Available online at Received 11 June 2008; revised 8 September 2008; accepted 8 September 2008

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1 Available online at Nutrition Research 28 (2008) Consumption of cereal is associated with positive health outcomes: evidence from the National Heart, Lung, and Blood Institute Growth and Health Ann M. Albertson a, Douglas Thompson b, Debra L. Franko c,d,, Ronald E. Kleinman d, Bruce A. Barton b, Susan J. Crockett a a Bell Institute of Health and Nutrition, General Mills Inc, Minneapolis, MN 55427, USA b Maryland Medical Research Institute, Baltimore, MD 21210, USA c Department of Counseling and Applied Educational Psychology, Northeastern University, Boston, MA 02115, USA d Department of Pediatrics, Massachusetts General Hospital, Boston, MA 02114, USA Received 11 June 2008; revised 8 September 2008; accepted 8 September 2008 Abstract The purpose of this study was to examine 3 possible explanations for the documented association between cereal consumption and positive health outcomes. The study design was a descriptive, longitudinal study known as the National Heart, Lung, and Blood Institute Growth Health. Data from annual 3-day food records were analyzed to answer study questions. The National Heart, Lung, and Blood Institute Growth Health recruited 2379 girls (1166 white and 1213 black), age 9 to 10 at baseline. Frequency of consumption of cereal; other types of foods eaten at ; and macronutrients, micronutrients, beverages, and fruits and vegetables and physical activity were the main outcome measures. The association of type of (cereal vs without cereal) with the outcomes of interest was estimated using regression techniques. The major findings were (1) cereal consumed at provided more fiber, iron, folic acid, and zinc and less fat, sodium, sugar, and cholesterol, compared with the nutrients in foods eaten during noncereal s. The cereal consumed provided less protein, carbohydrates, and calcium, compared to foods consumed during noncereal s; (2) eating cereal for appeared to facilitate milk consumption (leading to increased calcium intake) and to displace fats/sweets, quick breads, soda, and meat/eggs as foods. Eating cereal at was associated with increased consumption of fiber and carbohydrates and decreased consumption of fats throughout the day; and (3) greater physical activity was also associated with cereal. In conclusion, cereal consumption as part of a healthy lifestyle may play a role in maintaining adequate nutrient intake and physical activity among girls Elsevier Inc. All rights reserved. Keywords: Abbreviations: Cereal; Health; Physical activity; Adolescents; Breakfast; Humans, National Growth and Health ; BMI, body mass index; CI, confidence interval; OR, odds ratio; RTE, ready-to-eat. 1. Introduction Corresponding author. Tel.: ; fax: address: d.franko@neu.edu (D.L. Franko). Breakfast is touted as the most important meal of the day [1]. For children, eating is related to better nutrition [2], lower body mass index (BMI) [3,4], higher rates of /$ see front matter 2008 Elsevier Inc. All rights reserved. doi: /j.nutres

2 A.M. Albertson et al. / Nutrition Research 28 (2008) physical activity [5], and improved overall quality of life [6]. Investigators have recently turned their attention to understanding the role of composition (ie, the specific foods eaten at ) in relation to positive health benefits. Breakfast cereal has been the focus of several studies, due in part to its popularity as a food. Substantial evidence documents the positive association between cereal consumption and nutrient intake [7]. For example, one large scale study found that the more cereal consumed, the better the macronutrient profile. With 3 exceptions (magnesium, vitamins B12, and E), consumption of cereal was significantly associated with higher levels of all micronutrients and better quality [8]. Children who consume cereal, relative to eating other foods, evidence lower percentages of fat in their diet and lower cholesterol levels and lower BMI [9-11]. Overall, cereal eaters have improved nutrient status and health benefits [12] relative to noncereal eaters, suggesting that the consumption of cereal is a healthy choice for. Although evidence suggests that cereal consumption is associated with positive health outcomes [13], what is less clear is why this might be the case. To that end, the purpose of this study was to examine evidence for 3 possible assumptions that might help to explain this relationship. The first is that perhaps the ingredients in cereal (eg, vitamins) are conducive to positive health outcomes. This vitamin pill theory of cereal consumption postulates that it is the nutrient makeup of cereal that accounts for positive benefits. The second is that foods that are eaten along with cereal may be associated with positive health outcomes. This premise contends that it is not cereal per se but rather the associated foods eaten along with cereal (eg, milk) that explain the findings. Finally, cereal eating may be a marker for a