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Keywords:

  • whole grain breakfast cereal;
  • refined grain breakfast cereal;
  • weight gain;
  • overweight;
  • men

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgement
  8. References

Objective: Prospective studies have suggested that substituting whole grain for refined grain products may lower the risk of overweight and obesity. Breakfast cereal intake is a major source of whole and refined grains and has also been associated with having a lower BMI. The aim of this study was to prospectively assess the association between whole and refined grain breakfast cereal intakes and risk of overweight (BMI ≥ 25 kg/m2) and weight gain.

Research Methods and Procedures: We examined 17, 881 U.S. male physicians 40 to 84 years of age in 1982 who were free of cardiovascular disease, diabetes mellitus, and cancer at baseline and reported measures of breakfast cereal intake, weight, and height.

Results: Over 8 and 13 years of follow-up, respectively, men who consumed breakfast cereal, regardless of type, consistently weighed less than those who consumed breakfast cereals less often (p value for trend = 0.01). Whole and refined grain breakfast cereal intake was inversely associated with body weight gain over 8 years, after adjustment for age, smoking, baseline BMI, alcohol intake, physical activity, hypertension, high cholesterol, and use of multivitamins. Compared with men who rarely or never consumed breakfast cereals, those who consumed ≥1 serving/d of breakfast cereals were 22% and 12% less likely to become overweight during follow-up periods of 8 and 13 years (relative risk, 0.78 and 0.88; 95% confidence interval, 0.67 to 0.91 and 0.76 to 1.00, respectively).

Discussion: BMI and weight gain were inversely associated with intake of breakfast cereals, independently of other risk factors.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgement
  8. References

The prevalence of obesity in the United States has doubled in adults and children and tripled in adolescents over the past two decades. Approximately two-thirds of Americans are overweight or obese (1). In the United States, between 300, 000 and 400, 000 deaths annually are attributable to obesity, and $75 billion were spent in 2003 on health care and related costs (2, 3). Obesity increases risk of hypertension, dyslipidemia, type 2 diabetes, heart disease, cancer, and many other chronic diseases. Despite its epidemic proportions, the long-term efficacy of any specific dietary approach to weight control remains to be determined.

The consumption of whole grains and whole grain products has been recommended as a strategy to maintain a healthy weight. Whole grains may have beneficial effects on weight control through promoting satiety (4, 5, 6). The intake of whole grains may also slow starch digestion or absorption, leading to lower insulin and glucose responses that favor the oxidation and lipolysis of fat rather than storage (4, 5, 6). However, most grain products consumed in the United States are highly refined and contain more starch but less fiber (7, 8). Few studies have directly examined the effects of whole grains, as opposed to refined grains, on body weight and weight changes (9, 10). Whole grain breads, breakfast cereals, popcorn, oatmeal, and brown rice are some of the whole grain foods that are most commonly eaten in Western cultures (11). Breakfast cereals are a major source of both whole and refined grains in the American diet. Intake of breakfast cereals has also been related to weight control in several epidemiological studies (12, 13, 14); however, to date, studies of breakfast cereals have not examined whole as opposed to refined grains in relation to weight control. To further examine the association between intake of whole and refined grain breakfast cereals to changes in weight over time, we analyzed prospective data in a large cohort of middle-aged and elderly U.S. men from the Physicians’ Health Study.

Research Methods and Procedures

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgement
  8. References

Study Population

The Physicians’ Health Study is a completed randomized trial of low-dose aspirin and β-carotene in the primary prevention of cardiovascular disease and cancer. The participants, methods, and results have been described in detail previously (15, 16, 17). The study population consisted of 22, 071 U.S. male physicians 40 to 84 years of age in 1982, with no history of myocardial infarction, stroke, transient cerebral ischemia, or cancer (except non-melanoma skin cancer), who were followed for 13 years. Morbidity and mortality data were available for >99%. At baseline, 22, 066 participants (99.9%) reported weight and height. Of these, 635 were excluded because of history of diabetes, cancer, or cardiovascular disease reported at baseline or follow-up, resulting in a study population of 21, 431 men. After further excluding those who did not provide information on breakfast cereal intake (16.6%), the final population for analyses consisted of 17, 881 men.

