is hypothesized that providing whole grains to adolescents will increase their daily consumption to the recommended amount.

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58 CHAPTER 3 METHODS Study Design A six week r andomized, controlled, parallel arm study was carried out with 8 3 healthy adolescents, age s 11 1 6 years enrolled in Westwood Middle School, Gainesville, FL (Figure 3 1). Participants were started on the protocol in three waves. Wave 1 was randomized February 8 through 11 (whole grain, n=21; refined grain, n=24). Wave 2 was randomized Februar y 16 through 19 (whole grain, n=16; refined grain, n=16), and wave 3 was randomized on February 23 (whole grain, n=4; refined grain, n=2). Only one child from each household was enrolled to avoid having two children from the same household being randomized to two different treatment groups. If two students in the same household were interested in participating, the younger child was selected to participate. Institutional Review Board approval was obtained from the University of Florida IRB 01. Approval was also obtained by the Alachua County Public Scho ols and Westwood Middle School. Informed consent from one parent and assent from all study participants was obtained Inclusion / Exclusion Criteria after Obtaining Consent and Assent Participants were inclu ded if they were willing to eat three different study foods each day for six weeks. Subjects were excluded if they i) were taking any medications for constipation or diarrhea, receiving antibiotics during the four weeks prior to randomization, or consumin g probiotics or more than three servings per week of yogurt; ii) had any diseases or illnesses such as gastrointestinal disease (gastric ulcers, diabetes, kidney disease or immune modulating diseases (HIV, AIDS, autoimmu ne, hepatitis, cancer etc.) or any food allergies.

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59 Pre B aseline and Baseline All participants were given a disposable soup sized bowl marked in q uarter cup increments. Participants were told to use these bowls to estimate the se rving size of cereal, pas ta, rice and any other study foods provided. These same bowls were used during the targeted 24 hour diet recalls to more accurately describe serving sizes. The participant or family were contacted via phone or email to remind them of study appointments, sc hedule new appointments, discuss study procedures, deliver study foods, and obtain the 24 hour diet recalls. Pictures were taken of each student to keep in the subject file for identification purposes. In the week before randomization h eight, weigh t, age, and body mass index was obtained to determine BMI percentile for age. Trained study coordinators administered two targeted multiple pass 24 hour diet recalls. Participants were asked to list all of the foods and beverages they consumed in the previous 2 4 hours (midnight to midnight); but specific information (i.e., serving size, whole grain vs. refined grain, method of preparation, etc.) was only obtained for grain products, fruits, and vegetables. Time was limited for acquiring diet information; therefo re to obtain the most accurate measure, only extensive information on grains, fruits, and vegetables consumed was obtained. Cups, disposable soup bowls, and food diagrams were used to h elp determine serving size. A measurement guide and procedure booklet w as created for the interviewers to use while administrating the di et recall. The booklet included a step by step procedure of the multi pass method, pictures of foods and dimensions, measurement techniques, and pictures of grain foods that were provided to the children. I nvestigators worked closely with the food service director at the middle school to obtain menus, recipes, and lists of whole grain foods provided during the study period.

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60 On the first day of the study, participants were randomized and rec eived their study food for the week. Randomization Participants were proportionally stratified based on BMI (<95 th BMI percentile for age or BMI <30, > 95 th BMI percentile for age or BMI > 30) and randomized in to two groups (i.e., whole grain or refined g rain ). This study was not blinded but study groups were denoted as green (whole grain) or white (refined grain) to de emphasize the treatments. Participants were randomized via sealed envelopes to receive whole grain foods or refined grain foods. The strat ification and randomization schemes were generated by the study statistician, who did not have direct contact with any subjects. Treatment Foods, such as pasta, rice, bread, cereal, and pancake mix were provided for the for the six week study period. Four rotating weekly food packages were planned (Table 3 1, Table 3 2, Table 3 3, and Table 3 4). Foods for each type and brand between the groups. For exam ple, in whole grain package 1, whole grain pasta was included and in refined grain package 1, regular pasta was included. Parents were encouraged to pick up the weekly food packages before or after school; however, approximately half of all weekly food pac homes. Study staff were available at the school (e.g., before and after school or during home room or lunch) to distribute study snack foods and assist study participants with questionnaire completion. Two single servi ngs of whole grain cereal packs (whole grain group) or 100 kcal cookie packs (refined grain group) were distributed to subjects on school days. Students were asked to consume at least three different study foods each

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61 day. There was no maximum limit for dai ly study food consumption. Study staff emphasized replacing normally consumed grain products with study foods rather than adding more food, to ensure energy balance was maintained. The average nutrient information per ounce equivalent for the whole grain a nd refined grain packages is listed in Table 3 5. Ounce Equivalents USDA ChooseMyPlate guidelines for ounce equivalents were used in order to quantify the ounces of grains per serving consumed by the participants. According to ChooseMyPlate, one slice of b read, one cup of ready to eat cereal, or cup of cooked rice, cooked pasta, or cooked cereal is considered one ounce equivalent from the grains group (Table 3 5). If a grain food consumed by a participant was not included in the ChooseMyPlate guidelines f or ounce equivalents, the grain content was determined by entering the food into myfoodapedia.gov (61). Lastly, if the food was not found in myfoodapedia.gov, the grain content was determined using calculations based on the food label. Some examples of foo ds that were not found on myfoodapedia.gov are cookies, cakes, brownies, and granola bars. For these, total carbohydrate as well as sugar from carbohydrate was calculated to find the grain content. Since all grain ounce equivalents are based from one slice of bread and the average slice of bread contains 20% of its carbohydrate from sugar and contains 15 g of carbohydrates, the grain content was determined by multiplying the grams of carbohydrate by the amount of sugar found in one slice of bread (20% ). Nex t, that amount was subtracted from the sugar listed on the food la bel. Foods with greater than 20% carbohydrate from sugar will be subtracted from total carbohydrate and divided by 15 g. For example: Granola Bar

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62 23 g Carbohydrate (CHO) 12 g sugar 23 g CHO X 0.2= 4.6 g 12 g sugar 4.6 g = 7.4 g = sugar content of granola bar based on one slice of bread 23 g CHO 7.4 g = 15.6 g CHO 15.6 g/ 15 = 1.04 ounce equivalents Statistical Analyses Data were analyzed for intent to treat subjects (i ncluded all subjects enrolled in the study). Daily d ietary intake of grains during the pre baseline period was averaged for study and non study grain products during th e six week intervention period was The effect of gender, race/ethnicity study period (pre base line vs. treatment), treatment group and the interactions between treatment group and the othe r main effects on average daily intake of whole refined total grain fruit and vegetable intake was examined. Data were analyzed using mixed effects linear models with the above mentioned variables as fixed effects and student as a random effect to acc ount for the repeated measurements on each student ( pre baseline vs. treatment). Residuals were checked to ensure the assumptions of normality and constant variance were met. When fixed effect variables or their interactions were significant ( =0.05), treatment means were tested using the Tukey Kramer adjustment to control the family wise error rate at =0.05. Daily and Weekly Measures Participants were given study workbooks with tear out pages for daily logs (Appendix A) and asked to come to the designated study area (i.e., school trophy hall) each school day to drop off their completed logs. The daily logs asked about the consumpt ion of study foods. Each week the subject met with a study coordinator to be weighed and to provide a targeted 24 hour diet recall.

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63 Final Study Week During the last week of the study int ervention, one 24 hour targeted diet recall was obtained from each participant. On the last day of the study, h eight and weight was also reassessed. Incentives In addition to stud y foods, subjects received coupons with a total of seven coupons possible: one coupon for completing the pre study week and six additional coupons for completi ng each of the six study weeks. Each week they participate d they received another coupon. At the end of the study, the subjects trade d the coupons for one prize. There were seven levels of prizes of increasing dollar value to approximately $100 for seven coupons (i.e., for completing the study).

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64 Figure 3 1 Study design

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65 Table 3 1 Foods prov ided during weeks 1 and 5 for subjects in wave 1, week 4 for wave 2 and week 3 for wave 3 Whole Grain Package #1 Fiber/Ounce equivalent Whole Grain/Ounce equivalent Refined Package #1 Fiber/Ounce equivalent Honey Nut Cheerios (General Mills) 3 g 18.7 g F rosted Flakes 0.7 g 100% Whole Wheat Bread (Arnold) (2 loaves/week) 3 g 22 g Country White Bread (Arnold) (2 loaves/week) 1 g Whole Wheat Rotini (Barilla) 2 g 14 g Rotini Pasta (Barilla) 1 g Natural Brown Rice (Publix) 1 g 28 g Long Grai n Enriched Rice (Publix) 0.5 g Ready Brown Rice 1 g 25.5 g Ready White Rice 0.5 g Blueberry Cereal Bars (Nutri Grain) 1 g 8 g Fruit and Grain Blueberry Bars (Publix) 2 g Whole Wheat Blend Pancake Mix (Aunt Jemi ma) 1 g 6.5 g Original Complete Pancake Mix (Aunt Jemima) 0 g Oats and Honey Granola Bars (Nature Valley) (General Mills) 1 g 14 g Rice Krispies Treats Variety Pack 0 g Sun Chips Harvest Cheddar (Frito Lay) 2 g 14.4 g Mini Pretzels (Sun S nyder of Hanover) 1 g Whole Grain Goldfish (Pepperidge Farm) 1 g 11.2 g Goldfish (Pepperidge Farm) 1 g Nesquik Cereal Packs (General Mills) 1 g 9.7 g 100 Calorie Right Bites Macaroni and Cheese (Kraft) 1 g 1 g

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66 Table 3 2 Foods provided during weeks 2 and 6 for subjects in wave 1, weeks 1 and 5 for wave 2 and week 4 for wave 3 Whole Grain Package #2 Fiber/Ounce equivalent Whole Grain/Ounce equivalent Refined Grain Package #2 Fiber/Ounce equivalent Reese (General Mills) 2 g 14.5 g Special K 2.6 g Select Wheat Sandwich Rolls (Arnold) 3 g 10 g Sandwich Rolls with Sesame Seeds (Arnold) 1 g 100% Whole Wheat Bread (Arnold) 3 g 22 g Country White Bread (Arnold) 1 g Whole Wheat Roti ni (Barilla) 2 g 14 g Rotini Pasta (Barilla) 1 g Whole Grain Macaroni and Cheese (Kraft) 1 g 14.5 g Macaroni and Cheese (Kraft) 1 g Ready Brown Rice 1 g 25.5 g Ready White Rice 0.5 g Strawberry Cereal Bars (Nutri Grain)(Kello 1 g 8 g Fruit and Grain Strawberry Bars (Publix) 2 g Instant Oatmeal Packets: Flavor Variety (Quaker) 2 g 25 g Instant Cream of Wheat Variety Pack (B & G Foods) 1 g Nature Valley Granola Bars Variety Pack (General Mills) 1 g 14 g Rice Krispies Trea ts Variety Pack 0 g Tostitos Restaurant Style Tortilla Chips (Frito Lay) 1 g 6 g Mini Pretzels (Sun Snyder of Hanover) 1 g Whole Grain Goldfish (Pepperidge Farm) 1 g 11 g Goldfish (Pepperidge Farm) 1 g Orville Redenbacher Popcorn 3.5 g 35 g Rice Cake Snacks Ranch Flavor (Quaker) 0 g Nesquik Cereal Packs (General Mills) 1 g 9.7 g 100 Calorie Right Bites 1 g

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67 Table 3 3. Foods provided during week 3 for subjects in wave 1, weeks 2 and 6 for wave 2 and weeks 1 and 5 for wave 3. Whole Grain Package #3 Fiber/Ounce equivalent Whole Grain/Ounce equivalent Refined Grain Package #3 Fiber/Ounce equivalent Total Cinnamon Crunch (General Mills) 4 g 8 g Rice Krispies 0 g Wheat Bagels (Flower Foods) 1 g 4 g wn Original Bagels (Flower Foods) 0.6 g 100% Whole Wheat Bread (Arnold) 3 g 22 g Country White Bread (Arnold) 1 g Whole Grain Macaroni and Cheese (Kraft) 1 g 14.5 g Macaroni and Cheese (Kraft) 1 g Ready Brown Rice 1 g 25.5 g Ready White Rice 0.5 g Nutri Grain Apple Cinnamon Cereal Bars 1 g 8 g Fruit and Grain Apple Cinnamon Bar (Publix) 2 g Instant Oatmeal Packets: Flavor Variety (Quaker) 2 g 25 g Instant Cream of Wheat Variety Pack (B & G Foods) 1 g Nature Valley Granola Bars Variety Pack (General Mills) 1 g 14 g Rice Krispies Treats Variety Pack 0 g Original Sun Chips (Frito Lay) 2 g 14 g Mini Pretzels (Sun Snyder of Hanover) 1 g Whole Wheat Ritz Crackers (Nabisco World) 1 g 5 g Reduced Fat Ritz Crackers (Nabisco World) 0 g Nesquik Cereal Packs (General Mills) 1 g 9.7 g 100 Calorie Right Bites 1 g

