May 22, 2008
Differences in Dietary Patterns Among College Students According to Body Mass Index
By Brunt, Ardith Rhee, Yeong; Zhong, Li
Abstract. Objective and Participants: The authors surveyed 557 undergraduate students aged 18-56 years to assess weight status, health behaviors, and dietary variety. Methods: They used body mass index (BMI) to divide students into 4 weight categories: underweight (BMI 30 kg/m^sup 2^). Results: Approximately 33% of respondents were overweight or obese, and 8% were underweight. Among the weight categories, the authors observed significant differences in diet (eg, cheese, pork, lamb, veal and game, fish, green leafy vegetables, other vegetables, and the cumulative total of all meats). Overall, 33% of the students consumed 1 fruit in 3 days. The authors found no differences among the weight categories related to eating fatty, sugary snacks. Conclusions: College administrators should create health promotion and skill-building programs to improve students' diet variety. Keywords: body mass index, college health, dietary patterns, obesity
Obesity is a problem that it is not improving.1 Researchers estimate the prevalence of obesity in US college-aged people to have increased from 12% in 19912 to as high as 36% in 2004.3 Obesity in adolescence is the leading predictor of obesity in adulthood.4 This additional weight, most of which is excess body fat, has led to an increased risk for chronic disease development over a lifetime5; however, lifestyle changes can significantly reduce the risk.6
The increasing rates of obesity indicate an energy imbalance, with people taking in more than they expend. A healthy weight based on body mass index (BMI) ranges from 19 to 24.9 kg/m^sup 2^, with overweight being 25 to 29.9 kg/m^sup 2^ and obese being > 30 kg/ m^sup 2^. The dietary choices made by overweight and obese individuals are assumed to be higher in fat and less nutrient-dense than those made by individuals with lower body weight, yet no evidence links high dietary fat intake with long-term obesity.7,8
The college years are often the first time that students, living away from home, are faced with many different food choices. Most students are transitioning to independent living and are thus making their own food choices, which often results in poor eating habits.8 Against current dietary recommendations,9 college students typically consume a diet lacking in fruits, vegetables, and dairy products8,10- 13 and high in fat, sodium, and sugar.14,15 Students frequently have a diet of limited variety,16-19 snack,20,21 and consume fast food.20,22-24 To control weight, the student may develop a habit of skipping meals.24,25 These practices increase nutritional risk and unwanted weight gain for college students of all ages, as few differences in dietary intake exist between lower- and upperclassmen.26
Variety is one important aspect of total diet quality.27 Consuming many different foods from each food group increases the likelihood of meeting current dietary recommendations. 28 Moreover, consuming the same foods without variety in the food groups may be a factor in the increased prevalence of obesity.29
Reports of US college students' quantified dietary intake are scarce.15 Several researchers30-32 have relied on 2 or 3 general questions to assess dietary intake. The 1995 National College Health Risk Behavior Survey used only 2 questions to assess dietary intake: (1) did you have 5 servings of fruit and vegetables yesterday? and (2) did you have = 2 servings of high-fat food yesterday?31,32 Simple questions such as these tend to underestimate mean daily consumption of fruits and vegetables by 1 serving or more33 and do not adequately assess dietary variety. Other researchers have focused on nutrient intake15,34 or only fruits and vegetables. 35 From a public health point of view, discussing groups of foods rather than specific nutrients may be more useful when introducing students to information on diet and health because a meal comprises several foods.34,36
Therefore, in this study, we examined dietary and lifestyle practices in college students across all BMI categories. Our purpose was to assess students' weight status and the relationship between their BMI and dietary intake. Moreover, we investigated whether a difference exists in the kinds and groups of foods consumed among individuals in various BMI categories. We also examined how lifestyle habits relate to BMI.
The university's Institutional Review Board for the Protection of Human Participants in Research approved the protocol for this study, which we conducted during the first week of classes at a Canadian university. During implementation, a letter was read aloud and handed out with the Diet Variety Questionnaire (DVQ); implied student consent was given when students returned the survey. All students at this university are required to complete a semester of wellness education, and the class Principles of Nutrition fulfills the requirement. Therefore, we presumed that this course would generate a sample of students from a variety of majors. We asked all students in this nonmajor introductory nutrition class (N = 713) to complete a DVQ that included demographic, weight control, smoking, and anthropometric measures. On the DVQ, students identified which of the listed foods they had consumed in the past 3 days-1 day during the weekend and 2 days during the week.