Data Collection

Baseline information was self-reported and collected by a mailed questionnaire that asked about many demographic, medical history, and lifestyle variables. Every 6 months for the first year and annually thereafter, participants received follow-up questionnaires asking about compliance with randomized treatment assignments and newly diagnosed conditions, including diabetes, cardiovascular disease, and cancer. Study participants also completed an abbreviated, semiquantitative food-frequency questionnaire (SFFQ)1 at baseline. The abbreviated SFFQ included two questions on breakfast cereal consumption: “Please fill in your average use, during the past year, of each specified food. Cold Breakfast Cereal (1 cup).” Answers included “never or less than once per month, 1 to 3 per month, 1 per week, 2 to 4 per week, 5 to 6 per week, 1 per day, 2 to 3 per day, 4 to 5 per day, 6+ per day.” The second question was “Which cold breakfast cereal do you usually eat? Specify brand and type” with a blank line. The SFFQ included 61 food items divided into five groups and 10 questions on supplements, vitamins, and minerals. These items were selected from a validated SFFQ used in the Nurses’ Health Study in 1980 to discriminate and rank dietary intake among participants (18). The reproducibility and validity of the SFFQ in the Nurses’ Health Study have previously been described (18), along with the questionnaire's ability to assess intake of individual grain products (19). For example, between the SFFQ and the detailed diet records in a sample of the participants, the correlation coefficient was 0.75 for cold breakfast cereal. For each food item on the questionnaire, most responses ranged from never to ≥2 servings/d. A procedure developed by Jacobs et al. (20) was used to classify breakfast cereals into whole and refined grain. Specifically, the breakfast cereals listed in the SFFQ were evaluated for whole grain and bran content; breakfast cereals that contained ≥25% whole grain or bran by weight were classified as whole grain, which is the classification used by Jacobs et al. and others (11, 21). To maintain a high specificity in the definition of whole grain cereals, we included responses in which brand names were missing in the category of refined grains (thereby possibly misclassifying some responses as refined grains), because refined grain cereals were more readily available in the market in the 1980s than were whole grain cereals (7).

Statistical Analysis

Intakes of whole and refined grain breakfast cereals were considered as both continuous (servings per day) and categorical variables. We categorized cereal intake as rarely or never, 1 serving/wk, 2 to 6 servings/wk, and ≥1 serving/d to maintain a gradient of exposure and include adequate sample in each category. We computed means or proportions of baseline risk factors according to categories of whole grain, refined grain, or total cereal intake. Average change in BMI and weight gain in kilograms were calculated using a generalized linear regression model for two time intervals: 96 months (8 years) from baseline and 156 months (13 years) from baseline. Models were adjusted for age and baseline BMI as continuous variables and smoking, alcohol intake, physical activity, history of hypertension, history of high cholesterol, and use of multivitamins as categorical variables. Cox proportional hazards models were used to calculate relative risks (hazards) for attaining a BMI ≥25 or ≥30 kg/m2 and for body weight gain of ≥10, 15, or 20 kg over the follow-up periods according to breakfast cereal intake. These models were adjusted for the same covariates listed above. Tests for linear trend across increasing categories of breakfast cereal intake were conducted by treating the median intake (servings per day) in each category as a continuous variable. All analyses were conducted with SAS (version 8; SAS Institute, Cary, NC). All p values were two-sided. Both whole and refined grain cereals were included in the same regression models, and associations were unchanged.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgement
  8. References

At baseline, ∼19% of men reported consuming, on average, ≥1 serving/d breakfast cereal, and 13% reported consuming ≥1 serving/d whole grain breakfast cereal. Men who ate breakfast cereals more often tended to be older and tended to exercise, and were less likely to be overweight, smokers, or use multivitamin supplements than their counterparts with infrequent cereal intakes. Men with high intake of whole grain or total breakfast cereals were also less likely to have a history of hypertension than those with low intake. History of high cholesterol did not vary significantly across categories of breakfast cereal intake (Table 1).

