Obesity-Related Dietary Patterns and Health Status of Diabetes Among At-Risk Latino College Students

Abstract

Spanish

This study examined within-group differences in obesity-related dietary behaviors and the health status of 156 Latino students at risk for diabetes due to family history. Approximately 58% of students were overweight and/or obese, with female students reporting a greater risk for diabetes. Consumption of meats, fried potatoes, breads, and tortillas was associated with higher body mass index (BMI) and diabetes risk indices. Differences in dietary behaviors were found based on students’ college profile and sociodemographic characteristics. Implications for university-related intervention health initiatives are discussed.

Keywords

diabetes dietary patterns health status Latino college students

An estimated 2.5 million Latino Americans are currently afflicted with type 2 diabetes, with dramatic increases in prediabetes and diagnosed diabetes occurring among adolescent and college-age individuals (Centers for Disease Control and Prevention [CDC], 2011, 2014b; U.S. Department of Health and Human Services [HHS], Office of Minority Health, 2015). Dietary health-related factors associated with the obesity epidemic are primary reasons for the rising prevalence rates of type 2 diabetes among young Latinos (CDC, 2014b; Flegal, Carroll, Kit, & Ogden, 2012; Kposowa, 2013; T.F. Nelson, Gortmaker, Subramanian, Cheung, & Wechsler, 2007; Ogden, Carroll, Kit, & Flegal, 2014).

The present study responds to the Latino diabetes youth health crisis by reporting on the obesity-related eating behaviors and health status of Latino college students who are at a heightened risk for onset diabetes due to family history of the disease. Understanding obesity-related eating habits of vulnerable minorities such as the Latino college student is greatly needed if we are to effectively tackle diabetes as a preventable disease threat in young adults (U.S. Department of HHS, Office of Disease Prevention and Health Promotion, 2011). Because Latinos now comprise the largest ethnic minority group within our nation’s university college population (Fry & Lopez, 2012; Page, 2013), Hispanic-serving institutions are contextually ideal for examining risky eating behaviors in Latino young adults and for implementing targeted diabetes preventive health initiatives.

Obesity in College and Latino Students

The transition from adolescence to adulthood—a time typically associated with attending college—is recognized as a risky period for significant weight gain among young adults (Ferrara, 2009; M. C. Nelson, Story, Larson, Neumark-Sztainer, & Lytle, 2008). In fact, epidemiological studies indicate that the greatest increases in weight and obesity are now observed in persons 18 to 29 years of age (Mokdad et al., 2001; Mokdad et al., 1999; Winkleby & Cubbin, 2004), and that the rates of type 2 diabetes and related health conditions have also increased in this age group (CDC, 2011; Mokdad, Marks, Stroup, & Gerberding, 2004; Morrell, Lofgren, Burke, & Reilly, 2012). Likewise, recent large-scale studies of university students indicate that an estimated 30% to 35% of students are overweight and/or obese (American College Health Association [ACHA], 2011; Huang et al., 2003; Lowry, Galuska, Fulton, Wechsler, & Kann, 2002; Lowry et al., 2000), with many at risk for continued weight gain as they progress through 3 to 4 years of college (Gropper, Simmons, Connell, & Ulrich, 2012; Racette, Deusinger, Strube, Highstein, & Deusinger, 2005). The greatest increases in weight gain—approximately 4 pounds—occur during the freshman year (Lloyd-Richardson, Bailey, Fava, & Wing, 2009; Vella-Zarb & Elgar, 2009). Finally, demographic characteristics associated with being overweight and/or obese in college include being male, single, and older, as well as being of low socioeconomic status and living off-campus (Braithwaite, Delevi, & Fincham, 2010; Brunt & Rhee, 2008; T. F. Nelson et al., 2007).

Surprisingly, only one large-scale study (comprised of a nationally representative sample of 4-year universities) was found examining ethnic/racial differences in college students’ weight status (WS) that included Latinos (T. F. Nelson et al., 2007). In line with current epidemiological findings of Latino obesity among young adults (Garcia et al., 2012; Ogden et al., 2014), this study found a high incidence rate of obesity in Latino university students (41% were identified as overweight and/or obese) who were also more likely, as a group, to be overweight when compared with White students. Results from the few small-scale university studies conducted to date that included Latino samples also indicate that a sizable percentage of these students were overweight and/or obese (body mass index [BMI] scores across studies ranged from 32% to 58%), with percentages mirroring or greatly exceeding those reported for the larger U.S. college population (Freedman, 2010; D. Hu, Taylor, Blow, & Cooper, 2011; Hurtado-Ortiz, Santos, & Reynosa, 2011). Finally, the study by Hurtado-Ortiz, Santos, and Reynosa (2011) found that acculturative forces can impact students’ health status, with more assimilated Latino students reporting higher BMI indices and a less healthy WS—a finding that is consistent with that observed in the general Latino population (Garcia et al., 2012).

Obesity-Related Behaviors in College Students

Heightened stress levels and sleep disturbances, accompanied by poor dietary practices, increased caloric intake, and physical inactivity, are often cited as primary culprits for weight gain and diminished health among university students (Ferrara, 2009; M. C. Nelson et al., 2008; Patel & Hu, 2008; Serlachius, Hamer, & Wardle, 2007). Specifically, in terms of eating patterns, “all-you-can-eat” dining halls, meal frequency, skipping meals, evening snacking, and consumption of high-fat junk foods are all implicated in weight gain during the first year of college (DeBate, Topping, & Sargent, 2000; Freedman, 2010; Levitsky, Halbmaier, & Mrdjenovic, 2004; Poddar et al., 2009). Furthermore, counter to all dietary recommendations (Adams & Colner, 2008; Thompson & Veneman, 2005), the average college student “typically consumes a diet lacking in fruits, vegetables, and dairy products and high in fat, sodium and sugar” (Brunt et al., 2008, p. 629). Most alarming is the reportedly substantial consumption of sugar-sweetened beverages and fast food high in fat among college students (Bleich, Wang, Wang, & Gortmaker, 2009; Heidal et al., 2012; Huffman & West, 2007; O’Leary, Hattersley, King, & Allman-Farinelli, 2012; Racette et al., 2005), which are two dietary practices linked to long-term weight gain and a heightened risk for metabolic syndrome, insulin resistance, and type 2 diabetes (Heidal et al., 2012; F. B. Hu & Malik, 2010).

Accordingly, sociodemographic and university-related variables have been found to influence eating patterns among students. Previous studies report that college women are more likely to choose foods low in fat, avoid meats, and consume less fast food and sugar-sweetened beverages than male college students (Boek, Bianco-Simeral, Chan, & Goto, 2012; Huffman & West, 2007; Levi, Chan, & Pence, 2006; Mooney & Walbourn, 2001; Poddar et al., 2009; West et al., 2006). Younger-aged undergraduates, when compared with older students, consume more sugar-sweetened beverages (Huffman & West, 2007; West et al., 2006). Furthermore, students with higher incomes report healthier eating patterns in terms of consuming more fruits and vegetables and fewer sweets, fast-food meals, and high-sugar soft drinks (Knight, Killion, & Knight, 2014). In terms of university characteristics, studies indicate that students who live with their parents have healthier eating habits than those living on-campus (Freedman, 2010), and commuter students who pack lunches consumed less on-campus fast food (Jackson, Berry, & Kennedy, 2009). Likewise, students who live off-campus (not with parents) report consuming a less varied diet of fruits, vegetables, and dairy compared with students residing on-campus (Brunt & Rhee, 2008). Finally, greater fruit and vegetable consumption is linked to being a full-time student, not single and/or in a committed relationship, and living in a residential hall (Adams & Colner, 2008).

