The Journal of School Nursing2022, Vol. 38(3) 233–240© The Author(s) 2020Article reuse guidelines:sagepub.com/journals-permissionsDOI: 10.1177/1059840520928504journals.sagepub.com/home/jsn
The National School Lunch Program provides nutritious and inexpensive lunches, but low participation and food waste are challenges in many schools. Interventions aim to improve participation in the program, but little is known about how students’ perceptions affect their participation. This study explored how middle school students in a rural state perceive school food service staff, food served, and lunchroom atmosphere. An online survey was administered to middle school students at six schools participating in a larger lunchroom intervention. Mean perception scores were calculated for all measures. Multilevel logistic regression was used to examine the relationship between perceptions and consumption. Overall perceptions of staff, food, and atmosphere were positive, and students classified as school lunch eaters had more positive perceptions in all three areas than noneaters. Interventions to increase participation in school lunch programs and promote consumption of healthy food items should address multiple factors that contribute to school lunch participation.
school-based services, healthy eating, adolescent health, school nurse
Obesity rates for children and adults remain high despite significant resources being used to address this issue (Ogden et al., 2018; Ogden et al., 2017). Programming to instill healthy eating habits early in childhood and adolescence can help to prevent obesity and related disease later in life (Birch et al., 2007; Ebbeling et al., 2002; Rosettie et al., 2018; Ward et al., 2017). There are numerous comorbidities that result from obesity, including both physical and mental health. Additionally, obesity-related health costs in both childhood and adulthood place an enormous financial strain on the health care system (Finkelstein et al., 2014; Williams et al., 2015). Therefore, efforts to prevent obesity starting during childhood and adolescence will help to improve physical and mental health throughout the life span and reduce the related economic burden on the health care system. The impact of obesity and associated issues disproportionally affects certain populations, including children and adolescents living in rural areas, and work should be done to understand factors that contribute to these disparities (Johnson & Johnson, 2015).
While efforts need to be made at all ages from infancy to young adulthood to instill healthy eating habits, the developmental changes that occur in early adolescence may make the middle school students a particularly important group to target. Adolescence is a time of many physical, social, and cognitive developmental changes, all of which can affect eating habits (Alberga et al., 2012). In an analysis of the potential benefits of providing fresh fruit and vegetables and restricting sugar-sweetened beverages in schools at a national scale, researchers estimate that giving all children access to these programs has the potential to decrease cardiometabolic deaths by 3.2% annually (Rosettie et al., 2018). Therefore, working with adolescents to give them access to the tools they need to develop lifelong healthy eating habits can help reduce future risk of obesity and prevent weight gain.
Schools offer a promising venue to change eating habits and deliver obesity-preventing interventions to this population (Story et al., 2006; Wang et al., 2015). Examples of interventions include promotion of the school lunch program, delivering nutrition education to students, and engaging parents in fruit and vegetable promotion efforts (Appleton et al., 2016; Blanchette & Brug, 2005). Interventions that include multiple components targeting reduction of childhood obesity through improving nutrition and physical activity in school settings are the most effective (Khambalia et al., 2012; Verrotti et al., 2014). Meals provided by the school lunch program are designed to be a healthy option that accounts for a third of students’ daily energy needs and thus are a significant contribution to students’ overall diet quality (Fox et al., 2012). Due to the dietary guidelines introduced by the Healthy Hunger-Free Kids (HFFK) Act, school lunches are healthier than ever. One study found that along with improvements in nutritional quality of lunches, plate waste, and importantly, vegetable waste decreased following the implementation of the HFFK Act standards (Schwartz et al., 2015). Beyond the nutritional benefits, school lunch has a positive impact on a student’s ability to learn and succeed in a classroom environment (Belot & James, 2011). A study conducted using data prior to the implementation of the HFFK Act found that increasing participation in the National School Lunch Program was associated with increased educational attainment (Hinrichs, 2010).
Yet, despite the known benefits to eating school lunch, there is still room for improvement in participation rates for the National School Lunch Program. While participation rates for free and reduced-price lunch have either risen or stayed the same, rates for students who pay full price have been decreasing since 2007 (Food Research Action Center, 2015). Additionally, food waste in the school lunch program continues to be an issue. While some studies report improvements in food waste (Schwartz et al., 2015), others show that students may throw away up to 75% of vegetables and 40% of the fruit they are served (Cohen et al., 2012; Cohen et al., 2014). Thus, while the nutritional quality of the food served is improved, students do not fully benefit from these improvements if they are not consuming their lunch.