Table 1. . Baseline characteristics according to intakes of whole grain, refined grain, and total breakfast cereals in the Physicians’ Health Study I (N = 17, 881 men) in 1982*
 Whole grainRefined grainTotal breakfast cereals
CharacteristicsRarely≥1 serving/dRarely≥1 serving/dRarely≥1 serving/d
  • *

    p values for trend for all the variables except history of high cholesterol and history of hypertension for refined grain intake were <0.05.

Number of participants10, 867236512, 863101658493381
Age (mean ± SD, years)52 ± 954 ± 952 ± 955 ± 1052 ± 854 ± 9
BMI (mean ± SD, kg/m2)24.8 ± 2.724.1 ± 2.324.7 ± 2.724.2 ± 2.424.9 ± 2.824.2 ± 2.3
BMI ≥ 25 kg/m2 (%)433342344533
Vigorous exercise (%)      
<1 time/wk292327233223
1/wk191719172017
2 to 4 times/wk374138403441
≥5 times/wk152016191420
Cigarette smoking (%)      
Never485850564458
Past403739384237
Current, <20 cigarettes/d424352
Current, ≥20 cigarettes/d8373103
Alcohol consumption (%)      
Daily262524252925
Weekly504751454847
Monthly121111131112
Rarely/never131714171217
Current use of multivitamin supplement (%)182219201821
History of hypertension (%)231821222319
History of high cholesterol (%)121212131212

At baseline in 1982, men in the lowest category of whole grain breakfast cereal intake were significantly heavier than those in the highest category of whole grain intake (BMI: 24.8 versus 24.1 kg/m2; p for trend < 0.0001; Table 1). The same was true at follow-ups of 8 and 13 years (data not shown). Among consumers of refined grain breakfast cereals, men consuming ≥1 serving/d also weighed less than their counterparts who rarely or never consumed breakfast cereals (BMI: 24.7 versus 24.2 kg/m2; p for trend < 0.0001). Again, the same was true at follow-ups of 8 and 13 years (p for trend < 0.0001).

As shown in Table 2, over the 8-year follow-up period, men with higher intake of breakfast cereals had significantly less weight gain regardless of grain type, age, smoking, baseline BMI, alcohol intake, physical activity, history of hypertension, history of high cholesterol, and use of multivitamins. After 13 years, mean weight gain was significantly lower among participants consuming whole grain cereals at least 1 serving/d compared with those who rarely or never consumed whole grain cereals (2.28 ± 0.06 kg compared with 1.87 ± 0.12 kg; p for trend < 0.05) after adjustment for age. Additional adjustments attenuated the strength of this association. Corresponding trends were seen among men across intakes of refined grain breakfast cereals, but these did not reach the customary level of statistical significance. When intake of total breakfast cereals was examined among men, those with lower intakes gained more than those with higher intakes, independently of age and other covariates over the course of 13 years of follow-up.

Table 2. . Adjusted mean in body weight gain (in kg) according to intakes of whole grain, refined grain, and total breakfast cereals during an 8-year follow-up (from 1982 to 1990) and a 13-year follow-up (from 1982 to 1995)
 Adjusted mean of body weight gain (kg)p for trend*
  • *

    Tests for a linear trend are conducted by treating the median intake in each category as a continuous variable.

  • Linear regression model 1 adjusted for age.

  • Linear regression model 2 adjusted for age, smoking, baseline BMI, alcohol, physical activity, history of hypertension, history of high cholesterol, and use of multivitamins.