Obesity-Related Behaviors Among Latino College Students

The limited research conducted on Latino students suggests that they too tend to make poor dietary choices. For instance, Latino students consume fewer fruits and vegetables than recommended (Evans, Sawyer-Morse, & Betsinger, 2000; D. Hu et al., 2011), comparatively less than their White peers, and are more likely to skip meals and consume more fast food than other ethnic students (Freedman, 2010; Knight et al., 2014). Furthermore, a recent study by Hurtado-Ortiz et al. (2011) examining within-group differences in Latino students’ health behaviors found less healthy eating patterns among (a) Latino men who made fewer efforts to include fruits/vegetables and fiber in their diet and minimize animal fats/oils and refined flours, (b) younger-aged Latinos who reported more frequent fast-food consumption and meal skipping but were less likely to consume fruits/vegetables and avoid presweetened foods and adding sugar to foods, and (c) third-generation-plus Latinos who were also less likely to avoid sugars. Although the later study added important new findings to the literature concerning obesity-related eating habits of Latino college students, results for dietary fat, fruit and vegetable intake, and sugar consumption were based on a single item from a brief lifestyle nutrition questionnaire, which arguably provided a somewhat inadequate assessment of actual dietary variety and consumption of the aforementioned foods (Brunt et al., 2008). The present study will attempt to address this limitation.

Purpose of the Study

As noted previously, there is scarcity of research regarding the dietary habits of the Latino college student. Because the numbers of type 2 diabetes linked to weight gain and obesity have increased among college-age Latinos, research examining the eating behaviors of university students identified to be at high risk for diabetes, but for whom this disease may still be delayed or prevented, seems especially warranted (Arcury, Skelly, Gesier, & Dougherty, 2004; Hurtado-Ortiz et al., 2011). Hence, one of the primary purposes of this investigation was to provide a more comprehensive examination of obesity-related eating patterns for Latino students and of the relationship of such eating habits to students’ overall health status in terms of BMI, WS, and Diabetes Risk Index. We note that most studies of Latino college students typically only use BMI scores as a health indicator; therefore, this study adds to the literature by also including an index of diabetes risk. In terms of eating habits, we focused on students’ dietary fat-related behaviors (i.e., consumption of meats, milk, refined grains, beans, fried foods, cooking fat modifications, and low-fat substitutions) and consumption of fast food, fruits and vegetables, sugary junk foods high in fat, and sugar-sweetened beverages. Second, because demographic and university student variables have both been found to influence eating habits, a second aim of this study was to identify differences among Latino students in obesity-related eating behaviors based on sociocultural background characteristics (age, gender, income, and generational status in the United States) and college student profile (marital status, work status, enrollment status, living arrangement, and class ranking; Braithwaite et al., 2010; Brunt & Rhee, 2008; Brunt et al., 2008; Hurtado-Ortiz et al., 2011; Knight et al., 2014; T. F. Nelson et al., 2007). To our knowledge, no other study has examined obesity-related eating habits and the health status of Latino college students who are at risk for diabetes that simultaneously considers both sociocultural and college variables in the same analysis. This study will attempt to address this void in the literature.

Method

Participants

Sociodemographic data were collected from 156 Latino, undergraduate college students (34% male and 66% female) from a Hispanic-serving state university located in Southern California, with participants ranging in age from 18 to 60 years of age (M = 23.3 years, SD = 6.78). The age and gender composition of the sample mirrored that of the Latino students at this university. Participants who had blood relatives afflicted with type 2 diabetes were considered to be at risk for future diabetes acquisition due to familial genetic predisposition. Approximately 42% of the participants reported having a parent with diabetes, 14.1% a sibling with diabetes, and the remaining a grandparent or aunt/uncle afflicted with this disease. The ethnic distribution of the sample was as follows: 50.4% Mexican, 22.3% Latino, 21.1% Hispanic, and 6.2% Central American. In addition, 65% of the sample indicated that they were second-generation Latinos in the United States, and 21% stated that they were first generation. The median family income of participants ranged from US$25,001 to US$35,000.

A student profile of the sample based on university characteristics was compiled. In terms of class standing, 17.9% of participants were freshmen, 16.0% sophomores, 33.3% juniors, 27.6% seniors, and 5.1% postbaccalaureates/graduates. Furthermore, 91.7% of sample participants were enrolled in college full-time whereas only 8.3% attended part-time. A large number of students (62%) stating they lived with parents while in college. The majority of students were single (83.9%), with 14.8% reporting being married or cohabitating, and 1.2% separated or divorced. Finally, 55.7% of students worked part-time, 15.4% full-time, and 28.9% were not employed.

A health status profile was also collected for the sample. To assess whether participants were underweight, normal weight, or obese, BMI scores were calculated. The mean BMI score for the total sample is considered overweight (M = 26.7), with 57.7% of the sample classified as overweight and/or obese, and 56.3% of Latinas and 60.3% of Latinos falling under this classification. A lower percentage of the sample (38.5%) was classified to be at a healthy weight. In addition, to determine future risk for diabetes acquisition, the “Type 2 Diabetes Risk Test” was used (American Diabetes Association, n.d.). This test identifies individuals who are at a low, moderate, or high risk for diabetes. Of the total sample, 30.7% were at “low risk,” 44% were at “low to moderate risk,” and 25.3% were at “high risk.”

Measures

Sociodemographic and health profile

Participants answered a demographic questionnaire pertaining to their personal background and college student profile (e.g., age, gender, ethnicity, income, generational status, class standing, etc.). Furthermore, a brief health profile questionnaire was administered which allowed computation of participants’ BMI, WS, and Diabetes Risk Score (DRS) as measured by American Diabetes Association (n.d.). The latter two measures were used as objective indicators of participants’ health status.

Fat-Related Habits Questionnaire

A modified version of the Fat-Related Habits Questionnaire (Kristal, Shattuck, & Patterson, 1999) was used. This is a two-part, 25-item questionnaire answered on a 5-point rating scale ranging from almost never (≤10%) to almost always (≥90%), which has been used previously as a fat intake screener with Latino community samples (e.g., G. Block, Gillespie, Rosenbaum, & Jenson, 2000). Part 1 assessed participants’ eating habits of meat, grains (breads and tortillas), milk, and beans. Part 2 evaluated participants’ adherence to a low-fat diet, which provides a total scale score and five subscale scores: (a) Avoid Fried Foods (e.g., chicken fried or cooked with lard/oil), (b) Avoid Adding Fat as a Flavoring (e.g., add butter, margarine, or other fats to potatoes), (c) Modify Foods to Be Low in Fat (e.g., choose low-fat milk products), (d) Substitute for Low-Fat Alternatives (e.g., choose low-fat items from sit-down or fast-food restaurants), and (e) Eat Fruits (e.g., choose fresh fruit as a snack between meals and after dinner).

Fruits and vegetables

Five items were used based on the California Health Interview Survey (CHIS, 2006) Adolescent Questionnaire and the Youth Risk Behavior Surveillance Survey (Eaton et al., 2010) to assess daily intake of fruits and vegetables. Sample items included the following: During the past week how many servings and/or times did you “drink 100% fruit juice?” or “have a green salad?” The CDC (2014a) recommends about five servings of fruits and vegetables per day to help maintain a healthy dietary lifestyle and reduce the risk of chronic conditions.

Sugar intake

Five items based on the CHIS (2006) Adolescent Questionnaire and the Youth Risk Behavior Surveillance Survey (Eaton et al., 2010) were used to create a total daily sugar intake score. In addition, two subscales were calculated, one which tapped into daily intake of liquid sugars or sugar-sweetened beverages such as sodas, fruit-flavored drinks, and blended coffees, and the second which assessed the consumption of high-fat and high-sugar junk foods such as candy bars, ice cream, cakes, and cookies. According to the American Heart Association (2014), women should limit their total daily consumption of added sugars (liquid-sweetened beverages and high-sugar solid foods such as cookies and desserts) to approximately 100 calories, and men to 150 calories. No more than 450 calories of liquid sugar should be consumed per week (equivalent to 64 daily calories) to avoid weight gain and/or obesity. Earlier reported national health guidelines recommend two or less total servings per day of foods deemed high in fat (e.g., french fries, hot dogs, etc.), which include those high in both fat and sugar (e.g., cakes, doughnuts, cookies, pies, etc.; American Cancer Society, 1990; Lowry et al., 2000).

Fast-food consumption

Participants’ frequency of fast-food intake on weekdays and weekends at mainstream (e.g., McDonald’s) and ethnic-specific (e.g., tacos) eateries was measured using six items (Lowry et al., 2000). A sample item used is, “How many times during the school week (Monday-Friday) do you typically get something to eat at McDonald’s, Burger King, Domino’s, Pizza Hut, or other fast-food carry out or drive-thru restaurants?” The recommended frequency of fast-food dining is less than 2 times per week (U.S. Department of HHS, National Institutes of Health [NIH], National Heart, Lung, and Blood Institute, 2004).