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68 Table 3 4. Foods provided during week 4 for subjects in wave 1, week 3 for wave 2 and weeks 2 and 6 for wave 3. Whole Grain Pac kage #4 Fiber/Ounce equivalent Whole Grain/Ounce Equivalent Refined Grain Package #4 Fiber/Ounce equivalent (Maple and Brown Sugar) 5 g 46 g Cocoa Krispies 1 g Whole Wheat Tortillas (Mission) 1 g 15 g Flour Tortillas (Mission) 1 g 100% Whole Wheat Bread (Arnold) 3 g 22 g Country White Bread (Arnold) 1 g Whole Grain Thin Spaghetti (Barilla) 3 g 14 g Thin Spaghetti (Barilla) 1 g Ready Brown Rice 1 g 25.5 g Ready White Rice 0.5 g Nutri Grain Mixed Berry 1 g 8 g Fruit and Grain Mixed Berry Bars (Publix) 2 g Instant Oatmeal Packets: Flavor Variety (Quaker) 2 g 25 g Instant Cream of Wheat Variety Pack (B & G Foods) 1 g Nature Valley Granola Bars Variet y Pack (General Mills) 1 g 14 g Rice Krispies Treats Variety Pack 0 g Tostitos Restaurant Style Tortilla Chips (Frito Lay) 1 g 8 g Mini Pretzels (Sun Snyder of Hanover) 1 g Whole Grain Goldfish (Pepperidge Farm) 1 g 11 g Goldfish (Pepperidge Farm) 1 g Nesquik Cereal Packs (General Mills) 1 g 9.7 g 100 Calorie Right Bites 1 g

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69 Table 3 5 Specific amounts that count as 1 ounce equivalent of grains towards daily recommended intake. Grain Food Type of Grain Amount that counts as 1 ounce equivalent of grains Common portions and ounce equivalents Bagels WG*: whole wheat RG*: plain, egg 1 large bagel = 4 ounce equivalents Biscuits (baking powder/ buttermilk RG*) ounce equiv Bulgur cracked wheat (WG*) cup cooked Cornbread (RG*) equivalents Crackers WG*: 100% whole wheat, rye RG*: saltines, snack crackers 5 whole wheat crac kers 2 rye crispbreads 7 square or round crackers= 1 ounce equivalent English muffins WG*: whole wheat RG*: plain, raisin muffin 1 muffin = 2 ounce equivalents 1 muffin = 2 ounce equivalents Muffins WG*: whole wheat RG*: bran, corn, plain = 3 ounce equivalents Oatmeal (WG) cup cooked 1 packet instant 1 ounce dry (regular or quick) Pancakes WG*: Whole wheat, buckwheat RG*: buttermilk, plain 2 small panc diameter) diameter) = 3 ounce equivalents Popcorn (WG*) 3 cups, popped 1 microwave bag, popped = 4 ounce equivalents Ready to eat breakfast cereal WG*: whole wheat RG*: enriched, durum 1 cup flakes or rounds 1 cup puffed 1 cup cooked = 2 ounce equivalents

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70 Table 3 5. Continued. Grain Food Type of Grain Amount that counts as 1 ounce equivalent of grains Common portions and ounce equivalents Rice WG*: brown, wild RG*: enriched, white, polished cup cooked 1 ounce dry 1 cup cooked = 2 ounce equivalents Pasta -spaghetti, macaroni, noodles WG*: whole wheat RG*: enriched, durum cup cooked 1 ounce dry 1 cup cooked = 2 ounce equivalents WG*: whole wheat, whole grain corn RG*: Flour, corn 1 small flour tortil diameter) diameter) = 4 ounce equivalents

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71 CHAPTER 4 RESULTS Subject Demographics and C haracteristics From a population of 970 students, 196 were screened and 91 were consented (Figure 4 1 ). Of these potential subjects, eight were excluded. Four of the subjects did not meet inclusion/exclusion criteria (three changed schools, one started on antibiotics) and four were no longer interested in partici pating. Forty two subjects were randomized to the refined grain group and 41 to the whole grain group. All subjects completed the 8 week study period. There were no differences between groups in regards to gender, age, grade in school, race/ethnicity, the percentage of subjects classified as under or hea lthy weight (<85 th percentile BMI for age), overweight (85 th to <95 th percentile), or obese ( > 95 th percentile), participation in school breakfast or lunch, preference for study foods, the percentage of subjects who walk or bike to school or participate in organized sports/activities or number of days of targeted 24 hour diet recalls of intent to treat (ITT) subjects. However, fewer subjects in the whole grain group took a physical education class in school (Table 4 1 ). The average number of 24 hour targeted diet recalls obtained during the pre baseline and treatment periods were not significantly different between the treatment groups (Table 4 2). The percentage of school days (i.e., Monday through Friday) assessed by the targeted 24 hour recalls was compare d for all subjects across gender, treatment group, study period (pre baseline vs. treatment), and race/ethnicity. The percentage of the school day intakes did not depend on gender, race/ethnicity, the pre baseline or treatment periods or treatment group fo r the ITT analysis (Table 4 1).

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72 Nutrient information of the food packages was obtained using Food Processor software based on ounce equivalents. Foods in the whole grain packages had significantly higher total fat, dietary fiber, sugar, and protein and sig nificantly lower sodium than foods in the refined grain packages. On average, the whole grain packages provided 16 grams of whole grain per ounce equivalent (Table 4 3). Figure 4 2 and 4 3 represent the most commonly consumed food item provided in the food packages. Total Grain Intake Dietary intakes of grains during the pre baseline period were averaged for each subject to provide the average Intakes during the six week intervention period were averaged for each subject to provid e a intake. The effect of gender, race/ ethnicity, study period (pre baseline vs. treatment), and treatment group on average daily intake of all grains ( ounce equivalents) was examined for all subjects. The average daily ounces of grain repre sents intake of refined and whole grains from all foods (i.e ., study and non study foods). Gender, treatment group, study period race/ ethnicity and the interaction between treatment group and race/ ethnicity had a significant effect on the average daily in take of total grain ounce equivalents (Table 4 4) Males consumed significantly more ounce equivalents of total grains than females (P=0.0026) across both groups and treatment periods (pre baseline/treatment period) (Figure 4 4 ). However, there was not a s ignificant interaction between gender and treatment group or gender, treatment group, and study period (i.e., pre baseline vs. treatment periods). This suggests that males and females did not eat different amounts of total grains when they were randomized to receive refined grain versus whole grain foods.

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73 Total grain intake was significantly lower across study period s in subjects eventually randomized to the whole grain group (P=0.0063 ) (Figure 4 5 ), and all subjects consumed more grains during the study p eriod (P=0.0014) regardless of treatment group (Figure 4 6 ). There was no treatment group by study period interaction (P=0.6878) suggesting that total grain intake was not different between subjects in the refined grain and whole grain groups during the pr e baseline or treatment periods (data not shown ). Total grain intake was significantly different across race/ethnicity (Figure 4 7). Tests of effect slices for group*race/ethnicity sliced by race/ethnicity or by group t Difference Tests took in fewer grains when they were randomized to the whole grain group. category consisted of Asians (n=2), mixed White /African American (n=4) and s ubject defined as other (n=2). Refined Grain Intake Dietary intakes of grains during the pre baseline period were averaged for each week int ake. The effect of gender, race/ethnicity, study period (pre baseline vs. treatment periods), and group on average daily intake of refined grain (ounce equivalents) was examined for all subjects. The average daily ounce equivalents of refined grain represe nts intake from all foods (i.e ., study and non study foods). Gender, treatment group and the interaction between treatment group and study period significantly influenced the average daily intake of refined grains (Table 4 7 ). Males took in significantly m ore refined grains than females across treatment groups and periods

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74 (Figure 4 8 ). Pair wise comparisons show that participants randomized to the refined grain group had a significantly higher average daily intake of refined grains compared to those randomi zed to the whole grain group (data not shown). During the pre baseline period, subjects consumed on average 4.1 0.2 oz. (LS means SE) equivalents of refined grains, and there was no difference in intakes by subjects eventually randomized to the whole grain versus refined grain groups Subjects in the refined grain and whole grain groups significantly increased and decreased their average daily intake of refined grains, respectively during the treatment period compared with the pre baseline period (Figure 4 9) There were no differences in the average daily intake of refined grains among ethnic and racial groups Whole Grain Intake Dietary intakes of grains during the pre baseline period were averaged for each ntake. Intakes during the six week intake. The effect of gender, race/ethnicity study period (pre baseline vs. treatment periods), and treatment group on average daily inta ke of whole grain ( ounce equivalents ) was ex amined for all subjects. The average daily ounce equivalents of whole grain represents intake from all foods (i.e., study and non study foods). Treatment group, study period race/ethnicity and the interaction b etween group and study period had a significant effect on the average daily intake of ounce equivalent s of whole grain (Table 4 8 ). Subjects were consuming on average 1.0 0.2 oz. equivalents (LS mean SE) of whole grain d uring the pre baseline period. Ther e was no difference in average intake of whole grain ( ounce equivalent s) during the pre baseline period by subjects eventually

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75 randomized to the refi ned grain or whole grain groups Average intake of whole grain was significantly higher in those participan ts randomized to the whole grain treatment group compared to the refined grain treatment group. Subjects randomized to the whole grain or refined grain group significantly increased and decreased, respectively, their average intake of whole grains. Average intake of whole grains was significantly greater during the treatment p eriod across all participants Also, the treatment group and treatment period interaction was significantly affected by whole grain intake, resulting in those participants randomized t o the whole grain group consuming on average 3.6 ounce equivalents of whole grains per day (Figure 4 10). White participants consumed significantly higher amounts of whole grains when compared to Black/African American, Hispanic/Latino, and other particip ants. Additionally, whole grain intake by treatment group across the pre baseline and treatment periods of different races and ethnicities was significantly different (Figure 4 11). The table inset shows the tests of effect slices for group* race/ethnicity sliced by race/ethnicity t Significant Difference Test. These analyses suggest that differences in whole grain intake (ounce equivalents ) by African American, White se subj ects in the whole grain group. of Asians (n=2), mixed White /African American (n=4) and subject defined as other (n =2). Fruit Intake Dietary intakes of fruit (cup equivalents as indicated in ChooseMyPlate) during the p re baseline period were averaged for each subject to provide the Intakes during the six week intervention period were averaged for each subject to provid e:

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76 fruits and 100% fruit juice on a cup for cup basis, and fruit punch or lemonade 2 cups equal a cup equivalent). The effect of treatment group, gender, race/ ethnicity, and study period (pre baseline vs. treatment) and the interactions among these effec ts on fruit intake (cup equivalents) was tested for all subjects (Table 4 11). Only the gender by group interaction was significant (Figure 4 12 ). Fruit intake during the pre baseline and treatment period for both treatment groups was less than 1 cup/day and was not changed with either treatment. Vegetable Intake Dietary intakes of vegetables (cup equivalents as indicated in ChooseMyPlate) during the pre baseline period were averaged for each subject to provide the average during the six week intervention period were averaged for each subject to provid vegetable intake: whole vegetables, vegetable juice, salsa, ketchup, pizza sauce, pickles, French fries, and potat oes. The effect of treatment group, gender, race/ ethnicity, and study period (pre baseline vs. treatment) and the interactions among these effects on vegetable intake (cup equivalents) was tested for all subjects (Table 4 12). Only the gender was significa nt (Figure 4 13 ). Vegetable intake during the pre baseline and treatment period for both treatment groups was less than 1 cup/day and was not changed with either treatment.