The DVQ consisted of 42 items. Each food group was represented by foods that many college students commonly consume. We added an item to each food group for students who consumed foods other than those listed. For example, the dairy foods category contained 5 choices: milk, yogurt, cheese, ice cream and milk-based desserts, and other dairy products. The yes-no responses allowed us to assess variety from each food group and discretionary calories but did not allow quantification of calories and micronutrient intake. (Neither the concept of variety nor that of frequency requires minimum amounts to be set, if one assumes that quantitative estimates are not being made.) We previously pilot tested and validated the survey instrument by using 3-day food records from upper-level dietetics students (A. Brunt, PhD, unpublished data, October 2000).
Using Quetelet's index,37 we calculated BMI from students' self- reported height and weight. We excluded students who did not provide these measures. Self-reported height and weight were strongly correlated to measured height and weight (r2 = .98).38 Using goals set by Healthy People 2010, we divided BMI into 4 categories: underweight ( 30 kg/m^sup 2^).39
We combined each of the foods in specific categories to compare total variety within food groups. Total possible scores and category names (in parentheses) for the various food groups were 5 for dairy (all dairy); 7 for meat (all meat); 3 for meat alternatives, which included eggs, legumes, and nuts or seeds (all meat alternate); 5 for vegetables (all vegetables); 5 for fruits (all fruits); 7 for grains (all grains); and 7 for fatty, sugary snacks, including alcohol (all snacks). We did not place 2 other items-liquid supplements (eg, Slimfast) and water-in any food group.
We analyzed the data with SAS for the personal computer (version 9.1; SAS Institute Inc, Cary, NC), with a significance level set at p
Participants returned 557 usable surveys in which both height and weight were reported. Of the respondents, 60% were female. By comparison, 55% of the entire student body is male. Mean age was 21.3 +- 4.85 years, ranging from 18 to 56 years. Approximately 75% of the students were aged 21 years or younger (see Table 1 for additional descriptive characteristics). Most were white (96%), with the remaining racial groups divided among African American (1.5%), Native American (1.5%), and other (3%). By comparison, 90% of all students at this university, both graduate and undergraduate, are white; remaining racial percentages are similar to those in our study. Respondents included 29% freshman, 39% sophomores, and 32% upperclassmen. Approximately 60% of the respondents lived off campus, and 35% lived on campus. The remaining respondents lived off campus with their parents.
The mean BMI was 23.9 +- 4.5 kg/m^sup 2^, ranging from 16.5 to 44.4 kg/m^sup 2^. The median BMI was 23.1 kg/m^sup 2^. The mean BMI for men was 25.7 kg/m^sup 2^, compared with 22.7 kg/m^sup 2^ for women. Approximately 27% of the students (n = 148) were overweight, and 8% (n = 45) were obese. Another 8% (n = 43) were underweight, and the remainder (n = 321) were of healthy weight. Table 2 contains the distribution of BMI categories on the basis of sex and place of residence. The distribution of BMI categories was significantly different among male and female students and living arrangements. Men were almost 3 times more likely than women to be overweight or obese (55% vs 20%; p
According to students' responses from the 3-day DVQ, at least 1 student consumed each of the 42 listed foods. Table 3 contains the mean variety score for each food group, both overall and by BMI category. The percentage of students consuming a serving or less from the fruit, meat, dairy, grain, or vegetable group was 33%, 17%, 10%, 9%, and 9%, respectively. Seven percent of respondents consumed no meat or meat alternatives; 6% consumed no more than 2 servings of fruits and vegetables combined. The majority (95%) of students consumed at least 2 servings of discretionary sweets or fats. Just as important, 60% of students consumed no alcohol in the 3 days prior to taking the DVQ.
We observed few differences in diet variety among the BMI groups; green leafy vegetables (p = .0115), white bread (p = .0440), liquid supplements (p = .0481), and all meats, which was the sum of all the meats listed (p = .0149), were the exception. Separating responses by sex, we found that the only foods significantly related to male BMI were poultry (p = .0150), beef (p = .0031), and other fruits, which included all fruits that were not citrus fruits, melons, and berries (p = .43). For women, we found no significant differences among the types of foods consumed by the 4 BMI groups.
On the basis of BMI, Table 4 lists the percentage of students who consumed each of the foods at least once, as well as the cumulative total of each food group. Our analysis showed that obese and overweight students were more likely to report consuming pork (p = .0461); lamb, veal, and game (p = .0314); and fish (p = .0004), with all meats significantly related to BMI across all 4 groups (p = .0015). Underweight students were likely to report consuming cheese (p = .0196), green leafy vegetables (p = .0437), and other vegetables (p = .0188). For men, only consumption of all meats (p = .0157) was related to being obese but not to being overweight. For women, consuming yogurt (p = .0177), green leafy vegetables (p = .0051), and all vegetables (which was the sum of all vegetables listed; p = .0350) was significant only for the underweight group.