Procedure

After participants were recruited, they were screened by phone to ensure that they had a first- and/or second-degree relative afflicted with type 2 diabetes, which was the criterion for inclusion in the study. Participants were then scheduled for a 45-min appointment to complete a paper-and-pencil health dietary habits questionnaire. Participants were paid US$15 for participating in the study. Ethical guidelines stipulated by the American Psychological Association (2010) were followed by the researchers. In addition, informed consent was obtained for all participants, and payment and debriefing were given at the end of the study. As part of the debriefing procedure, participants previewed a brief NIH diabetes film and were given educational brochures about the causes of diabetes and lifestyle changes that can be adopted to delay and/or prevent this disease.

Results

Overview of Data Analyses

Descriptive analyses were first performed on the obesity-related dietary variables examined in this study.¹ ANOVA and t-test procedures were then conducted to assess group differences on the three health indicators—BMI score, WS, and DRS—and on the obesity-related eating variables based on Latinos’ sociocultural background (age, gender, generational status, and income) and college student profile (marital status, work status, college class standing, enrolled part-time/full-time, and residence status). Third, bivariate correlation analyses were executed to determine the relationship between health status indicators and specific obesity-related eating behaviors. Fourth, bivariate analyses among key obesity-related dietary variables were performed to identify high-risk eating patterns among Latino students.

Descriptive Analyses

An overview of Table 1 indicates that, on average, sample participants reported they often or very often—approximately 50% to 75% or more of the time—consumed meats, milk, beans, and refined grains/flours in the form of breads and tortillas and that, in general, they attempted to follow a low-fat diet (indicated by means approximating 3-4 on the Eating Habits Questionnaire subscales and on the Low-Fat Diet Questionnaire subscales). Furthermore, we note that total daily consumption of fruits and vegetables for the sample averaged only 2.12 servings, which is considered far below the recommended national dietary guideline (ACHA, 2011) of five or more servings per day. Students on average consumed about one daily serving of 100% juice and one serving of vegetables. Furthermore, the average consumption of total sugars was high, with students reporting approximately one serving of liquid sugars (e.g., sodas, sweetened beverages, and coffee drinks) plus one serving of high-sugar high-fat junk foods (e.g., cookies, pastries, chocolate bars, ice cream, or frozen desserts) on a daily basis. Finally, during the course of a typical 7-day week, students reported eating fast foods 43% of the time (or about 3 days a week).

Table 1.

Descriptive Statistics on Dietary Variables.

Variables	M	Minimum	Maximum	SD
Eating Habits Questionnaire
Meat subscale	3.02	1.00	5.00	0.87
Refined Flour (bread and tortillas) subscale	3.07	1.00	5.00	0.95
Milk	3.66	1.00	5.00	1.30
Beans	3.52	1.00	5.00	1.23
Low-Fat Diet Questionnaire	3.47	1.81	4.69	0.64
Avoid Fried Food subscale	3.91	1.33	5.00	0.76
Avoid Adding Fat as Flavoring subscale	3.76	1.00	5.00	1.16
Modify Meat to Be Low in Fat subscale	3.52	1.00	5.00	1.29
Substitute for Low-Fat Foods subscale	2.80	1.00	5.00	0.96
Eat Fresh Fruit as Snack or in Between Meals subscale	2.98	1.00	5.00	1.24
Total daily fruit and vegetables	2.12	0.00	5.57	1.19
Daily 100% Fruit Juice subscale	0.66	0.00	3.43	0.61
Daily Vegetable subscale	0.83	0.00	3.00	0.63
Total daily sugar consumption	1.62	0.00	5.43	0.99
Daily Liquid Sugar subscale	0.91	0.00	3.43	0.68
Daily Solid Sugar subscale (junk foods)	0.72	0.00	3.57	0.59
Weekly fast-food consumption	3.26	0.00	10.00	2.10

Analyses of Health Indicators by Sociodemographic and College Profile Variables

In regard to the health indicators—BMI, WS, and DRS—women reported a higher DRS than men with no other differences observed based on age group and generational status (as reported in Hurtado-Ortiz et al., 2011) or by participants’ household income. Likewise, ANOVA and t-test analysis performed on participants’ BMI scores, WS, and DRS by the college profile variables showed no differences between groups in terms of students’ marital status (single or married/cohabitating), work status (not employed, part-time, or full-time), college enrollment status (part-time or full-time), residence status (live with parents or dorm/rent), and class standing (freshman, sophomore, junior, senior, and postbaccalaureate).

Analyses of Obesity-Related Dietary Variables by Sociodemographic Variables

The results of the t-test analysis and ANOVA conducted on dietary variables by gender, age group, generational status, and income are presented in Table 2.

Table 2.

Mean Differences on Dietary Variables by Gender, Age Group, Generational Status, and Income.

Dietary variables	Demographics	Variable levels			Statistical test
	Gender	Male	Female
Avoid fried food		3.73	4.00		t(149) = 2.09, p = .038
Sub. low-fat		2.57	2.91		t(150) = 2.09, p = .038
Breads/tortillas		3.34	2.94		t(152) = −2.49, p = .008
Beans		3.79	3.39		t(153) = −1.93, p = .055
Daily vegetables		0.70	0.90		t(148) = 1.81, p = .072
Daily fruit juice		0.96	0.50		t(145) = −4.74, p = .001
	Age	18-24	25-35	36+
Meats		3.06	3.11	2.36	F(2, 153) = 3.49, p = .033
Sub. low-fat		2.70	3.00	3.40	F(2, 149) = 3.20, p = .043
Weekly fast-food		3.47	2.79	2.18	F(2, 152) = 2.84, p = .062
Total sugar intake		1.71	1.47	0.10	F(2, 140) = 3.00, p = .053
	Generation	First	Second	Third
Avoid add fat		4.03	3.77	3.28	F(2, 146) = 2.67, p = .073
Daily vegetables		0.73	0.80	1.17	F(2, 145) = 3.57, p = .031
Milk		3.26	3.82	3.48	F(2, 150) = 2.51, p = .085
Meats		2.63	3.10	3.15	F(2, 151) = 4.03, p = .020
	Income (US$)	<25,000	25,000–55,000	55,000+
Daily F/V		2.01	1.97	2.60	F(2,130) = 2.93, p = .057
Daily vegetables		0.71	0.86	1.11	F(2,139) = 4.25, p = .016

Note. Sub. low-fat = substitute for low-fat foods; Avoid add fat = avoid adding fat as a flavoring; Daily F/V = daily total fruits and vegetables.

Gender

The t-test analyses revealed that women were more likely to adhere to a low-fat diet when compared with their male counterparts. Specifically, Latina women reported avoiding fried foods (i.e., beef, chicken, and fish) more frequently than men did and were also more likely to modify meats to be low in fat and substitute for low-fat alternatives (i.e., low-fat milk products, low-fat items at sit-down restaurants). Although the genders did not differ in their total consumption of fruits and vegetables, women reported a greater daily consumption of vegetables compared with men, whereas men had a higher daily consumption of fruit juice. Finally, college men consumed more beans and refined grains/flours in the form of breads and tortillas than women did.

Age groups

The ANOVA results indicated that older college students (36 years and above) were more likely to choose low-fat alternatives than younger-aged students (18- to 24-year-olds) were. Conversely, younger-aged students reported more frequent consumption of meats and fast foods than their older counterparts (35 years and above) did. Finally, younger college students (18-24 and 25-35 years) also had a higher total daily consumption of sugars compared with older-aged students; more specifically, this came in the form of daily intake of liquid sugar (i.e., sodas, sugar-sweetened beverages, and coffee drinks).

Income

College students with household incomes of US$25,000 or less reported a lower daily consumption of fruits and vegetables compared with those earning US$55,001 or greater. More explicitly, household incomes of US$55,001 or greater consumed more vegetables daily than did household with earnings of US$25,000 or less.

Generational status

Immigrant college students were more likely to avoid adding fat as a flavoring (butter to bread and potatoes) when compared with third-generation-plus Latino students. Although no differences were found in terms of total daily intake of fruits and vegetables, immigrant and second-generation Latinos reported a lower consumption of vegetables than third-generation Latinos did. Finally, immigrant students reported a less frequent consumption of milk, as well as meats, when compared with the later generations.

