Abstract
Background
We sought to determine if perceived barriers, benefits, and modifiable behaviors support or interfere with breakfast consumption in a racially and economically diverse rural high school population.
Methods
The participants were 832 Minnesota adolescents from 16 rural high schools. We used baseline data from a group randomized trial aimed at increasing school breakfast participation through policy and environmental-level school changes. Students completed an online survey asking about demographics, breakfast eating behaviors, and the barriers and benefits of eating as it relates to school performance. Bivariate and multivariate logistic regression, accounting for clustering by school, was performed using SAS. Each scale was modeled independently.
Results
Participants were 9th and 10th grade students, 36% free/reduced price lunch (FRL), 30% non-white and 55% female. Breakfast skippers compared to non-breakfast skippers reported fewer school related benefits and beliefs and more barriers to eating breakfast (p < .01). Adjusted models revealed students reported more positive beliefs (OR= 0.78, 95%CI=0.73-0.83), more benefits (OR=0.95, 95% CI=0.93-0.97) and fewer barriers (OR=0.85, 95%CI=0.82-0.87) and were less likely to skip breakfast.
Conclusions
Future intervention research should focus on alleviating barriers and enhancing education around the school related benefits of eating breakfast.
Keywords: adolescent, school breakfast, barriers, rural
High school students in the United States (US) are frequent breakfast skippers, contributing to suboptimal health and academic outcomes. Nearly 25% of high school students do not eat any breakfast and this has increased over time1. Breakfast skipping behavior varies by student demographic characteristics2-4. Data from the National Health and Nutrition Examination Study (2001-2002) show that breakfast eating prevalence is highest among 2-5 year-olds (95%) dropping to 70% among 12-19 year-olds. Girls are more likely to skip breakfast than boys, reporting that skipping breakfast will allow them to lose weight.5-7
There is growing evidence to suggest that eating breakfast has positive health- and school-related outcomes for children and adolescents. Breakfast consumption is associated with improved cognitive function, attention, and memory,8 improved math testing scores and attendance9, and lower body mass index (BMI).10 Conversely, breakfast skipping is associated with higher BMI11 and poorer nutrient intake.12 There are some known reasons why adolescents skip breakfast. Adolescent girls report that they skip breakfast to control their weight.13,14 Adolescents also report skipping breakfast because they do not feel hungry in the morning or they do not have enough time to eat breakfast.15 Other reasons for breakfast skipping are not well understood, particularly those that are modifiable.
There are several weaknesses in the scientific literature on the causes and consequences of breakfast skipping behavior. First, the strength of the evidence linking weight status to breakfast skipping has been historically weak, predominantly descriptive studies, hence showing correlation but not causation.16 Studies to date linking breakfast consumption with health and academic achievement are weighted towards younger students, with less information available on adolescents in general and more specifically their perception or knowledge of the potential benefits of breakfast consumption and reducing modifiable barriers.17 Finally, the literature is sparse on breakfast consumption patterns and rationale among diverse adolescents from rural areas. These gaps limit the efficacy of current research for rural adolescents and subsequently may reduce the purported benefits of breakfast consumption as research is translated to school policy and practice. Increasing the frequency of breakfast consumption may require a multipronged approach from individual awareness to policy and environmental change.
Therefore, the purpose of this study is to provide baseline analysis, as part of a larger group randomized trial, of the association between adolescent perceived barriers and benefits of eating breakfast and skipping breakfast behavior among a racially and economically diverse rural high school population. A secondary question was if the relationship differed by sex or by weight status of the student. The literature suggests the motivations for skipping breakfast vary between boys and girls, with the expectation that skipping breakfast will result in weight loss. This analysis will provide data on a little known population and geography. Researchers will be able to use the results of this analysis to target messaging in conjunction with school environmental changes to reduce barriers to breakfast consumption.
Methods
Participants
This analysis uses baseline data from the BreakFAST Study, a group randomized trial aimed at increasing school breakfast participation through policy and environmental-level school changes. Sixteen secondary schools in rural Minnesota were recruited to participate. Schools were randomly assigned to intervention or control conditions. All students in the 9th and 10th grade in all 16 schools present on the day of data collection (N = 5767) were asked to complete a brief screening survey. The screening survey asked student to report sex, number of days per week the student eats breakfast, student grade, if he/she is scheduled to be in class when the school day begins, skill in reading and writing English and home access to a phone and the internet. Students were eligible to enroll in the BreakFAST study if they were in 9th or 10th grade, spoke and wrote English well, had access to a phone at home, was typically in school at the beginning of the day and ate breakfast ≤3 days per week (N = 2512).
Of the eligible students, between 50-75 students, depending on school size, were randomly selected from each school and invited to participate in longitudinal data collection. Minority students were oversampled. Parent consent was passive and student assent was obtained at time of measurement. The final consented sample size was 904. The analytic sample for this analysis included 16 schools with 832 students because 70 students did not complete baseline survey and another 2 students did not answer the question that the outcome variable was derived from.