healthy lifestyle that is advantageous to positive health outcomes. This assertion postulates that cereal consumption serves as a proxy for other positive health behaviors (eg, exercise). These explanations were tested by looking within participants and comparing their cereal to their noncereal s. To examine these questions, the present study capitalized on data from the National Heart, Lung and Blood Institute Growth and Health (). The National Heart, Lung and Blood Institute Growth and Health included 3-day food diaries collected during multiple years in a racially diverse cohort of 2379 girls followed longitudinally through adolescence. This study focused specifically on composition s including cereal ( cereal s ) were compared with s that did not include cereal ( noncereal s ). The results described here represent food and beverages consumed at time; data for skipped s (ie, times when no food or beverages were consumed) were not included in the analyses. Information about the frequency and correlates of skipping in the cohort has been reported elsewhere [11,14]. This study will contribute to nutrition by providing information about the possible links between cereal consumption and positive health outcomes. 2. Methods and materials As previously reported, the is a 10-year longitudinal study of 2379 girls who were 9 or 10 years old at study entry in 1987 [15]; data collection ended in The study is a descriptive study and not experimental in design. The sample consisted of 1166 white girls and 1213 black girls. Girls were recruited from 3 study sites as follows: University of California at Berkeley (Calif), University of Cincinnati/Cincinnati Children's Hospital Medical Center (Ohio), and Westat Inc/ Group Health in Rockville, Md. The study protocol was approved by the institutional review boards of all participating sites. All girls who entered the had assented, and a parent or guardian consented to their participation. Three-day food records that had been previously validated [16] were collected at visits (years) 1 to 5 and then again at visits 7, 8, and 10. Dietitians instructed girls to record all food and drink and time of intake for 3 consecutive days (2 weekdays and 1 weekend day). Dietitians reviewed completed food records individually with the girls, using standard probes to clarify incomplete responses. Food records were coded and analyzed for nutrient content [17]. This analysis focused on study years 3 to 10. The analysis included only those girls who contributed some food diary data between years 3 and 10 (n = 2318 of the 2379 total participants in ). The mean ± SD ages of the girls when food diaries were collected were 11.5 ± 0.6 (year 3), 12.5 ± 0.6 (year 4), 13.5 ± 0.6 (year 5), 15.5 ± 0.6 (year 7), 16.5 ± 0.6 (year 8), and 17.9 ± 0.2 years (year 10). Breakfast composition was coded based on foods and eating times reported in the food diaries. Following Barton et al [11], was defined as eating that occurred between 5 AM and 10 AM on weekdays and 5 AM and 11 AM on weekends, whereas cereal was defined as including both ready-to-eat (RTE) and cooked cereals. Girls' age was recorded as age at last birthday. Race (black or white) was self-reported. Girls were categorized as being from 1-parent or 2-parent households. The highest level of parental education for either parent was categorized as 4 or more years of college or less than 4 years. Physical activity was assessed using the Habitual Activity Questionnaire [18] by which a physical activity score was computed by multiplying an estimate of metabolic equivalents for the recorded activities by the weekly frequency, duration, and fraction of the year during which activities were performed Statistical analysis For the first assumption ( cereal is more nutritious than foods eaten during noncereal s), nutrients in the cereal consumed at time were compared with nutrients in noncereal s. (The nutrient content of noncereal foods such as milk consumed during cereal s was addressed separately, in relation to the second assumption.) For selected micronutrients (calcium, cholesterol, iron, folicacid, vitaminc, sodium, and zinc), macronutrients (protein, carbohydrates, and fats), and fiber and sugars, the

3 746 A.M. Albertson et al. / Nutrition Research 28 (2008) Table 1 Median amount consumed per day at by type of food (cereal vs foods consumed at s that did not include cereal) and study the Nutrient Median amount of nutrient consumed at time from Cereal All foods consumed at noncereal s statistical significance (cereal vs noncereal comparison) a Fat (g) , P b Protein (g) , P b Fiber (g) , P b Sodium (mg) , P b Sugar (g) , P b Carbohydrates (g) , P b Calcium (mg) , P b Cholesterol (mg) , P b Iron (mg) , P b Table 1 (continued) Nutrient Median amount of nutrient consumed at time from Cereal All foods consumed at noncereal s statistical significance (cereal vs noncereal comparison) a Folic acid (mg) , P b Vitamin C (mg) Not available b Zinc (mg) , P b For ease of interpretation, the descriptive results show median amounts consumed. The