Analyses of Obesity-Related Dietary Patterns by College Student Profile

Presented in Table 3 are the findings of the t-test analysis and ANOVA conducted on dietary variables by marital status, enrollment status, work status, residence status, and class standing.

Table 3.

Mean Differences on Dietary Variables by Marital Status, College Enrollment, Work Status, and Class Ranking.

Dietary variables	Demographics	Variable levels					Statistical test
	Marital status	Single		Married/cohabitating
Low-fat diet		3.41		3.75			t(139) = −2.37, p = .019
Modify meats		3.45		3.99			t(150) = −1.83, p = .069
Sub. low-fat		2.68		3.36			t(147) = −3.18, p = .012
Total sugar intake		1.70		1.21			t(138) = 2.12, p = .036
Daily liquid sugar		0.98		0.06			t(140) = 2.26, p = .025
Weekly fast-food		3.42		2.57			t(150) = 1.82, p = .071
	Enrolled status	PT		FT
Avoid fried foods		4.24		3.88			t(149) = 1.68, p = .095
	Work status	No		PT		FT
Daily F/V		2.45		2.05		1.81	F(2, 133) = 2.35, p = .099
Breads/tortillas		2.76		3.23		3.17	F(2, 144) = 3.51, p = .033
	Class ranking	FM	SP	JN	SN	PB
Sub. low-fat		2.45	2.78	2.76	2.95	3.50	F(4, 147) = 2.24, p = .067

Note. PT = part-time; FT = full-time; Daily F/V = total daily fruits and vegetables; FM = freshman; SP = sophomore; JN = junior; SN = senior; PB = postbaccalaureate.

Marital status

The t-test results revealed that married/cohabitating college students were more likely to follow a low-fat diet, modify meats to be low in fat, and choose low-fat substitutes when compared with single college students. Conversely, students who were single reported a higher daily consumption of total sugars; more specifically, single students drank more liquid sugar (i.e., sodas and high-caloric sweetened beverages) and consumed more fast food on a weekly basis than married/cohabitating students did.

Enrollment status and work status

Results of the t-test analyses showed that students who attended college part-time were more likely to avoid fried foods than students enrolled full-time. Furthermore, ANOVA results indicated that students who worked full-time reported a lower daily consumption of fruits and vegetables compared with students who were working part-time or not employed. Likewise, students who worked while in college (full-time and part-time) reported a more frequent consumption of breads and tortillas (refined grains/flours) than students who were not employed.

College class ranking and residence status

College freshmen were less likely to substitute for low-fat alternatives when compared with senior and postbaccalaureate students. Likewise, juniors were less likely to substitute for low-fat alternatives when compared with postbaccalaureate students. Finally, no differences were observed on the obesity-related variables between students who lived with parents, on-campus, or off-campus.

Correlations of BMI Scores, WS, and DRS With Dietary Habits

Pearson moment bivariate correlations were performed between participants’ BMI score, WS, and DRS with the dietary total scale scores, subscale scores, and individual items. The results showed that frequent consumption of meats–BMI, r(155) = .146, p = .069; WS, r(156) = .153, p = .057; DRS, r(151) = .223, p < .007–and specifically chicken–BMI, r(155) = .217, p < .008; WS, r(156) = .206, p < .02; DRS, r(151) = .267, p < .002–was associated with having a higher BMI score, WS, and DRS among Latino college students. Likewise, a high consumption of breads and tortillas–BMI, r(153) = .232, p < .005; WS, r(154) = .249, p < .003; DRS, r(149) = .181, p < .03–and fried (not avoided) potatoes–BMI, r(153) = −.204, p < .02; WS, r(154) = −.267, p < .002; DRS, r(149) = −.280, p < .002–was related to having poorer health. Furthermore, avoiding fried foods in general, r(151) = −.146, p = .073, was associated with having a lower WS. Interestingly, the consumption of beans correlated positively with BMI scores, r(154) = .144, p = .074, and WS, r(155) = .162, p < .05; however, we note that the consumption of beans correlated negatively with avoiding cooking beans in oil/lard, r(154) = −.279, p < .001, and when participants did avoid fried beans, it was related to having a lower WS, r(155) = −.150, p = .063. Likewise, consuming fruits mixed with other foods (cereal or yogurt) was associated with having a higher BMI, r(152) = .226, p < .006, and WS, r(153) = .184, p < .03; however, fruit eaten in this manner was also positively associated with a higher daily consumption of high-fat, sugary junk foods, r(150) = .238, p < .004, and total sugars overall among participants, r(142) = .169, p < .05, which may explain this seemingly incongruent association.

Pertaining solely to DRS, we found that adhering to a low-fat diet, r(139) = −.150, p = .078, and avoiding adding fat as a flavoring, r(147) = −.284, p < .001, were associated with having a lower risk score for future diabetes onset. Furthermore, daily consumption of 100% juice, r(142) = −.150, p = .075, and eating fresh fruit as a snack in between meals or after dinner, r(151) = −.246, p < .003, were also associated with a lower DRS. Finally, a higher DRS was positively associated with more frequent fast-food consumption, r(150) = .191, p < .02 (as reported in Hurtado-Ortiz et al., 2011). We note that the consumption of fruits in either juice or solid form was not associated with a greater consumption of sugar intake (total daily sugars: p > .05) in participants, as was fruits mixed with other foods. This points to the importance of eating fruits by themselves and not added as a condiment to other foods, as well as consuming 100% fruit juices with no added sugars to obtain a health benefit.

Correlations Between Consuming Meats, a Low-Fat Diet, and Fast Foods With Other Dietary Habits

Frequent consumption of meats was positively associated with eating more breads/tortillas, r(154) = .214, p < .009; drinking milk, r(155) = .145, p = .072; a higher daily intake of total sugars, r(143) = .268, p < .002; and weekly fast-food consumption, r(155) = .286, p < .001. Conversely, frequent eating of meats was negatively associated with adhering to low-fat diet, r(143) = −.316, p < .001.

Adherence to a low-fat habit diet was positively associated with a higher daily intake of fruits and vegetables, r(131) = .275, p < .002; less frequent consumption of breads/tortillas, r(143) = −.291, p < .001; less fast foods, r(142) = −.435, p < .001; less total sugars, r(131) = −.357, p < .001, in solid junk foods, r(139) = −.257, p < .003, and liquid sugar-sweetened beverages, r(133) = −.296, p < .002.

Finally, weekly fast-food consumption correlated negatively with all four subscales of the Fat Habit Questionnaire: Avoiding Fried Foods such as fried chicken, beef, fish, potatoes, tortillas, and beans, r(150) = −.391, p < .01; Modifying Meats to Be Low in Fat, r(154) = −.192, p < .02; Avoiding Fat as a Flavoring, r(150) = −.284, p < .001; Substituting for Low-Fat Alternatives, r(151) = −.254, p < .003; and Eating Fruits as a snack in between meals or after dinner, r(155) = −.230, p < .005. Conversely, frequent fast-food consumption was positively associated with a higher total daily intake of sugars, r(143) = .454, p < .001, in both liquid form such as sodas and other sugar-sweetened beverages, r(145) = .382, p < .001, and solid junk foods such as cookies, chocolate bars, doughnuts, ice cream, or frozen desserts, r(151) = .331, p < .001.

Discussion

This study is the first to simultaneously examine the influences of sociocultural and university-related factors on eating behaviors, dietary patterns, and health status indicators of Latino college students who are at a heightened risk for future diabetes onset. The general picture to emerge from this study is that counter to all dietary recommendations (ACHA, 2011), Latino college students in our sample follow an unhealthy diet comprised of few fruits and vegetables, excessive fast-food consumption, as well as a high ingestion of sugar-sweetened beverages, high-sugar fatty junk foods, refined flours (such as breads/tortillas), and meats. These findings mirror those reported in other studies of university students (Adams & Colner, 2008; J. P. Block, Gillman, Linakis, & Goldman, 2013; Byrd-Bredbenner et al., 2012; Cohen, Sturm, Scott, Farley, & Bluthenthal, 2010; Evans et al., 2000; D. Hu et al., 2011; Larson et al., 2008). The above-mentioned dietary behaviors are generally linked to excess weight gain and increased risk for diabetes in young adults and college students (Heidal et al., 2012; Huffman & West, 2007; O’Leary et al., 2012; Racette et al., 2005).