Instrumentation
Enrolled students completed a computer-based survey, had their height and weight measured, and completed 24-hour dietary recall. The school also provided administrative data for each student in the cohort. For this analysis, survey and anthropometric data was used. Of the enrolled students, 92% completed baseline survey.
Student height and weight were measured by trained staff at school according to established protocols, available upon request. Two staff members were present, one to measure, and one to record and verify. Height was measured in centimeters using a portable stadiometer (Infant/Child/Adult wooden ShorrBoard, Weigh and Measure, LLC (formerly Shorr Productions) Olney, Maryland) to the nearest 0.1 cm. Students were asked to remove their shoes and stand erect, head level, with their heels touching the back of the stadiometer. Height was measured twice for every student and in the event that the 2 measures differed by more than .5 centimeters, a third measurement was taken. The 2 measures within 0.5 cm were averaged. Weight was assessed using a portable scale (TBF-300) [Tanita/TBF-300/ Tanita Corporation of America, Inc. in Arlington Heights IL]. Students removed their shoes and anything from their pockets. Students were asked to stand quietly with their arms at their sides. Each weight measurement was taken twice, and in the event that the percent body fat differed by more than 2 percentage points, a third measurement was taken. The 2 measures within 2 percentage points were averaged. BMI percentile was calculated from the height and weight data using the Centers for Disease Control and Prevention Growth Charts18 Students with BMI percentile 85% or higher were classified as overweight or obese.
The student survey was completed online at home or at school in the computer lab. The outcome variable was derived from the question, “During a normal school week, how many days per week do you skip breakfast?” The variable was dichotomized by students who reported skipping breakfast 0-2 days (‘non-breakfast skippers’) per week compared to 3 or more days per week (‘breakfast skippers’).
Three scales were created to represent student beliefs about the benefits of breakfast, barriers to consuming breakfast and likelihood of eating breakfast if the student believed there would be positive outcomes. Reponses for questions were in the form a Likert response, ranging from 1 (most negative category) to 4 (most positive category). Individual variables were reverse coded as necessary. Scales were calculated by summing item responses.
Breakfast beliefs were assessed using 4 questions. Students asked to report how strongly they disagree or agree (Likert scale 1-4) to the following statements: (1) Eating breakfast helps me pay attention in class; (2) I have more energy when I eat breakfast; (3) If I miss breakfast, I feel more tired in the morning; and (4) Eating breakfast helps me control my weight. Cronbach's alpha for the scale was 0.85.
Breakfast barriers were assessed by asking how strongly the student agreed with the following statements: (1) I plan to eat school breakfast most days; (2) I am too busy to eat school breakfast; (3) School breakfast costs too much; (4)Eating breakfast takes too much time; (5) The breakfast food sold at my school tastes bad; (6) It is easy for me to get school breakfast; (7) The bus arrives too late for me to get the school breakfast; (8)I am not comfortable eating in my classroom; (9) I skip breakfast because it might cause me to gain weight; and (10)I skip breakfast because I am not hungry in the morning. Cronbach's alpha for this scale was 0.62.
Students were asked what the likelihood that eating school breakfast would (1) improve math, reading and standardized test scores; (2) getting along better with your peers; (3) reducing your absences and tardiness; (4) improving your memory, attention span and problem-solving ability; (5) getting important nutrients, vitamins and minerals; (6)establishing healthy habits; and (7) maintain or reach a healthy weight. Cronbach's alpha for this scale was 0.91.
School level data were linked by student identification numbers for students who received free or reduced cost lunch (FRL), which was used as a socioeconomic marker. Students reported their race, grade and sex. Weight status and sex were independently assessed as effect modifiers and if not statistically significant (p < .05), were treated as a confounder.
Data Analysis
Bivariate analysis (chi-square tests and 2-sample t tests) and multivariate logistic regression, accounting for clustering by school, was performed. The unadjusted logistic regression models included random effect of school. The test for interaction by sex and by weight was done using unadjusted models. The adjusted logistic regression models included random effect of school and fixed effects of sex, grade, race, FRL, and weight status if the test for interaction was not statistically significant. Each scale was modeled independently. All analysis was performed using Statistical Analysis Software (version 9.3, SAS Institute Inc., Cary, NC). A 2-tailed p-value < .05 was considered statistically significant.
Results
Data were available on 832 students. The participants were 9th and 10th grade students from 16 rural Minnesota schools, 55% female, 36% receiving FRL and racially diverse (30% non-white). Thirty-six percent of the students were classified as overweight or obese. Bivariate analysis revealed no statistical differences in sociodemographic characteristics and breakfast skipping (breakfast <3 days per week). Individual scale items and scales are shown in Table 1. There is a consistent pattern of statistical difference between breakfast skippers and non-breakfast skippers across most individual items. Subsequently, the scales also revealed statistical differences. Breakfast skippers compared to non-breakfast skippers reported fewer school related benefits and beliefs and more barriers to eating breakfast (p < .01, Table 1).