statistical analyses (results in the rightmost column of the table) used log-transformed values. a Effect size estimate (statistical significance) representing the effect of type of (cereal vs no cereal) in a design effect regression model adjusting for race, study site, parental education, and average daily energy intake, with multiple imputation of missing data. The effect size estimate is r, computed from t values and df via a conversion of Rosenthal and Rosnow (1991) [27]. r 0.10 = small, 0.10 b r 0.30 = medium, and r N 0.30 = large. Statistical significance was determined by testing the main effect of cereal (H 0, no difference between cereal at and foods consumed during noncereal s). b The distribution of vitamin C did not approach normality even after transformation; therefore, only descriptive analyses are presented. Sample size, n = mean amount that each girl consumed per day from the cereal itself during cereal s was computed, as well as the mean amount that each girl consumed per day from all foods eaten during noncereal s. This was done separately for each study year. For the second assumption ( cereal facilitates consumption of other nutritious foods and displaces less healthful foods), girls' consumption of selected foods (ie, cereal, milk, quick breads such as pancakes and muffins, sweets/fats, meat/eggs, fruit, and soda) at time was quantified separately for cereal s and noncereal s. The food typology was based on an article by Cho et al [3], and the coding of fruit and beverages is based on earlier publications [19,20]. For each type of food, the mean percentage of days that a girl consumed the food during each type of (cereal vs noncereal) was computed. This was done separately for each study year.

4 A.M. Albertson et al. / Nutrition Research 28 (2008) For the third assumption ( cereal consumption is a proxy for a generally healthy lifestyle), girls' intake of selected nutrients (fat, protein, fiber, and sodium; carbohydrates and sugar) at all times of day was quantified separately on days that girls ate cereal and days that they ate noncereal. Also, physical activity on days that girls ate cereal was compared with physical activity on days when noncereal was consumed. Because a lifestyle represents a pattern of behavior exhibited at all times of day (in the morning and after), these behaviors were examined across the entire day, in contrast to the analyses for the previous analyses, which focused specifically on time. The association of type of (cereal vs noncereal ) with each outcome of interest was estimated using regression adjusted for design effects. Briefly, when participants are measured repeatedly, measurements within subjects tend to be correlated, which often results in increased standard errors (the design effect ) [21] and P values of hypothesis tests. Regression adjusted for design effects involves adjusting the model standard errors and P values to account for the correlation among repeated measurements within girls [22,23]. Nutrient intake measures were analyzed as continuous, using linear models. Because intake of all nutrients and physical activity were positively skewed, medians are presented in descriptive analyses and log-transformed values were used in statistical analyses. Measures of types of foods eaten at time (fruit, meat/eggs, and others) were analyzed assuming a binomial distribution (girls consumed each type of food on n days of N days possible in a visit) and logit link function [24]. All analyses were adjusted for race, study site, and parental education. The analyses of foods consumed at non times also adjusted for average daily energy intake. Predictors were center-coded, so that the estimates are interpreted as differences in the outcome by type of, averaging over (race, study site, parental education) or at the median (age, energy intake) of the predictors [25]. Multiple imputation was used to enable unbiased estimation in the presence of some missing data for the dependent variables [26]. Briefly, multiple imputation involves replacing each missing data point with several plausible values that are estimated based on regression using the nonmissing data points, with an element of randomness added to the imputation. This enables efficient use of data from participants who failed to complete some measurements (as opposed to excluding such participants from the analysis) while at the same time adjusting for the uncertainty arising from some data that are being imputed. Significance tests were 2-sided, and α =.05 was used as the criterion of statistical significance. The odds ratio (OR) is given as an indicator of effect size for types of foods eaten at, whereas r (the product moment correlation coefficient) is given as an indicator of effect size for nutrient intake. Formulas have been developed to estimate r based on t values and degrees of freedom in regression models [27]; r ranges from 1 to 1, with values further away from 0 indicating greater effect sizes. As a rule of thumb, when r is used as an effect size indicator, values of r 0.10 have been considered small, 0.10 b r 0.30 are medium, and r N 0.30 are large [27]. Analyses were conducted using SAS 9.1 (SAS Institute, Cary, NC; Procs Surveyreg and Surveylogistic for design effect regression and MI and MIanalyze for multiple imputation). 