- Email: [email protected]
School Lunch Timing and Children's Physical Activity During Recess: An Exploratory Study
Research Brief School Lunch Timing and Children's Physical Activity During Recess: An Exploratory Study Gabriella M. McLoughlin, PhD1; Caitlyn G. Edwards, BS2; Alicia Jones, MS1; Morgan R. Chojnacki, MS2; Nicholas W. Baumgartner, MS1; Anne D. Walk, PhD1; Amelia M. Woods, PhD1; Kim C. Graber, EdD1; Naiman A. Khan, PhD, RD1,2 ABSTRACT Objective: To examine the relationship between school lunch timing (before vs after recess) on physical activity (PA) during recess and energy balance and food intake at lunch. Methods: A cross-sectional study design was used to examine lunch intake and PA during recess among fourth- and fifth-graders (n = 103) over 5 school days. Lunch and PA were measured using a weighted plate waste technique and accelerometry, respectively. Results: Children who received lunch before recess accumulated lower residual energy (ie, energy intake at lunch minus energy expenditure during recess) and consumed a greater proportion of milk servings. No timing effects were observed for other lunch and PA variables. Conclusions and Implications: Lunch intake and activity during recess are related to lunch timing policy. Findings warrant further examination using experimental and quasi-experimental studies to better understand the impact of timing on health behaviors. Key Words: plate waste, policy, recess, school health (J Nutr Educ Behav. 2019; 51:616−622.) Accepted January 14, 2019. Published online February 12, 2019.
INTRODUCTION Over 30% of US children are classified as being overweight.1 Obesity during childhood often tracks into adulthood,2 leading to exacerbated risks for type 2 diabetes,3 cardiovascular disease,4 and cancer.5−7 A principal cause of overweight and obesity is a chronic energy imbalance, such that energy expended is less than that consumed over extended periods of time.8 Because the majority of school-aged children consume at least 1 meal in the school setting via the National School Lunch Program (NSLP), increasing children’s opportunities to consume fruits and vegetables and reasonably well-balanced meals is a priority.9 Another vital component of a healthy school
1
environment is the promotion of physical activity (PA) to help students accrue the recommended 60 min/d of moderate to vigorous physical activity (MVPA).10 The benefits of regular PA for children include enhanced cognitive functioning, positive psychosocial behavior, increased bone density, and gains in physical fitness.11,12 School recess may have an important role in providing children with opportunities to make progress toward their daily PA.13,14 Indeed, most schoolaged children spend more time per week in recess than they do in physical education or after-school programs.15 Therefore, optimizing recess represents an excellent opportunity for children to improve their daily PA.
Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL 2 Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL Conflict of Interest Disclosure: The authors have not stated any conflicts of interest. Address for correspondence: Naiman A. Khan, PhD, RD, Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, 317 Freer Hall, 906 South Goodwin Ave, Urbana, IL 61801; E-mail: [email protected] Ó 2019 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved. https://doi.org/10.1016/j.jneb.2019.01.006
616
Although school lunch and recess are often provided consecutively, their interactive relationships are seldom studied together. Indeed, there is a dearth of knowledge pertaining to the influence of lunch timing on the level of PA during recess. Regarding lunch timing (ie, before vs after recess), the US Department of Agriculture (USDA) recommended that to reduce plate waste, schools should schedule lunch after recess.10 This reflects prior work suggesting that children consume more food when recess is offered before lunch.16,17 However, little is known regarding food-specific consumption patterns as a consequence of lunch timing. One study examined the impact of lunch and recess timing on the consumption of fruits and vegetables and found an increase in fruit and vegetable intake when the timing of recess was changed to before lunch in intervention schools.18 However no research examined timing factors on other aspects of school lunch consumption. Furthermore, the extent to which lunch timing influences the degree of the residual or energy surplus that children accumulate based on
Journal of Nutrition Education and Behavior Volume 51, Number 5, 2019
Journal of Nutrition Education and Behavior Volume 51, Number 5, 2019
McLoughlin et al
617
Table 1. School Demographic Characteristics and Participant Weight Status School 1 Variable Age, y Sex (M, F) BMI-for-age percentile Underweight, n (%) Healthy weight, n (%) Overweight, n (%) Obese, n (%) Racea White or Caucasian Black or African American Hispanic Asian American Indian ≥2 races Pacific Islander
School 2
Lunch After Recess (n = 21)
Lunch Before Recess (n = 33)
Lunch After Recess (n = 30)
Lunch Before Recess (n = 19)
10.5 § 0.5 9, 12 69.4 § 28.2 0 13 (62) 2 (9) 6 (29)
9.6 § 0.4 13, 20 69.0 § 24.9 0 20 (61) 5 (15) 8 (24)
9.5 § 0.4 11, 19 63.8 § 33.4 2 (7) 17 (57) 4 (13) 7 (23)
10.6 § 0.3 7, 12 73.7 § 22.8 0 12 (63) 1 (5) 6 (32)
43.7 20.0
13.6 59.8
12.4 12.0 0.2 11.7 0
11.4 9.3 0.2 5.7 0
F indicates female; M, male. Data are based on school-wide information provided by the Illinois State Board of Education. Note: Data are presented as mean § SD.