In order to increase both participation and consumption, it is important to understand students’ perceptions of the lunchroom and the food that is served to them. While food quality and presentation are important, other factors affect students’ consumption behavior as well. A number of factors including staff interactions (Asperin et al., 2010; Kjosen et al., 2015), access to food, the lunchroom organization and atmosphere (Payán et al., 2017), and the time given to eat lunch (Gosliner, 2014) have been identified through both survey research and qualitative studies as being determinants of students’ consumption behavior.
The factors that contribute to school lunch participation and consumption are still not well understood, especially in rural schools. The objective of this study was to better understand the perceptions of the food served during school lunch, the lunchroom atmosphere, and the food service staff using the results of a survey conducted with students at six middle schools in a rural midwestern state. Students were split into two groups based on their reported school lunch consumption behavior, and differences between perceptions of students in the two groups were compared.
We used a cross-sectional study design to evaluate online survey data. Six schools in a midwestern state participated in this study, and all enrolled middle school students were eligible to complete the survey. Schools ranged in the grades that they served, and so for this purpose, we considered students from Grades 5 to 8 to be middle schoolers. This data collection occurred as part of a larger, behavioral economics-based intervention in the lunchroom. Results and details about this project are published elsewhere (N. M. Askelson et al., 2019). All schools in the state were invited to apply, and the final schools invited to participate were selected based on their interest in the project, ability to identify a group of students to participate in the intervention activities, and the food service director’s availability to complete intervention activities. Data reported in this article were collected in fall 2016 and served as the pretest assessment for evaluation of the intervention. The University of Iowa, a midwestern university, approved the institutional review board (IRB) application for this study and deemed it exempt from informed consent documentation, as the survey was anonymous and posed no more than minimal risk to subjects.
The survey was developed to capture students’ perceptions about the lunchroom in three different categories: interaction with food service staff, food, and atmosphere. Questions were based on prior evaluation work in school lunchrooms as well as surveys previously implemented with parent and staff populations (Alcaraz & Cullen, 2014; Castillo & Lofton, 2012; Meier et al., 2017). Several questions from these tools were adapted to be used with a student population. For all perception questions, response options ranged from strongly disagree to strongly agree with no neutral option. Additionally, two questions were developed to measure consumption. The first two consumption questions focused on school lunch, asking whether the student had eaten school lunch in the last week and approximately what percentage of their lunch the student had consumed on the previous day. Two additional questions were included to capture white milk and whole fruit consumption. The milk and fruit consumption questions asked students to report on behavior in a “typical” week regarding drinking white milk and eating whole fruit.
The survey was administered online using the Qualtrics platform and designed to take 3–5 min to complete. A link to the survey was emailed to the food service director at participating schools, who was responsible for ensuring it was disseminated to the student body. Schools were allowed to distribute the survey in the way that made the most sense for their students. Some schools directly emailed the survey link to students, and others used existing class time to allow students to participate in the survey.
Once the survey was closed, raw data were downloaded and cleaned in Excel and exported to SPSS Version 24 for analysis. In all cases, statistics were calculated excluding any missing data. To obtain means, response categories were coded from 1 (strongly disagree) to 4 (strongly agree), with any negatively worded questions reverse coded to ensure that a higher mean indicated a more positive response. Frequencies and descriptive statistics were calculated for all variables. Responses to the question “How much of your school lunch did you eat yesterday?” were dichotomized to create a new variable representing either high or low consumption. Respondents who reported eating 75% or more of their lunch were categorized as school lunch eaters, and those who consumed less than 75% were considered noneaters. To analyze the data, multilevel logistic regression models were employed as the independence assumption of ordinary least squares regression was violated because of the likeness of student responses by school of attendance. Each multilevel logistic regression model tested for significant differences in perceptions of staff, food, and atmosphere between high and low school lunch consumers while controlling for school of attendance. The results from logistic regressions are reported as odds ratios (OR), where an OR greater than 1 is interpreted as an increased odds of the event occurring and an OR less than 1 is a decreased odds of an event occurring.