3. Results Descriptive results for food/beverage and nutrient intake by type of and study year are shown in Tables 1-3. Our first assumption was that cereal is more nutritious than foods eaten during noncereal s. The results were largely consistent with this assertion (Table 1). Cereal consumed at provided more fiber, iron, folic acid, and zinc and less fat, sodium, sugar, and cholesterol, compared with the nutrients contained in foods eaten during noncereal s (Ps b.0001; Table 1 shows effect size estimates). However, cereal contained less protein, carbohydrates, and calcium (Ps b.0001). The distribution of vitamin C was severely skewed and did not approach normality even after transformation; therefore, only descriptive analyses are presented for vitamin C. Significant type by study year interactions for fat, protein, calcium, and cholesterol (Ps b.0001) indicated that the difference in nutrient content between cereal and noncereal foods was greater in the earlier study years and narrowed later in the study. Significant interactions for iron, folic acid, and zinc (Ps b.05) showed the opposite trend, with the difference in nutrient content between cereal and noncereal foods tending to increase in later years. Our second assumption was that eating cereal facilitates consumption of other nutritious foods and displaces less healthful foods. The results were also largely consistent with this assertion (Table 2). Eating cereal appeared to facilitate milk consumption (OR, 5.6; 95% confidence interval [CI], ; P b.0001; interpretation is as follows: girls were 5.6 times more likely to consume milk during cereal s compared with noncereal s). Cereal consumption appeared to displace fats/sweets (OR, 0.41; 95% CI, ; P b.0001; interpretation is as follows: girls were 0.41 times as likely to consume fats/sweets during cereal s compared with noncereal s, or conversely, girls were 1/0.41 = 2.4 times more likely to consume fats/sweets during noncereal s compared with cereal s), quick breads (OR, 0.44; 95% CI, ; P b.0001), soda (OR, 0.68; 95% CI, ; P b.0001), and meat/eggs (OR, 0.24; 95% CI, ; P b.0001). However, contrary to the assumption, fruit consumption was less during cereal (OR, 0.70; 95% CI, ; P b.0001). Significant type by study year interactions for milk, fats/sweets, meat/eggs, and quick breads (Ps b.0001)

5 748 A.M. Albertson et al. / Nutrition Research 28 (2008) Table 2 Mean percentage of days consuming selected types of food at time by type of ( including cereal vs not including cereal) and study the Type of food Mean % of days consuming type of food at on days of Cereal Breakfast without cereal statistical significance (cereal vs without cereal comparison) a Cereal Not available Milk , P b Soda , P b Fruit , P b Fats/sweets , P b Meat/eggs , P b Quick breads , P b a Odds ratio (statistical significance) of the association between type of (cereal vs no cereal) in a design effect logistic regression model adjusting for race, study site, and parental education, with multiple imputation of missing data. Statistical significance was determined by testing the main effect of cereal (H 0, no difference between cereal s and noncereal s). Sample size, n = indicated that the differences between cereal s and noncereal s were less in the earlier study years but tended to increase later in the study. These results help to clarify some of the differences observed in relation to the first assumption. Although few cereals are fortified with calcium, cereal is often consumed Table 3 Median amount consumed per day across all times (including both and non) by type of consumed ( including cereal vs not including cereal) and study the Nutrient Median amount of nutrient consumed at across the entire day on days of Cereal Noncereal statistical significance (cereal vs noncereal comparison) a Sodium (mg) n.s Sugar (g) n.s Protein (g) n.s Fat (g) , P b Fiber (g) , P = Carbohydrates (g) , P = For ease of interpretation, the descriptive results show median amounts consumed. The statistical analyses (results in the rightmost column of the table) used log-transformed values. a Estimated difference (statistical significance) by type of (cereal vs no cereal) in a design effect regression model adjusting for race, study site, parental education, and average daily energy intake, with multiple imputation of missing data. The effect size estimate is r, computed from t values and df via a conversion of Rosenthal and Rosnow (1991) [27]. r 0.10 = small, 0.10 b r 0.30 = medium, and r N 0.30 = large. n.s. indicates not statistically significant; estimates are not shown in this case as they are not different from 0. Statistical significance was determined by testing the main effect of cereal (H 0, no difference between cereal s and noncereal s). Sample size, n = 2318.