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77 Figure 4 1. Flow chart of subject recruitment, allocation and analyses Table 4 1. Subject characteristics and dietary intake data. Refined Grain Group (n=42) Whole Grain Group (n=41) P value Gender (M/F) 25/17 23/18 0.826 Age in years (median [25 th 75 th ]) 12.9 (11.8, 13.5) 12.3 (11.7, 13.5) 0.503 Grade in school 6 th (n[%]) 7 th (n[%]) 8 th (n[%]) 19 (45%) 15 (36%) 8 (19%) 22 (54%) 9 (22%) 10 (24%) 0.199 Race/ethnicity (n[%]) White Black/African American Hispanic/Latino Mixed/Other 1 18 (43%) 14 (33%) 6 (14%) 4 (10%) 20 (49%) 12 (29%) 5 (12%) 4 (10%) 0.213

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78 Table 4 1. Continued. Refined Grain Group (n=42) Whole Grain Group (n=41) P value Baseline BMI percentiles for age (n[%]) < 85 th (under or healthy weight) 85 th 94 th (overweight) > 95 th (obese) 23 (55%) 10 (24%) 9 (21%) 23 (56%) 6 (15%) 12 (29%) 0.492 Ac tivity (n[%]) Walks or bikes to school Daily physical education class Participates in organized sports/activities 5 (12%) 19 (45%) 14 (33%) 5 (12%) 5 (12%) 21 (51%) 1.000 0.001 0.122 School meals (d/wk, meanSEM) Participates in school breakfast P articipates in school lunch 0.7 + 0.2 4.0 + 0.3 0.5 + 0.2 3.4 + 0.3 0.690 0.216 Preferences for foods in weekly food packs Foods would eat (out of 9, median [25 th 75 th ]) 8 (7, 9) 8 (8, 9) 0.268 Targeted 24 hour diet recalls Number of days (median [25th 75th]) Pre baseline Treatment Dietary intake recorded for school days Pre baseline (%, LSmeanSEM) Treatment (%, LSmeanSEM) 3 (2, 3) 5 (5, 5) 735 655 3 (2, 3) 5 (5, 6) 755 725 0.181 0.362 0.6552 Total grain intake (oz eq/day, LSme anSEM) Pre baseline Treatment 5.70.4 6.70.4 4.40.4 5.70.4 0.6883

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79 Table 4 1. Continued Refined Grain Group (n=42) Whole Grain Group (n=41) P value Whole grain intake (oz eq/day, LSmeanSEM) Pre baseline Treatment 1.30.2 0.30.25 0. 60.2 3.50.25 <0.00014 0.098 <0.0001 Refined grain intake (oz eq/day, LSmeanSEM) Pre baseline Treatment 4.40.3 6.50.35 3.90.4 2.10.35 <0.00016 0.681 <0.0001

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80 Table 4 2. The average number of targeted 24 hour recalls obtained during the pre baseline and treatment periods for the intent to treat subjects Refined Grain Group (n=42) Whole Grain Group (n=40 for baseline, 41 for intervention) P value Number of recalls/subject (mean+SEM) Pre baseline period Tr eatment period 2.6 0.1 5.2 0.1 2.4 0.1 5.2 0.1 0.166 0.565 Table 4 3. Average caloric, nutrient, and fiber content per ounce equivalent of whole grain and refined grain foods provided in the weekly food packages. Nutrient Refined Grain Whole Gr ain P value Weight (g) 34.80.6 35.60.4 0.329 Whole grain (g) 0 161 0.029 Calories 1142 1193 0.260 Total fat (g) 1.70.1 2.50.2 0.019 Saturated fat (g) 0.40.03 0.40.1 0.343 Sodium (mg) 1583 12212 0.029 Carbohydrate (g) 22.10.5 21.10.4 0. 162 Dietary fiber (g) 0.90.04 1.80.04 <0.001 Sugar (g) 4.30.3 5.30.2 0.034 Protein (g) 2.60.1 3.00.04 0.007 Vitamin A (IU) 26242 16918 0.088 Vitamin C (mg) 2.00.3 3.21.3 0.441 Calcium (mg) 412 6725 0.355 Iron (mg) 2.30.2 2.20.3 0.829

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81 Figure 4 2. Ranking of most common refined grain package foods consumed. Figure 4 3. Ranking of most common whole grain package foods consumed.

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82 Table 4 4. The main effects of gender, group, study period, race/ethnicity, and their interactions on average daily intake of all grains. Type III Tests of Fixed Effects Effect Num DF Den DF F Value Pr > F Gender 1 151 9.36 0.0026 Group (RG, WG) 1 151 7.68 0.0063 Gender*Group 1 151 0.22 0.6417 When (pre baseline, treatment) 1 151 10.54 0.0014 Gender *when 1 151 1.75 0.1880 Group*when 1 151 0.16 0.6878 Gender*Group*when 1 151 0.62 0.4307 Race/ethnicity 3 151 3.43 0.0186 Group*Race/ethnicity 3 151 2.87 0.0383 Figure 4 4 The least squares means for the average daily intake o f all grains by fema les and males across treatment groups and the pre b aseline and treatment periods. The effect of gender on total grain intake was significant (P=0.0026)

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83 Figure 4 5. The least squares means for the average daily intake of all grains by subjects in the refined grain or whole grain groups across the pre baseline and treatment periods. The effect of treatment group on total grain intake was significant (P=0.0063).

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84 Figure 4 6. The least squares means for the average daily intake of all grains by all su bjects during the pre baseline and treatment periods across treatment groups. The effect of study period on total grain intake was significant (P=0.0014). Figure 4 7. Total grain intake by treatment group across the pre baseline and treatment periods by subjects of differen t races and ethnicities randomized to the refined or whole grain groups.

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85 Table 4 5. Tests of effect slices for group and race/ethnicity interaction. Race/ethnicity Num DF Den DF F Value Pr > F Black/African American (n=26) 1 151 0 .02 0.8997 Hispanic/Latino (n=11) 1 151 5.90 0.0163 Other (n=8) 1 151 4.40 0.0376 White (n=38) 1 151 0.01 0.9363 Table 4 6. T ests of effect slices for group and r ace/ethnicity interaction. Group Num DF Den DF F Value Pr > F Refined Grain (n=42) 3 15 1 2.74 0.0452 Whole Grain (n=41) 3 151 3.70 0.0132 Table 4 7. The main effects of gender, group, study period, race/ethnicity, and their interactions on average daily intake of refined grain. Type III Tests of Fixed Effects Effect Num DF Den DF F Valu e Pr > F Gender 1 151 8.18 0.0048 Group (RG, WG) 1 151 42.98 <.0001 Gender*Group 1 151 3.04 0.0833 When (pre baseline, treatment) 1 151 0.17 0.6848 Gender*when 1 151 0.04 0.8502 Group*when 1 151 38.49 <.0001 Gender*Group*when 1 151 0.58 0.4473 Race /ethnicity 3 151 0.56 0.6425 Group* Race/ethnicity 3 151 1.59 0.1940

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86 Figure 4 8. The least squares means for the average daily intake of refined grain (ounce equivalents) by females and males. The interaction between genders was significant (P= 0.004 8).

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87 Figure 4 9. The least squares means for the average daily intake of refined grain by subjects in the refined grain or whole grain groups during the pre baseline and treatment periods. The interaction between treatment group and study period was sig nificant (P<0.0001). Table 4 8. The main effects of gender, group, study period, race/ethnicity, and their interactions on average daily intake of whole grains. Type III Tests of Fixed Effects Effect Num DF Den DF F Value Pr > F Gender 1 151 0.35 0.553 9 Group (RG, WG) 1 151 29.20 <.0001 Gender*Group 1 151 2.70 0.1023 When (pre baseline, treatment) 1 151 23.38 <.0001 Gender*when 1 151 3.25 0.0734 Group*when 1 151 104.67 <.0001 Gender*Group*when 1 151 0.00 0.9688 Race/ethnicity 3 151 4.04 0.0085 G roup*Race/ethnicity 3 151 2.44 0.0667

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88 Figure 4 10. The least squares means for the average daily intake of whole grains (ounce equivalents) by all subjects in the refined grain or whole grain groups during the pre baseline and treatment periods. The i nteraction between treatment group and study period was significant (P<0.0001).

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89 Figure 4 11. Whole grain intake (ounce equivalents) by treatment group across the pre baseline and treatment periods by subjects of di fferent races and ethnicities. Table 4 9. Tests of effect slices for group and race/ethnicity interaction. Ethnicity Num DF Den DF F Value Pr > F Black/African American 1 151 17.68 <.0001 Hispanic/Latino 1 151 0.31 0.5808 Other 1 151 4.58 0.0340 White 1 151 47.38 <.0001 Table 4 10. Te sts of effect slices for group and r ace/ethnicity interaction. Group Num DF Den DF F Value Pr > F White 3 151 1.15 0.3305 Green 3 151 5.37 0.0015

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90 Table 4 11. The main effects of gender, group, study period, race/ethnic ity, and their interactions on average daily intake of fruit. Type III Tests of Fixed Effects Effect Num DF Den DF F Value Pr > F Gender 1 151 1.24 0.2665 Group (RG, WG) 1 151 0.84 0.3610 Gender*Group 1 151 5.88 0.0165 When (pre baseline, treatment) 1 151 1.45 0.2305 Gender*when 1 151 1.23 0.2688 Group*when 1 151 0.02 0.8975 Gender*Group*when 1 151 0.71 0.4006 Race/ethnicity 3 151 0.64 0.5909 Group*Race/ethnicity 3 151 0.68 0.5662 Figure 4 12. The least squares means for the average daily int ake of fruit (cup equivalents) by gender and treatment group. The interaction between treatment group and gender on fruit intake was significant (P=0.0165).

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91 Table 4 12. The main effects of gender, group (refined grain [RG] or whole grain [WG]), study pe riod (pre baseline or treatment), race/ethnicity and their interactions on average daily intake of vegetable (cup equivalents). Type III Tests of Fixed Effects Effect Num DF Den DF F Value Pr > F Gender 1 151 4.95 0.0276 Group (RG, WG) 1 151 0.50 0.4818 Gender*Group 1 151 0.70 0.4042 When (pre baseline, treatment) 1 151 1.42 0.2350 Gender*when 1 151 0.02 0.8908 Group*when 1 151 0.57 0.4511 Gender*Group*when 1 151 1.15 0.2860 Race/ethnicity 3 151 0.93 0.4299 Group*Race/ethnicity 3 151 0.40 0.7502 Figure 4 13. The least squares means for the average daily intake of vegetables (cup equivalents) by gender. The interaction between genders was significant. (P=0.0276).

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92 CHAPTER 5 DISCUSSION AND CONCLUSION This study provides new information on the e ffect of providing whole grain foods to adolescents. Previous work suggests that adolescents are not consuming the recommended amount of whole grains per day ( 64). In fact, most adolescents are consuming less than 1 serving of whole grains per day ( 65). In this study, middle school students (ages 11 16 years old) were randomized to receive weekly groceries of either refined grain or whole grain foods. Pre baseline and treatment period 24 hour targeted recalls were obtained from all participants in order to report grain, fruit, and vegetable intake. At least two thirds of the recalls were obtained on weekdays. The percentages of weekday recalls were similar across treatment groups, genders, racial and ethnic groups, and pre baseline and treatment periods. Dif ferences in dietary intake are not due to difference in dietary patterns observed between weekdays and weekends. As anticipated, the average total grain intake, upon receiving the study foods, increased by 1 ounce equivalent when male and female intake was combined. The average total gain intake in males was over 6 ounce equivalents per day (recommended level is 6 to 7 ounce equivalents per day) and was greater than that of female subjects (Figure 4 4). The average total grain intake in females was over 5 ounce equivalents per day (recommended level is 5 to 6 ounce equivalents per day). Across the pre baseline and treatment periods, participants in the refined grain group consumed 1 ounce equivalent more total grains than participants in the whole grain gr oup (Figure 4 ounce equivalents fewer total grains when they were randomized to the whole grain group (Figure 4 7). In terms of diet improvement, the quality of the diet improved for both

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93 treatmen t groups, with an increase in total grain intake to the recommended amount (Figure 4 6). The pre baseline intake of whole grains was not different between groups and was similar to the typical intake for adolescents (1 ounce equivalent). When participants were provided with groceries of whole grain foods and encouraged to eat at least 3 different study foods per day, their whole grain intake was over 3 ounce equivalents higher than participants receiving refined grain foods (Figure 4 10). Participants in t he whole grain group increased their intake of whole grains by 3 ounce equivalents, whereas those in the refined grain group decreased their intake of whole grains by a 1 ounce equivalent (Figure 4 10). In terms of ethnicity and race, Whites took in a 1 ou nce equivalent more whole grain than any other racial/ethnic group across both study periods and groups (Figure 4 11). During pre baseline and treatment periods, Whites and African Americans took in 2 ounce and 1.5 ounce equivalents more whole grains when they were in the whole grain versus refined grain group. Hispanic subjects took in an average of 1.3 ounce equivalents of whole grains and there was no significant difference in intake when randomized to the whole grain group (Figure 4 11). Explanations fo r the poor intake of whole grains by Hispanic participants need to be pursued. Possible explanations include: language barrier when reporting food intake, unfamiliar study foods, and challenges in food delivery or pick up. According to the results, as a gr oup, middle school students will increase their intake to the recommended amount of whole grains if they are provided whole grain foods. All participants consumed on average, 4 ounce equivalents of refined grain during the pre baseline period. The partici pants randomized to the whole grain group

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94 decreased their intake of refined grains by almost 2 ounce equivalents (Figure 4 7). On average, males consumed 1 ounce equivalent more refined grains than females across the pre baseline and treatment periods (Fig ure 4 8). As predicted, participants in the refined grain group increased their intake of refined grains by 2 ounce equivalents per day (Figure 4 9). However, participants randomized to the whole grain group still consumed 2 ounce equivalents of refined gr ain foods during the treatment period (Figure 4 9). This difference is attributed to the intake of males in the refined grain group. There was no difference in refined grain intake among racial and ethnic groups. The results show that when middle school st udents are provided whole grain foods, they will decrease but not eliminate their refined grain intake. Also, when provided refined grains and encouraged to eat at least three different grain foods per day, middle school students will increase their intake of refined grains. Across ethnic and racial backgrounds and study period, fruit and vegetable intake was not significantly altered. The average daily intake of fruit was approximately one half cup. The USDA recommends that girls consume 1.5 cups per day a nd boys consume 1.5 to 2 cups per day and so fruit intake was low for all subjects and not changed by treatment group. A significant difference was found between the gender and treatment group interaction for average daily fruit consumption (Figure 4 12). The average daily intake of vegetables was less than one cup. The USDA recommends that girls consume 2 to 2.5 cups per day and boys consume 2.5 to 3 cups per day and so vegetable intake was low for all subjects and not changed by treatment. A significant d ifference was found between the average daily intakes of vegetables across gender, showing that females consumed more vegetables than males (Figure 4 13).