 Rarely1 serving/wk2 to 6 servings/wk≥1 serving/d 
Whole grain breakfast cereals     
8-year follow-up     
Model 11.61 ± 0.051.53 ± 0.111.41 ± 0.091.13 ± 0.100.0001
Model 21.55 ± 0.051.40 ± 0.121.37 ± 0.101.13 ± 0.110.003
13-year follow-up     
Model 12.28 ± 0.062.39 ± 0.142.17 ± 0.111.87 ± 0.120.014
Model 22.18 ± 0.062.24 ± 0.152.07 ± 0.121.83 ± 0.130.08
Refined grain breakfast cereals     
8-year follow-up     
Model 11.53 ± 0.041.60 ± 0.101.47 ± 0.121.00 ± 0.150.005
Model 21.46 ± 0.051.63 ± 0.111.48 ± 0.130.94 ± 0.160.005
13-year follow-up     
Model 12.27 ± 0.052.21 ± 0.122.08 ± 0.151.83 ± 0.190.11
Model 22.14 ± 0.062.19 ± 0.132.13 ± 0.161.77 ± 0.200.33
Total breakfast cereals     
8-year follow-up     
Model 11.76 ± 0.061.57 ± 0.071.43 ± 0.071.09 ± 0.08<0.0001
Model 21.66 ± 0.071.53 ± 0.081.40 ± 0.081.07 ± 0.09<0.0001
13-year follow-up     
Model 12.44 ± 0.082.29 ± 0.092.13 ± 0.091.86 ± 0.10<0.0001
Model 22.27 ± 0.082.22 ± 0.102.09 ± 0.101.81 ± 0.110.007

We calculated adjusted relative risks for attaining a BMI in the overweight (≥25 kg/m2) range (Table 3; Figure 1) during the course of 8 and 13 years of follow-up. Men consuming more breakfast cereals, on average, were less likely to become overweight during the follow-up periods. Compared with men who rarely or never consumed breakfast cereals, those who ate ≥1 serving/d of total breakfast cereals were 22% and 12% less likely to become overweight over 8 and 13 years of follow-up, respectively [relative risk (RR), 0.78 and 0.88; 95% confidence interval (CI), 0.67 to 0.91 and 0.76 to 1.00, respectively). When cereal intakes were divided by type of grain, trends for attaining BMI ≥25 kg/m2 were present but did not reach statistical significance after adjustment. The same was true when breakfast cereal intakes were used to predict attaining a BMI ≥30 kg/m2, after adjustment for age and other covariates (data not shown).

Table 3. . Adjusted RRs and 95% CIs for attained BMI ≥25 kg/m2 according to intakes of whole grain, refined grain, and total breakfast cereals over an 8-year follow-up (from 1982 to 1990) and a 13-year follow-up (from 1982 to 1995)
 RR (95% CI) for BMI ≥ 25 kg/m2 
 Rarely/ never1 serving/wk2 to 6 servings/wk≥1 serving/dp for trend*
  • *

    Tests for a linear trend are conducted by treating the median intake in each category as a continuous variable.

  • Cox proportional hazards model 1 adjusted for age.

  • Cox proportional hazards model 2 adjusted for age, smoking, baseline BMI, alcohol, physical activity, history of hypertension, history of high cholesterol, and use of multivitamins.

8-year follow-up     
Whole grain breakfast cereals     
Number of cases1286222339234 
Model 11.000.99 (0.85 to 1.15)1.03 (0.90 to 1.17)0.86 (0.74 to 1.00)0.09
Model 21.001.04 (0.88 to 1.23)1.05 (0.91 to 1.21)0.83 (0.71 to 0.98)0.06
Refined grain breakfast cereals     
Number of cases153028217198 
Model 11.000.98 (0.86 to 1.13)0.88 (0.74 to 1.04)0.85 (0.69 to 1.06)0.06
Model 21.001.02 (0.88 to 1.19)0.86 (0.71 to 1.04)0.81 (0.64 to 1.03)0.03
Total breakfast cereals     
Number of cases735504510332 
Model 11.000.93 (0.83 to 1.05)0.92 (0.81 to 1.04)0.81 (0.71 to 0.93)0.005
Model 21.000.98 (0.86 to 1.12)0.93 (0.81 to 1.06)0.78 (0.67 to 0.91)0.001
13-year follow-up     
Whole grain breakfast cereals     
Number of cases1682273415343 
Model 11.000.91 (0.79 to 1.04)0.95 (0.84 to 1.07)0.99 (0.87 to 1.13)0.76
Model 21.000.97 (0.83 to 1.13)0.93 (0.82 to 1.06)0.91 (0.79 to 1.05)0.13
Refined grain breakfast cereals     
Number of cases1943401247122 
Model 11.001.12 (0.99 to 1.26)1.03 (0.89 to 1.19)0.85 (0.69 to 1.03)0.15
Model 21.001.19 (1.05 to 1.36)1.01 (0.86 to 1.19)0.81 (0.65 to 1.01)0.08
Total breakfast cereals     
Number of cases912674662465 
Model 11.001.01 (0.91 to 1.13)0.97 (0.87 to 1.08)0.94 (0.84 to 1.07)0.26
Model 21.001.07 (0.95 to 1.21)0.95 (0.84 to 1.08)0.88 (0.76 to 1.00)0.01
image