Table 1. Study Sample Description and Bivariate Comparison of Sample Characteristics, Beliefs, Benefits and Barriers With Breakfast Skipping Behavior among Rural Adolescents. The BreakFAST Study. 2013-14.
| Skip breakfast | ||||
|---|---|---|---|---|
|
| ||||
| Overall (N = 832) | 0-2 days (N = 420) | 3 days or more (N = 412) | p value | |
|
| ||||
| SES, N (column %) | ||||
| free/reduced | 302 (36%) | 155 (37%) | 147 (36%) | .73 |
| full priced | 529 (64%) | 265 (63%) | 264 (64%) | |
|
| ||||
| Race, N (column %) | ||||
| white | 558 (70%) | 277 (69%) | 281 (71%) | .60 |
| nonwhite | 236 (30%) | 122 (31%) | 114 (29%) | |
|
| ||||
| Grade, N (column %) | ||||
| 9 | 407 (49%) | 215 (51%) | 192 (47%) | .19 |
| 10 | 425 (51%) | 205 (49%) | 220 (53%) | |
|
| ||||
| Sex, N (column %) | ||||
| female | 458 (55%) | 233 (55%) | 225 (55%) | .80 |
| male | 374 (45%) | 187 (45%) | 187 (45%) | |
|
| ||||
| Weight categories, N (column %) | ||||
| underweight | 22 (3%) | 13 (3%) | 9 (2%) | .10 |
| normal | 508 (62%) | 269 (65%) | 239 (58%) | |
| overweight/obese | 296 (36%) | 135 (32%) | 161 (39%) | |
|
| ||||
| Weight categories, N (column %) | ||||
| underweight/normal | 530 (64%) | 282 (68%) | 248 (61%) | .04 |
| overweight/obese | 296 (36%) | 135 (32%) | 161 (39%) | |
|
| ||||
| breakfast beliefs scale | ||||
| N | 808 | 407 | 401 | <.0001 |
| Mean (SD) | 10.4 (2.5) | 11.1 (2.3) | 9.7 (2.4) | |
| Median | 11 | 11 | 10 | |
| Range | 4 – 16 | 4 – 16 | 4 – 16 | |
|
| ||||
| breakfast barriers scale | ||||
| N | 797 | 400 | 396 | <.0001 |
| Mean (SD) | 19.6 (3.7) | 20.6 (3.5) | 18.6 (3.6) | |
| Median | 20 | 21 | 19 | |
| Range | 9 – 30 | 10 – 30 | 9 – 29 | |
|
| ||||
| breakfast benefits scale | ||||
| N | 801 | 403 | 397 | .0002 |
| Mean (SD) | 19.5 (5.0) | 20.2 (4.8) | 18.9 (5.0) | |
| Median | 20 | 21 | 19 | |
| Range | 7 – 28 | 7 – 28 | 7 – 28 | |
| Belief Scale Items | Overall | Skip breakfast 0-2 days | Skip breakfast 3 days or more | p value | |
|---|---|---|---|---|---|
| Eating breakfast helps me pay attention in class | Strongly Disagree | 46 (5.7%) | 12 (2.9%) | 34 (8.5%) | <.001 |
| Disagree | 254 (31.4%) | 88 (21.6%) | 166 (41.4%) | ||
| Agree | 415 (51.4%) | 238 (58.5%) | 177 (44.1%) | ||
| Strongly agree | 93 (11.5%) | 69 (17.0%) | 24 (6.0%) | ||
| I have more energy when I eat breakfast | Strongly Disagree | 35 (4.3%) | 11 (2.7%) | 24 (6.0%) | <.001 |
| Disagree | 198 (24.5%) | 60 (14.7%) | 138 (34.4%) | ||
| Agree | 451 (55.8%) | 248 (60.9%) | 203 (50.6%) | ||
| Strongly agree | 124 (15.3%) | 88 (21.6%) | 36 (9.0%) | ||
| If I miss breakfast, I feel more tired in the morning | Strongly Disagree | 50 (6.2%) | 20 (4.9%) | 30 (7.5%) | <.001 |
| Disagree | 308 (38.1%) | 111 (27.3%) | 197 (49.1%) | ||
| Agree | 352 (43.6%) | 213 (52.3%) | 139 (34.7%) | ||
| Strongly agree | 98 (12.1%) | 63 (15.5%) | 35 (8.7%) | ||
| Eating breakfast helps me control my weight | Strongly Disagree | 94 (11.6%) | 35 (8.6%) | 59 (14.7%) | 0.001 |
| Disagree | 431 (53.3%) | 205 (50.4%) | 226 (56.4%) | ||
| Agree | 250 (30.9%) | 146 (35.9%) | 104 (25.9%) | ||
| Strongly agree | 33 (4.1%) | 21 (5.2%) | 12 (3.0%) |
| Barriers Scale Items | Overall | Skip breakfast 0-2 days | Skip breakfast 3 days or more | p value | |
|---|---|---|---|---|---|
| I am too busy to eat school breakfast | Strongly Disagree | 100 (12.6%) | 51 (12.8%) | 49 (12.4%) | <.001 |