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95 Few studies have looked at ethnic influences on whole grain consumption in this age group. This study found that subjects who self identified themselves as Hispanic/Latino did not have an increase in intake of whole grains when randomized to the whole grain versus refined grain group. Interestingly, the data suggest that these subjects did not eat the who le grain study foods or replace them in their diet with refined grains (i.e., intake of refined grains was not dependent upon race/ethnicity). Total grain intake across study periods was 6.7 0.7 versus 4.4 0.7 ( P =0.016) in Hispanic/Latino subjects randomiz ed to the refined grain versus whole grain groups, respectively. Due to the small sample size, we could not examine the three way interaction between treatment group, study period (baseline, treatment), and race/ethnicity. Project EAT (Eating Among Teens) found differences in whole grain intake according to race ethnicity. Approximately 90% of the participants from the mixed/other ethnic group consumed 1 or less than 1 whole 1994 96 Continuing Survey of Food Intakes by Individuals show that only 5% of Hispanic adults consume greater than or equal to 3 servings of whole grain per day. Participants most inclined to consume higher levels of whole grains were generally White and had higher education. The Hispanic group had the lowest whole grain intake when randomized to the whole grain group. This suggests that foods provided may have been unfamiliar; therefore ethnically acceptable options need to be explored when trying to increase whole grain consumption in eth nic populations. This study reveal s, for the first time, that when middle school students are provided whole grain foods and encouraged to eat at least three different whole grain foods per day, their whole grain intake will increase to the daily recommend ed amount

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96 (at least 3 servings per day). School meals represent a strategic point of intervention for children because 31 million children participate in the National School Lunch Program, therefore introducing whole grains in school lunch may be the key t o increasing consumption to the recommended amount in adolescents ( 66). Not only have whole grains been associated with a reduced risk of certain diseases, consumption has also been related with improved diet quality and nutrient intake in children and ado lescents ( 65). Currently, the USDA has issued a policy for encouraging adherence to the Dietary Guidelines for Americans in the National School Lunch Program (3). Future studies that involve an intervention with whole grain foods should include a follow up assessment to see if participants changed their whole grain consumption post intervention.

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97 APPENDIX A DOCUMENTS SUBMITTED TO THE INSTITUTIONAL REVIEW BOARD Protocol 1. Project Title The addition of whole grains to the diets of middle school children: A study of digestive health and immune defenses 2. Investigator(s): Principal Investigator Bobbi Langkamp Henken, PhD, RD Professor Food Science and Human Nutrition Department and the Center for Nutritional Sciences University of Florida Phone: 35 2 392 1991 ext. 205 Email: henken@ufl.edu Co Investigators Wendy Dahl, PhD, RD Assistant Professor Food Science and Human Nutrition Department and Center for Nutritional Sciences University of Florida Phone: 35 2 392 1991 ext. 224 Email: wdahl@ufl.edu Volker Mai, PhD, MPH Assistant Professor Microbiology and Cell Science Emerging Pathogen Institute University of Florida Phone: 352 846 0956 v mai@ufl.edu Consultant Mary Christman, PhD Associate Professor Department of Statistics IFAS PO Box 110339 Gainesville, FL 32611 0339 Phone: 352 392 3724 Fax: 352 392 8555 Email: mcxman@ufl.edu Study Coordinator a nd Senior Biological Scientist

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98 CJ Nieves, MS Senior Biological Scientist Food Science and Human Nutrition, University of Florida Phone: 352 392 1991 ext. 239 Email: cjnieves@ufl.edu

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99 Study Sponsors / Collabora tors Tom Boileau, PhD Satya Jonnalagadda, PhD, RD General Mills, Inc. Frank Thielecke Cereal Partners Worldwide Research Sites University of Florida PO Box 110370 Gainesville, FL 32611 Phone: 352 392 1991 ext. 205 Westwood Middle School (970 students: grades 6 through 8) Preliminary verbal approvals of the basic study design and study location have been obtained from the Alachua County School District and Westwood Middle School. Final approvals are contingent on obtaining University of Flori da Institutional Review Board approval. 3. Abstract: Dietary Guidelines for Americans grain controlled stud ies, to our knowledge, examine the role of whole grains on gastrointestinal and immune health in adolescents. Therefore, the purpose of this study is to determine if adolescents eating diets rich in whole grains vs. diets rich in refined grains (i.e., a t ypical diet) have improved markers of digestive health and natural immune defenses. Middle school students (11 15 years of age, n=80) will be recruited from Westwood Middle School, Gainesville, Florida, and randomized to receive > 80 g of whole grains ( > 5 servings) or similar foods made with refined grains each day for six weeks. Based on treatment group, subject s will be provided either whole grain or refined grain foods and snacks. They will be instructed on how to use these foods to replace other foods already contained in the diet. Stool, blood, and saliva samples will be obtained at baseline and at study end to examine the microbiota and markers of digestive and immune health. Daily records will be maintained by the students to assess bowel habits a nd compliance. It is anticipated that whole grains will increase stool bulk resulting in increased stool frequency and softer stools. Additionally, fermentation of the fiber within the colon will alter the microbiota profile B ecause the majority of the immune system resides within the gastrointestinal tract, improved balance of the intestinal microbiota may prime the immune system thus contributing to improved immune defense. 4. Background: Dietary Guidelines for Americans recommend that children and grain (1) Whole grains are se eds that

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100 consist of the bran, germ, and endosperm. The bran is the outer cell wall of the grain seed which contains fiber, antioxidants, B vitamins and most of the minerals found in grains (e.g., iron, copper, zinc, magnesium). Ferulic acid is a phytoche mical that links cellulose to other polysaccharide components within the cell wall. Ferulic acid also functions as an antioxidant. The germ is the part of the seed that sprouts into the new plant. It contains B vitamins, some protein, phytochemicals, an tioxidants such as vitamin E, and unsaturated fats. The endosperm, which is the largest part of the grain, provides energy for the sprouting seed. It contains carbohydrate, B vitamins and minerals. Refined flours are made from the endosperm. During the refining process, the majority of the fiber, vitamins, minerals, antioxidants and phytochemicals are lost; however, the B vitamins, folic acid, and iron are added back to the refined flours. Whole grains offer the benefit of all of the aforementioned n utrients and phytochemicals. Additionally, grains provide fiber, resistant starches, and oligosaccharides that contribute to fecal bulking and the production of short chain fatty acids via bacterial fermentation. Epidemiological studies associate consump tion of whole grains with protection from cancer, cardiovascular disease, diabetes, and obesity; however, few randomized, controlled studies examine the effect of whole grains on health (2 4) No randomized, controlled studies, to our knowledge, examine the role of whole grains on gastrointestinal and immune health in adolescents. Because whole grain foods are typically more expensive and possibly not as well accepted than the refined grain version, it is a challenge to add whole grain foods to school breakf asts and lunches within public schools. whole grains are initiated seems to be a logical first step. Therefore, the purpose of this study is to determine i f adolescents eating diets rich in whole grains vs. diets rich in refined grains (i.e., a typical diet) have improved markers of digestive health and natural immune defenses. Middle school students (11 15 years of age) will be recruited from Westwood Midd le School and randomized to receive > 80 g of whole grains ( > 5 servings) or similar foods made with refined grains each day for six weeks. According to MyPyramid Plans (www.mypryamid.gov), adolescent males require between 5 to 10 servings of grains per day with 3 to 5 of these servings coming from whole grains. Adolescent females require between 5 to 8 servings of grains per day with 3 to 4 servings from whole grains. Based on treatment group, subject s will be provided either whole grain or refined grain foods and snacks. They will be instructed on how to use these foods to replace other foods already contained in the diet. Stool, blood, and saliva samples will be obtained at baseline and at study end to examine the microbiota and markers of digestive an d immune health. Daily records will be maintained by the students to assess bowel habits and compliance. This study will be completed during the early spring when students are undergoing their Florida Comprehensive Assessment Tests (FCAT). This is also peak flu season for this region. The academic stress associated with the exams and the increased prevalence of cold and flu may provide for a larger treatment difference in markers of immune health. Anticipated Results Based on work by Costabile et al. ., in adults (20 to 42 years of age) fed 48 g of whole grain wheat per day, we anticipate seeing improved bowel habits and a change in the microbiota profile with an increase in fecal bifidobacteria and lactobacilli (2) Whole grain wheat is a source of antioxidants (ferulic acid). The fasting concentration of ferulic acid tripled in the plasma after subjects consumed a whole grain wheat diet f or 3 wk. The authors suggested that

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101 regular consumption of whole grains results in a slow and continuous release of phenolic compounds such as ferulic acid, into the bloodstream (2) In this regard, ferulic acid could be used as a biomarker for compliance for the adolescents consuming the whole grain diet. Continuous release of compounds with antioxidant potential could also improve antio xidant capacity in subjects. If this is the case, we would anticipate seeing an increase in the serum antioxidant capacity and a decrease in the inflammatory cytokines and acute phase proteins (i.e., C reactive protein, fibrinogen). However, this assumes that acute phase proteins and inflammatory cytokines are elevated in adolescents We would anticipate seeing elevated C reactive protein, fibrinogen, and inflammatory cytokines in obese subjects, but this may not be the case in lean subjects (5) Bacterial fermentation of fiber in the colon results in an increase in short chain fatty acids, including butyrate the primar y energy source for colon epithelial cells. We hope to see an increase in short chain fatty acids in the stool samples with the whole grain diet; however, it would not be surprising if no differences in the short chain fatty acid profiles were observed wi th the whole grain intervention as short chain fatty acids are readily absorbed by the colon. The academic stress model is associated with decreased natural killer cell activity, decreased mitogen ( PHA/LPS ) stimulated peripheral blood mononuclear secre tion of interleukin ( IL ) 2, IL 4, and IL 1 and increased days of cold and flu (6, 7) The stress associated with FCAT exams d uring cold and flu season may result in impaired immune defenses and increased cold and flu resulting in increased student absences. If improved health of the intestinal environment reduces the burden on the immune system, we would anticipate observing in creased natural killer cell activity and decreased absences from school in subjects consuming the whole grain diet. Increased production of short chain fatty acids and the release of phenolic compounds (i.e., potential antioxidants) in the whole grains by the intestinal microbiota may be responsible for improved immune health. In fact, an increase in bifidobacteria and lactobacilli is associated with increased blood natural killer cell activity and an increase in bifidobacteria is associated with incre ased fecal levels of secretory immunoglobulin A (sIgA) (8, 9) Because the colon is part of the common mucosal immune system, it is anticipated that an increase in fecal sIgA would also result in an increase in salivary sIgA. Altered microbiota and increased short chain fatty acids and antioxidant compound s within the colon may also result in a decrease in colonic inflammatory cytokines. If this is the case, we would anticipate seeing a decrease in IL 17 A and TNF within the fecal water. A shift in inflammatory status may also result in an increase in th e epithelial cell derived cytokines (i.e., IL 25 and IL 33) which promote Th2 dependent immune responses (9, 10) Treatments that modulate the microbiota profile also modulate cytokine responses in mitogen stimulated peripheral blood mononuclear cells. Vulevi c et al. supplemented the diets of elders with a trans galactooligosaccharide mixture and observed an increase in the numbers of beneficial bacteria including bifidobacteria and lactobacilli. The investigators also noted an increase in LPS stimulated peri pheral blood mononuclear cell production of the immunosuppressive cytokine IL 10 and a decrease in the proinflammatory cytokines IL 1 TNF and IL 6 (9) We anticipate altered fecal microbiota profiles with the addition of whole

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102 grains to the diets of adolescents. If this affects inflammatory status, we would be more likely to see this change following mito gen (LPS) stimulation of peripheral blood mononuclear cells versus finding measurable changes in serum levels. This is primarily because adolescents, especially lean teens, should not have elevated levels of inflammatory cytokines as is observed with adva nced age and obesity. It is also more likely that the whole grain diet is associated with changes in Th1 Th2 cytokine balance rather than changes in T cell subtypes. Therefore, we are proposing to measure Th1 (IL 2, IFN ) and Th2 (IL 4, IL 5, IL 10) cyt okines in mitogen (PHA) stimulated lymphocytes. 5. Specific Aims: I. Examine the effect of incorporating five or more servings with a minimum of three servings, of whole grains into the usual diets of adolescents on digestive health. The working hy pothesis is that fiber in the whole grains will increase stool bulk resulting in increased stool frequency and softer stools. Additionally, fermentation of the fiber within the colon will alter the microbiota profile and increase fermentation products wit hin the stool. II. Characterize the effect of incorporating five or more servings with a minimum of three servings, of whole grains into the usual diets of adolescents on immune defenses The working hypothesis is that the whole grains will provide nutr ients and phytochemicals important in natural immune defenses. Additionally, because the majority of the immune system resides within the gastrointestinal tract improved balance of the intestinal environment (i.e., a microbiota profile associated with im proved health) will prime the immune system thus contributing to improved immune defense Research Plan: Study Design A six week randomized controlled, parallel arm study will be carried out with 80 healthy adolescents, ages 11 15 years enrolled in West wood Middle School, Gainesville, FL (Figure 1). The study population will consist of healthy, middle school students (primarily sixth and seventh graders) undergoing the Florida Comprehensive Assessment Tests (FCAT). These exams are typically given in Fe bruary and early March, a period of time that coincides with peak cold and flu season in the state of Florida. Although only healthy students will be enrolled, the psychological stress associated with the FCATs may increase the incidence of cold and flu s ymptoms; thereby maximizing the differences in immune defense between treatment groups. Institutional Review Board approval will be sought from the University of Florida IRB 1. Approval will also be sought from the Alachua County Public Schools and Wes twood Middle School. Informed consent from one parent (as per UF guidelines for minimal risk interventions with minors) and assent from all study participants will be sought.