6 A.M. Albertson et al. / Nutrition Research 28 (2008) with milk, which does provide a large amount of calcium. As shown in Table 4, when foods consumed along with cereal at, such as milk, were taken into account, girls consumed significantly more calcium during cereal s than they did during noncereal s (P b.0001). Noncereal s were more likely to include meat and eggs (possibly accounting for part of the protein difference) and quick breads (possibly accounting for the carbohydrate difference). Finally, we examined whether cereal consumption was a proxy for a generally healthy lifestyle. Several results supported this assertion (Table 3). Eating cereal at was associated with increased consumption of fiber and carbohydrates and decreased consumption of fats (Ps b.0001) across all times of day, including times and non times. However, type of was not significantly associated with sodium, sugar, and protein consumed across the entire day. There was a significant type by study year interaction for fats (P b.05), indicating that the difference in fat intake across the day varied more by types during the earlier years of the study. There was also a significant interaction for carbohydrates (P b.0005), indicating the opposite trend (ie, the difference by type of increased as girls grew older). A significant association was found between days eating cereal and physical activity girls who had cereal on 1 or 3 days had significantly greater physical activity than those who ate cereal on 0 days (Ps b Table 4 Median amount of calcium consumed per day at by type of (cereal vs noncereal ) and study the Median calcium (mg) consumed at time from Cereal s (cereal plus foods consumed with cereal, including milk) All foods consumed at noncereal s statistical significance (cereal vs without cereal comparison) a , P b In this analysis, cereal includes both cereal and foods consumed along with cereal, such as milk. a Estimated difference (statistical significance) by type of (cereal vs no cereal) in a design effect regression model adjusting for race, study site, parental education, and average daily energy intake, with multiple imputation of missing data. The effect size estimate is r, computed from t values and df via a conversion of Rosenthal and Rosnow (1991) [27]. r 0.10 = small, 0.10 b r 0.30 = medium, and r N 0.30 = large. Statistical significance was determined by testing the main effect of cereal (H 0, no difference between cereal s and noncereal s). Sample size: n = Fig. 1. Physical activity (natural logarithm of MET) by days eating cereal (of 3 possible), after adjusting for study the, participant race, parental education, and study site. MET = metabolic equivalents..05; Fig. 1). There was no association between physical activity and the number of days eating noncereal. 4. Discussion Several studies have shown that cereal intake is associated with positive health outcomes [3,7,12], but few studies have explored potential explanations for this association. We believe the most important findings from this study are as follows: (1) the cereal itself contains high levels of healthful micronutrients and macronutrients, relative to foods consumed during noncereal s; (2) cereal tends to facilitate consumption of other healthful foods at and displace consumption of less healthful foods; and (3) cereal consumption may be a marker for a pattern of behavior that includes healthful eating and high levels of physical activity throughout the day. The analyses reported here, which look within subjects, found that cereal consumed at, relative to foods consumed during noncereal s, contained more healthful micronutrients and less fat, protein, sugars, and carbohydrates. Eating cereal was also associated with higher milk consumption (and consequently, greater calcium intake) at time and lower intake of foods characterized as fats/sweets, meat/eggs, and quick breads. Moreover, cereal consumption was linked with less soda consumption at time. We also found that eating cereal for was related to healthier eating throughout the entire day, including more fiber and less fat consumed, as well as greater physical activity. By facilitating intake of healthful levels of micronutrients and macronutrients and by displacing types of foods that are high in fat, cholesterol, and energy, eating cereal for appears to provide a healthier start to the day in overall nutrient intake, compared to eating noncereal. Healthier eating has been linked to lower cholesterol levels, better cardiovascular health, and lower BMI [28,29], and it is possible that the improved nutrient