A total of 1,120 middle school–aged students initiated the survey. Initially, 63 responses were excluded for failing to identify their school, and another 68 responses were excluded due to the respondent’s failure to answer a question beyond identifying what school they attended. This left a final sample size of 989 students and an overall, crude response rate of 29.7%. Table 1 outlines key characteristics of the schools that were surveyed as well as individual schools’ completion rates.
The majority of respondents, 85.7% (n = 828) had eaten school lunch at least once in the prior week. When asked about their lunch consumption the previous day, 15.8% (n = 132) had eaten all their lunch, 47.3% (n = 394) had eaten 75% of their lunch, 23.3% (n = 194) ate half, 12.7% (n = 106) ate 25%, and 0.8% (n = 7) reported eating none of their lunch.
Generally, perceptions of staff, food, and atmosphere were more positive than negative, with the lowest mean score being 2.48 (standard deviation [SD] = 1.12) for the question “Staff offer suggestions to me when going through the line.” Of all the staff perception questions, the ones that had the highest means were ones that were related to students’ general interactions with staff, which were unrelated to food. These questions asked whether the staff is friendly (3.43; SD = 0.74) and whether the staff care about kids in school (3.26; SD = 0.85). Questions that asked specifically about interactions with staff as students go through the lunch line were slightly lower and had more variation. The mean response for being able to offer suggestions to staff was 2.50 (SD = 0.96), the mean for staff offering suggestions to students was 2.48 (SD = 1.12), and the mean for perceptions of staff speaking to students as they went through the line was 2.69 (SD = 1.06).
Students reported liking school food (2.64; SD = 0.97) and that the food usually tastes good (2.65; SD = 0.97). They also had positive perceptions of the atmosphere of the lunchroom and generally agreed that the school lunchroom is fun to hang out in (3.09; SD = 0.95) and that the lunchroom is clean (3.20; SD = 0.85). Table 2 lists survey questions along with the mean, SD, and OR of being a high consumer.
Of the sample of 989 students, 307 were classified as noneaters, 526 were classified as school lunch eaters, and 156 students did not respond to this question and were excluded from further analysis. This left a final sample size of 833 students. For all questions, means for students who were school lunch eaters (75% or more) in the previous day were more positive than those for students who were noneaters. For 14 of the 17 variables (82.4%), these differences were statistically significant at the α = .05 level.
The results of the multilevel logistic regressions highlight that there are significant differences in perceptions of school lunch between school lunch eaters compared to noneaters when controlling for school of attendance (Table 1.) School lunch eaters had more positive perceptions of the lunchroom staff than noneaters. They were more likely to report feeling that school lunch staff care about the students at their school (OR = 1.61, p < .001) and report speaking to school lunchroom staff more frequently (OR = 1.17, p = .030).
Additionally, students who were identified as school lunch eaters were more likely to agree that they liked the food being served for lunch compared to noneaters (OR = 2.41, p < .001). There were also differences in the perception of the variety of food served. School lunch eaters were more likely (OR = 2.07, p < .001) to agree that there was a good variety of food served. Students who were school lunch eaters had a lower odds (OR = 0.79, p < .001) of agreeing that the lunchroom runs out of popular food before everyone was served.
Finally, perceptions of lunchroom atmosphere also revealed differences between the two groups. School lunch eaters were more likely to report having enough time to eat lunch after they purchased it (OR = 1.50, p < .001) and were more likely to know what was being offered for lunch before entering the lunchroom (OR = 1.37, p < .001).
School lunch is a healthy and easy option for middle school students and their parents, but a full understanding of how to encourage students to participate is still lacking. With evidence showing that students who eat school lunch have a better overall diet quality and consume less empty calories than students who bought lunch from home (Au et al., 2016), continuing to examine what can be done to improve school lunch participation and consumption is vital. Results of this survey suggest that student perceptions of lunchroom staff, the food served, and the lunchroom atmosphere are all important components of the school lunch experience. Students who reported eating more of their lunch also reported having more positive perceptions in each of these three areas, which suggests that these might be important targets for future intervention.