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103 Pre baseline After obtaining informed consent and assent, the inclusion/ex clusion criteria will be reviewed. Exclusion criteria will include: known gastrointestinal disease ; other chronic disease ; allergy to wheat, gluten, milk, egg, soy, nuts or any other foods or food ingredients; use of gastrointestinal motility agents or l axatives or immunosuppressive drugs or treatments; regular consumption of probiotics or yogurt (>3 servings per week), use of antibiotics in the four weeks prior to randomization, or refusing to provide a baseline blood or saliva sample Potential subject s will be asked to identify all of the types of foods that they would be willing to eat as a participant. Subjects will only be included in the study if they are willing to consume at least three different foods on the list of foods ( > 80 g of whole grains ), every day for the six week study. Eligible subjects and their guardian will then be instructed on how to obtain a stool sample and where to deliver the sample or call for pickup. Appointment times will be given for stool sample collection (estimated d ay/time) two 24 hour diet recalls food delivery, and study start date. All participants will be given a sleeve of disposable soup sized (i.e., larger sized) bowls. Subjects will be told to use these bowls to eat their cereal, pasta, and rice. These sa me bowls will then be used during the targeted 24 hour diet recalls to more accu rately describe serving sizes of grain products. Contact information will be obtained from the subject and family. The subject or family will be contacted via phone or email to remind them of study appointments, schedule new appointments, discuss study procedures, deliver study foods, obtain the 24 hour diet and activity recalls, etc. We will also take a picture of the student to keep in his subject file for identification pu rposes. In the week before randomization a single stool sample will be obtained from each subject. If subjects decide that they cannot provide the stool sample after assenting, they will not be dropped from the study as long as we have n=25 per group (50 total) willing to provide the sample. This number should be sufficient to observe significant differences in microbiota between study groups. A 24 hour activity recall will be obtained to broadly classify levels of activity (e.g., sedentary, moderately active, vigorously active). Activity recalls will provide

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104 import information because activity can influence both bowel and immune function. Height, weight, age, and body mass index will be obtained. Trained study coordinators or graduate dietetic stud ents will contact study participants on two different days the week or so before randomization to administer a targeted 24 hour diet recall. Subjects will be asked to list all of the foods and beverages they ate in the previous 24 hours (midnight to midni ght); but specific information (i.e., serving size, whole grain vs. refined grain, method of preparation, etc.) will only be obtained for grain products, fruits, and vegetables. Food models, measuring cups and spoons, and the disposable soup bowls will be used to help determine serving size. Parents or guardians may be contacted to obtain additional information or clarification of dietary intake or activity during the recall period. It is anticipated that many of the subjects will be participating in the school breakfast and lunch program at the middle school. pancakes and tortillas. The investigators will work with closely with the food service director at the middle school and the dietitian with Alachua County Public Schools to obtain menus, recipes, and lists of whole grain foods provided during the study period. This will help with the accuracy of the targeted 24 hour diet recalls. Baseline On the first day of the study, after an overnight (6 hour minimum) fast, subjects will have their blood drawn by a licensed phlebotomist in the school clinic. Approximately a tablespoon of blood will be obtained to assess immune health (see outcomes below). Saliva will be o btained by unstimulated, passive drool. Students will be asked to rinse their mouth thoroughly with water 10 minutes before the sample is collected. They will then be asked to spit all of their saliva into a collection tube for a defined period, such as two to three minutes. Students who refuse to provide a blood or saliva sample will not be eligible for randomization into the study. Randomization. Because obesity is associated with increased inflammation even in adolescents, subjects will be stratifie d based on BMI (<95 th BMI percentile for age or BMI <30, > 95 th BMI percentile for age or BMI > 30) and p articipants will be randomized to two groups, a whole grain or refined grain group This study will not be blinded but study groups will be denoted as s de emphasize the differences between the groups. Intervention. Foods, such as pasta, rice, bread, cereal, and pancake mix, will be provided for the for the six week study period. I ndividual servings of foods, such as breakfast bars, cereal, or snack foods, will be provided to the subject either in their family food package or at a study booth at the school. As much as possible, food packages for the subject and family will be prepa labels on the food will be removed. Study staff will be available at the school (e.g., before and after school or during home room or lunch) to distribute study foods and assist study participants with questionnaire completion. Study participants will be given the opportunity to consume study foods at school. Students will be asked to consume at least three different study foods each day. It is anticipated that the students will cons ume more than one serving of each type of food. There is no maximum limit for daily study food consumption. Ideally, we would like to see

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105 students eat five servings (80 g of whole grain) per day. However, we will discourage overeating and weight gain. Weekly body weights will be obtained. Daily and Weekly M easures Subjects will be given study workbooks with tear out pages for daily logs. Students will be asked to come to the study booth each school day to drop off their completed logs. The daily logs will ask about the number of stools, consumption of study foods, level of stress, and gastrointestinal symptoms such as gas, bloating, and abdominal discomfort. To avoid giving the subjects the idea that they should be stressed and have gastrointestinal symptoms, we will embed these questions with other more positive distracting questions, such as level of happiness, etc. Each week the subject will meet with a study coordinator or graduate dietetic student to be weighed (weights will be done in kg) and t o provide a targeted 24 hour diet recall. If the subject is unable to complete the study record or requires help, a study coordinator with very limited knowledge of the study design and no knowledge of the study group to which the subject is assigned, wil l contact the subject daily and record the answers to the questions. This will be done to eliminate any bias when recording answers for the subject. Final Study Week During the last week of the study intervention, one stool sample and 24 hour targeted di et and activity recalls will be obtained. On the last day of the study ( + 3 days), blood and saliva collections will be obtained as described for baseline collections. Height and weight will also be reassessed and the subjects will be asked about any sick nesses during the study. Information on new medications, antibiotic use, and influenza vaccinations will be obtained at that time. Parents, guardians, or physicians (for severe adverse events) may be contacted to help clarify subject responses. Absences from school will be recorded by the study staff with the help of the school attendance office over the course of the study. Students will be asked if they missed school due to illness and if so what type of illness. Incentives In addition to study foo ds, subjects will receive coupons with a total of seven coupons possible: one coupon for completing the pre study week and six additional coupons for completing each of the six study weeks. Each week they participate they will receive another coupon. At t he end of the study they can trade the coupons for ONE prize. Subjects may select a prize from a category or level for which they qualified for or from a level worth fewer coupons. There were be seven levels of prizes that represent an increase in dollar value of about $14 each or approximately $100 for seven coupons (i.e., completing the study). Rewards are of reasonable value to prevent the possibility of coercion. In a recently published article, middle school students received a $10 bookstore gift c ard for providing height, weight, one diet recall, and one interview (11) Outcomes ( N ote: some samples may be sent off campus for analyses. The only identifying information that will be included with the sample will be subject number and date no PHI.) Digestive Health: Bowel Habit: Bowel movement frequency and GI symptoms (e.g., gas, bloating, and abdominal discomfort) will be recorded daily by subjects.

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106 Stool samples: Consistency of collected stool samples will be scored by study s taff using the Bristol Stool Form Scale. Stools will be weighed and pH will be obtained. Fermentation profiles: Short chain and branched chain fatty acids, lactate, and ammonia will be quantified in stool samples. Microbiota studies: Changes in overall m icrobiota diversity Quantitative changes in the proportions of bacteria, such as Bifidobacteria, Lactobacilli, C. perfringens and E. Coli, will be determined to give an indication of the prebiotic effect of the interventions. Immune Health: Approximately one tablespoon of blood will be obtained for the lymphocyte, natural killer cell, and serum studies described below. Ideally, this should be a fasting blood draw (6 hour minimum fast). Peripheral blood mononuclear cells (PBMC): mitogen induced lymphocy te proliferation (mitogens: PHA, ConA, Pokeweed, and LPS) mitogen induced cytokine production (mitogens: PHA and LPS) cytokines: such as but not limited to Th1 [IL 2, IFN ], Th2 [IL 4, IL 5, IL 10], inflammatory [IL 1 IL 6, TNF ] and misc. [IL 12p40, IL 12p70, IL 8, IL 17, TGF ] natural killer cell activity Serum antioxidant capacity ABTS (plus triglycerides) phenolic compounds present in whole grains, such as feruli c acid (the main phenolic compound in whole wheat, which is often used as a biomarker of cereal grain ingestion) acute phase proteins and inflammatory cytokines (C reactive protein, fibrinogen, IL1 TNF IL 8, IL 6) Fecal water: sIgA cytokines : such as IL 25 and IL 33 (epithelial cell derived cytokines that enhances Th2 dependent immune responses), IL 17 (proinflammatory), IL 10 (immunosuppressive), TNF (proinflammatory) pH Saliva sIgA Well being: Level of daily stress (0 to 10) Sick days, school days missed, doctor visits, new medications Other information:

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107 Height, weight, body mass index (BMI), BMI percentile for age Age, gender Dietary intake: 8 targeted 24 hour diet recalls, daily intake of study foods Level of activity: two 24 hour activi ty recalls (one at baseline and one during the final week) This will be basic information to classify the subjects as sedentary, moderately active, or vigorously active.

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108 Sample Size Based on changes in fecal water IgA with whole grain associated incre ases in bifidobacteria, we estimate that 80 subjects will be required to detect a change in IgA of 2.0 mg/g feces with 80% power, <0.05, and 20% attrition rate (2, 8) Only one child from each household will be enrolled to avoid having two children from the same household being randomized to two different treatment groups. Sixth and seve nth graders will be recruited and enrolled first. If we do not have sufficient numbers of sixth and seventh graders, then eighth graders will be enrolled. At randomization, students will be stratified by BMI (<95 th BMI percentile for age or BMI <30, > 95 t h BMI percentile for age or BMI > 30). Data will be analyzed two different ways compliant and intent to treat. Compliant subjects will be those who average at least 3 servings ( 48 g) of whole grains per day (whole grain group) or less than one serving ( 16 g) of whole grains per day (control group) based on the average intake from the weekly targeted 24 hour diet recalls that were completed during the intervention. Stool microbiota data from subjects who begin a course of antibiotics during the study wil l not be included in either group. Extension Activity intervention will be carried out at the completion of the study Teachers at Westwood will have access to wh ole grain and fiber lesson plans (on a CD) and classroom resources. They will also have the option to have one of the nutrition student study assistants give a presentation in their classroom on understanding whole grains and fiber. Educational materials will also be made available to the parents of all subjects and the Food and Nutrition Services of Alachua County Public Schools. References 1. U.S. Department of Health and Human Services, U.S. Department of Agriculture. Dietary Guid elines for Americans, 2005. 6th Edition ed. Washington, DC: U.S. Government Printing Office; 2005. 2. Costabile A, Klinder A, Fava F, Napolitano A, Fogliano V, Leonard C, Gibson GR, Tuohy KM. Whole grain wheat breakfast cereal has a prebiotic effect on the human gut microbiota: a double blind, placebo controlled, crossover study. Br J Nutr 2008; 99: 110 120. 3. McIntosh GH, Noakes M, Royle PJ, Foster PR. Whole grain rye and wheat foods and markers of bowel health in overweight middle aged men. Am J Clin Nut r 2003; 77: 967 974. 4. Slavin J. Why whole grains are protective: biological mechanisms. Proc Nutr Soc 2003; 62: 129 134. 5. Balagopal P, George D, Patton N, Yarandi H, Roberts WL, Bayne E, Gidding S. Lifestyle only intervention attenuates the inflammator y state associated with obesity: a randomized controlled study in adolescents. J Pediatr 2005; 146: 342 348. 6. Kiecolt Glaser JK, Garner W, Speicher C, Penn GM, Holliday J, Glaser R. Psychosocial modifiers of immunocompetence in medical students. Psychoso m Med 1984; 46: 7 14. 7. Takkouche B, Regueira C, Gestal Otero JJ. A cohort study of stress and the common cold. Epidemiology 2001; 12: 345 349. 8. Fukushima Y, Kawata Y, Hara H, Terada A, Mitsuoka T. Effect of a probiotic formula on intestinal immunoglobu lin A production in healthy children. Int J Food Microbiol 1998; 42: 39 44.