7 750 A.M. Albertson et al. / Nutrition Research 28 (2008) profile associated with cereal s accounts for these positive health effects. Beginning the day with cereal may have implications for healthier eating throughout the day, as evidenced by our findings of greater fiber and less fat intake during the entire day. It is possible that those who start out the day eating in healthy ways continue this pattern throughout the day and that eating cereal is a proxy for a commitment to healthy eating in general. That cereal consumption has been linked to lower BMI in this sample [11] suggests that eating cereal combines with healthy eating during the rest of the day to assist in healthy weight control. The link between cereal consumption and reduced BMI may operate through multiple mechanisms. Cereal consumption is related to increased physical activity, which may lead to reduced BMI; in addition, cereal consumption appears to facilitate healthier eating, which may lead to healthier BMI regardless of physical activity. The links between cereal eating, BMI, and weight management have also been reported in other studies [3,7,30-32], and the accumulating evidence advocates for encouraging the consumption of cereal in the maintenance of healthy weight in children and adults. The estimated effect sizes for the association of cereal with nutrient consumption throughout the day were relatively small (r = ); thus, the lifestyle effect represented by cereal appears to be significant yet small. A number of specific findings should be noted. Intake of milk (and consequently, calcium) is known to decrease over the course of childhood and declines particularly in adolescence [33]. This is highly problematic because adolescence is a critical time for accumulating peak bone mass [34]. Calcium intake has also been associated with decreasing the risk for hypertension [35]. Cereal consumption was linked with milk consumption and calcium levels in our studies, as in others [36], suggesting that encouraging the intake of cereal at may be a way to promote much needed calcium, particularly in adolescents. Related, decreased intake of soda at time was also associated with cereal consumption. Soda consumption increases dramatically over the course of adolescence [37,38] and has been linked with lower calcium intake [39] and risk for obesity [40-42]. All combined the positive association between cereal consumption and decreased soda intake suggests that eating cereal may benefit the reduction of unhealthy beverage intake in children and adolescents. Cereal consumption was also related to higher rates of physical activity, consistent with finding that RTE cereal consumption positively correlated with a test of physical fitness [43]. Cereal eating may serve as a proxy for a healthy lifestyle, that is, individuals who eat cereal for recognize the important role of physical activity for good health. Related, cereal eaters in this study may have parents who promote both the consumption of a healthy diet and physical activity. The role of the family in eating will be the subject of future reports, but data clearly indicate the importance of parents in consumption [44]. Finally, cereal eaters may be more likely to be conscious about their weight and may include physical activity as a component of health weight management. The impact of this study is to increase our understanding of the link between cereal consumption and positive health outcomes such as BMI and nutrient profile. The findings of this study have implications for dietetics professionals, who might promote the importance of eating cereal at for children and adolescents. This study sheds light on several reasons why cereal may have been associated with positive health outcomes in past studies. This by no means implies that cereal is the only type of healthy. For example, s consisting of whole wheat toast and fruit may also facilitate positive health outcomes. Future research should examine whether the same associations are found for other potentially healthy foods. Several limitations need to be considered. As is typical for epidemiological studies, dietary information was based on self-report and may therefore be subject to recall errors or underreporting. Because the started out with a limited age range of 9 to 10-year-olds and did not collect food diaries in every year, it was not possible to report consumption for each age. Finally, although demographically diverse in geographic (sites in the western, southeastern, and midwestern regions of the United States) and socioeconomic diversity, the is not a nationally representative sample of girls. Therefore, no information was available on ethnic minority groups such as Hispanic populations or in males. These limitations are offset by several strengths, such as the large number of black girls, low dropout, and availability of 3 days of food intake data. Our findings suggest that cereal consumption is related to healthful food choices both at and throughout the day. Cereal eating is also associated with increased physical activity. Encouraging the choice of cereal for may have implications for the nutrient intake, BMI, and overall health of children and adolescents. Acknowledgment This research was supported by General Mills Inc (Minneapolis, Minn) and by a grant from the National Heart, Lung, and Blood Institute (NHLBI) (HL/ DK71122). The manuscript was completed while one of the authors (DF) was a distinguished research fellow at the Institute for Advanced and the School of Psychological Science at La Trobe University, Melbourne, Australia. The work was also supported by contracts HC and Cooperative Agreements U01-HL Participating centers included Children's Medical Center, Cincinnati, Ohio (Stephen R.