School lunch eaters also reported having positive interactions with and perceptions of the staff in their lunchroom. School nutrition staff have unique opportunities to interact with students and encourage them to make healthy choices. However, there are structural, logistical, and other barriers that hinder school nutrition staff from being used most effectively in health promotion activities (Cho & Nadow, 2004). These challenges may be even more relevant in rural schools due to their unique characteristics (N. Askelson et al., 2015). Similarly, many lunchroom interventions do not explicitly focus on food service staff either, despite the fact that they play such a crucial role in school lunch participation and consumption. Based on these results, intervention activities for staff could aim to encourage positive communication with their students both generally and around healthy eating as a strategy to increase school lunch participation and consumption.
The second area that should be explored is the food itself. While school lunch food is nutritious, often more so than food brought from home (Au et al, 2016), there is still room for improvement. School lunch eaters were more likely to agree that there was a good variety of food and that the food looked appealing to them. This suggests that in addition to serving healthy and good-tasting food, presentation and variation in the food served are important and should be addressed in interventions. Multiple aspects of food service need to be addressed, and while it is important for students to have access to healthy food choices (Blanchette & Brug, 2005), if the quality, variety, and appearance are substandard, students will be unlikely to eat these foods.
Finally, addressing the lunchroom atmosphere is necessary as well. Making the lunchroom a fun place for students to interact that also facilitates eating school lunch should be a priority for schools looking to improve school lunch participation and consumption. School lunch eaters were more likely to report that the lunchroom was a fun place to hang out with their peers and that they had enough time to eat their lunch after purchasing it. Any changes made to the lunchroom should ensure that the lunchroom atmosphere improves in a way that supports healthy eating. For example, previous studies have shown that incorporating artwork and signage highlighting healthy food choices as part of a multicomponent intervention is one strategy to improve the atmosphere in order to promote healthy eating (N. M. Askelson et al., 2019; Quinn et al., 2018). Properly arranging the lunchroom and using signs and postings to improve the flow of traffic through the lunch line is another strategy to reduce time spent waiting for food, giving students more time to eat.
This study offered new insights into the combination of factors that are important to address when designing interventions to improve school lunch consumption. However, it is important to note a few limitations. In the first place, the measure for school lunch consumption was self-reported and not adapted from a validated measure. Second, no demographic data were collected from participants, so we are unable to assess potential confounders like age, gender, or grade level. Finally, these data are cross-sectional and therefore do not allow for conclusions to be made about the direction of the relationship between consumption and perceptions. For example, noneaters may have less contact with lunch staff and therefore have less positive perceptions of them or they may have had negative interactions with them and, as a result, avoid school lunch. Despite these limitations, this study adds to the growing body of literature on factors affecting school lunch participation and lays the groundwork for future research and intervention work with this population.
Our results highlight the importance of understanding student perceptions of lunchroom staff, food, and atmosphere. School staff, including nurses, play a crucial role in encouraging school lunch participation and consumption. Evidencebased interventions already exist that schools could implement; however, these interventions should be chosen to fit schools’ individual needs. For example, implementing an intervention focused on improving student–staff communication may not be effective if students actually perceive the lunchroom atmosphere, not the staff, to be a barrier to lunch participation. Therefore, schools should continually utilize feedback mechanisms to understand students’ perceptions. Prior to choosing interventions or making changes to the lunchroom, schools should gather information on their students’ perceptions to best understand what areas to target. While a survey was utilized in this study, schools could also engage in more informal feedback mechanisms with their students. This could include focus groups, a student-led group, or meal advisory council working with food service staff, or shorter paper or online surveys.
With school nurses’ strong relationships with both children and teachers, they could be instrumental in helping to collect this kind of information. Nurses could run focus groups or help students to form these kinds of advisory councils. Additionally, in qualitative studies with school nurses, researchers found that nurses perceive their role to be to help educate students and support healthy lifestyles (Hoekstra et al., 2016) and are eager and willing to support nutrition programming (Muckian et al., 2017). Schools should look to nurses as experts and utilize their skills to help plan and implement interventions focusing on healthy eating.
Ultimately, there is no one key strategy that can be implemented to increase school lunch participation and consumption. Instead, multicomponent interventions that target key areas such as staff interaction, food quality and variety, and lunchroom atmosphere are more likely to be successful in increasing school lunch participation and consumption. For example, making menu changes to improve the variety of food served may not be significantly impactful on its own. However, when combined with other strategies, including improving communication between food service staff and students and reorganizing the lunchroom to improve the layout, these changes could help to improve both participation and consumption.
