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Ready-to-Eat Cereal Consumption Patterns and the Association with
Journal of Nutrition & Food Sciences

Journal of Nutrition & Food Sciences
Open Access

ISSN: 2155-9600

Research Article - (2012) Volume 2, Issue 5

Ready-to-Eat Cereal Consumption Patterns and the Association with Body Mass Index and Nutrient Intake in American Adults

Ann M. Albertson1*, Sandra G. Affenito1 and Nandan Joshi2
1General Mills: Bell Institute of Health and Nutrition 9000 Plymouth Avenue North Minneapolis, MN 55427, USA, E-mail: sandra@gmail.com
2General Mills Inc., 601-Prudential, Hiranandani Business Park, Powai, Mumbai 400076, India, E-mail: sandra@gmail.com
*Corresponding Author: Ann M. Albertson, Senior Nutrition Research Scientist, General Mills: Bell, Institute of Health and Nutrition, James Ford Bell Technical Center, 9000 Plymouth Avenue North, Minneapolis, MN 55427, USA, Tel: 763-764-4133, Fax: 763-764-7926

Keywords: Breakfast; Cereals; Micronutrients; BMI

Introduction

Obesity rates among U.S. adults remain over 30% for both men and women, and across socioeconomic, racial, and ethnic groups [1]. Obesity, one of the 10 leading U.S. health indicators [2], is associated with increased risk for hypertension, dyslipidemia, coronary heart disease, stroke, type 2 diabetes mellitus, and certain cancers [3-5]. This alarming health crisis has led to widespread interest in dietary patterns that promote healthy body weight.

Obesity experts have used an epidemiological model to illustrate multifaceted interactions between environmental agents, including food, medication, physical inactivity, toxins and viruses, and genetic and physiologic responses of the host [6]. Recent evaluative studies have focused on diet, a significant environmental variable, and specifically, eating patterns, food selection, diet composition, energy density, and physical inactivity with increased body weight [6-14].

Regular breakfast consumption is one dietary pattern promoted as providing positive nutritional benefit, as well as healthy weight maintenance. Growing evidence indicates people of all ages who eat breakfast consistently regulate their body weight and are less likely to be at risk for overweight compared to those who skip breakfast [15-25]. Breakfast eaters of all ages also exhibit improved nutrient intakes and consume lower fat diets than non-breakfast eaters [16-18,20-23].

Ready-to-eat (RTE) cereal is a prevalent U.S. breakfast food and has been associated with regular breakfast consumption [22]. Cereal provides a significant nutrient source in the diets of U.S. children [17,18,20,22-24] and adults [16,23,25]. Previous studies have suggested a relationship between RTE cereal consumption and healthy BMI in children [16,18,20,22]. Supporting (although not specific) information also exists regarding the relationship between RTE cereal consumption and adult BMI [16]. One study revealed a gender-specific effect regarding RTE cereal consumption on BMI [25] in women, and indicated cereal consumption was associated with favourable dietary composition and obesity prevention. In fact, frequency of RTE cereal consumption predicted weight status in adult female study participants.

Relatively few studies have examined the potential relationship between BMI and RTE cereal consumption. This association is difficult to evaluate, given the influence of various dietary patterns on an outcome measure such as BMI, and particularly when only one or two days of food intake have been reported [16,25]. Because most survey data are not amenable to providing an examination of longer-term dietary patterns and their impact on the development of overweight and obesity, the present study uses a 14-day food intake methodology to investigate RTE cereal consumption patterns on BMI and nutrient intake in U.S. men and women aged 19-64.

Methods

To determine the effect of food consumption patterns on nutrient intakes, a unique, proprietary methodology utilizing The NPD Group’s National Eating Trend (NET) 14-day food diary data was developed at the General Mills Bell Institute of Health and Nutrition. This methodology combines NET’s 14-day food diary data with portion-size estimates derived from the National Health and Nutrition Examination Survey (NHANES) 1999-2004 [26] and nutrient data from the University of Minnesota’s Nutrition Data System for Research (NDS-R)® Version 34, 2008 (Nutrition Coordinating Center, Minneapolis, MN). The resulting integrated database is housed and analyzed using SAS® (SAS Institute, Cary, NC). The dynamic system allows the user to categorize the population based on typical food consumption categories, specific foods, and/or specific brands of foods, and determines dietary differences between the study population and their non-consuming counterparts.