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109 9. Vulevic J, Drakoularakou A, Yaqoob P, Tzortzis G, Gibson GR. Modulation of the fecal microflora profile and immune function by a novel trans galactooligosaccharide mixture (B GO S) in healthy elderly volunteers. Am J Clin Nutr 2008; 88: 1438 1446. 10. Saenz SA, Taylor BC, Artis D. Welcome to the neighborhood: epithelial cell derived cytokines license innate and adaptive immune responses at mucosal sites. Immunol Rev 2008; 226: 172 190. 11. Gordon AR, Cohen R, Crepinsek MK, Fox MK, Hall J, Zeidman E. The third School Nutrition Dietary Assessment Study: background and study design. J Am Diet Assoc 2009; 109: S20 30.

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110 Tentative Time Line (Dates are subject to change.) April 2009 M eet with school officials to discuss study protocol. May 2009 Sign contract. Write IRB proposal. June 2009 Investigators meet to discuss specifics of the protocol. August 28, 2009 Paperwork submitted to UF IRB for approval. September 2009 Approved UF I RB paperwork submitted to Alachua County Public Schools for approval. Standard operating procedures for immune function studies completed. September 2009 (If possible) Present study to parents at Westwood open house. Contact information collected from int erested students/parents. November 2009 Study staff trained and recruits full time. Laboratory staff trained. February 1 5, 2010 Initial visit: stool collection and 24 hr recalls for first group of students February 8 11, 2010 Randomize first group of s tudents (Flex day Friday, Feb. 12) Initial visit, stool collection 24 hr recalls for second group of students February 16 19, 2010 Randomize second group of students (Holiday Monday, Feb 15) March 8 12, 2010 FCAT exams, UF spring break March 15 1 9, 2010 Stool collection and 24 hr recalls for first group of students March 22 26, 2010 Final visit blood draw first group Stool collection and 24 hr recalls for second group March 30 April 2, Final visit blood draw second group

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111 2010 April 2010 Begin i mmune function and fecal studies/assays. Begin data entry. September 2010 Begin manuscript preparation. May 1, 2011 Contract end.

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112 7. Possible Discomforts and Risks: Typical risks and discomforts associated with drawing blood. We will minimize any discomforts by using an experienced phlebotomist. Some students may feel sick if they cannot eat first thing in the morning before the blood draw. After the students have their blood drawn, they will be given a continental breakfast containing appropriat e study foods based on their study group (baseline draw). At the final blood draw, students will be allowed to choose from a variety of breakfast items. Some students may be uncomfortable providing the stool samples. This will be minimized by giving the students/parents the option of bringing fresh stool to study staff at the school in the morning or paging study staff to pick up the samples from their home. Students who will be providing samples at school will be told to get a pass to go to the school c linic. Stool collection materials will be available in the clinic and study staff will be available to take the samples. Students providing fresh samples in the evening or on weekends will be asked to page the study staff for pick up. Some students may be uncomfortable describing their bowel habits. To hopefully make the students more comfortable with this and all study procedures, every attempt will be made to pair subjects up with the same study coordinator for the entire study. Students receiving th e whole grain foods may experience gas, bloating, or abdominal discomfort from the fiber in the grains. Students experiencing these problems may need to decrease their intake of the whole grains and then slowly increase intake as their gastrointestinal tr act begins to adjust to the extra fiber. Some students may gain or lose weight while participating in the study. This may or may not be a desirable outcome. We hope to minimize this by instructing students to use the foods to replace other foods in their diets. We will also monitor student weight over the course of the study. Some student may be uncomfortable having their height and weight measured. To minimize this concern, weights will be obtained in a private location. Additionally, weight and heigh t measurements will be obtained and recorded in kg and cm, units that are less familiar to students. 8. Possible Benefits: Westwood Middle School has a high percentage of students qualifying for free and reduced lunch and therefore may not have access to nutritious foods at home. Foods provided to the family and the student would provide nutrients and energy to all participants. The students randomized to the whole grain group will be receiving fiber and additional phytonutrients / antioxidants that may improve gastrointestinal and immune health. All students will be interacting with University of Florida study coordinators. It is possible that both groups may be more likely to attend classes because they enjoy interacting with their study coordinator and/or they are healthier because they are eating healthier foods.

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113 9. Conflict of Interest: The study investigators, who are employees of the University of Florida, are receiving funding from General Mills Bell Institute of Health and Nutrition, Minnea polis, MN to complete this study. Their careers may benefit if the results of this study are presented at scientific meetings or in scientific journals. The study investigators will receive no financial compensation from the completion of this study othe r than that provided as salaries by the University of Florida. The study sponsor will reimburse the researcher for study operating costs only. The study protocol was developed in collaboration with employees of General Mills and Europe Cereal Partners Wo rldwide. Some of the study foods are being provided by General Mills and Europe Cereal Partners Worldwide; however, where possible food package labels will be removed to avoid a potential conflict of interest Most of the study foods used in this study w ill be purchased from area grocery or wholesale stores.

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114 Recruitment Materials Script for Westwood Middle School Open House or other oral announcements/presentations to parents (PTA, etc.) Script for Westwood Middle School morning announcements Telep hone / Initial Contact Script Flyers Email Data Collection Forms Contact information Food preference list Inclusion/exclusion Initial visit Daily workbook questions Final visit Other information Stool Collection Information Targeted 24 hour diet recall 24 hour activity recall

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115 Script for Westwood Middle School Open House or other oral announcements/presentations to parents (PTA, etc.) Hello! My name is ________. I am a University of Florida study coordinator /principal investigator for the Food for Fu n study at Westwood Middle School We hope to enroll 80 Westwood students in February to examine whether whole grain foods are important for maintaining digestive health and immune defenses in adolescents. The Dietary Guidelines for Americans recommend that adolescents consume half their grain foods as whole grains, but very few do this. Grain foods are breakfast cereals, breads, noodles, rice, crackers, etc. Whole grain foods are these grain products that contain all parts of the grain (i.e., bran, f lour, germ). No studies show that the whole grain foods are better for adolescents. That is what we would like to determine with this study. If your child participates in the study, we will give your family and primarily your child grain products to ea t for 6 weeks. Foods will include breakfast digestive and immune health. To do this we will keep records of food intake and bowel movements and measure various parameters in yo stool, and saliva. We will ask for 2 stool samples and 2 blood draws As a reward for completing all of the study procedures, your child will be given coupons to trade for rewards valued up to $100 for completing the study These rewar ds will include things such as sp orts equipment, electronics, games, cameras, books, and bikes

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116 Script for Westwood Middle School morning announcements Good morning! We are looking for 80 Westwoo d students to help us with our Food for Fun study. We are trying to determine whether whole grain foods are important for maintain health in middle school students. If you participate, you will receive a six week supply of grain products for you and your family. Examples of these foods include breakfast cereal, bread, noodles, rice, and snacks. If you are interested in helping us out, please come to our Food for Fun booth (location/time/day) to get a study flyer

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117 Telephone / Initial Contact Script He llo! My name is ________. With whom am I speaking? ___(record name on telephone inclusion criteria form) ___ I would like to thank you for responding to the flyers regarding this study. I am a University of Florida study coordinator /principal investigator for the food study at Westwood Middle School Do you have a few minutes right now for me to tell you about the study or would you like me to call back at a more convenient time? (If yes continue, if no get contact information and good time to call.) Fir st I will tell you about the study. If you think your child may be interested in participating I will then list the inclusion criteria so you can determine if your child qualifies (qualify) for this study. If you think (your child) qualifies then I will set up the first study visit. The Dietary Guidelines for Americans recommend that adolescents consume half their grain foods as whole grains. Grain foods are breakfast cereals, breads, noodles, rice, crackers, etc. Whole grain foods are these grain p roducts that contain all parts of the grain (i.e., bran, flour, germ) not just the grain flour. No studies show that the whole grain foods are better for adolescents. That is what we would like to determine with this study. If your child participates in the study, we will give your family and primarily your child grain products to eat for 6 weeks. Foods will include breakfast digestive and immune health. To do this we will ke ep records of food intake, stool, and saliva. We will ask for 2 stool samples and 2 blood draws. As a reward for completing all of the study procedures, your child will be given coupo ns to trade for rewards valued up to $100 for completing the study These rewards will include things such as sports equipment, electronics, games, cameras, books, and bikes This study will start in early February and end six weeks later. I will list o ff the inclusion criteria. Please think about these criteria, but do not answer. I will ask you at the end if your child still wants to participate in the study. If you think your child may qualify and still be interested we will need

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118 to sign an informe d consent. At that time, I will again ask these questions to make sure your child qualifies. Stop me at any time if you have any questions. Complete the Telephone / Initial Contact Script Inclusion Criteria form.

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119 Telephone / Initial Contact Scrip t Inclusion Criteria form. Date: Time: Caller name: Relationship to potential subject: grade: Call Back Number/ Cell Number : E mail: them answer after each criterion.) To participate in the study your child must be student at Westwood Middle School be able to obtain parental/guardian consent. be willing to eat 3 different study foods each day for 6 weeks. be willing to provide 2 blood samples, 2 saliva samples, and 2 stool samples over the course of the study. NOT be taking medications for constipation or diarrhea. NOT be taking any antibiotics in the 4 weeks before randomization. NOT have any diseases or illnesses etc.), other chronic diseases (diabetes, kidney disease, etc.) or immune modulating diseases (HIV, AIDS, autoimmune, hepatitis, cancer etc.).

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120 Not have any food allergies (wheat, soy, egg, milk, gluten, nuts, or any other food or food ingredient)? Is yo ur child i nterested in participating? Would the student be willing to provide 2 blood samples, 2 saliva samples, and 2 stool samples over the course of the study ? Best time to contact ? Appointment time? yes no yes no Time:______ __ _______ Day:_______ __ __ _____ Time:______ ______ _______ Day:______ ______ ________

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123 Email: To: From: Subject: Participants Needed for Food Study Food for Fun! Join our Food Study. 80 healthy Westwood Middle School students are needed for a study examining the benef its of whole grain foods on digestive and immune health. Study participants will receive a six week supply of grain products (breakfast cereal, bread, noodles, rice, snacks). The study will begin February 1, 2010. If you are interested, please stop by o ur study booth Where: When: Or contact: Dr. Bobbi Henken University of Florida Phone: 352 682 4883 Email: nutrition study@ufl.edu

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124 Contact Information Student name: Grade: 6 th 7 th 8 th Parent name : home phone: cell phone: email: address: Parent name: home phone: cell phone: email: address: Guardian name: home phone: cell phone: email: address: Advocate for Wards of State or other agencies (we would ask someone (teacher) not related to study) If the legally authorized repr esentative is consenting, document steps to determine validity of the proxy. Homeroom teacher name: room #: Grade: Most likely address for stool sample pickup: Availability:

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125 Time arrives at school? How? (walks, bus, parent): Time leaves school? How? (walks, bus, parent):

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126 Date: Subject Number: Food Preference List Please put a check mark in the box that best describes your likes and dislikes for each food. Food I would eat it each day. I would eat it a couple times a week. I would never eat i t. Granola bar Cereal bar sugared with milk Cereal eaten dry as a snack Oatmeal other hot cereals Bagels Bread slices as toast or a sandwich Tortillas Corn chips / other chips

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127 How many days a week do you eat the school prepared lunch? How many days a week do you eat the school prepared breakfast?

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128 Date: Time: Subject Number: Inclusion / Exclusion Criteria after Obtaining Consent and Assent (Study coo rdinators to complete this form with the help of the child and guardian) YES No Parental/guardian consent has been obtained. Advocate appointed if necessary. YES No Student assent has been obtained. YES No Would you be willing to eat three different study foods each day for 6 weeks? (Check food preference list. Can they get in > 80 g of whole grains per day ) YES No Are you willing to provide 2 blood samples, 2 saliva samples, and 2 stool samples over the course of the study? PLEASE NOTE THA REORDERED BELOW. NO YES Are you taking medications for constipation or diarrhea? NO YES Have you taken antibiotics recently (i.e., in the 4 weeks before randomization)? NO YES Do you take probiotics or consume >3 servi ngs of yogurt per week?