More specifically, in reference to students’ health status, we found that a large percentage (57.7%) of Latinos in our study were indeed overweight and/or obese, exceeding the numbers observed in national studies of U.S. Latino adults and university samples (ACHA, 2011; Huang et al., 2003; Lowry et al., 2002; Lowry et al., 2000; T. F. Nelson et al., 2007). Furthermore, we note that Latina participants were at a greater risk for developing diabetes than Latino males, as indicated by their higher DRS (as reported previously by Hurtado-Ortiz et al., 2011), being the only within-group difference observed in regard to the three health indicators (BMI, WS, and DRS). Unlike prior research based on predominately White university students, we did not find an unhealthy status (BMI scores and WS) to be greater among Latino students who were older, male, of a lower income, single, and living off-campus (but not with parents), suggesting that our sample was relatively homogeneous across sociodemographic and college characteristics (Braithwaite et al., 2010; Brunt et al., 2008; T. F. Nelson et al., 2007). In sum, the findings generally pointed to a poor health status (as indicated by BMI scores and DRS) among Latino college students, regardless of their sociodemographic profile or college-related factors.

Previous researchers have attempted to identity which specific foods or eating behaviors contribute to a poor health status among college students (Brunt et al., 2008; Poddar et al., 2009). Our findings suggest that a diet that included a high intake of meats (especially poultry), or a regular consumption of fried potatoes and fried beans, as well as breads and tortillas, was linked to having a poorer health status—based on BMI scores, WS, and DRS—among Latino college students. Moreover, a diet generally high in fat, as well as frequent fast-food consumption (Hurtado-Ortiz et al., 2011), contributed to an increased risk for diabetes among sample participants, a result consistent with findings on food habits in other studies associated with obesity (Brunt et al., 2008; Knight et al., 2014; Poddar et al., 2009). Conversely, students who generally adhered to a low-fat diet that included fruits, specifically 100% fruit juice and fruits as snacks (between meals and after dinner), were at a lower risk for developing diabetes. This finding underscores the importance for students at risk for developing diabetes to increase their daily intake of fresh fruits while lowering their overall consumption of fatty foods (Carter, Gray, Troughton, Khunti, & Davies, 2010), as well as breads/tortillas made with refined flours which have a low nutritional value.

In addition, within-group differences based on Latino students’ sociodemographic characteristics were analyzed in regard to their dietary choices. Consistent with prior research, we found that women were more likely to adhere to a low-fat diet and consume more vegetables than men were (Boek et al., 2012; Hurtado et al., 2011), yet Latino males’ daily intake of fruit juice was higher. Furthermore, similar to studies of White students, we found that younger-aged Latino college students exhibited poorer dietary behaviors in regard to drinking more high-caloric, sugar-sweetened beverages and were less likely to include low-fat alternatives in their diet compared with older-aged Latino students (CDC, 2014a; Wang, Bleich, & Gortmaker, 2008). Likewise, as reported in another study with Latino students (Knight et al., 2014), we also found that lower income students consumed less fruits and vegetables, a difference we believe can be attributed in part to the higher cost of such foods (i.e., salad and fruit bars) when sold on college campuses. Finally, generational status in the United States was also an important factor influencing dietary choices in students, with immigrant Latinos being less likely to add fat such as butter to foods for flavor and report a lower consumption of milk and meats in their diet when compared with later generations. These findings are similar to other studies that also reported generational differences among Mexican Americans (Hurtado-Ortiz et al., 2011; Neuhouser, Thompson, Coronado, & Solomon, 2004).

Similarly, examination of within-group variations based on participants’ college profile also revealed important group differences in terms of healthy and unhealthy eating behaviors among Latinos. Students who were single, when compared with married/cohabitating Latinos, were less likely to follow a low-fat diet by modifying meats to be less fatty or choosing low-fat alternatives as part of their diet. This finding is consistent with previous research indicating that married persons tend to consume more nutritious meals (Braithwaite et al., 2010; Koball, Moiduddin, Henderson, Goesling, & Besculides, 2010). Upperclassmen were also found to be more likely to choose low-fat alternatives when making dietary choices than Latino freshmen and juniors were. This finding is similar to earlier research that points to poorer dietary behaviors, such as a higher consumption of junk foods and sugar-sweetened beverages, among lower ranking students (Huffman & West, 2007; Levitsky et al., 2004). A plausible explanation is that upper ranking and married/cohabitating students are more likely older, with greater life-related health experiences and education (i.e., completed a general studies health course), which enabled them to make healthier dietary choices when compared with lower classmen and single students. Furthermore, we found that students who were employed or enrolled in college full-time engaged in poorer dietary behaviors, such as consuming more fried foods, breads, and tortillas, and eating fewer fruits and vegetables, supporting the link reported in the literature between hours worked weekly and less healthy eating among young adults (Escoto, Laska, Larson, Neumark-Sztainer, & Hannan, 2012). It is clear that students who are employed or enrolled in college full-time have less time to prepare nutritious meals; yet, they are constantly surrounded by unhealthy, yet economical “grab and go” fast-food options that are high in fat and sugars (Larson, Perry, Story, & Neumark-Sztainer, 2006; Pelletier & Laska, 2013; Rydell et al., 2008).

Accordingly, the literature indicates that negative obesity-related dietary behaviors tend to cluster together to form poor eating patterns in college students (M. C. Nelson et al., 2008; Reyes-Velázquez & Hoffman, 2011). Unfortunately, frequent fast-food consumption is a common practice among young adults (Heidal et al., 2012; Racette et al., 2005), which was also linked to other unhealthy dietary choices, such as drinking high-caloric sugar-sweetened beverages and eating sugary, fatty snacks and desserts (junk foods) in our student sample. Such foods are typically packaged together as a “combo meal,” with their regular consumption leading to significant long-term weight gain in persons and increased risk for diabetes and other chronic diseases (F. B. Hu & Malik, 2010). Likewise, eating fast foods was also associated with other poor dietary behaviors, such as a higher ingestion of meats, breads, tortillas, fried foods, and added fats for flavor (such as butter), but fewer fruits as a nutritious snack. Indeed, earlier research with community Latino samples and White students also reports that a diet high in fat tends to be associated with eating less fruits and vegetables (Larson et al., 2008; Neuhouser et al., 2004). Hence, Latino students in our study who engaged in one poor eating behavior, such as regularly eating fast foods, were also more likely to be making other unhealthy dietary choices, thereby increasing their overall accumulated risk for becoming obese (Chen, Pegram, Adcock, & Johnson, 2014; Hendricks, Herbold, & Fung, 2004; Jackson et al., 2009).

Arguably, the risky eating patterns observed among Latino college students point to the intersection between American and Latino acculturative forces. For example, the diet of Latino students in our study included frequent consumption of fried beans and fried potatoes, as well as breads and tortillas. Fried potatoes are a very common side dish in most American meals at fast-food establishments and sit-down restaurants, as including fried beans as a side dish is in Latino cooking. Likewise, bread is a common compliment in American meals as tortillas are in Mexican dishes. Indeed, we found that consuming fried beans was associated with eating more tortillas among Latino students, which is said to reflect the “traditional Mexican diet” by Carrera, Gao, and Tucker (2007). Furthermore, other more Americanized dietary habits observed in Latino students, such as adding butter to foods for flavor and consuming few fruits and vegetables, are contrary to the traditional Latino diet (Neuhouser et al., 2004). Unfortunately, the incorporation of more Americanized unhealthy eating behaviors coupled with common, poor Latino dietary practices (i.e., cooking beans in lard/oil and a high consumption of tortillas) explains in part why a large percentage of this student sample was overweight and/or obese (Neuhouser et al., 2004; Perez-Escamilla & Putnik, 2007).

Accordingly, it is apparent that Latino students’ unhealthy diet is only exacerbated by the highly accessible, low-cost fast foods present within and outside the university context relative to healthy food options (Jackson et al., 2009). Hence, it is of paramount importance “that university food services” take a more active role in offering healthier and more affordable “taste satisfying food choices . . . on campus [that] promote healthy eating behaviors” among students (Jackson et al., 2009, para. 30). This is especially relevant in the case of Latino students who tend to report greater levels of psychological distress when compared with White peers in juggling academic demands with work and familial obligations (Rowland, 2008). As noted in a recent qualitative study conducted by LaCaille, Dauner, Krambeer, and Pedersen (2011), college students state that the high cost of healthy foods, coupled with limited nutritious options and meal-time preparation, all contribute to their current unhealthy eating patterns.