Overall, this study identified important factors for rural students that contribute to participation and consumption of school lunch. Many current interventions in the lunchroom are untested with rural populations, and there is a lack of research in rural schools. Thus, understanding perceptions of rural students about the school lunch experience and the factors that affect school lunch consumption is key. Future efforts should focus on understanding how strongly perceptions affect participation and consumption, and schools should look to nurses as key partners in these efforts.
As this project was part of an evaluation of a larger intervention, the University of Iowa IRB determined that evaluation activities were not human subjects research. The contents of this publication do not necessarily reflect the view or policies of the U.S. Department of Agriculture, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. The U.S. Department of Agriculture had no role in the design, analysis, or writing of this article.
All authors contributed to the conception of the manuscript, while the draft was prepared by Grace Ryan, Natoshia Askelson, G. Ryan, Patrick Brady. Cristian. L. Meier contributed to the acquisition, analysis, and interpretation of the data. All authors critically revised the manuscript, gave final approval, and agreed to be accountable for all aspects of work ensuring integrity and accuracy.
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: This project has been funded at least in part with Federal funds from the U.S. Department of Agriculture. This project was supported by 2015 Team Nutrition Training Grant (CFDA 10.574).
Grace Ryan, MPH https://orcid.org/0000-0002-0354-2644
Cristian L. Meier, MSW, MPH, PhD https://orcid.org/0000-0001-6328-4272
Alberga, A. S., Sigal, R. J., Goldfield, G., Prud’homme, D., & Kenny, G. P. (2012). Overweight and obese teenagers: Why is adolescence a critical period? Pediatric Obesity, 7(4), 261–273. https://doi.org/10.1111/j.2047-6310.2011.00046.x
Alcaraz, B., & Cullen, K. W. (2014). Cafeteria staff perceptions of the new USDA school meal standards. Journal of Child Nutrition & Management, 38(2), 1–12.
Appleton, K. M., Hemingway, A., Saulais, L., Dinnella, C., Monteleone, E., Depezay, L., Morizet, D., Armando Perez-Cueto, F. J., Bevan, A., & Hartwell, H. (2016). Increasing vegetable intakes: Rationale and systematic review of published interventions. European Journal of Nutrition, 55(3), 869–896. https://doi.org/10.1007/s00394-015-1130-8
Askelson, N., Cornish, D., & Golembiewski, E. (2015). Rural school food service director perceptions on voluntary school meal reforms. Journal of Agriculture, Food Systems, and Community Development, 6(1), 65–75. https://doi.org/10.5304/jafscd.2015.061.007
Askelson, N. M., Brady, P., Ryan, G., Meier, C., Ortiz, C., Scheidel, C., & Delger, P. (2019). Actively involving middle school students in the implementation of a pilot of a behavioral economics–based lunchroom intervention in rural schools. Health Promotion Practice, 20(5), 675–683. https://doi.org/10.1177/1524839918807717
Asperin, A. E., Nettles, M. F., & Carr, D. H. (2010). The nonparticipation survey: Understanding why high school students choose not to eat school lunch. Journal of Child Nutrition & Management, 34(1).
Au, L. E., Rosen, N. J., Fenton, K., Hecht, K., & Ritchie, L. D. (2016). Eating school lunch is associated with higher diet quality among elementary school students. Journal of the Academy of Nutrition and Dietetics, 116(111), 1817–1824. https://doi.org/10.1016/j.jand.2016.04.010
Belot, M., & James, J. (2011). Healthy school meals and educational outcomes. Journal of Health Economics, 30(3), 489–504. https://doi.org/10.1016/j.jhealeco.2011.02.003
Birch, L., Savage, J. S., & Ventura, A. (2007). Influences on the development of children’s eating behaviours: From infancy to adolescence. Canadian Journal of Dietetic Practice and Research, 68(1), s1–s56.
Blanchette, L., & Brug, J. (2005). Determinants of fruit and vegetable consumption among 6-12-year-old children and effective interventions to increase consumption. Journal of Human Nutrition and Dietetics, 18(6), 431–443.