Figure 1. Multivariate adjusted relative risks for attained BMI ≥ 25 kg/m2 according to intakes of whole grain, refined grain, and total breakfast cereals over 8 years of follow-up (from 1982 to 1990).

Download figure to PowerPoint

Adjusted RRs for having a weight gain of 10 or 15 kg were also calculated and are shown in Table 4. At the 13-year follow-up, risk for major weight gain (≥10 kg) was significantly lower among participants who were in the highest category of whole and refined grain breakfast cereal intakes than their counterparts with lower intake, after adjustment for age and other risk factors (Table 4). For example, participants consuming ≥1 serving/d of whole grain breakfast cereals were 22% less likely (RR, 0.78; 95% CI, 0.64 to 0.96; p for trend < 0.01) to experience a weight gain of ≥10 kg over the follow-up period. We also calculated RRs of weight gain ≥20 kg. These results followed the same trends as those for weight gain of ≥10 and ≥15 kg. Because of a much smaller event rate, CIs were wider, and significant trends were present for total cereals only (data not shown).

Table 4. . Adjusted RRs and 95% CIs for attained body weight gain ≥10 or ≥15 kg according to intakes of whole grain, refined grain, and total breakfast cereals over a 13-year follow-up (from 1982 to 1995)
 RR (95% CI) 
 Rarely/ never1 serving/wk2 to 6 servings/wk≥1 serving/dp for trend*
  • *

    Tests for a linear trend are conducted by treating the median intake in each category as a continuous variable.

  • Cox proportional hazards model 1 adjusted for age.

  • Cox proportional hazards model 2 adjusted for age, smoking, baseline BMI, alcohol, physical activity, history of hypertension, history of high cholesterol, and use of multivitamins.

Whole grain breakfast cereals     
Number of cases (weight gain ≥10 kg)1005176226143 
Model 11.000.98 (0.82 to 1.16)0.85 (0.73 to 0.99)0.68 (0.57 to 0.82)<0.0001
Model 21.000.90 (0.75 to 1.10)0.86 (0.72 to 1.02)0.78 (0.64 to 0.96)0.01
Number of cases (weight gain ≥15 kg)362598743 
Model 11.000.90 (0.68 to 1.20)0.92 (0.73 to 1.17)0.58 (0.42 to 0.80)0.001
Model 21.000.84 (0.61 to 1.15)0.94 (0.71 to 1.25)0.82 (0.58 to 1.16)0.27
Refined grain breakfast cereals     
Number of cases (weight gain ≥10 kg)115821811460 
Model 11.000.98 (0.84 to 1.15)0.78 (0.64 to 0.96)0.72 (0.55 to 0.94)0.002
Model 21.001.02 (0.86 to 1.21)0.87 (0.70 to 1.09)0.77 (0.56 to 1.06)0.05
Number of cases (weight gain ≥15 kg)409834415 
Model 11.001.06 (0.83 to 1.35)0.87 (0.64 to 1.20)0.52 (0.31 to 0.87)0.01
Model 21.001.10 (0.84 to 1.43)0.96 (0.67 to 1.37)0.69 (0.39 to 1.22)0.21
Total grain breakfast cereals     
Number of cases (weight gain ≥10 kg)613394340203 
Model 11.000.85 (0.74 to 0.97)0.72 (0.63 to 0.83)0.60 (0.51 to 0.71)<0.0001
Model 21.000.87 (0.75 to 1.01)0.78 (0.66 to 0.91)0.70 (0.58 to 0.85)0.0003
Number of cases (weight gain ≥15 kg)22014213158 
Model 11.000.86 (0.69 to 1.07)0.79 (0.64 to 0.99)0.50 (0.37 to 0.67)<0.0001
Model 21.000.92 (0.72 to 1.17)0.89 (0.69 to 1.16)0.74 (0.54 to 1.02)0.08