| Disagree | 338 (42.5%) | 211 (52.8%) | 127 (32.1%) | ||
| Agree | 261 (32.8%) | 112 (28.0%) | 149 (37.6%) | ||
| Strongly agree | 97 (12.2%) | 26 (6.5%) | 71 (17.9%) | ||
| School breakfast costs too much | Strongly Disagree | 156 (19.6%) | 71 (17.8%) | 85 (21.5%) | .208 |
| Disagree | 436 (54.8%) | 234 (58.5%) | 202 (51.0%) | ||
| Agree | 152 (19.1%) | 71 (17.8%) | 81 (20.5%) | ||
| Strongly agree | 52 (6.5%) | 24 (6.0%) | 28 (7.1%) | ||
| Eating school breakfast takes too much time | Strongly Disagree | 101 (12.7%) | 57 (14.3%) | 44 (11.1%) | <.001 |
| Disagree | 381 (47.9%) | 220 (55.0%) | 161 (40.7%) | ||
| Agree | 261 (32.8%) | 107 (26.8%) | 154 (38.9%) | ||
| Strongly agree | 53 (6.7%) | 16 (4.0%) | 37 (9.3%) | ||
| The breakfast food sold at my school tastes bad | Strongly Disagree | 43 (5.4%) | 20 (5.0%) | 23 (5.8%) | .005 |
| Disagree | 353 (44.3%) | 200 (50.0%) | 153 (38.6%) | ||
| Agree | 273 (34.3%) | 130 (32.5%) | 143 (36.1%) | ||
| Strongly agree | 127 (16.0%) | 50 (12.5%) | 77 (19.4%) | ||
| It is easy for me to get school breakfast | Strongly Disagree | 51 (6.4%) | 17 (4.3%) | 34 (8.6%) | .001 |
| Disagree | 187 (23.5%) | 84 (21.0%) | 103 (26.0%) | ||
| Agree | 477 (59.9%) | 246 (61.5%) | 231 (58.3%) | ||
| Strongly agree | 81 (10.2%) | 53 (13.3%) | 28 (7.1%) | ||
| The bus arrives too late for me to get the school breakfast | Strongly Disagree | 192 (24.1%) | 95 (23.8%) | 97 (24.5%) | .009 |
| Disagree | 425 (53.4%) | 233 (58.3%) | 192 (48.5%) | ||
| Agree | 128 (16.1%) | 49 (12.3%) | 79 (19.9%) | ||
| Strongly agree | 51 (6.4%) | 23 (5.8%) | 28 (7.1%) | ||
| I am not comfortable eating in my classroom | Strongly Disagree | 166 (20.9%) | 81 (20.3%) | 85 (21.5%) | .420 |
| Disagree | 420 (52.8%) | 222 (55.5%) | 198 (50.0%) | ||
| Agree | 167 (21.0%) | 76 (19.0%) | 91 (23.0%) | ||
| Strongly agree | 43 (5.4%) | 21 (5.3%) | 22 (5.6%) | ||
| I skip breakfast because it might cause me to gain weight | Strongly Disagree | 264 (33.2%) | 139 (34.8%) | 125 (31.6%) | <.001 |
| Disagree | 409 (51.4%) | 222 (55.5%) | 187 (47.2%) | ||
| Agree | 83 (10.4%) | 27 (6.8%) | 56 (14.1%) | ||
| Strongly agree | 40 (5.0%) | 12 (3.0%) | 28 (7.1%) | ||
| I skip breakfast because I am not hungry in the morning | Strongly Disagree | 89 (11.2%) | 68 (17.0%) | 21 (5.3%) | <.001 |
| Disagree | 262 (32.9%) | 181 (45.3%) | 81 (20.5%) | ||
| Agree | 323 (40.6%) | 124 (31.0%) | 199 (50.3%) | ||
| Strongly agree | 122 (15.3%) | 27 (6.8%) | 95 (24.0%) |
| Benefit Scale Items | Overall | Skip breakfast 0-2 days | Skip breakfast 3 days or more | p value | |
|---|---|---|---|---|---|
| …improving your math, reading and standardized test scores | Very likely | 130 (16.3%) | 73 (18.1%) | 57 (14.4%) | .516 |
| Somewhat likely | 448 (56.0%) | 223 (55.3%) | 225 (56.7%) | ||
| Somewhat unlikely | 147 (18.4%) | 70 (17.4%) | 77 (19.4%) | ||
| Not at all likely | 75 (9.4%) | 37 (9.2%) | 38 (9.6%) | ||
| …getting along better with your peers | Very likely | 125 (15.6%) | 74 (18.4%) | 51 (12.8%) | .001 |
| Somewhat likely | 340 (42.5%) | 188 (46.7%) | 152 (38.3%) | ||
| Somewhat unlikely | 221 (27.6%) | 93 (23.1%) | 128 (32.2%) | ||
| Not at all likely | 114 (14.3%) | 48 (11.9%) | 66 (16.6%) | ||
| …reducing your absences and tardiness | Very likely | 96 (12.0%) | 59 (14.6%) | 37 (9.3%) | .010 |
| Somewhat likely | 231 (28.9%) | 125 (31.0%) | 106 (26.7%) | ||