Last, we compared diet variety in those who were underweight (the lowest quartile) with diet variety in those who were obese (the highest quartile). Students who were underweight consumed more cheese (p
Our purpose in this study was to compare differences in diet variety among BMI categories. The survey population was young, with 88% aged 24 years or younger. Approximately 27% (n = 148) were overweight, and 8% (n = 45) were obese. These percentages were similar to those found in the 1995 National College Health Risk Behavior Survey and other studies11,21,31 but much lower than those reported in the 2004 National Health and Nutrition Examination Survey III.3 Fifty-five percent of men and 20% of women had a BMI greater than 25 kg/m^sup 2^, which is similar to values observed by Silliman et al.21 Our respondents' demographics (ie, sex and ethnicity) were similar to those of other universities in the US Midwest.26,32,34,35 Approximately 14% of students in our study smoked, which coincides with similar percentages (10% to 31%) in other studies.15 However, fewer students in our study than in others reported consuming alcohol.15 One explanation might be that this study took place on a dry campus (ie, alcohol consumption was prohibited) and because many students lived on campus, they did not consume alcohol. Moreover, only 25% of the respondents were of legal drinking age, which may have deterred some students from drinking alcohol.
Demographics associated with being overweight or obese were living off campus, being older, and being male. Overall, fruit variety was the most limited food group (with 33% reporting 1 or fewer daily servings); meat variety (17%) was the second-most limited. Ten percent of participants reported consuming 1 or fewer foods from each of the categories of grains, vegetables, and dairy products. These percentages indicate that there is room for improvement in college students' dietary variety. Moreover, in regard to food type, 95% of all respondents reported consuming fatty, sugary, and salty snacks (ie, sources of discretionary calories). This finding coincides with that of Silliman et al,21 who also found that 95% of their participants consumed snacks at least once daily, with 31% snacking at least 3 times per day. These findings are worrisome, as snacking was coupled with low consumption of nutrient-dense foods-2 trends that increase the risk for developing chronic disease.
Our findings demonstrate significant differences in diet variety between those who are at a healthy weight and underweight compared with those who are overweight and obese. Students with higher BMIs reported a higher intake of pork, lamb, veal, game, and all meats; likewise, many of the saturated fats that Hendricks et al15 observed in participants' diets were from meat. Furthermore, our participants with lower BMIs consumed more vegetables, especially green leafy vegetables. And in a review of adults' dietary intake patterns, Togo et al36 found that a varied diet high in fruits and vegetables and low in meat and fat was associated with lower BMI. We found that these patterns develop before adulthood-at least by late adolescence.
A limitation of this study is the self-reported data. Students may have inaccurately reported dietary intake over the 3 days prior to the administration of the DVQ. Moreover, those 3 days may not be representative of participants' usual dietary patterns. Furthermore, BMI is only a proxy measure of obesity, and using it instead of measures of body composition may result in misclassification. For example, a student who follows a strength-training regimen may be identified as overweight or obese yet may have a greater lean body mass than is estimated by BMI. Nevertheless, using self-reported height and weight is a common practice in epidemiological studies and enables researchers to predict obesity with reasonable accuracy.40 Study findings must be interpreted cautiously; however, our sizable sample suggests actual health risks in this age group.
Because weight loss programs have achieved only limited success,40,41 prevention of obesity is an important issue for all young adults. To ensure healthful dietary practice, nutrition education and healthy behaviors should start at least at the high school level. Healthy People 2010 recommends that postsecondary students receive information in 6 areas that carry significant health risks, and nutrition is one of those areas.39 Health promotion efforts should be targeted toward first-year college students because many are away from home for the first time. They need to be able to identify healthful foods and practice healthful dietary habits that encourage intake of a wide variety of foods. Health behavior change can be challenging; therefore, they also need social support and skill-building programs to assist with their behavior change. We must create an environment to make healthy positive choices. The early years of college are an important time to encourage individuals living healthful lifestyles and to develop interventions for individuals who could do better. Only changes at this level will reduce future chronic disease.
The authors are all with the Department of Health Nutrition and Exercise Sciences at North Dakota State University, Fargo.
Copyright (c) 2008 Heldref Publications
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Ardith Brunt, PhD; Yeong Rhee, PhD; Li Zhong, MS
For comments and further information, address correspondence to Dr Ardith Brunt, North Dakota State University, Health, Nutrition and Exercise Sciences, 351 EML, Fargo, ND 58105, USA (e-mail: [email protected]).
Copyright Heldref Publications May/Jun 2008
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