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129 NO Yes Do you have any diseases or illnesses such as gastrointestinal diseases (diabetes, kidney disease, etc.) or immune modulating diseases (HIV, AIDS, au toimmune, hepatitis, cancer etc.). NO Yes Do you have any food allergies (wheat, soy, egg, milk, gluten, nuts, or any other food or food ingredient)? Pre Qualifies? (Yes, if all boxes in first column marked) yes no Qualifies? (Yes, if student provid es a baseline blood sample and a saliva sample) yes no Student provided a baseline blood sample Student provided a baseline saliva sample yes yes no no

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130 Date: Subject Number: Initial Visit Data Collection Sheet Age: years Date of Birth: Ge nder (circle): male female Height: cm BMI: kg/M 2 Weight: kg BMI percentile: Ethnicity/Race: White American Indian/Alaskan Native Black/African American Native Hawaiian/Pacific Islander Hispanic/Latino Asian

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131 Day 1 Date: Subject Number: Daily Workbook Questions For each question below, circle the appropriate number. 1. Were you bothered by stomach ache or pain yesterday ? Stomach ache refers to all kinds of aches or pains in your stomach or belly. No stomach pain Extreme pain 0 ----1 ----2 ----3 ----4 ----5 ----6 ----7 ----8 ----9 ----10 2. Did your stomach feel bloated yesterday ? Feeling bloated refers to swelling in the stomach or belly. No bloating Extremely bloated 0 ----1 ----2 ----3 ----4 ----5 ----6 ----7 ----8 ---9 ----10 3. Were you bothered by passing gas or flatus yesterday ? Passing gas refers to the release of air or gas from the bowels. No gas Very severe gas 0 ----1 ----2 ----3 ----4 ----5 ----6 ----7 ----8 ----9 ----10 4. What was your level of stre ss yesterday ? Other ways to describe stress include being up tight, anxious, worried, uneasy or stressed out. No stress Extremely stressed 0 ----1 ----2 ----3 ----4 ----5 ----6 ----7 ----8 ----9 ----10 5. What was your level of happiness yesterday ? O ther ways to describe happiness include: joyful, glad, pleased. Not happy Extremely happy 0 ----1 ----2 ----3 ----4 ----5 ----6 ----7 ----8 ----9 ----10 6. How many times did you have a bowel movement or stool yesterday ? 0 1 2 3 4 5 >5 7. How many different kinds of study foods did you eat yesterday ?

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13 2 0 1 2 3 4 5 6 7 8 9

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133 Date: Subject Number: Final Visit Data Collection Sheet (Study coordinators to complete this form with the help of the child and guardian) Height: cm BMI: k g/M 2 Weight: kg BMI percentile: Did you receive an influenza vaccination this school year (i.e., either in the fall or this spring). It could have been a shot (flu shot) or something they sprayed in your nose (Flu Mist Nasal Spray). No Yes about when? Did you receive the swine (H1N1) flu vaccination this school year (i.e., either in the fall or this spring). This would be a shot and 2 shots are recommended. No Yes about when? Did you have 1 or 2 swine flu shots? Did you go to the doctor or clin ic at any time during the study because you were not feeling well? No Yes What was not feeling well? Did you start taking any medications while you were helping us with the study? No Yes what were they? Did you miss any school days while you were helping us with the study? No Yes why did you miss? Which study group do you think you were in? Whole grain Refined grain

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134 Why do you think that?

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135 Subject Number: Other Information Weekly weights post study week 1 weight: kg Date: post study week 2 weight: kg Date: post study week 3 weight: kg Date: post study week 4 weight: kg Date: post study week 5 weight: kg Date: School recorded absences Study participation dates: Date absent: Reason: Date absent: Reason: Date ab sent: Reason: Date absent: Reason: Date absent: Reason: Date absent: Reason: Date absent: Reason: Date absent: Reason:

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136 Date absent: Reason:

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137

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138

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139

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140 Targeted 24 hr Diet Recall Subject number: Study coordinator: Date these foo ds were consumed: D ay: S M T W Th F Sa Page of Location (home/scho ol/out) Time Meal Food and Beverages Give Specific Details Get details on grains, fruit, &vegetables AMOUNT and/or DIMENSIONS Fresh frozen canne d Whole or refined grai n? Brand? COMMENTS

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141 LIST OF REFERENCES 1. Slavin JL, Jacobs D, Marquart L. Grain processing and nutrition. Crit Rev Biotechnol 2001;21(1):49 66. 2. Slavi n J. Whole grains and human health. Nutr Res Rev 2004;17(1):99 110. 3. US Food and Drug Administration. The Scoop on Whole Grains. Available at: http://www.fda.gov/ForConsumers/ ConsumerUpdates/ucm151902.htm Accessed June, 14, 2011. 4. Frolich W, Aman P. Whole grain for whom and why? Food Nutr Re s. 2010;54:10.3402/fnr.v54i0.5056. 5. Cummings JH, Stephen AM. Carbohydrate terminology and classification. Eur J Clin Nut r. 2007;61 Su ppl 1:S5 18. 6. De Moura FF, Lewis KD, Falk MC. Applying the FDA definition of whole grains to the evidence for cardiovascular disease health claims. J Nut r. 2009;139(11):2220S 6S. 7. Okarter N, Liu RH. Health benefits of whole grain phytochemicals. Crit R ev Food Sci Nut r. 2010;50(3):193 208. 8. US Food and Drug Administration. Health Claim Notifications for Whole Grain Foods. Available at: htt p://www.fda.gov/Food/LabelingNutrition/LabelClaims/FDAModernizationActFDA MAClaims/ucm073639.htm Accessed June/14, 2011. 9. US Food and Drug Administration. Draft Guidance: Whole Grain Label Statements. Available at: http://www.fda.gov/Food/GuidanceComplianceRegulatoryInformation/GuidanceDo cuments/FoodLabelingNutrition/ucm059088.htm Accessed June/2011, 2011. 10. Jonnalagad da SS, Harnack L, Hai Liu R, McKeown N, Seal C, Liu S, Fahey GC. Putting the whole grain puzzle together: Health benefits associated with whole grains -summary of american society for nutrition 2010 satellite symposium. J Nut r. 2011. 11. Harris KA, Kris Et herton PM. Effects of whole grains on coronary heart disease risk. Curr Atheroscler Re p. 2010;12(6):368 376. 12. Whole Grains Council. Whole Grain Stamp. Available at: http://www.wholegrai nscouncil.org/whole grain stamp Accessed June/2011, 2011. 13. Slavin JL, Martini MC, Jacobs DR,Jr, Marquart L. Plausible mechanisms for the protectiveness of whole grains. Am J Clin Nut r. 1999;70(3 Suppl):459S 463S.

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142 14. IFIC Foundation. Background on fun ctional foods. Available at: http://www.ific.org/nutrition/index.cfm Accessed October/28, 2008. 15. Adom KK, Sorrells ME, Liu RH. Phytochemicals and antioxidant activity of milled fractions of diffe rent wheat varieties. J Agric Food Che m. 2005;53(6):2297 2306. 16. Adom KK, Liu RH. Antioxidant activity of grains. J Agric Food Che m. 2002;50(21):6182 6187. 17. Slavin J, Jacobs D, Marquart L. Whole grain consumption and chronic disease: Protective mechan isms. Nutr Cance r. 1997;27(1):14 21. 18. Slavin J. Why whole grains are protective: Biological mechanisms. Proc Nutr So c. 2003;62(1):129 134. 19. van Loo J, Coussement P, de Leenheer L, Hoebregs H, Smits G. On the presence of inulin and oligofructose as na tural ingredients in the western diet. Crit Rev Food Sci Nut r. 1995;35(6):525 552. 20. Fraser GE. Associations between diet and cancer, ischemic heart disease, and all cause mortality in non hispanic white california seventh day adventists. Am J Clin Nut r. 1999;70(3 Suppl):532S 538S. 21. Jacobs DR,Jr, Slavin J, Marquart L. Whole grain intake and cancer: A review of the literature. Nutr Cance r. 1995;24(3):221 229. 22. Slavin JL, Jacobs D, Marquart L, Wiemer K. The role of whole grains in disease prevention. J Am Diet Asso c. 2001;101(7):780 785. 23. Marquart L, Jacobs DR,Jr, Slavin JL. Whole grains and health: An overview. J Am Coll Nut r. 2000;19(3 Suppl):289S 290S. 24. Marquart L, Wiemer KL, Jones JM, Jacob B. Whole grains health claims in the USA and other e fforts to increase whole grain consumption. Proc Nutr So c. 2003;62(1):151 160. 25. Jacobs DR,Jr, Meyer KA, Kushi LH, Folsom AR. Whole grain intake may reduce the risk of ischemic heart disease death in postmenopausal women: The iowa women's health study. A m J Clin Nut r. 1998;68(2):248 257. 26. Pietinen P, Malila N, Virtanen M, Hartman TJ, Tangrea JA, Albanes D, Virtamo J. Diet and risk of colorectal cancer in a cohort of finnish men. Cancer Causes Contro l. 1999;10(5):387 396. 27. Liu S, Stampfer MJ, Hu FB, Giovannucci E, Rimm E, Manson JE, Hennekens CH, Willett WC. Whole grain consumption and risk of coronary heart disease: Results from the nurses' health study. Am J Clin Nut r. 1999;70(3):412 419.

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143 28. Anderson JW, Hanna TJ, Peng X, Kryscio RJ. Whole grain fo ods and heart disease risk. J Am Coll Nut r. 2000;19(3 Suppl):291S 299S. 29. Lockheart MS, Steffen LM, Rebnord HM, Fimreite RL, Ringstad J, Thelle DS, Pedersen JI, Jacobs DR,Jr. Dietary patterns, food groups and myocardial infarction: A case control study. Br J Nut r. 2007;98(2):380 387. 30. Tighe P, Duthie G, Vaughan N, Brittenden J, Simpson WG, Duthie S, Mutch W, Wahle K, Horgan G, Thies F. Effect of increased consumption of whole grain foods on blood pressure and other cardiovascular risk markers in health y middle aged persons: A randomized controlled trial. Am J Clin Nut r. 2010;92(4):733 740. 31. Brownlee IA, Moore C, Chatfield M, Richardson DP, Ashby P, Kuznesof SA, Jebb SA, Seal CJ. Markers of cardiovascular risk are not changed by increased whole grain intake: The WHOLEheart study, a randomised, controlled dietary intervention. Br J Nut r. 2010;104(1):125 134. 32. Liu S, Manson JE, Stampfer MJ, Hu FB, Giovannucci E, Colditz GA, Hennekens CH, Willett WC. A prospective study of whole grain intake and risk o f type 2 diabetes mellitus in US women. Am J Public Healt h. 2000;90(9):1409 1415. 33. Liu S. Intake of refined carbohydrates and whole grain foods in relation to risk of type 2 diabetes mellitus and coronary heart disease. J Am Coll Nut r. 2002;21(4):298 30 6. 34. Meyer KA, Kushi LH, Jacobs DR,Jr, Slavin J, Sellers TA, Folsom AR. Carbohydrates, dietary fiber, and incident type 2 diabetes in older women. Am J Clin Nut r. 2000;71(4):921 930. 35. van Dam RM, Rimm EB, Willett WC, Stampfer MJ, Hu FB. Dietary patter ns and risk for type 2 diabetes mellitus in U.S. men. Ann Intern Me d. 2002;136(3):201 209. 36. Fung TT, Hu FB, Pereira MA, Liu S, Stampfer MJ, Colditz GA, Willett WC. Whole grain intake and the risk of type 2 diabetes: A prospective study in men. Am J Clin Nut r. 2002;76(3):535 540. 37. Montonen J, Knekt P, Jarvinen R, Aromaa A, Reunanen A. Whole grain and fiber intake and the incidence of type 2 diabetes. Am J Clin Nut r. 2003;77(3):622 629. 38. de Munter JS, Hu FB, Spiegelman D, Franz M, van Dam RM. Whole g rain, bran, and germ intake and risk of type 2 diabetes: A prospective cohort study and systematic review. PLoS Me d. 2007;4(8):e261. 39. McKeown NM, Meigs JB, Liu S, Wilson PW, Jacques PF. Whole grain intake is favorably associated with metabolic risk fact ors for type 2 diabetes and cardiovascular disease in the framingham offspring study. Am J Clin Nut r. 2002;76(2):390 398.