| Somewhat unlikely | 253 (31.6%) | 125 (31.0%) | 128 (32.2%) | ||
| Not at all likely | 220 (27.5%) | 94 (23.3%) | 126 (31.7%) | ||
| …improving your memory, attention span and problem-solving ability | Very likely | 169 (21.1%) | 98 (24.3%) | 71 (17.9%) | .006 |
| Somewhat likely | 412 (51.5%) | 212 (52.6%) | 200 (50.4%) | ||
| Somewhat unlikely | 139 (17.4%) | 53 (13.2%) | 86 (21.7%) | ||
| Not at all likely | 80 (10.0%) | 40 (9.9%) | 40 (10.1%) | ||
| …getting important nutrients, vitamins and minerals | Very likely | 312 (39.0%) | 168 (41.7%) | 144 (36.3%) | .038 |
| Somewhat likely | 364 (45.5%) | 187 (46.4%) | 177 (44.6%) | ||
| Somewhat unlikely | 76 (9.5%) | 29 (7.2%) | 47 (11.8%) | ||
| Not at all likely | 48 (6.0%) | 19 (4.7%) | 29 (7.3%) | ||
| …maintaining or reaching a healthy weight | Very likely | 194 (24.3%) | 109 (27.0%) | 85 (21.4%) | .001 |
| Somewhat likely | 374 (46.8%) | 198 (49.1%) | 176 (44.3%) | ||
| Somewhat unlikely | 156 (19.5%) | 72 (17.9%) | 84 (21.2%) | ||
| Not at all likely | 76 (9.5%) | 24 (6.0%) | 52 (13.1%) | ||
| …establishing healthy habits | Very likely | 245 (30.6%) | 139 (34.5%) | 106 (26.7%) | .004 |
| Somewhat likely | 369 (46.1%) | 191 (47.4%) | 178 (44.8%) | ||
| Somewhat unlikely | 126 (15.8%) | 50 (12.4%) | 76 (19.1%) | ||
| Not at all likely | 60 (7.5%) | 23 (5.7%) | 37 (9.3%) |
Student sex and weight status were independently assessed as effect modifiers of the relationship between beliefs, barriers and benefits scales and breakfast skipping. Neither sex nor weight status was a statistically significant effect modifier. Therefore, sex and weight status were included as potential confounders in subsequent models.
Beliefs, barriers and benefits scales were each assessed individually (not mutually adjusted). Adjusted models including random effects of school and fixed effects of sex, race, grade, FRL and weight status. The adjusted model revealed students who reported more positive beliefs (OR=0.78, 95%CI=0.73-0.83), more benefits (OR=0.95, 95% CI=0.93-0.97) and less barriers (OR=0.85, 95%CI=0.82-0.87) were less likely to be breakfast skippers (Table 2).
Table 2. Logistic Regression Analysis of the Association between Beliefs, Benefits and Barriers Related to School Breakfast Consumption and Breakfast Skipping Behavior among Rural Adolescents. The BreakFAST Study. 2013-14.
| Unadjusted models* | Adjusted models** | |||
|---|---|---|---|---|
| OR (95% CI) | P value | OR (95% CI) | P value | |
| breakfast beliefs scale | 0.78 (0.74, 0.83) | <.0001 | 0.78 (0.73, 0.83) | <.0001 |
| breakfast barriers scale | 0.86 (0.82, 0.89) | <.0001 | 0.85 (0.82, 0.87) | <.0001 |
| breakfast benefits scale | 0.95 (0.93, 0.97) | <.0001 | 0.95 (0.93, 0.97) | <.0001 |
Unadjusted models include random effect of school.
Adjusted models include random effect of school and fixed effects of sex, race, grade, frl, and weight categories (2 categories).
Discussion
Breakfast consumption patterns, or breakfast skipping, among rural adolescents may in fact have a complex underlying cause. According to the findings from this analysis, rural adolescents who skip breakfast 3 or more days per week report more barriers to eating school breakfast and are less likely to report the potential positive benefits of consuming breakfast on their academic, social and overall health status compared to students who skip breakfast 0-2 times per week.