Limitations and Conclusions

A limitation of the present study, albeit always a concern with retrospective self-report data, is that participants’ memories of their eating behaviors could have been biased or inaccurate. Second, we note the possibility of a Type I error occurring given the number of statistical analyses performed (t tests, ANOVAs, and bivariate correlations). Furthermore, the findings are based on a single sample of Latino students recruited from one university. Although the study site is designated as a Hispanic-serving, 4-year institution, it is also a commuter campus with limited on-campus apartment housing available, and with most students driving to the university to attend classes and participate in activities. Hence, the results may have differed if sample participants were recruited from a more traditional, larger university site or a smaller institution. This sampling weakness speaks to issues related to external validity and the importance of replicating this work using a multisite design that encompasses a larger cross-section of Latino college students. Notwithstanding this single-sample, single-institution limitation, it is argued that given the scarcity of research on obesity, diabetes, and Latino college students, the results afford an important and relevant contribution to our understanding of health-related life experiences of Latino students from a moderate-sized, Hispanic-serving institution situated in a large metropolitan area in Southern California. Finally, the above sampling concern is further mitigated by the fact that the reported findings were largely in line with former studies of ethnic others as well as Latino college students, which increases our confidence in the validity and generalizability of the results.

To conclude, the typical Latino student in this study consumed a diet detrimental to long-term health and linked to obesity in young adults (Heidal et al., 2012; Huffman & West, 2007; O’Leary et al., 2012; Racette et al., 2005). Likewise, the negative obesity-related dietary behaviors observed in Latino students tended to cluster together to form an overall unhealthy lifestyle eating pattern. These findings are particularly troubling considering that the Latinos in this study were identified as having a familial genetic predisposition for type 2 diabetes, yet approximately 58% were overweight and/or obese, further augmenting their risk for early onset of this disease. Although past research has signaled emerging adulthood as a time marked by “adverse changes in diet . . . and weight” (M. C. Nelson et al., 2008, p. 2205), it is also a critical period for disease prevention where lasting healthy dietary patterns can be learned and established. Hence, in line with goals set forth by Healthy People 2020, Hispanic-serving institutions can play a pivotal role in addressing ethnic health disparities by serving as agents of change during this critical developmental stage through campus health initiatives that promote healthy lifestyle changes among young Latinos, which can lead to long-term positive health outcomes in preventing chronic diseases such as type 2 diabetes (U.S. Department of HHS, Office of Disease Prevention and Health Promotion, 2011).

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the National Institutes of Health, Grant NIH/NIGMS/MBRS S06 GM008156-29S10019 (Mental Models of Diabetes Among At-Risk Latino Students).

Notes

Author Biographies

Silvia J. Santos received her PhD from the University of California, Riverside in social-personality psychology and is a Professor of Psychology at California State University, Dominguez Hills. Her research interests and publications are within the areas of ethnic minority health disparities and disease prevention, immigrant mental health, and ethnic identity and college student adaptation. She is the Principal Investigator of a National Institutes of Health funded grant examining diabetes illness beliefs and health-related attitudes and practices of young Latino adults at high risk for future diabetes onset.

Maria T. Hurtado-Ortiz received her PhD in developmental psychology from the University of California, Riverside and is a Professor of Psychology at California State University, Dominguez Hills. Her areas of research include ethnic health psychology, cultural and developmental influences on adolescents’ college-planning behaviors, and mothers’ child care practices. She is the co-Principal Investigator of a National Institutes of Health funded project concerning Latinos at risk for type 2 diabetes.

Marina Armendariz graduated from California State University, Dominguez Hills, with a Bachelor’s in Psychology. She is currently pursuing a doctoral degree in Biobehavioral Health at The Pennsylvania State University.

Victoria vanTwist is a Master’s level graduate student at California State University, Fullerton, in the Department of Public Health. She is pursuing a concentration in health promotion and disease prevention. Her research interests include obesity and diabetes related eating patterns among college students.

Yessenia Castillo graduated from California State University, Dominguez Hills, with a Bachelor’s in Psychology. She is currently a second year doctoral student in the School of Applied Health and Educational Psychology at Oklahoma State University.

References

Adams

T. B.

Colner

(2008). The association of multiple risk factors with fruit and vegetable intake among a nationwide sample of college students. Journal of American College Health, 56, 455-461. doi:10.3200/JACH.56.44.455-464

American Cancer Society. (1990). Report of the planning advisory council. Atlanta, GA: Author.

American College Health Association. (2011). National College Health Assessment II: Reference group executive summary, fall 2010. Hanover, MD: Author. Retrieved from http://www.acha-ncha.org/docs/ACHA-NCHA-II_ReferenceGroup_ExecutiveSummary_Fall2010.pdf

American Diabetes Association. (n.d.). Type 2 Diabetes Risk Test. Retrieved from http://www.diabetes.org/are-you-at-risk/diabetes-risk-test

American Heart Association. (2014). Frequently asked questions about sugar. Retrieved from http://www.acha-ncha.org/docs/ACHA-NCHA-II_ReferenceGroup_ExecutiveSummary_Fall2010.pdf

American Psychological Association. (2010). Ethical principles of psychologists and code of conduct: Including 2010 amendments. Retrieved from http://www.apa.org/ethics/code/index.aspx

Arcury

T. A.

Skelly

A. H.

Gesier

W. M.

Dougherty

M. C.

(2004). Diabetes meanings among those without diabetes: Explanatory models of immigrant Latinos in rural North Carolina. Social Science & Medicine, 59, 2183-2193. doi:10.1016/j.socscimed.2004.03.024

Bleich

S. N.

Wang

Y. C.

Wang

Gortmaker

S. L.

(2009). Increasing consumption of sugar-sweetened beverages among US adults: 1988-1994 to 1999-2004. The American Journal of Clinical Nutrition, 89, 1-10. doi:10.3945/ajcn.2008.26883

Block

Gillespie

Rosenbaum

E. H.

Jenson

(2000). A rapid food screener to assess fat and fruit and vegetable intake. American Journal of Preventive Medicine, 18, 284-288. doi:10.1016/S0749-3797(00)00119-7

10.

Block

J. P.

Gillman

M. W.

Linakis

S. K.

Goldman

R. E.

(2013). “If it tastes good, I’m drinking it”: Qualitative study of beverage consumption among college students. Journal of Adolescent Health, 52, 702-706. doi:10.1016/j.jadohealth.2012.11.017

11.

Boek

Bianco-Simeral

Chan

Goto

(2012). Gender and race are significant determinants of students’ food choices on a college campus. Journal of Nutrition Education and Behavior, 44, 372-378. doi:10.1016/j.jneb.2011.12.007

12.

Braithwaite

S. R.

Delevi

Fincham

F. D.

(2010). Romantic relationships and the physical and mental health of college students. Personal Relationships, 17, 1-12. doi:10.1111/j.1475-6811.2010.01248.x

13.

Brunt

A. R.

Rhee

Y. S.

(2008). Obesity and lifestyle in U.S. college students related to living arrangements. Appetite, 51, 615-621. doi:10.1016/j.appet.2008.04.019

14.

Brunt

A. R.

Rhee

Y. S.

Zhong

(2008). Differences in dietary patterns among college students according to body mass index. Journal of American College Health, 56, 629-634. doi:10.3200/JACH.56.6.629-634

15.

Byrd-Bredbenner

Johnson

Quick

V. M.

Walsh

Greene

G. W.

Hoerr

Horacek

T. M.

(2012). Sweet and salty: An assessment of the snacks and beverages sold in vending machines on US post-secondary institution campuses. Appetite, 58, 1143-1151. doi:10.1016/j.appet.2012.02.055

16.

California Health Interview Survey. (2006). CHIS Adolescent Questionnaire, 2005. Los Angeles, CA: UCLA Center for Health Policy Research, Regents of the University of California.

17.

Carrera

P. M.

Gao

Tucker

K. L.

(2007). A study of dietary patterns in the Mexican-American population and their association with obesity. Journal of the American Dietetic Association, 107, 1735-1742. doi:10.1016/j.jada.2007.07.016

18.