Castillo, A., & Lofton, K. L. (2012). Development of middle/junior high school student surveys to measure factors that impact participation in and satisfaction with the national school lunch program. https://theicn.org/resources/347/technical-reports/106603/development-of-middle-junior-high-school-student-surveys-to-measure-factors-that-impact-participation-in-and-satisfaction-with-the-national-school-lunch-program.pdf
Cho, H., & Nadow, M. Z. (2004). Understanding barriers to implementing quality lunch and nutrition education. Journal of Community Health, 29(5), 421–435.
Cohen, J. F. W., Richardson, S., Austin, S. B., Economos, C. D., & Rimm, E. B. (2012). School lunch waste among middle school students: Nutrients consumed and costs. American Journal of Preventive Medicine, 44(2), 114–121. https://doi.org/10.1016/j.amepre.2012.09.060
Cohen, J. F. W., Richardson, S., Parker, E., Catalano, P. J., & Rimm, E. B. (2014). Impact of the new U.S. Department of Agriculture school meal standards on food selection, consumption, and waste. American Journal of Preventive Medicine, 46(4), 388–394. https://doi.org/10.1016/j.amepre.2013.11.013
Ebbeling, C. B., Pawlak, D. B., & Ludwig, D. S. (2002). Childhood obesity: Public-health crisis, common sense cure. The Lancet, 360(9331), 473–482. https://doi.org/10.1016/S0140-6736(02)09678-2
Finkelstein, E., Graham, W., & Malhotra, R. (2014). Lifetime direct medical costs of childhood obesity. Pediatrics, 133(5), 854–862. https://doi.org/10.1542/peds.2014-0063
Food Research Action Center. (2015). National school lunch program: Trends and factors affecting student participation. http://frac.org/wp-content/uploads/national_school_lunch_report_2015.pdf
Fox, M. K., Condon, E., Crepinsek, M. K., Niland, K., Mercury, D., Forrestal, S., Cabili, C., Oddo, V., Gordon, A., Wozny, N., & Killewald, A. (2012). School nutrition dietary assessment Study IV, Volume 1, school foodservice operations, school environments, and meals offered and serve (Report No. CN-12-SNDA). Retrieved from the USDA website https://fns-prod.azureedge.net/sites/default/files/SNDA-IV_Vol1Pt1_0.pdf
Gosliner, W. (2014). School-level factors associated with increased fruit and vegetable consumption among students in California middle and high schools. Journal of School Health, 84(9), 559–568. https://doi.org/10.1111/josh.12188
Hinrichs, P. (2010). The effects of the national school lunch program on education and health. Journal of Policy Analysis and Management, 29(3), 479–505. https://doi.org/10.1002/pam.20506
Hoekstra, B. A., Young, V. L., Eley, C. V., Hawking, M. K. D., & McNulty, C. A. M. (2016). School nurses’ perspectives on the role of the school nurse in healthy education and health promotion in England: A qualitative study. BMC Nursing, 15(73). https://doi.org/10.1186/s12912-016-0194-y
Johnson, J. A., & Johnson, A. M. (2015). Urban-rural differences in childhood and adolescent obesity in the United States: A systematic review and meta-analysis. Journal of Childhood Obesity, 11(3), 233–241. https://doi.org/10.1089/chi.2014.0085
Khambalia, A. Z., Dickinson, S., Hardy, L. L., Gill, T., & Baur, L. A. (2012). A synthesis of existing systematic reviews and metaanalyses of school-based behavioural interventions for controlling and preventing obesity. Obesity Reviews, 13(3), 214–233. https://doi.org/10.1111/j.1467-789X.2011.00947.x
Kjosen, M. M., Moore, C. E., & Cullen, K. W. (2015). Middle school student perceptions of school lunch following revised federal school meal guidelines. Journal of Childhood Nutrition Management, 39(2).
Meier, C., Askelson, N. M., Brady, P., Budzyn, S., Delger, P., & Scheidel, C. (March 31, 2017). Challenges encountered engaging stakeholders in a school-based setting: Lessons learned from working collaboratively with food service directors and students to improve school lunchrooms [Poster presentation]. The Meeting of the Society for Public Health Education, Denver, CO, USA.