Participants/food consumption data

Study findings are based on information provided by more than 5,000 demographically- representative individuals who completed food and beverage consumption journals for a two-week period. The NPD Group’s National Eating Trends service, which provided the data, has been continuously tracking the eating habits of U.S. consumers since March 1, 1980. While initially focused on capturing all foods and beverages consumed or carried from home by a representative sample of U.S. households, in 1989 the focus expanded to include foods and beverages consumed from all sources.

Panel households are recruited randomly, with an annual sample consisting of 2,000 households containing approximately 5,100 individuals. This study utilized NET data collected from March 2006 through February 2008. The panel is demographically and geographically calibrated to U.S. Census Bureau statistics each year at the household level (including ages of panel participants, household income level, household size, age of head of household, employment status, and race) [27].

The sample is divided into 52 sub-samples. Each week a group of nearly 60 households begins recording all foods and beverages consumed by every household member. Each household maintains a daily eating diary for two weeks. The person most responsible for meal preparation is instructed to record the name and brand of each food and beverage consumed by all members of the household, including all additives, ingredients and cooking aids.

The diary consists of separate sections for each meal and snack situation, and collects food names, flavour descriptors, brand names, package types, product forms, appliances used in preparation, and any special nutritional attributes, among other details. The same information is collected on ingredient and additive items used to create dishes or meals in the home. At the end of each day, the homemaker is instructed to mail the daily diary back to The NPD Group’s offices. After all 14 daily diaries are received from a household; they are coded and made ready for data processing. The annual diary return rate is approximately 97%.

Portion-size data

NET panellists record the foods and beverages consumed by household members, but do not note the quantities. This procedure is standard for panel surveys to minimize recorder burden and thus increase reliability. Portion sizes were estimated by combining data from the NHANES 1999-2004 [26]. Serving weights for individual food codes were aggregated and then collapsed for like-foods to strengthen cell sizes, and statistically smoothed to eliminate outliers. Age- and gender-specific mean serving weights were then determined for over 800 food types. Portion sizes were subsequently assigned to each food recorded and coded in the NET diary.

Nutrient data

Nutrient intakes were estimated according to previously reported procedures [22]. Nutrient values for foods that were recorded and coded in the NET diary were determined using the recipe component of the Nutrition Data System for Research (NDS-R) software. This system is a highly accurate and comprehensive nutrient calculation system that contains complete values for 160 nutrients found in more than 18,000 foods, including many brand-name products.

Each recorded food or recipe was entered into NDS-R per 100 grams of that food, and was closely matched to the description provided in the NET diary. Recipes were created to account for foods with special nutritional attributes (i.e. low fat, fat-free, low cholesterol, calcium fortified, low sodium, or reduced sodium). Additionally, each food was assigned to one of over 100 food groups, making analysis possible by specific food group.

For this study, estimated mean daily intake values were reported for the following nutrients: carbohydrates, sugar, fat, saturated fat, protein, cholesterol, sodium, dietary fiber, vitamin A, vitamin E, vitamin C, thiamin, riboflavin, niacin, vitamin B-6, folate, calcium, magnesium, iron, zinc, and energy (kilocalories). The percentage of adults falling below their Estimated Average Requirement (EAR) [28] was calculated for the total sample, as well as for adults in each of the RTE cereal consumption categories.