The barriers to breakfast consumption reported here are consistent with what is observed in the literature to date. Girls skip breakfast as a strategy to lose weight.13 Yet, breakfast skipping is not an effective strategy for losing weight. Meal skipping often results in higher caloric intake later in the day, preventing weight loss and even weight gain. In obese adult breakfast-skippers, simply adding breakfast to their daily routine resulted in lowered dietary fat intake and reduced impulse eating.19 A similar pattern is seen in adolescents. Adolescents who skip breakfast tend to eat more snacks between meals, have lower micronutrient content and consume more alcohol and sucrose compared to those who eat breakfast regularly.20 A second common reason for not eating breakfast supported in our results is that adolescents are not hungry in the morning or do not have enough time to eat breakfast.15 Sleep is a priority for this age group. According to the National Sleep Foundation, adolescents need 8-10 hours per sleep each night, but only 15% report sleeping 8-1/2 hours on school nights.21 Although in a slightly younger age category, experimental evidence showed that less sleep resulted in higher food intake compared to more sleep.22 Rural students also may face longer commute time to school in the morning adding additional time constraints. In our sample, 62% reported getting to school by car. Twenty-three percent agreed that their bus arrives too late to get the school breakfast.
Other perceived barriers to breakfast consumption included cost, food quality and stigma. The School Nutrition Association reported the most common way in which school breakfast programs have been altered to address barriers is to provide grab-n-go breakfast option,23 but it is not yet widely implemented.24 Not all students who qualify for free or reduced cost meals receive them. In the current sample, approximately one-third of the students receive free or reduced cost meals. It is not known how many of the students qualify and do not receive, but data on rural areas show higher rates of poverty and school meal eligibility.25 Normalizing school breakfast by making it a school wide offering helps reduce stigma, particularly in low-income schools.
Reddan, Wahlstrom, and Reicks assessed child (4th-, 5th- and 6th-grade students) perceived benefits and barriers to eating breakfast in schools that offered universal school breakfast compared to schools that did not.15 The pilot intervention was parents and teachers encouraging the children to eat school breakfast and education about the positive effects of eating breakfast. The children in the schools with universal school breakfast reported more positive benefits of eating breakfast, including reporting having more energy and being better able to pay attention in class. These children also reported higher weekly breakfast consumption. We saw a similar pattern in the present study. Adolescents who ate breakfast more frequently reported higher positive beliefs, including paying attention in class and more energy. Although correlational, the evidence appears consistent through middle and high school that those who eat breakfast more frequently report higher benefits of breakfast consumption.
Students in the present study were also asked about the likelihood that eating school breakfast would improve academic skills (eg, test scores, memory), improve social interaction (eg, get along better with peers) and overall health (eg, achieve adequate nutrients, reach a healthy weight). Again, adolescents who ate breakfast more frequently reported a higher likelihood that eating breakfast would have more positive school, social and health outcomes. This is particularly noteworthy given the study sample. One-third of the students participating are low-income, one-third are racial/ethnic minorities and all are from rural communities. Each of these categories (low-income, racial/ethnic minority, rural) is associated with lower academic achievement and poorer health outcomes compared to the dominant population. There is an important opportunity to determine, through experimental studies, whether increasing the co-occurrence of breakfast consumption by way of reducing barriers and increasing knowledge of potential benefits of breakfast consumption will in actuality improve school, social and health outcomes.
Limitations
Surprisingly, there was no interaction by sex or by weight category. It is possible that the use of scales, in particular the barriers scale with a Cronbach's alpha of 0.62, had too much internal variability to detect the expected differences by males and females. Other limitations are that the data are cross-sectional. However, these data represent baseline associations as part of a larger group randomized trial aimed at reducing environmental barriers and increasing student positive perceptions of eating breakfast. Future analysis will help ascertain the validity of our conclusions once the longitudinal and experimental data are available. Finally, breakfast skipping behavior was self-reported and based on a typical week. It is possible that student under or overestimate breakfast consumption patterns, particularly among those who do not routinely eat or not eat breakfast daily. There may also be weekly or seasonal variation. It is not expected that there is any systematic bias in breakfast consumption reporting between school or the treatment arms.
Conclusions
In conclusion, there is a dearth of research on rural adolescents. The results from this paper indicate a need to address barriers and misaligned perceptions of the relationship between school breakfast consumption and school, social and health outcomes. Much of the data to date is observational, as is the current study. A carefully done intervention study is necessary to ascertain if observed associations to date are in fact mutable and achieve the expected school, social and health benefits for students. There is a unique opportunity to address one factor – breakfast consumption – that will simultaneously improve life changes for low-income, racial/ethnic minority and rural adolescents. Access to the School Breakfast Program has been a neglected area of research. The BreakFast study was designed for this purpose specifically and these baseline findings support the need for testing interventions aimed at increasing school breakfast participation.