a
lunch timing policy is unknown. Accordingly, the current exploratory study aimed to understand differences in lunch intake and PA between children receiving different lunch timing policies (ie, lunch before or after recess). The central hypothesis was that PA during recess and children’s nutritional intake at lunch would be interrelated and influenced by recess timing.
METHODS Institutional Review Board All procedures were approved by the Institutional Review Board at the University of Illinois at UrbanaChampaign after a full board review.
Study Design The researchers employed a cross-sectional study design in 2016. The protocols were implemented over 5 days in the school setting. Participants’ school lunch intake and activity levels during outdoor recess were assessed. Data collection occurred from September through October, 2016.
Participants and Setting Fourth- and fifth-grade children attending 2 elementary schools participated in this study. Demographic characteristics were obtained from school-wide data provided by the Illinois Board of Education.19 The researchers provided informed consent forms to parents of students. Of the total number of fourth- and fifth-grade students in both schools (n = 235), 158 provided consent to participate. Among those who consented, complete data were available for 103 children. Reasons for excluding participants from the final sample analyses included absences and/or voluntary dropout (n = 8), <3 days’ participation in the study (n = 22), and consuming packed lunches (n = 25). Regarding lunch timing, 51 participants had recess before lunch and 52 had recess afterward. Table 1 lists demographic characteristics (ie, age, sex, grade, body mass index [BMI] percentile) of the final sample.
Weight Status Participants’ height and weight were measured using a combination weighing scale (calibrated using a
known weighted item and weighing twice) and stadiometer (model 769, Seca, Hamburg, Germany) to determine BMI (in kg/m2). The researchers took measurements in schools in a private area to maintain confidentiality and comfort. Participants were asked to remove their shoes before the assessment. Calculations were based on the average of 2 measurements of height and weight. The BMI percentiles for age and sex were determined based on raw BMI data and Centers for Disease Control and Prevention age- and sex-specific growth charts.20 Children’s weight status was subsequently bifurcated across the cutoff for overweight as either non-overweight (<85th percentile BMI-for-age) or overweight/obese (≥85th percentile BMI-for-age).
Lunch Assessment Each child’s lunch intake was assessed for 5 consecutive school days and averaged before analyses. Menu items for each school for the 5day period are displayed in Table 2. All data were collected in the cafeteria; school 1 scheduled lunch over a 30-minute session (immediately followed or preceded by a 30-minute
618
McLoughlin et al
recess period) and school 2 over a 15minute period session (immediately followed or preceded by a 15-minute recess period). Therefore, certain classes in each school had either recess before or recess after lunch. Table 3 represents average food consumption by lunch and recess timing. A total of 51 children received lunch after recess (30 children had 15-min lunch and 15-min recess and 21 children had 30-min lunch and 30-min recess) whereas 52 children received lunch before recess (19 children had 15-min lunch and 15-min recess and 33 children had 30-min lunch and 30-min recess). Nutritional intake was measured using a modified weighted plate waste technique assisted by digital photography.21 Both schools participated in the NSLP, adopting an offer vs serve system; options included a prepackaged or portioned serving of fruits and vegetables, a choice of 2 entrees, and milk. As per rules set by the USDA,22 children receiving school lunches had to select at least 3 of the 5 options (1 grain, 1 milk, 1 protein, and 1 vegetable and/or 1 fruit). One of each prepackaged food item available for lunch each day was weighed at the beginning of the lunch period to establish a standard baseline/preconsumption weight. For items that were not prepackaged (chicken tenders, corn dogs, and hot dogs), 3 samples were weighed and the average was used as the standard or premeal weight. During the meals, trained research assistants stood next to food disposal bins to prevent the loss of food items owing to disposal. After the meals, children returned the trays and each item was weighed using a food-weighing scale (digital food scale, The Sharper Image, Farmington Hills, MI). The differential between the standard and established food item weight and the weight of food items at postmeal and tray return was calculated to index the degree of consumption for each food item. In addition, digital photographs of lunch trays were taken before and after the meal to facilitate recording and confirmation of items selected and returned. Students were given a tray identification number at the beginning of the study; to ensure accurate depiction of what each student took and brought back to the researchers after