8 A.M. Albertson et al. / Nutrition Research 28 (2008) Daniels, principal investigator; John A. Morrison, coinvestigator); Westat Inc, Rockville, Md (George B. Schreiber, principal investigator; Ruth Striegel-Moore, coinvestigator), and University of California, Berkeley, Calif (Zak I. Sabry, principal investigator; Patricia B. Crawford, coinvestigator); Maryland Medical Research Institute, Baltimore, Md (Bruce A. Barton, principal investigator) served as the data coordinating center. Program office: NHLBI (Eva Obarzanek, PhD, MPH, RD, project officer [ ]; Gerald H. Payne, project officer [ ]). References [1] Affenito SG. Breakfast: a missed opportunity. JADA 2007;107: [2] Williams P. Breakfast and the diets of Australian children and adolescents: an analysis of data from the 1995 National Nutrition Survey. Int J Food Sci 2007;58: [3] Cho S, Dietrich M, Brown CJP, Clark CA, Block G. The effect of type on total daily energy intake and body mass index: results from the third National Health and Nutrition Examination (NHANES III). J Am Coll Nutr 2003;22: [4] Moreno LA, Rodríguez G. Dietary risk factors for development of childhood obesity. Curr Opin Clin Nutr Metab Care 2007;10: [5] Godin G, Anderson D, Lambert LD, Desharnais R. Identifying factors associated with regular physical activity in leisure time among Canadian adolescents. Am J Health Promo 2005;20:20-7. [6] Chen X, Sekine M, Hamanishi S, Wang H, Gaina A, Yamagami T, et al. Lifestyles and health-related quality of life in Japanese school children: a cross-sectional study. Prev Med 2005;40: [7] Albertson AM, Anderson GH, Crockett SJ, Goebel MT. Ready-to-eat cereal consumption its relationship with BMI and nutrient intake of children aged 4 to 12 years. J Am Diet Assoc 2003;103: [8] van den Boom A, Serra-Majem L, Ribas L, Ngo J, Perez-Rodrigo C, Aranceta J, et al. The contribution of ready-to-eat cereals to daily nutrient intake and quality in a Mediterranean setting. J Am Coll Nutr 2006;25: [9] Nicklaus TA, O'Neil CE, Berenson GS. Nutrient contribution of, secular trends, and the role of ready-to-eat cereals: a review of data from the Bogalusa Heart. Am J Clin Nutr 1998;67(supp): 757S-63S. [10] Sampson AE, Dixit S, Meyers AF, Houser Jr R. The nutritional impact of consumption on the diets of inner-city African American elementary school children. J Natl Med Asso 1995;87: [11] Barton BA, Eldridge AL, Thompson D, Affenito SG, Striegel-Moore RH, Franko DL, et al. The relation of and cereal consumption to nutrient intake and body mass index: the National Heart, Lung and Blood Institute Growth and Health. J Am Diet Assoc 2005;105: [12] Gibson S. Micronutrient intakes, micronutrient status and lipid profiles among young people consuming different amounts of cereals further analysis of data from the national diet and nutrition survey of young people aged 4 to 18 years. Pub health Nutr 2003;6: [13] Timlin MT, Pereira MA, Story M, Neumark-Sztainer D. Breakfast eating and weight change in a 5-year prospective analysis of adolescents: Project EAT (Eating Among Teens). Ped 2008;121:e [14] Affenito SG, Thompson D, Barton BA, Franko DL, Daniels SR, Obarzanek E, et al. Breakfast consumption in black and white adolescent girls correlates positively with calcium and fiber intake and negatively with body mass index: the National Heart, Lung, and Blood Institute Growth and Health. J Am Diet Assoc 2005;105: [15] National Heart, Lung, and Blood Institute Growth and Health Research Group. Obesity and cardiovascular disease risk factors in black and white girls: the NHLBI Growth and Health. Am J Pub Health 1992;82: [16] Crawford PB, Obarzanek E, Morrison J, Sabry ZI. Comparative advantage of 3-day food records over 24-hour recall and 5-day food frequency validated by observation of 9- and 10-year-old girls. J Am Diet Assoc 1994;94: [17] Schakel SF, Sievert YA, Buzzard IM. Sources of data for developing and maintaining a nutrient database. J Am Diet Assoc 1988;88: [18] Kimm SYS, Glynn NW, Kriska AM, Barton BA, Kronsberg SS, Daniels SR, et al. Decline in physical activity in black girls and white girls during