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgement
  8. References

In this 13-year prospective study of U.S. male physicians, we identified an inverse relationship between intake of breakfast cereals and body weight and changes in weight over time. Few epidemiological studies have examined the role of breakfast cereals in weight control. Those that have were generally cross-sectional or short-term dietary interventions. This is one of the first large prospective studies to examine breakfast cereal intake, a major source of whole grains, in relation to long-term weight gain. Higher intake of breakfast cereals was associated with lower BMI, lower risk of becoming overweight or obese, and lower risk of major weight gain during the study follow-up periods. These results have important clinical and public health implications, given the growing prevalence of obesity in the United States and worldwide. Our findings suggest that greater intake of breakfast cereals may help to decrease weight gain over time. Given their contributions to health, whole grain breakfast cereals, in particular, may be beneficial in avoiding weight gain and maintaining an optimal weight in the long term.

Breakfast is generally the first meal of the day and plays an important role in determining total intake of energy for the day, hence affecting weight control. The effect of breakfast type on total daily energy intake and BMI was examined cross-sectionally by Cho et al. (12) in the Third National Health and Nutrition Examination Survey. They found that participants consuming ready-to-eat cereals or cooked cereals for breakfast had lower BMI after adjustment for age, sex, race, smoking, alcohol intake, physical activity, and poverty index ratio compared with their counterparts eating other types of breakfasts or skipping breakfast (12). Similarly, in a cross-sectional analysis, Albertson et al. (13) found that among 4- to 12-year-old children, ready-to-eat cereal consumption was inversely associated with mean BMI (p < 0.01). They also found that the proportion of children at risk for being overweight or already overweight was significantly lower in the upper tertile of cereal consumption (p < 0.05). Waller et al. (14) tested the hypothesis that providing a structured snack in the form of a ready-to-eat breakfast cereal would help regulate energy intake and contribute to weight loss in night snackers. Forty-four women and 14 men between 18 and 65 years of age with BMI ≥25 kg/m2 and self-reported night snacking behaviors were randomized into a cereal group and a no cereal group. During a period of 4 weeks, the cereal group was instructed to consume a serving of ready-to-eat cereal with low-fat milk 90 minutes after their evening meal, whereas the no cereal group continued their regular diet. Participants in the cereal group lost a small amount of weight and decreased their after dinner calorie intake in comparison with those in the no cereal group; however, these results were not statistically significant. In our study, we found that more frequent breakfast cereal consumption was associated with lower BMI at baseline and less weight gain over the course of both 8 and 13 years of follow-up.

Whole grain consumption has been associated with reduced risk of both weight gain and the development of obesity in large cohorts of both middle-aged women (9) and men (10). In the first study, women who consumed more whole grains weighed significantly less than did women who consumed fewer whole grains. Those who increased their dietary fiber intake over the 12 years of follow-up gained significantly less weight than those who did not increase their dietary fiber intake, independently of body weight at baseline, age, and changes in covariates. Women in the highest quintile of dietary fiber intake had a 9% lower risk of major weight gain than did women in the lowest quintile (odds ratio, 0.51; 95% CI, 0.39 to 0.67; p for trend < 0.0001). Similarly, a study by Koh-Banerjee et al. (10) found that men who consumed more whole grains weighed significantly less than men who consumed fewer whole grains. Increases in consumption of whole grain over the 8-year follow-up period were inversely related to weight gain, even after adjustment for weight at baseline, age, and changes in covariates and other dietary factors (p for trend < 0.01). It is worth noting that whole grain breakfast cereals contributed the most to overall whole grain intakes (37.6%), and 70.2% of the male cohort reported eating whole grain breakfast cereals.