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144 40. Steffen LM, Jacobs DR,Jr, Murtaugh MA, Moran A, Steinberger J, Hong CP, Sinaiko AR. Whole grain intake is associated with lower bo dy mass and greater insulin sensitivity among adolescents. Am J Epidemio l. 2003;158(3):243 250. 41. Liu S, Willett WC, Manson JE, Hu FB, Rosner B, Colditz G. Relation between changes in intakes of dietary fiber and grain products and changes in weight and development of obesity among middle aged women. Am J Clin Nut r. 2003;78(5):920 927. 42. Koh Banerjee P, Franz M, Sampson L, Liu S, Jacobs DR,Jr, Spiegelman D, Willett W, Rimm E. Changes in whole grain, bran, and cereal fiber consumption in relation to 8 y weight gain among men. Am J Clin Nut r. 2004;80(5):1237 1245. 43. Bazzano LA, Song Y, Bubes V, Good CK, Manson JE, Liu S. Dietary intake of whole and refined grain breakfast cereals and weight gain in men. Obes Re s. 2005;13(11):1952 1960. 44. Sahyoun NR, Ja cques PF, Zhang XL, Juan W, McKeown NM. Whole grain intake is inversely associated with the metabolic syndrome and mortality in older adults. Am J Clin Nut r. 2006;83(1):124 131. 45. Lutsey PL, Jacobs DR,Jr, Kori S, Mayer Davis E, Shea S, Steffen LM, Szklo M, Tracy R. Whole grain intake and its cross sectional association with obesity, insulin resistance, inflammation, diabetes and subclinical CVD: The MESA study. Br J Nut r. 2007;98(2):397 405. 46. Rose N, Hosig K, Davy B, Serrano E, Davis L. Whole grain int ake is associated with body mass index in college students. J Nutr Educ Beha v. 2007;39(2):90 94. 47. McKeown NM, Yoshida M, Shea MK, Jacques PF, Lichtenstein AH, Rogers G, Booth SL, Saltzman E. Whole grain intake and cereal fiber are associated with lower abdominal adiposity in older adults. J Nut r. 2009;139(10):1950 1955. 48. Esmaillzadeh A, Mirmiran P, Azizi F. Whole grain consumption and the metabolic syndrome: A favorable association in tehranian adults. Eur J Clin Nut r. 2005;59(3):353 362. 49. van de V ijver LP, van den Bosch LM, van den Brandt PA, Goldbohm RA. Whole grain consumption, dietary fibre intake and body mass index in the netherlands cohort study. Eur J Clin Nut r. 2009;63(1):31 38. 50. Thane CW, Stephen AM, Jebb SA. Whole grains and adiposity: Little association among british adults. Eur J Clin Nut r. 2009;63(2):229 237. 51. McKeown NM, Troy LM, Jacques PF, Hoffmann U, O'Donnell CJ, Fox CS. Whole and refined grain intakes are differentially associated with abdominal visceral and subcutaneous ad iposity in healthy adults: The framingham heart study. Am J Clin Nut r. 2010;92(5):1165 1171.

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145 52. Larsson SC, Giovannucci E, Bergkvist L, Wolk A. Whole grain consumption and risk of colorectal cancer: A population based cohort of 60,000 women. Br J Cance r. 2005;92(9):1803 1807. 53. Schatzkin A, Park Y, Leitzmann MF, Hollenbeck AR, Cross AJ. Prospective study of dietary fiber, whole grain foods, and small intestinal cancer. Gastroenterolog y. 2008;135(4):1163 1167. 54. Nicodemus KK, Jacobs DR,Jr, Folsom AR. Wh ole and refined grain intake and risk of incident postmenopausal breast cancer (united states). Cancer Causes Contro l. 2001;12(10):917 925. 55. Rohan TE, Jain M, Miller AB. A case cohort study of diet and risk of benign proliferative epithelial disorders o f the breast (canada). Cancer Causes Contro l. 1998;9(1):19 27. 56. Kasum CM, Nicodemus K, Harnack LJ, Jacobs DR,Jr, Folsom AR, Iowa Women's Health Study. Whole grain intake and incident endometrial cancer: The iowa women's health study. Nutr Cancer 2001;3 9(2):180 186. 57. Chan JM, Wang F, Holly EA. Whole grains and risk of pancreatic cancer in a large population based case control study in the san francisco bay area, california. Am J Epidemiol 2007;166(10):1174 1185. 58. United States Department of Agricu lture. Dietary Guidelines for Americans 2010. Available at: http://www.health.gov/dietaryguidelines/dga2010/DietaryGuidelines2010.pdf Accessed June/2011, 2011. 59. Cleveland LE, Moshfegh AJ, Albertson AM, Goldman JD. Dietary intake of whole grains. J Am Coll Nut r. 2000;19(3 Suppl):331S 338S. 60. Bachman JL, Reedy J, Subar AF, Krebs Smith SM. Sources of food group intakes among the US population, 2001 2002. J Am Diet Asso c. 2008;108(5):804 814. 61. United States Department of Agriculture. ChooseMyPlate. Available at: http://www.choose ChooseMyPlate .gov/ Accessed June/2011, 2011. 62. Larson NI, Neumark Sztainer D, Story M, Burgess Champoux T. Whole grain intake correlates among adolescents and young adults: Findings from project EAT. J Am Diet Asso c. 2010;110(2):230 237. 63. Burgess Champoux TL, Larson NI, Neumark Sztainer DR, Hannan PJ, Story MT. Longitudinal and secular tr ends in adolescent whole grain consumption, 1999 2004. Am J Clin Nut r. 2010;91(1):154 159.

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146 64. Harnack L, Walters SA, Jacobs DR,Jr. Dietary intake and food sources of whole grains among US children and adolescents: Data from the 1994 1996 continuing survey of food intakes by individuals. J Am Diet Asso c. 2003;103(8):1015 1019. 65. O'Neil CE, Nicklas TA, Zanovec M, Cho SS, Kleinman R. Consumption of whole grains is associated with improved diet quality and nutrient intake in children and adolescents: The nat ional health and nutrition examination survey 1999 2004. Public Health Nut r. 2011;14(2):347 355. 66. Burgess Champoux T, Marquart L, Vickers Z, Reicks M. Perceptions of children, parents, and teachers regarding whole grain foods, and implications for a sch ool based intervention. J Nutr Educ Beha v. 2006;38(4):230 237. 67. Whole Grains Council. Whole Grain Statistics. Available at: http://www.wholegrainscouncil.org/newsroom/whol e grain statistics Accessed June/2011, 2011. 68. Rockett HR, Berkey CS, Colditz GA. Evaluation of dietary assessment instruments in adolescents. Curr Opin Clin Nutr Metab Car e. 2003;6(5):557 562. 69. Thompson F, Subar A. Dietary assessment methodology. I n: Nutrition in the Prevention and Treatment of Disease San Diego, California : Academic Press; 2001:3. 70. Trabulsi J, Schoeller DA. Evaluation of dietary assessment instruments against doubly labeled water, a biomarker of habitual energy intake. Am J Phy siol Endocrinol Meta b. 2001;281(5):E891 9. 71. Taren DL, Tobar M, Hill A, Howell W, Shisslak C, Bell I, Ritenbaugh C. The association of energy intake bias with psychological scores of women. Eur J Clin Nut r. 1999;53(7):570 578. 72. Sawaya AL, Tucker K, Ts ay R, Willett W, Saltzman E, Dallal GE, Roberts SB. Evaluation of four methods for determining energy intake in young and older women: Comparison with doubly labeled water measurements of total energy expenditure. Am J Clin Nut r. 1996;63(4):491 499. 73. Bl ack AE, Prentice AM, Goldberg GR, Jebb SA, Bingham SA, Livingstone MB, Coward WA. Measurements of total energy expenditure provide insights into the validity of dietary measurements of energy intake. J Am Diet Asso c. 1993;93(5):572 579. 74. Martin LJ, Su W Jones PJ, Lockwood GA, Tritchler DL, Boyd NF. Comparison of energy intakes determined by food records and doubly labeled water in women participating in a dietary intervention trial. Am J Clin Nut r. 1996;63(4):483 490.

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147 75. Rothenberg E. Validation of the food frequency questionnaire with the 4 day record method and analysis of 24 h urinary nitrogen. Eur J Clin Nut r. 1994;48(10):725 735. 76. Rockett HR, Colditz GA. Assessing diets of children and adolescents. Am J Clin Nut r. 1997;65(4 Suppl):1116S 1122S. 7 7. Rockett HR, Breitenbach M, Frazier AL, Witschi J, Wolf AM, Field AE, Colditz GA. Validation of a youth/adolescent food frequency questionnaire. Prev Me d. 1997;26(6):808 816. 78. McNaughton SA. Understanding the eating behaviors of adolescents: Applicati on of dietary patterns methodology to behavioral nutrition research. J Am Diet Asso c. 2011;111(2):226 229. 79. Livingstone MB, Robson PJ, Wallace JM. Issues in dietary intake assessment of children and adolescents. Br J Nut r. 2004;92 Suppl 2:S213 22. 80. W eber JL, Cunningham Sabo L, Skipper B, Lytle L, Stevens J, Gittelsohn J, Anliker J, Heller K, Pablo JL. Portion size estimation training in second and third grade american indian children. Am J Clin Nut r. 1999;69:782 787. 81. Baxter SD, Thompson WO, Davi s HC, Johnson MH. "How do you remember you ate...?": A delphi technique study to identify retrieval categories from fourth grade children. J Am Diet Asso c. 1997;97(1):31 36. 82. Domel SB. Self reports of diet: How children remember what they have eaten. Am J Clin Nut r. 1997;65(4 Suppl):1148S 1152S. 83. Baxter SD, Thompson WO, Davis HC, Johnson MH. Impact of gender, ethnicity, meal component, and time interval between eating and reporting on accuracy of fourth graders' self reports of school lunch. J Am Diet Asso c. 1997;97(11):1293 1298. 84. National Cancer Institute. Dietary Assessment Calibration/Validation Register; Available at: http://appliedresearch.cancer.gov/cgi bin/dacv/index.pl Accessed June/14, 2011. 85. Speakman JR. The history and theory of the doubly labeled water technique. Am J Clin Nut r. 1998;68(4):932S 938S. 86. Burrows TL, Martin RJ, Collins CE. A systematic review of the validity of dietary assessment methods in child ren when compared with the method of doubly labeled water. J Am Diet Asso c. 2010;110(10):1501 1510. 87. Blanton CA, Moshfegh AJ, Baer DJ, Kretsch MJ. The USDA automated multiple pass method accurately estimates group total energy and nutrient intake. J Nut r. 2006;136(10):2594 2599.

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148 88. Moshfegh AJ, Rhodes DG, Baer DJ, Murayi T, Clemens JC, Rumpler WV, Paul DR, Sebastian RS, Kuczynski KJ, Ingwersen LA, Staples RC, Cleveland LE. The US department of agriculture automated multiple pass method reduces bias in t he collection of energy intakes. Am J Clin Nut r. 2008;88(2):324 332. 89. Conway JM, Ingwersen LA, Moshfegh AJ. Accuracy of dietary recall using the USDA five step multiple pass method in men: An observational validation study. J Am Diet Asso c. 2004;104(4): 595 603. 90. Johnson RK, Driscoll P, Goran MI. Comparison of multiple pass 24 hour recall estimates of energy intake with total energy expenditure determined by the doubly labeled water method in young children. J Am Diet Asso c. 1996;96(11):1140 1144. 91. Smith KW, Hoelscher DM, Lytle LA, Dwyer JT, Nicklas TA, Zive MM, Clesi AL, Garceau AO, Stone EJ. Reliability and validity of the child and adolescent trial for cardiovascular health (CATCH) food checklist: A self report instrument to measure fat and sodium intake by middle school students. J Am Diet Asso c. 2001;101(6):635 647. 92. Vereecken CA, Covents M, Matthys C, Maes L. Young adolescents' nutrition assessment on computer (YANA C). Eur J Clin Nut r. 2005;59(5):658 667. 93. Matthys C, Pynaert I, De Keyzer W, De Henauw S. Validity and reproducibility of an adolescent web based food frequency questionnaire. J Am Diet Asso c. 2007;107(4):605 610. 94. Cullen KW, Watson K, Zakeri I. Relative reliability and validity of the block kids questionnaire among youth age d 10 to 17 years. J Am Diet Asso c. 2008;108(5):862 866. 95. Foster E, Matthews JN, Lloyd J, Marshall L, Mathers JC, Nelson M, Barton KL, Wrieden WL, Cornelissen P, Harris J, Adamson AJ. Children's estimates of food portion size: The development and evaluat ion of three portion size assessment tools for use with children. Br J Nut r. 2008;99(1):175 184. 96. Ambrosini GL, O'Sullivan TA, de Klerk NH, Mori TA, Beilin LJ, Oddy WH. Relative validity of adolescent dietary patterns: A comparison of a FFQ and 3 d food record. Br J Nut r. 2011;105(4):625 633. 97. Kobayashi T, Kamimura M, Imai S, Toji C, Okamoto N, Fukui M, Date C. Reproducibility and validity of the food frequency questionnaire for estimating habitual dietary intake in children and adolescents. Nutr J. 2 011;10(1):27. 98. Ross AB, Pineau N, Kochhar S, Bourgeois A, Beaumont M, Decarli B. Validation of a FFQ for estimating whole grain cereal food intake. Br J Nut r. 2009;102(11):1547 1551.

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149 99. Zhu F, Bosch M, Woo I, Kim S, Boushey CJ, Ebert DS, Delp EJ. The u se of mobile devices in aiding dietary assessment and evaluation. IEEE J Sel Top Signal Proces s. 2010;4(4):756 766. 100. Six BL, Schap TE, Zhu FM, Mariappan A, Bosch M, Delp EJ, Ebert DS, Kerr DA, Boushey CJ. Evidence based development of a mobile telephon e food record. J Am Diet Asso c. 2010;110(1):74 79.

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150 BIOGRAPHICAL SKETCH Ally Radford was born and r aised in Vero Beach, FL where her family currently resides. She re ceived her Bachelor of Science at Stetson University in DeLand, FL in 2008. This thesis is a part of the completion of her Master of Science degree in the Department of Food Science and Human Nutrition at the University of Florida in Gainesville, FL.