Carter

Gray

L. J.

Troughton

Khunti

Davies

M. J.

(2010). Fruit and vegetable intake and incidence of type 2 diabetes mellitus: A systematic review and meta-analysis. British Medical Journal, 341, 543-548. doi:10.1136/bmj.c4229

19.

Centers for Disease Control and Prevention. (2011). National diabetes fact sheet: National estimates and general information on diabetes and prediabetes in the United States, 2011. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention. Retrieved from http://www.cdc.gov/diabetes/pubs/pdf/ndfs_2011.pdf

20.

Centers for Disease Control and Prevention. (2014a). The CDC guide to strategies to increase the consumption of fruits and vegetables. Atlanta, GA: U.S. Department of Health and Human Services. Retrieved from http://www.cdc.gov/nutrition/strategies-guidelines/index.html

21.

Centers for Disease Control and Prevention. (2014b). National diabetes statistics report: Estimates of diabetes and its burden in the United States, 2014. Atlanta, GA: U.S. Department of Health and Human Services. Retrieved from http://www.cdc.gov/diabetes/data/statistics/2014StatisticsReport.html

22.

Chen

J. J.

Pegram

L. I.

Adcock

K. R.

Johnson

M. R.

(2014). Assessing risk factors for chronic diseases and dietary behaviors of college students in Southeast Texas. American Journal of Nutrition and Food Science, 1(3), 64-71.

23.

Cohen

D. A.

Sturm

Scott

Farley

T. A.

Bluthenthal

(2010). Not enough fruit and vegetables or too many cookies, candies, salty snacks, and soft drinks? Public Health Reports, 125, 88-95.

24.

DeBate

R. D.

Topping

Sargent

R. G.

(2000). Racial and gender differences in weight status and dietary practices among college students. Adolescence, 36, 819-833.

25.

Eaton

D. K.

Kann

Kinchen

Shanklin

Ross

Hawkn

. . . Lim

(2010). Youth risk behavior surveillance—United States, 2009. Morbidity & Mortality Weekly Report: Surveillance Summaries, 59(5), 1-142.

26.

Escoto

K. H.

Laska

M. N.

Larson

Neumark-Sztainer

Hannan

P. J.

(2012). Work hours and perceived time barriers to healthful eating among young adults. American Journal of Health Behavior, 36, 786-796. doi:10.5993/AJHB.36.6.6

27.

Evans

A. E.

Sawyer-Morse

M. K.

Betsinger

(2000). Fruit and vegetable consumption among Mexican-American college students. Journal of the American Dietetic Association, 100, 11, 1399-1402. doi:10.1016/S0002-8223(00)00388-6

28.

Ferrara

C. M.

(2009). The college experience: Physical activity, nutrition, and implications for intervention and future research. Journal of Exercise Physiology, 12(1), 23-35. Retrieved from http://connection.ebscohost.com/c/articles/36932452/college-experience-physical-activity-nutrition-implications-intervention-future-research

29.

Flegal

K. M.

Carroll

M. D.

Kit

B. K.

Ogden

C. L.

(2012). Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999-2010. Journal of the American Medical Association, 307, 491-497. doi:10.1001/jama.2012.39

30.

Freedman

M. R.

(2010). Gender, residence and ethnicity affect freshman BMI and dietary habits. American Journal of Health Behavior, 34, 513-524. doi:10.5993/AJHB.34.5.1

31.

Fry

Lopez

M. H.

(2012). Hispanic student enrollments reach new highs in 2011. Washington, DC: Pew Hispanic Center. Retrieved from http://www.pewhispanic.org/2012/08/20/ii-hispanic-public-school-enrollments/

32.

Garcia

Gold

E. B.

Wang

Yang

Mao

Schwartz

A. V.

(2012). The relation of acculturation to overweight, obesity, pre-diabetes and diabetes among US Mexican-American women and men. Ethnicity & Disease, 22(1), 58-64.

33.

Gropper

S. S.

Simmons

K. P.

Connell

L. J.

Ulrich

P. V.

(2012). Changes in body weight, composition, and shape: A 4-year study of college students. Applied Physiology, Nutrition, & Metabolism, 37, 1118-1123. doi:10.1139/h2012-139

34.

Heidal

K. B.

Colby

S. E.

Mirabella

G. T.

Al-Numair

K. S.

Bertrand

Gross

K. H.

(2012). Cost and calorie analysis of fast food consumption in college students. Food & Nutrition Sciences, 3, 942-946. doi:10.4236/fns.2012.37124

35.

Hendricks

K. M.

Herbold

Fung

(2004). Diet and other lifestyle behaviors in young college women. Nutrition Research, 24, 981-991. doi:10.1016/j.nutres.2004.09.004

36.

Taylor

Blow

Cooper

T. V.

(2011). Multiple health behaviors: Patterns and correlates of diet and exercise in a Hispanic college sample. Eating Behaviors, 12, 296-301. doi:10.1016/j.eatbeh.2011.07.009

37.

F. B.

Malik

V. S.

(2010). Sugar-sweetened beverages and risk of obesity and type 2 diabetes: Epidemiologic evidence. Physiology & Behavior, 100, 47-54. doi:10.1016/j.physbeh.2010.01.036

38.

Huang

T. T. K.

Harris

K. J.

Lee

R. E.

Nazir

Born

Kaur

(2003). Assessing overweight, obesity, diet and physical activity in college students. Journal of American College Health, 52, 83-86. doi:10.1080/07448480309595728

39.

Huffman

West

D. S.

(2007). Readiness to change sugar sweetened beverage intake among college students. Eating Behaviors, 8, 10-14. doi:10.1016/j.eatbeh.2006.04.005

40.

Hurtado-Ortiz

M. T.

Santos

Reynosa

(2011). Health behaviors and health status of at-risk Latino students for diabetes. American Journal of Health Studies, 26, 196-207.

41.

Jackson

R. A.

Berry

T. R.

Kennedy

M. D.

(2009). The relationship between lifestyle and campus eating behaviors in male and female university students. College Student Journal, 43, 860-871.

42.

Knight

M. Y.

Killion

Knight

L. P.

(2014). Nutrition, exercise habits, and perceptions of obesity in Hispanic college students in South Texas: A 10 year follow-up. International Journal of Applied Science & Technology, 4(1), 16-22.

43.

Koball

H. L.

Moiduddin

Henderson

Goesling

Besculides

(2010). What do we know about the link between marriage and health? Journal of Family Issues, 31, 1019-1040. doi:10.1177/0192513X10365834

44.

Kposowa

A. J.

(2013). Mortality from diabetes by Hispanic groups: Evidence from the US National Longitudinal Mortality Study. International Journal of Population Research, 2013, 1-12. doi:10.1155/2013/571306

45.

Kristal

A. R.

Shattuck

A. L.

Patterson

R. E.

(1999). Differences in fat-related dietary patterns between black, Hispanic and white women: Results from the Women’s Health Trial Feasibility Study in minority populations. Public Health Nutrition, 2, 253-262. doi:10.1017/S1368980099000348

46.

LaCaille

L. J.

Dauner

K. N.

Krambeer

R. J.

Pedersen

(2011). Psychosocial and environmental determinants of eating behaviors, physical activity, and weight change among college students: A qualitative analysis. Journal of American College Health, 59, 531-538. doi:10.1080/07448481.2010.523855

47.

Larson

N. I.

Neumark-Sztainer

D. R.

Story

M. T.

Wall

M. M.

Harnack

L. J.

Eisenberg

M. E.

(2008). Fast food intake: Longitudinal trends during the transition to young adulthood and correlates of intake. Journal of Adolescent Health, 43, 79-86. doi:10.1016/j.jadohealth.2007.12.005

48.

Larson

N. I.

Perry

C. L.

Story

Neumark-Sztainer

(2006). Food preparation by young adults is associated with better diet quality. Journal of the American Dietetic Association, 106, 2001-2007. doi:10.1016/j.jada.2006.09.008

49.

Levi

Chan

K. K.

Pence

(2006). Real men do not read labels: The effects of masculinity and involvement on college students’ food decisions. Journal of American College Health, 55, 91-98. doi:10.3200/JACH.55.2.91-98

50.