In our study, associations did not differ by type of grain in breakfast cereal. However, we were not able to evaluate total whole or refined grain intake but only that available in breakfast cereals. In addition, we used the definition of Jacobs et al. (20), in which cereals with ≥25% whole grain or bran content were defined as whole grain. This definition was used so that our results would be more comparable with those of other studies (11, 21); however, this definition may lead to misclassification that would bias our results toward similar associations between whole and refined grains. Our findings may suggest that eating breakfast cereals is part of an overall prudent dietary pattern that contributes to weight management. With the data from our SFFQ, we are unable to compare breakfast cereal intake to other types of breakfast foods or to skipping breakfast. As discussed previously, the SFFQ in this study was an abbreviated version that did not provide a comprehensive assessment of the participants’ usual diet; thus, we could not evaluate or adjust for dietary intakes of some other foods that may contribute to a healthy lifestyle (e.g., whole grain breads). We were able to adjust for fruit, vegetable, and dairy intake, which did not change trends of adjusted mean weight gain over 8 or 13 years for whole grain, refined grain, and total cereals but attenuated all associations for attaining BMI in the overweight or obese ranges. In addition, a smaller portion of the cohort was available for analysis in this study compared with others (22).

While our study did not show a difference between weight gain with whole compared with refined grain breakfast cereal consumption, evidence suggests that whole grains may have other important health benefits. For example, in the Physician's Health Study cohort (22), whole grain, not refined grain, breakfast cereal consumption was inversely related to total and cardiovascular disease—specific mortality, independently of age, BMI, smoking, alcohol intake, physical activity, history of diabetes, hypertension or high cholesterol, and use of multivitamins. Compared with men who rarely or never consumed whole grain cereal, men in the highest category of whole grain cereal intake (≥1 serving/d) had multivariate adjusted RRs of 0.83 (95% CI, 0.73 to 0.94; p for trend < 0.001) for total mortality and 0.80 (95% CI, 0.66 to 0.97; p for trend < 0.001) for cardiovascular disease—specific mortality. Participants eating refined grain breakfast cereals had no significant differences by category of intake in total or cardiovascular disease—specific mortality. Several other large prospective studies have examined the relationship between total whole grain intake and the risk of chronic diseases and have found that increased intakes of whole grain rather than refined grain products are associated with reduced risks of type 2 diabetes (21, 23), hypertension (24, 25), and cardiovascular disease (11, 20, 26).

This study has the advantage of a large cohort with prospective data and 13 years of follow-up over which to examine weight changes. In addition, we were able to differentiate whole and refined grain breakfast cereal intake. Some potential limitations of our study include confounding by lifestyle, dietary change, and measurement error. First, the observed inverse association between breakfast cereal intake and BMI could be caused by confounding of other lifestyle factors such as smoking, exercise, and alcohol intake. To address this issue, we adjusted for these factors and others in multivariate models; however, the possibility of residual confounding cannot be excluded in any observational study. Second, the diagnosis of certain conditions such as hyperlipidemia and hypertension may lead to changes in eating habits and, therefore, confound the association between breakfast cereal intakes and weight gain or BMI. We adjusted multivariate models for history of hypertension and hyperlipidemia at baseline. Finally, measurement error is inherent in any dietary assessment method. The SFFQ used in this study assessed a limited number of foods, which hindered our ability to adjust for total energy intake and other dietary factors that may affect weight gain.

In conclusion, in this large cohort of male physicians, development of overweight or obesity and weight gain over time were inversely associated with the intake of breakfast cereals. As in any observational study, there is the possibility of residual or unknown confounders that may affect results. Nevertheless, it seems that there is growing evidence suggesting that whole grain foods, of which breakfast cereals are a major source, contribute to attaining and maintaining a healthy weight. Interpreted with caution, our findings may suggest that intake of breakfast cereals could be a facet of some dietary strategies to prevent obesity.

Acknowledgement

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgement
  8. References

This work was supported by NIH Grants CA-34944, CA-40360, HL-26490, and HL-34595 and by a grant from the General Mills Corporation. The sponsor of the study had no role in study design, data collection, data analysis, or data interpretation. C.K.G. is employed by General Mills, Bell Institute of Health and Nutrition, Minneapolis, MN, and is a stock shareholder of this corporation. S.L. received honorarium and consulting fees from General Mills.

Footnotes
  • 1

    Nonstandard abbreviations: SFFQ, semiquantitative food-frequency questionnaire; RR, relative risk; CI, confidence interval.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgement
  8. References
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