Journal of Nutrition Education and Behavior Volume 51, Number 5, 2019
Activity Energy Expenditure
consumption, research staff wrote the identification number on students’ trays. To determine the proportions of items consumed (ie, fruits, vegetables, entree, milk), the remaining or wasted item weight was calculated as a percentage of the total item weight determined before lunch. Photographs were used to identify what students chose for lunch that day; in the case of discrepancies in weight or an item not weighed at the end (ie, one without packaging), the researchers were able to check what students chose, to discern accurately what they consumed. If students did not choose an item (ie, milk, entree, fruit, vegetable), this was a missing data point for the day and was not counted as 0 consumption. Average percent consumption of each item was calculated by dividing the total consumption of each item by the number of days of data collected for each student (variation owing to student absences). Nutrient content of all foods available on the menu was analyzed with NUTRIKIDS Menu Planning and Nutritional Analysis software (Lunchbyte Systems, Inc, Rochester, NY, 2001).
Energy expenditure during recess in terms of metabolic equivalent scores was calculated.27 To estimate caloric expenditure based on the duration of recess (in minutes) and participant body weight (in kilograms), the regression equation developed by Puyau et al28 was applied to accelerometer counts (average counts per minute). This provided activity energy expenditure (AEE) expressed as AEE (kcal kg−1 min−1). To calculate total AEE for the duration of recess, AEE was multiplied by participant body weight (in kilograms) and the average amount of wear time per school (to account for day-to-day differences for when students entered and left the recess playground). To calculate energy balance, a separate variable was created based on the differential between total caloric intake at lunch and total AEE during recess to provide residual caloric intake or surplus for the duration of the lunch or recess period.
Physical Activity Assessment
Data Analysis
The researchers measured PA objectively during recess over each of the 5-day period using accelerometry and averaged it before analyses. Each participant was fitted with an ActiGraph wGT3X+ accelerometer (Actigraph, LLC, Pensacola, FL) worn around the waist during lunch and recess. Accelerometers were validated for use with children, as well as to measure recess PA.23−25 ActiLife software was used to analyze accelerometry data using previously validated cut points to calculate MVPA.22 The researchers chose to examine MVPA because current PA recommendations aim to improve activity within the moderate and vigorous PA range.26 Two trained research assistants were positioned at the entrance to the school playground to record the exact time that classes left and returned to the school building for recess, providing a time window for analysis. The accelerometers were retrieved once children returned to the classrooms.
All data were analyzed using the SPSS software (version 24, IBM Corporation, Armonk, NY). After descriptive analysis, Pearson bivariate correlations were run to investigate relations between demographic and behavioral variables. One-way ANOVA was conducted to determine the effect of lunch timing (before vs after recess) on primary nutrition (ie, energy intake and food items) and activity (percent time spent in MVPA range and raw/absolute time spent in MVPA) variables, after adjusting for sex, age, and duration of lunch or recess (to account for school differences). Because weight status was strongly correlated with energy intake (r = .29; P < .01), activity-related energy expenditure (r = .45; P < .01), and energy balance (r = .22; P = .01), the researchers controlled for it in the primary analyses. Any significant effects were subsequently examined using independent t tests. Data were analyzed with an a threshold of P = .05.
Journal of Nutrition Education and Behavior Volume 51, Number 5, 2019
McLoughlin et al
619
Table 2. Food Items Offered During Study for Each School Variable
e Items Entre
Side Items
Drink Options
School 1
Bosco cheese sticks Hot dog Walking taco Ham salad Chicken and waffles Corn dog Beef and cheese nachos Soft taco
Milk (1%) Milk (skim) Milk (chocolate 1%) Apple mango juice
School 2
Pizza Chicken strip wrap Hot dog Turkey and cheese sub Chicken strips Pretzel and cheese sauce Bosco cheese sticks
Peach cup Broccoli Charro beans Raspberry lemon Slushie Apple slices French fries Pineapple Grapes Green beans Orange wedges Mashed potatoes Blue raspberry applesauce Banana Watermelon Celery sticks Broccoli (bag) Grape tomatoes Pineapple Peach cup Applesauce Baby carrots Mashed potatoes Refried beans Orange
Milk (1%) Milk (skim) Milk (chocolate 1%)
Note: Menus were different for schools 1 and 2; each school had students who received lunch either before or after recess.