adolescence. NEJM 2002;347: [19] Striegel-Moore RH, Thompson DR, Affenito SG, Franko DL, Barton BA, Schreiber GB, et al. Fruit and vegetable intake: few adolescent girls meet national guidelines: the National Heart, Lung, and Blood Institute (NHLBI) Growth and Health. Prev Med 2006;42: [20] Stiegel-Moore RH, Thompson D, Affenito SG, Franko DL, Obarzanek E, Barton BA, et al. Correlates of beverage intake in adolescent girls: the National Heart, Lung, and Blood Institute Growth and Health. J Peds 2006;148: [21] Kish L. Survey sampling. New York: John Wiley & Sons Inc.; [22] Lavange LM, Koch GG, Schwartz TA. Applying sample survey methods to clinical trials data. Stat Med 2001;20: [23] Neuhaus JM, Segal MR. Design effects for binary regression models fitted to dependent data. Stat Med 1993;12: [24] McCullagh P, Nelder JA. Generalized linear models. Second edition. London: Chapman and Hall; [25] Kraemer HC, Blasey CM. Centering in regression analyses: a strategy to prevent errors in statistical inference. Int J Meth Psych Res 2004;13: [26] Allison P. Missing data. Thousand Oaks (Calif): Sage; [27] Rosenthal R, Rosnow RL. Essentials of behavioral research: methods and data analysis. New York: McGraw Hill; [28] Brighenti F, Casiraghi MC, Canzi E, Ferrari A. Effect of consumption of a ready-to-eat cereal containing inulin on the intestinal milieu and blood lipids in healthy male volunteers. Eur J Clin Nutr 1999;53: [29] Nitzke S, Freeland-Graves J. Position of the American Dietetic Association: total diet approach to communicating food and nutrition information. J Am Diet Assoc 2007;107: [30] Bertrais S, Polo Luque ML, Preziosi P, Fieux B, Torra De Flot M, Galan P, et al. Contribution of ready-to-eat cereals to nutrition intakes in French adults and relations with corpulence. Ann Nut Metab 2000; 44: [31] Song WO, Chun OK, Obayashi S, Cho S, Chung CE. Is consumption of associated with body mass index in US adults. J Am Diet Assoc 2005;105: [32] Waller SM, Vander Wal JS, Klurfeld DM, McBurney MI, Cho S, Bijlani S, et al. Evening ready-to-eat cereal consumption contributes to weight management. J Am Coll Nutr 2004;23: [33] Bowman SA. Beverage choices of young females: changes and impact on nutrient intakes. J Am Diet Assoc 2002;102: [34] Baker SS, Cochran WJ, Flores CA, Georgieff MK, Jacobson MS, Jaksic T, et al. Calcium requirements of infants, children, and adolescents. Ped 1999;104: [35] Hajjar IM, Grim CE, Kotchen TA. Dietary calcium lowers the agerelated rise in blood pressure in the United States: the NHANES III survey. J Clin Hyperten 2003;5: [36] Song WO, Chun OK, Kerver J, Cho S, Chung CE, Chung SJ. Readyto-eat cereal consumption enhances milk and calcium intake in the US population. J Am Diet Assoc 2006;106: [37] Ballew C, Kueste S, Gillespie C. Beverage choices affect adequacy of children's nutrient intakes. Arch Ped Adol Med 2000;154: [38] Rampersaud GC, Bailey LB, Kauwell GP. National survey beverage consumption data for children and adolescents indicate the need to encourage a shift toward more nutritive beverages. J Am Diet Assoc 2003;103:

9 752 A.M. Albertson et al. / Nutrition Research 28 (2008) [39] Harnack L, Stang J, Story M. Soft drink consumption among US children and adolescents: nutritional consequences. J Am Diet Assoc 1999;99: [40] Ludwig DS, Peterson KE, Gortmaker SL. Relation between consumption of sugar-sweetened drinks and childhood obesity: a prospective, observational analysis. Lancet 2001;357: [41] Berkey CS, Rockett HR, Field AE, Gillman MW, Colditz GA. Sugaradded beverages and adolescent weight change. Obes Res 2004;12: [42] Bray GA, Nielsen SJ, Popkin BM. Consumption of high-fructose corn syrup in beverages may play a role in the epidemic of obesity. Am J Clin Nutr 2004;79: [43] Kafatos A, Linardakis M, Bertsias G, Mammas I, Fletcher R, Bervanaki F. Consumption of ready-to-eat cereals in relation to health and diet indicators among school adolescents in Crete, Greece. Ann Nutr Metab 2005;49: [44] Moore J, Harre N. Eating and activity: the importance of family and environment. Health Promo J Australia 2007;18:143-8.