Data tabulation

A minimum submission of seven days of food collection documentation was required for participant inclusion in the study. Of the 4,829 adults who participated, only 53 (1.1%) failed to complete the seven-day diary information minimum; 4,127 (85.5%) provided complete 14-day diaries of food intake data. The number of times RTE cereal was consumed in 14 days was recorded for each participant. Intake of cereal was considered as both a continuous and categorical variable. Because the distribution of cereal consumption was not symmetrical and was somewhat truncated, quartiles were not used to categorize data. Instead, adults were classified into the following three groups based on cereal consumption patterns during their 14-day data collection period: 0 servings, 1-6 servings (infrequent), and ≥ 7 servings (frequent).

For the purposes of this analysis, a serving is defined as one record of cereal consumption. Each serving is assigned an age- and genderappropriate mean serving amount. For study participants providing 7-13 diary days, cereal consumption was normalized to 14 days by multiplying the rate of RTE consumption per day by 14.

Body mass index

Individual, self-reported heights and weights were recorded in the diary for each respondent and used to calculate BMI according to the formula BMI = weight (kilograms)/height (meters2). Overweight was defined as a BMI ≥ 25, and obese was defined as a BMI ≥ 30 [29]. Study sample participants who did not record height and/or weight (n = 359) were excluded from the analysis. Individuals reporting less than seven of 14 days of food consumption data were also excluded from the study (n = 28), resulting in a final sample size of 4,414 adults (2015 men and 2399 women).

Statistical analysis

Mean values or proportions were computed according to cereal intake category. Analysis of variance was used to determine whether BMI differed among the cereal consumption categories. Pair-wise t-tests were performed when differences were found among the cereal intake categories. Logistic regression was used to analyze the association between cereal consumption patterns and risk for overweight in each of the age and gender groups. Contrasts were examined between possible pairs of cereal consumption categories using the Wald chi-square.

The analysis was performed after adjusting for age, age2, energy intake, fruits, vegetables and dairy intake and household income. Comparisons were made using analysis of variance on intakes of 21 key nutrients among RTE cereal consumption categories. An alpha level of 0.05 was used to determine significance for the analysis of variance comparisons, except where otherwise noted. All analyses were performed using SAS version 9.2 (SAS® Institute, Cary, NC, 2008).

Results

Frequency of consumption of cereals for 4,414 adults ages 19-64 is shown in Table 1. Overall, 70.7% of adults reported eating cereal at least once during their 14-day reporting window. The total population was analyzed according to the RTE cereal consumption categories Frequent (23.0%), Infrequent (47.7%), and None (29.3%). More than 20% of men and women were classified as frequent cereal eaters. Younger women (19-34 years) were found to be more frequent cereal eaters (25.1%) than younger men (21.9%). Consumption of cereal ranged from 0 to 29 servings in 14 days.

  Cereal Consumption Pattern
None
0 Servings/14d
Infrequent
1-6 Servings/14d
Frequent
>7 Servings/14d
Gender/Age Sample Size n (%) n (%) n (%)
All adults ages 19-64 4414 1294 (29.3) 2104 (47.7) 1016 (23.0)
Male ages 19-64 2015 644 (31.9) 917 (45.5) 454 (22.5)
Male ages 19-34 611 181 (29.6) 296 (48.4) 134 (21.9)
Male ages 35-64 1404 463 (32.9) 621 (44.2) 320 (22.8)
Female ages 19-64 2399 650 (27.1) 1187 (49.5) 562 (23.4)
Female ages 19-34 746 160 (21.4) 399 (53.5) 187 (25.1)
Female ages 35-64 1653 490 (29.6) 788 (47.7) 375 (22.7)

Table 1: Cereal consumption patterns of adults (n=4414) aged 19-64.

A statistically significant, inverse relationship was identified between BMI and frequency of RTE cereal consumption for men and women (Table 2). Significantly lower BMI was found to be associated with adults who ate more than seven servings of RTE cereal during a two-week period. Significantly lower BMI was also found in frequent cereal eaters for all men and women in both age groups (19-34 years and 35-64 years). BMI was higher for men and women ages 35-64 compared to those ages 19-34, but in each age category, frequent cereal eaters exhibited the lowest BMI.