Muckian, J., Snethen, J., & Buseh, A. (2017). School nurses’ experiences and perceptions of healthy eating school environments. Journal of Pediatric Nursing, 35, 10–15. https://doi.org/10.1016/j.pedn.2017.02.001
Ogden, C. L., Carroll, M. D., Fakhouri, T. H., Hales, C. M., Fryar, C. D., Li, X., & Freeman, D. S. (2018). Prevalence of obesity among youths by household income and education level of head of household—United States 2011–2014. Morbidity and Mortality Weekly Report, 67(6), 186–189. https://doi.org/10.15585/mmwr.mm6706a3
Ogden, C. L., Fakhouri, T. H., Carroll, M. D., Hales, C. M., Fryar, C. D., Li, X., & Freeman, D. S. (2017). Prevalence of obesity among adults, by household income and education—United States, 2011–2014. Morbidity and Mortality Weekly Report, 66(50), 1369–1373. https://dx.doi.org/10.15585/mmwr.mm6650a1
Payán, D. D., Sloane, D. C., Illum, J., Farris, T., & Lewis, L. B. (2017). Perceived barriers and facilitators to healthy eating and school lunch meals among adolescents: A qualitative study. American Journal of Health Behavior, 41(5), 661–669. https://doi.org/10.5993/AJHB.41.5.15
Quinn, E. L., Johnson, D. B., Podrabsky, M., Saelens, B. E., Bignell, W., & Krieger, J. (2018). Effects of a behavioral economics intervention on food choice and food consumption in middle-school and high-school cafeterias. Preventing Chronic Disease, 15, 1–11.
Rosettie, K. L., Micha, R., Cudhea, F., Penalvo, J. L., O’Flaherty, M., Pearson-Stuttard, J., Economos, C. D., Whitsel, L. P., & Mozaffarian, D. (2018). Comparative risk assessment of school food environment policies and childhood diets, childhood obesity, and future cardiometabolic mortality in the United States. PloS One, 13(7), 1–15.
Schwartz, M. B., Henderson, K. E., Read, M., Danna, N., & Ickovics, J. R. (2015). New school meal regulations increase fruit consumption and do not increase total plate waste. Childhood Obesity, 11(3), 242–247. https://doi.org/10.1089/chi.2015.0019
Story, M., Kaphingst, K. M., & French, S. (2006). The role of schools in obesity prevention. Future Child, 16(1), 109–142.
Verrotti, A., Penta, L., Zenzeri, L., Agostinelli, S., & De Feo, P. (2014). Childhood obesity: Prevention and strategies of intervention. A systematic review of school-based interventions in primary schools. Journal of Endocrinological Investigation, 37(12), 1155–1164.
Wang, Y., Cai, L., Wu, Y., Wilson, R. F., Weston, C., Fawole, O., Bleich, S. N., Cheskin, L. J., Showell, N. N., Lau, B. D., Chiu, D. T., Zhang, A., & Segal, J. (2015). What childhood obesity prevention programmes work? A systematic review and metaanalysis. Obesity Reviews, 16(7), 547–565. https://doi.org/10.1111/obr.12277
Ward, Z. J., Long, M. W., Resch, S. C., Giles, C. M., Cradock, A. L., & Gortmaker, S. L. (2017). Simulation of growth trajectories of childhood obesity into adulthood. The New England Journal of Medicine, 377(22), 2145–2153. https://doi.org/10.1056/NEJMoa1703860
Williams, E., Mesidor, M., Winters, K., Dubbert, P., & Wyatt, S. (2015). Overweight and obesity: Prevalence, consequences, and causes of a growing public health problem. Current Obesity Reports, 4(3), 363–370. https://doi.org/10.1007/s13679-015-0169-4
Natoshia Askelson, MPH, PhD, is an assistant professor at the University of Iowa.
Grace Ryan, MPH, is a graduate research assistant at the University of Iowa.
Patrick Brady, MS, is a graduate research assistant at the University of Iowa.
Cristian L. Meier, MSW, MPH, PhD, is an assistant professor at the Utah State University.
Patti Delger, RN, LD, is a team nutrition codirector at the Iowa Department of Education.
Carrie Scheidel, MPH, is a team nutrition codirector at the Iowa Department of Education.
1 Public Policy Center, College of Public Health, University of Iowa, IA, USA
2 Utah State University, Logan, UT, USA
3 Iowa Department of Education, Des Moines, IA, USA
Corresponding Author:Natoshia Askelson, MPH, PhD, Public Policy Center, College of Public Health, University of Iowa, 145N., Riverside Drive, Iowa City, IA 52246, USA.Email: natoshia-askelson@uiowa.edu