Levitsky

D. A.

Halbmaier

C. A.

Mrdjenovic

(2004). The freshman weight gain: A model for the study of the epidemic of obesity. International Journal of Obesity, 28, 1435-1442. doi:10.1038/sj.ijo.0802776

51.

Lloyd-Richardson

E. E.

Bailey

Fava

J. L.

Wing

(2009). A prospective study of weight gain during the college freshman and sophomore years. Preventive Medicine, 48, 256-261. doi:10.1016/j.ypmed.2008.12.009

52.

Lowry

Galuska

D. A.

Fulton

J. E.

Wechsler

Kann

(2002). Weight management goals and practices among U.S. high school students: Associations with physical activity, diet, and smoking. Journal of Adolescent Health, 31, 133-144. doi:10.1016/S1054-139X(01)00408-6

53.

Lowry

Galuska

D. A.

Fulton

J. E.

Wechsler

Kann

Collins

J. L.

(2000). Physical activity, food choice, and weight management goals and practices among US college students. American Journal of Preventive Medicine, 18, 18-27. doi:10.1016/S0749-3797(99)00107-5

54.

Mokdad

A. H.

Bowman

B. A.

Ford

E. S.

Vinicor

Marks

J. S.

Koplan

J. P.

(2001). The continuing epidemics of obesity and diabetes in the United States. Journal of the American Medical Association, 286, 1195-1200. doi:10.1001/jama.286.10.1195

55.

Mokdad

A. H.

Marks

J. S.

Stroup

D. F.

Gerberding

J. L.

(2004). Actual causes of death in the United States, 2000. Journal of the American Medical Association, 291, 1238-1245. doi:10.1001/jama.291.10.1238

56.

Mokdad

A. H.

Serdula

M. K.

Dietz

W. H.

Bowman

B. A.

Marks

J. S.

Koplan

J. P.

(1999). The spread of the obesity epidemic in the United States, 1991-1998. Journal of the American Medical Association, 282, 1519-1522. doi:10.1001/jama.292.20.2519

57.

Mooney

K. M.

Walbourn

(2001). When college students reject food: Not just a matter of taste. Appetite, 36, 41-50. doi:10.1006/appe.2000.0384

58.

Morrell

J. S.

Lofgren

I. E.

Burke

J. D.

Reilly

R. A.

(2012). Metabolic syndrome, obesity, and related risk factors among college men and women. Journal of American College Health, 60, 82-89. doi:10.1080/07448481.2011.582208

59.

Nelson

M. C.

Story

Larson

N. I.

Neumark-Sztainer

Lytle

L. A.

(2008). Emerging adulthood and college-aged youth: An overlooked age for weight-related behavior change. Obesity, 16, 2205-2211. doi:10.1038/oby.2008.365

60.

Nelson

T. F.

Gortmaker

S. L.

Subramanian

S. V.

Cheung

Wechsler

(2007). Disparities in overweight and obesity among US college students. American Journal of Health Behavior, 31, 363-373. doi:10.5993/AJHB.31.4.3

61.

Neuhouser

M. L.

Thompson

Coronado

G. D.

Solomon

C. C.

(2004). Higher fat intake and lower fruit and vegetables intakes are associated with greater acculturation among Mexicans living in Washington State. Journal of the American Dietetic Association, 104, 51-57. doi:10.1016/j.jada.2003.10.015

62.

Ogden

C. L.

Carroll

M. D.

Kit

B. K.

Flegal

K. M.

(2014). Prevalence of childhood and adult obesity in the United States, 2011-2012. Journal of the American Medical Association, 311, 806-814. doi:10.1001/jama.2014.732

63.

O’Leary

Hattersley

King

Allman-Farinelli

(2012). Sugary drink consumption behaviors among young adults at university. Nutrition & Dietetics, 69, 119-123. doi:10.1111/j.1747-0080.2012.01583.x

64.

Page

(2013). Hispanics: A diverse population of students to influence the landscape of higher education. Journal of Hispanic Higher Education, 12, 37-48. doi:10.1177/1538192712454133

65.

Patel

S. R.

F. B.

(2008). Short sleep duration and weight gain: A systematic review. Obesity, 16, 643-653. doi:10.1038/oby.2007.118

66.

Pelletier

J. E.

Laska

M. N.

(2013). Campus food and beverage purchases are associated with indicators of diet quality in college students living off campus. American Journal of Health Promotion, 28, 80-87. doi:10.4278/ajhp.120705-QUAN-326

67.

Perez-Escamilla

Putnik

(2007). The role of acculturation in nutrition, lifestyle, and incidence of type 2 diabetes among Latinos. The Journal of Nutrition, 137, 860-870. Retrieved from http://jn.nutrition.org/content/137/4/860.full.pdf+html

68.

Poddar

K. H.

Hosig

K. W.

Nickols-Richardson

S. M.

Anderson

E. S.

Herbert

W. G.

Duncan

S. E.

(2009). Low-fat dairy intake and body weight and composition changes in college students. Journal of the American Dietetic Association, 109, 1433-1438. doi:10.1016/j.jada.2009.05.005

69.

Racette

S. B.

Deusinger

S. S.

Strube

M. J.

Highstein

G. R.

Deusinger

R. H.

(2005). Weight changes, exercise, and dietary patterns during freshman and sophomore years of college. Journal of American College Health, 53, 245-251. doi:10.3200/JACH.53.6.245-251

70.

Reyes-Velázquez

Hoffman

E. W.

(2011). Toward reducing the diabetes pandemic: College students’ perspectives of type 2 diabetes. Diabetes Spectrum, 24, 161-168. doi:10.2337/diaspect.24.3.161

71.

Rowland

A. L.

(2008). The health challenges of urban Latino college students as revealed through student journaling. Journal of Hispanic Higher Education, 7, 131-143. doi:10.1177/1538192707313937

72.

Rydell

S. A.

Harnack

L. J.

Oakes

J. M.

Story

Jeffery

R. W.

French

S. A.

(2008). Why eat at fast-food restaurants: Reported reasons among frequent consumers. Journal of the American Dietetic Association, 108, 2066-2070. doi:10.1016/j.jada.2008.09.008

73.

Serlachius

Hamer

Wardle

(2007). Stress and weight change in university students in the United Kingdom. Physiology & Behavior, 92, 548-553. doi:10.1016/j.physbeh.2007.04.032

74.

Thompson

T. G.

Veneman

A. M.

(2005). Dietary guidelines for Americans, 2005. Washington, DC: U.S. Department of Health and Human Services and U.S. Department of Agriculture.

75.

U.S. Department of Health and Human Services, National Institutes of Health, National Heart, Lung, and Blood Institute. (2004 December). Eating at fast-food restaurants more than twice per week is associated with more weight gain and insulin resistance in otherwise healthy young adults. Retrieved from http://www.nhlbi.nih.gov/news/press-releases/2004/eating-at-fast-food-restaurants-more-than-twice-per-week-is-associated-with-more-weight-gain-and-insulin-resistance-in-otherwise

76.

U.S. Department of Health and Human Services, Office of Disease Prevention and Health Promotion. (2011). Healthy people 2020, Diabetes. Washington, DC. Retrieved from http://www.healthypeople.gov/2020/topicsobjectives2020/overview.aspx?topicid=8

77.

U.S. Department of Health and Human Services, Office of Minority Health. (2015). Diabetes and Hispanic Americans. Retrieved from http://www.minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=63

78.

Vella-Zarb

R. A.

Elgar

F. J.

(2009). The “freshman 5”: A meta-analysis of weight gain in the freshman year of college. Journal of American College Health, 58, 161-166. doi:10.1080/07448480903221392

79.

Wang

Y. C.

Bleich

S. N.

Gortmaker

S. L.

(2008). Increasing caloric contribution from sugar-sweetened beverages and 100% fruit juices among US children and adolescents, 1988–2004. Pediatrics, 121, 1604-1614. doi:10.1542/peds.2007-2834

80.

West

D. S.

Bursac

Quimby

Prewitt

T. E.

Spatz

Nash

Eddings

(2006). Self-reported sugar-sweetened beverage intake among college students. Obesity, 14, 1825-1831. doi:10.1038/oby.2006.210

81.

Winkleby

M. A.

Cubbin

(2004). Changing patterns in health behaviors and risk factors related to chronic diseases, 1990-2000. American Journal of Health Promotion, 19, 19-27. doi:10.4278/0890-1171-19.1.19