Gender/Age BMI by Cereal Consumption Pattern P
None
0 Servings/14d
Infrequent
1-6 Servings/14d
Frequent
>7 Servings/14d
n (%) n (%) n (%)
Male ages 19-64 28.2a 28.2a 26.7b <0.0001
Male ages 19-34 27.2a 27.5a 25.7b 0.0156
Male ages 35-64 28.6a 28.5a 27.0b 0.0002
Female ages 19-64 27.6a 28.1a 26.7b 0.0002
Female ages 19-34 27.1a 26.9a 25.4b 0.0331
Female ages 35-64 27.8ab 28.8a 27.2b 0.0015
a,bMeans within the same row with the same letter are not significantly different (P < 0.05).

Table 2: Mean Body Mass Index for adults (n=4414) by cereal consumption status.

A significant inverse relationship was found between frequency of cereal consumption and that portion of the population classified as overweight (Table 3). Frequent cereal eaters (7 or more servings per 14 days) were less likely to be overweight or obese compared to those who ate cereal infrequently (1-6 servings per 14 days) or not at all. Sixty-one percent of males and 48 % of females who consumed seven or more RTE cereal servings in two weeks were classified as overweight, compared with 69% of males and 58% of females who consumed no cereal.

 Gender/Age Cereal Consumption Pattern P
None
0 Servings/14d
Infrequent
1-6 Servings/14d
Frequent
>7 Servings/14d
% Overweight/ Obese % Overweight/ Obese % Overweight/ Obese
Male ages 19-64 69.4a 69.3a 60.8b 0.0051
    Male ages 19-34 58.0a 62.5b 49.3a 0.0272
    Male ages 35-64 73.9a 72.5a 65.6b 0.0545
Female ages 19-64 58.0a 58.1a 48.4b 0.0004
    Female ages 19-34 54.4a 49.6a 41.2b 0.0416
    Female ages 35-64 59.2a 62.4a 52.0b 0.0026
a,bProportions of individual at risk within the same row with the same letter are not significantly different (P < 0.05).

Table 3: Percentage of adults (n=4414) classified as overweight or obese by cereal consumption pattern.

Micronutrient and macronutrient consumption (including energy intake) differed significantly across cereal consumption groups, with higher reported nutrient intakes (except fat intake) in those consuming ≥ 7 cereal servings in two weeks (P < 0.01) (Tables 4 and 5). Overall, frequent cereal eaters had significantly higher intakes of fibre, vitamins, and minerals (P < 0.0001), and lower intakes of cholesterol (P < 0.0001). Macronutrients, as a percentage of energy, differed by cereal consumption category, with frequent cereal eaters consuming a higher percentage of calories from carbohydrates and a lower percentage of calories from fat.

Nutrient Nutrient Intake by Cereal Consumption Pattern P
None
0  Serving/14d    
Infrequent
1-6 Servings/14d
Frequent
>7 Servings/14d
Mean ± SD Mean ± SD Mean ± SD
Energy (kcal) 1949 ± 609a 2167 ± 620b 2345 ± 627c <0.0001
Carbohydrates (g) 227 ± 86a 263 ± 87b 303 ± 88c <0.0001
Fat (g) 79 ± 26a 86 ± 26b 86 ± 27b <0.0001
Saturated fat (g) 27 ± 9a 29 ± 10b 29 ± 10b <0.0001
Protein (g) 79 ± 22a 85 ± 22b 92 ± 22c <0.0001
%Kcal from carbohydrate 45 ± 7a 48 ± 6b 51 ± 5c <0.0001
%Kcal from protein 16.4 ± 3a 15.8 ± 2b 15.8 ± 2b <0.0001
%Kcal from fats 36 ± 5a 35 ± 4b 32 ± 4c <0.0001
Cholesterol (mg) 281 ± 128ab 294 ± 114a 269 ± 100b 0.0003
Sodium (mg) 3614 ± 1048a 3877 ± 1037b 4021 ± 1088b <0.0001
Dietary fiber (g) 14 ± 6a 16 ± 5b 19 ± 6c <0.0001
Vitamin A (mcg RAE) 570 ± 474a 677 ± 357b 900 ± 385c <0.0001
Vitamin E (mg α-toc) 6.6 ± 4a 7.4 ± 4b 8.9 ± 5c <0.0001
Vitamin C (mg) 67 ± 57a 84 ± 61b 107 ± 70c <0.0001
Thiamin (mg) 1.6 ± 0.6a 1.8 ± 0.5b 2.3 ± 0.6c <0.0001
Riboflavin (mg) 1.9 ± 0.7a 2.3 ± 0.7b 2.9 ± 0.8c <0.0001
Niacin (mg) 22 ± 7a 25 ± 6b 30 ± 8c <0.0001
Vitamin B-6 (mg) 1.6 ± 0.5a 1.9 ± 0.5b 2.5 ± 0.7c <0.0001
Folate (mcg DFE) 416 ± 140a 560 ± 166b 854 ± 272c <0.0001
Calcium (mg) 728 ± 356a 908 ± 342b 1208 ± 394c <0.0001
Magnesium (mg) 223 ± 81a 256 ± 77b 317 ± 91c <0.0001
Iron (mg) 13 ± 4a 16 ± 4b 22 ± 6c <0.0001
Zinc (mg) 10 ± 3a 12 ± 3b 15 ± 5c  <0.0001
a,b,cMeans within the same row with the same letter are not significantly different (P < 0.01).