Implications for School Health
Compelling evidence suggests that breakfast consumption, particularly participation in the school breakfast program, has positive effects on both health and academic achievement. This cross sectional analysis, baseline data of a group randomized trial to increase breakfast participation through policy and environmental change, support the need to address real and perceived barriers to breakfast consumption as well as emphasize benefits to adolescents. It is clear from these results that children who skip breakfast also report that school breakfast is not easy to obtain, their bus arrives late which prohibits breakfast consumption, and school breakfast does not taste good. Contrarily, students who eat breakfast regularly report more positive social, academic and positive health outcomes. These results provide an important opportunity for school to alter actual and perceived factors that limit school breakfast consumption, particularly in student populations at greater risk for health and academic challenges.
Human Subjects Approval Statement
The University of Minnesota Institutional Review Board approved study procedures.
Acknowledgments
This study was funded through grant number R01HL113235 from the National Heart Lung and Blood Institute (PI: Marilyn S. Nanney). We acknowledge the schools participating in this study, University of Minnesota Extension staff, Community Blueprint, and all study staff for their dedication and commitment to this research.
Contributor Information
Mary O. Hearst, Email: mohearst@stkate.edu, Associate Professor, St. Catherine University, Henrietta Schmoll School of Health, 2004 Randolph Ave, St. Paul, MN 55105, Phone: (651) 690-6157.
Amy Shanafelt, Email: shanafel@umn.edu, Project Manager, University of Minnesota, Department of Family Medicine and Community Health, Program in Health Disparities Research, 717 Delaware Ave, Minneapolis, MN 55454, Phone: 612-626-4273.
Qi Wang, Email: wangx890@umn.edu, Statistician, University of Minnesota, Department of Family Medicine and Community Health, 717 Delaware Ave, Minneapolis, MN 55454.
Robert Leduc, Email: robertl@ccbr.umn.edu, Statistician, University of Minnesota, 717 Delaware Ave, Minneapolis, MN 55454.
Marilyn S. Nanney, Email: msnanney@umn.edu, Associate Professor, University of Minnesota, Department of Family Medicine and Community Health, Program in Health Disparities Research, 717 Delaware Ave, Minneapolis, MN 55454.
References
- 1.Siega-Riz AM, Popkin BM, Carson T. Trends in breakfast consumption for children in the United States from 1965-1991. Am J Clin Nutr. 1998;67(4):748S–756S. doi: 10.1093/ajcn/67.4.748S. [DOI] [PubMed] [Google Scholar]
- 2.Rampersaud GC, Pereira MA, Girard BL, Adams J, Metzl JD. Breakfast habits, nutritional status, body weight, and academic performance in children and adolescents. J Am Diet Assoc. 2005;105(5):743–760. doi: 10.1016/j.jada.2005.02.007. quiz 761-742. [DOI] [PubMed] [Google Scholar]
- 3.Delva J, O'Malley PM, Johnston LD. Racial/ethnic and socioeconomic status differences in overweight and health-related behaviors among American students: national trends 1986-2003. J Adolesc Health. 2006;39(4):536–545. doi: 10.1016/j.jadohealth.2006.02.013. [DOI] [PubMed] [Google Scholar]
- 4.O'Dea JA, Caputi P. Association between socioeconomic status, weight, age and gender, and the body image and weight control practices of 6- to 19-year-old children and adolescents. Health Educ Res. 2001;16(5):521–532. doi: 10.1093/her/16.5.521. [DOI] [PubMed] [Google Scholar]
- 5.Zapata LB, Bryant CA, McDermott RJ, Hefelfinger JA. Dietary and physical activity behaviors of middle school youth: the youth physical activity and nutrition survey. J Sch Health. 2008;78(1):9–18. doi: 10.1111/j.1746-1561.2007.00260.x. quiz 65-17. [DOI] [PubMed] [Google Scholar]
- 6.Moore LL, Singer MR, Qureshi MM, Bradlee ML. Dairy intake and anthropometric measures of body fat among children and adolescents in NHANES. J Am Coll Nutr. 2008;27(6):702–710. doi: 10.1080/07315724.2008.10719747. [DOI] [PubMed] [Google Scholar]
- 7.Barton BA, Eldridge AL, Thompson D, et al. The relationship of breakfast and cereal consumption to nutrient intake and body mass index: the National Heart, Lung, and Blood Institute Growth and Health Study. J Am Diet Assoc. 2005;105(9):1383–1389. doi: 10.1016/j.jada.2005.06.003. [DOI] [PubMed] [Google Scholar]