Table 4: Mean daily nutrient intake for adult men (n=2015), ages 19-64, by cereal consumption pattern.

Nutrient Nutrient Intake by Cereal Consumption Pattern P
None
0 Servings/14d
Infrequent
1-6 Servings/14d
Frequent
>7 Servings/14d
Mean ± SD Mean ± SD Mean ± SD
Energy (kcal) 1508 ± 448a 1650 ± 484b 1801 ± 544c <0.0001
Carbohydrates (g) 180 ± 64a 207 ± 71b 237 ± 80c <0.0001
Fat (g) 61 ± 19a 64 ± 20b 66 ± 23b <0.0001
Saturated fat (g) 20 ± 7a 22 ± 7b 23 ± 8b <0.0001
Protein (g) 60 ± 16a 64 ± 16b 69 ± 17c <0.0001
%Kcal from carbohydrate 47 ± 7a 49 ± 6b 51 ± 5c <0.0001
%Kcal from protein 16.0 ± 3a 15.6 ± 2b 15.5 ± 3b 0.0077
%Kcal  from fats 36 ± 5a 35 ± 4b 32 ± 4c <0.0001
Cholesterol (mg) 213 ± 96ab 219 ± 84a 205 ± 81b 0.0041
Sodium (mg) 2710 ± 788a 2930 ± 772b 3034 ± 868b <0.0001
Dietary fiber (g) 11 ± 4a 13 ± 4b 15 ± 6c <0.0001
VitaminA (mcgRAE) 488 ± 298a 559 ± 295b 695 ± 267c <0.0001
Vitamin E (mg α-toc) 5.5 ± 3a 5.9 ± 3b 7.2 ± 5c <0.0001
Vitamin C (mg) 58 ± 45a 68 ± 45b 86 ± 61c <0.0001
Thiamin (mg) 1.2 ± 0.4a 1.4 ± 0.4b 1.7 ± 0.5c <0.0001
Riboflavin (mg) 1.5 ± 0.5a 1.8 ± 0.5bbb 2.2 ± 0.7c <0.0001
Niacin (mg) 17 ± 5a 19 ± 5b 22 ± 6c <0.0001
Vitamin B6 (mg) 1.2 ± 0.4a 1.4 ± 0.4b 1.9 ± 0.7c <0.0001
Folate (mcg DFE) 330 ± 109a 442 ± 134b 653 ± 230c <0.0001
Calcium (mg) 592 ± 250a 710 ± 264b 911 ± 338c <0.0001
Magnesium (mg) 180 ± 61a 202 ± 64b 245 ± 81c <0.0001
Iron (mg) 9.9 ± 3a 12.5 ± 4b 16.8 ± 5c <0.0001
Zinc (mg) 7.5 ± 2a 8.5 ± 2b 10.6 ± 3c  <0.0001
a,b,cMeans within the same row with the same letter are not significantly different (P < 0.01).