- 8.Wesnes KA, Pincock C, Scholey A. Breakfast is associated with enhanced cognitive function in schoolchildren. An internet based study. Appetite. 2012;59(3):646–649. doi: 10.1016/j.appet.2012.08.008. [DOI] [PubMed] [Google Scholar]
- 9.Murphy JM, Pagano ME, Nachmani J, Sperling P, Kane S, Kleinman RE. The relationship of school breakfast to psychosocial and academic functioning: cross-sectional and longitudinal observations in an inner-city school sample. Arch Pediatr Adolesc Med. 1998;152(9):899–907. doi: 10.1001/archpedi.152.9.899. [DOI] [PubMed] [Google Scholar]
- 10.Fiore H, Travis S, Whalen A, Auinger P, Ryan S. Potentially protective factors associated with healthful body mass index in adolescents with obese and nonobese parents: a secondary data analysis of the third national health and nutrition examination survey, 1988-1994. J Am Diet Assoc. 2006;106(1):55–64. doi: 10.1016/j.jada.2005.09.046. quiz 76-59. [DOI] [PubMed] [Google Scholar]
- 11.Timlin MT, Pereira MA, Story M, Neumark-Sztainer D. Breakfast eating and weight change in a 5-year prospective analysis of adolescents: Project EAT (Eating Among Teens) Pediatrics. 2008;121(3):e638–645. doi: 10.1542/peds.2007-1035. [DOI] [PubMed] [Google Scholar]
- 12.Dubois L, Girard M, Potvin Kent M, Farmer A, Tatone-Tokuda F. Breakfast skipping is associated with differences in meal patterns, macronutrient intakes and overweight among pre-school children. Public Health Nutr. 2009;12(1):19–28. doi: 10.1017/S1368980008001894. [DOI] [PubMed] [Google Scholar]
- 13.Cohen B, Evers S, Manske S, Bercovitz K, Edward HG. Smoking, physical activity and breakfast consumption among secondary school students in a southwestern Ontario community. Can J Public Health. 2003;94(1):41–44. doi: 10.1007/BF03405051. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Zullig K, Ubbes VA, Pyle J, Valois RF. Self-reported weight perceptions, dieting behavior, and breakfast eating among high school adolescents. J Sch Health. 2006;76(3):87–92. doi: 10.1111/j.1746-1561.2006.00074.x. [DOI] [PubMed] [Google Scholar]
- 15.Reddan J, Wahlstrom K, Reicks M. Children's perceived benefits and barriers in relation to eating breakfast in schools with or without Universal School Breakfast. J Nutr Educ Behav. 2002;34(1):47–52. doi: 10.1016/s1499-4046(06)60226-1. [DOI] [PubMed] [Google Scholar]
- 16.Brown AW, Bohan Brown MM, Allison DB. Belief beyond the evidence: using the proposed effect of breakfast on obesity to show 2 practices that distort scientific evidence. Am J Clin Nutr. 2013;98(5):1298–1308. doi: 10.3945/ajcn.113.064410. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Hoyland A, Dye L, Lawton CL. A systematic review of the effect of breakfast on the cognitive performance of children and adolescents. Nutr Res Rev. 2009;22(2):220–243. doi: 10.1017/S0954422409990175. [DOI] [PubMed] [Google Scholar]
- 18.US Centers for Disease Control and Prevention. [January 28, 2008];Growth Charts 2000: United States. 2000 Available at: http://www.cdc.gov/growthcharts.
- 19.Schlundt DG, Hill JO, Sbrocco T, Pope-Cordle J, Sharp T. The role of breakfast in the treatment of obesity: a randomized clinical trial. Am J Clin Nutr. 1992;55(3):645–651. doi: 10.1093/ajcn/55.3.645. [DOI] [PubMed] [Google Scholar]
- 20.Sjoberg A, Hallberg L, Hoglund D, Hoglund D, Hulthen L. Meal pattern, food choice, nutrient intake and lifestyle factors in The Goteborg Adolescence Study. Eur J Clin Nutr. 2003;57(12):1569–78. doi: 10.1038/sj.ejcn.1601726. [DOI] [PubMed] [Google Scholar]
- 21.National Sleep Foundation. [February 18, 2015];Teens and Sleep. 2014 Available at: http://sleepfoundation.org/sleep-topics/teens-and-sleep.
- 22.Hart CN, Carskadon MA, Considine RV, et al. Changes in children's sleep duration on food intake, weight, and leptin. Pediatrics. 2013;132(6):e1473–1480. doi: 10.1542/peds.2013-1274. [DOI] [PubMed] [Google Scholar]
- 23.Rainville A, Carr D. [niovember 30, 2015];National Food Service Management Institute Best Practice Guide for In-Classroom Breakfast. 2008 Available at: http://nfsmi-web01.nfsmi.olemiss.edu/documentlibraryfiles/PDF/20090126024201.pdf.
- 24.Lewi J, Coppess S. School Nutrition Operations Report: The State of School Nutrition 2007. Alexandria, VA: School Nutrition Association; 2007. [Google Scholar]
- 25.Provasnik S, Kewal Ramani A, McLaughlin C, Gilbertson L, Herring W, Xie Q. [November 30, 2015];Status of Education in Rural America. 2007 Available at: http://nces.ed.gov/pubs2007/ruraled/