Table 5: Mean daily nutrient intake for adult women (n=2399), ages 19-64, by cereal consumption pattern.

The percent of the population consuming below 100% of the EAR was also examined for adults in the three cereal consumption categories (Table 6). Sizable proportions of adults did not meet the EAR for vitamin E (89% of men and 93% of women) and magnesium (81% of men and 80% of women). However, among both men and women, frequent cereal consumption was associated with significantly fewer failing to meet the EAR (p < 0.01) for all micronutrients (except vitamin E in women).

Nutrient Cereal Consumption Pattern
None
0 Servings/14 d
Infrequent
1-6 Servings/14 d
Frequent
>7 Servings/14d
Men Women Men Women Men Women
Vitamin Aa,b 40.9 37.2 23.9 25 19.6 18
Vitamin Ea 79.2 92.1 73.6 91.7 70.3 88.3
Vitamin Ca,b 42.6 41 29.6 29.9 23.9 28.8
Thiamina,b 5.5 8.2 0.3 2 1 1.5
Riboflavina,b 7.7 6 1 1.4 1.6 1.2
Niacinb 3.3 3.8 0.3 1.4 1 1.2
Vitamin B6a,b 8.8 21.3 2.6 8.2 2.3 3
Folatea,b 21.9 23.9 3.2 2.2 0.7 0
Magnesiuma,b 71.3 71.7 63.3 59.9 52.6 52.9
Ironb 2.4 9 0 2.4 0 0.9
Zinca,b 17.5 15.8 9.4 7.9 6.9 5.7
Calciuma,b            67.7 85.4 41.4 72.8 11.7 49.3
Vitamin Da,b 97.7 99.4 95.7 99.2 85.2 95.9
aSignificantly fewer men failed to meet the EAR for nutrients among cereal eaters compared to those who did not eat cereal (P < 0.01).
bSignificantly fewer women failed to meet the EAR for nutrients among cereal eaters compared to those who did not eat cereal (P < 0.01).

Table 6: Percentage of adults (n=4414) falling below the Estimated Average Requirement (EAR) by cereal consumption category.

Significantly fewer individuals failed to meet the EAR for calcium among cereal eaters (11.7% of men and 49.3% of women) as compared to non cereal eaters (67.7% of men and 85.4% of women) (p < 0·01). 95.9% of frequent cereal consuming women failed to meet the EAR for vitamin D when compared to 99.2% infrequent cereal eaters and 99.4% of none cereal eaters (Table 6).

Discussion

Results from this study of RTE cereal consumption, BMI, and nutrient intakes demonstrate the important role that cereal plays in the diets of U.S. adults. Frequent cereal consumption was associated with more healthy body weights and improved nutrient profiles. Among those who consumed cereal, fewer adults fell below the EAR, indicating that cereal consumers had more adequate diets than those who did not consume cereal.

Although difficult to compare directly because of differences in methodology, cereal consumption among adults in this study is comparable to patterns reported in other nationally representative samples in the U.S. In this study, 23% of adults consumed cereal frequently (> 7 times in 14 days). In single, 24-hour recall data collected from NHANES III during the years 1988-91 and 1991-94, 17.1% of the population ages 18 and older were categorized as RTE cereal eaters [16].

Data from the 1999-2000 NHANES documents single-day cereal consumption among adults at 21.7% [19]. Single-day cereal consumption reports necessarily include both frequent and infrequent cereal eaters, thus explaining the somewhat lower number of frequent RTE cereal consumers in the present study. Cereal consumption among adults has been reported to increase with age [24]. However, this result was not obtained in the present study. Instead, older adults (ages 35-64) reported eating cereal less often than those under age 35.

Frequent cereal eaters in this study were found to have lower BMI measures than those who consumed cereal less frequently or not at all. The average BMI for frequent cereal eaters in this study was 26.7 for both men and women. This result is consistent with the reported BMI of 26.0 among adult RTE cereal consumers in NHANES III [16]. Body mass index in men who ate one or more servings of cereal per day in the Physicians’ Health Study was lower (BMI = 24.4) [30], but this is likely due to the unique composition of the study population (male physicians, rather than a sample matched to the heterogeneous demographics of the U.S. population).

Several possible explanations may explain the association between cereal consumption and body weight. First, RTE cereal consumption may be a marker for other healthy lifestyle factors. Dietary patterns featuring RTE cereal consumption have been associated with increased levels of physical activity [21], smaller weight gains in women and smaller waist circumference increases in both men and women [31], and lower BMI with reduced mortality rates in men [30]. In addition, adults who eat cereal frequently are most likely to eat breakfast. Thus, the association may reflect eating patterns that are more beneficial for the regulation of body weight.

For example, breakfast skipping has been associated with higher BMI in adults [15,17,19], and additional weight gain as children grow through adolescence [18,20,22,32]. Furthermore, breakfast consumption and low-fat intake are characteristics common to people who have successfully maintained long-term weight loss [31,33]. Because RTE cereals are lower in fat content compared to other breakfast alternatives, overall daily fat intakes are lower for adults who consume RTE cereal [16,20,24,25]. Lower fat intake may contribute to a more favourable energy balance and, hence, healthy BMI.

Consumption of RTE cereal has been shown to improve intakes of macronutrients, dietary fibre, and micronutrients [16,20-24]. The frequent cereal consumers in this study had significantly higher intakes of carbohydrates and dietary fibre, and significantly lower intakes of fat as a percentage of total calories. Frequent cereal eaters also had higher intakes of micronutrients and were more likely to meet the recommended levels. Higher intakes of B-vitamins, calcium, iron, and zinc, in particular, are characteristic of breakfasts including fortified RTE cereals eaten with milk. An improved nutrient intake profile appears to be largely related to the consumption of RTE cereal and the breakfast foods it may replace, as well as a pattern of healthy eating throughout the day.

This study has certain inherent limitations. First, the data are selfreported. However, The NPD Group provides instruction for panellists to fully describe food intakes, and diaries are returned on a daily basis. Second, estimates of portion size are applied based on average serving size for 15 age and gender groups reported in national surveys. This method assumes that the average serving size applies to all individuals of the same age and gender, which clearly provides errors of the estimate for the individual. However, when applied to the total sample, it is expected that mean serving size intakes will approximate estimates of intake provided by dietary survey data. This appears to be true because of the agreement with previously published population-based surveys [16-22].

In addition, it should be noted that differences in the mean comparisons across categories of RTE cereal consumption cannot be explained by an error in the accuracy of the estimate of total intake, an error which would be present across all categories. Thus, the conclusion remains that the most frequent consumers of RTE cereals have better nutrient intakes compared with those who consume RTE cereals least frequently. A strong element of this survey design is the recording of 14 days of food intake information. Thus, it is possible to determine additional associations between other food patterns and BMI, and will lead to continued research in this area.

Conclusions

Regular cereal consumption is related to lower BMI and improved nutrient intakes in adults. While cereal eating by itself may not ensure a healthy body weight, cereal consumption plays a significant role as part of a healthful eating pattern that includes regular breakfast consumption and appropriate energy intakes. Thus, the consumption of RTE cereals should be encouraged as a component of an eating pattern promoting the maintenance of healthy body weights and nutrient intakes by adults.

Acknowledgements

This research was funded by General Mills, Inc., Minneapolis, MN. Authors acknowledge Arohi Bapna for helping in editing the manuscript.

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Citation: Albertson AM, Affenito SG, Joshi N (2012) Ready-to-Eat Cereal Consumption Patterns and the Association with Body Mass Index and Nutrient Intake in American Adults. J Nutr Food Sci 2:145.

Copyright: © 2012 Albertson AM, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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