RESULTS Table 2 lists lunch menu items that were offered. The mean percentage of children who selected fruits, vegetables, entree, and milk over the data collection period was 57%, 26%, 68%, and 64%, respectively. Therefore,
vegetables were the least selected food item. Descriptive data and 1-way ANOVA results for the sample, bifurcated by lunch timing, are displayed in Table 3. After controlling for age, sex, recess or lunch duration, and BMI percentile, significant main effects for lunch timing were found
for energy intake, milk consumption, and energy balance. No significant main effects for recess timing were observed on activity variables such total MVPA (minutes) and percentage of time spent in MVPA. Nonsignificant findings were also found for fruit, vegetable, and entr ee consumption.
Table 3. Descriptive Information and 1-Way ANOVA Results Regarding Activity and Nutrition Variables Based on Timing of Recess and Lunch
Variable MVPA (%) MVPA, min es (%) Entre Vegetables (%) Milk (%) Fruit (%) Energy intake, kcal Activity-related energy expenditure, kcal Residual energy, kcal
Lunch After Recess (n = 30 [15 min L and R]; n = 21 [30 min L and R])
Lunch Before Recess (n = 19 [15 min L and R]; n = 33 [30 min L and R])
F
P
Partial h2
29.4 § 9.7 5.0 § 1.6 70.8 § 21.6 57.0 § 43.7 57.5 § 29.9 58.2 § 27.0 355.6 § 88.3 36.4 §16.5
27.6 § 8.5 6.1 § 3.0 71.4 § 21.3 69.5 § 37.5 47.0 § 26.2 52.1 § 29.7 314.5 § 97.2 40.6 § 15.0
0.08 2.32 0.93 2.54 4.46 2.53 10.15 1.23
.78 .13 .34 .11 .03** .11 .001** .27
.00 .02 .01 .02 .04 .02 .09 .01
319.2 § 82.6
273.8 § 94.7
9.34
.001**
.08
% indicates percentage of recess time spent in MVPA; L, lunch; MVPA, moderate to vigorous physical activity; R, recess. Note: Data are presented as mean § SD.
620
McLoughlin et al
Journal of Nutrition Education and Behavior Volume 51, Number 5, 2019
Figure. Effects of lunch timing (after vs before recess) on energy intake and residual energy. *Significant (P < .05) difference between groups receiving recess before vs after lunch.
Although significant main effects of lunch timing were observed for energy intake, such effects were not apparent for energy expenditure. Subsequent independent t tests revealed significant differences in milk consumption, in which children who received lunch before recess consumed less milk (11.4%; 95% confidence interval [CI], 0.70−22.1; P = .04), expended less energy (55 kcal; 95% CI, 21−90; P < .01), and accumulated lower residual energy (53 kcal; 95% CI, 19−88; P < .01). The Figure illustrates differences in energy intake and residual energy.
DISCUSSION This exploratory study revealed that differences in lunch intake and energy balance were observable in children according to different lunch timing policy. Children who received lunch before recess had lower residual energy than did their counterparts who received lunch after recess. However, specific food item analyses indicated that children who received lunch after recess consumed a greater proportion of milk. To the authors’ knowledge, the current work provides new insights regarding nutrition at lunch and objectively measured PA patterns during recess as a function of timing of lunch periods over the course of a school week.
That participants consumed significantly more calories when receiving lunch after recess is consistent with previous studies conducted among schools that followed USDA guidelines to schedule recess before lunchtime to increase food consumption and reduce waste.10,17,29 However, to understand the health implications of lunch timing comprehensively, it is important also to account for its influence on quality of nutritional intake. Although food consumption was higher after recess, the researchers observed differential patterns of intake for specific food items and energy balance in relation to timing policy. Based on the report from the USDA,10 it may seem that children rush eating and consume fewer calories to leave the cafeteria quickly for recess. However, this explanation did not pertain to the current study because of the fixed amount of time children were given to eat lunch at each school. Alternatively, providing meals before recess may provide adequate nourishment for children to optimize activity during subsequent recess in a manner consistent with the expectation that children may need to be nourished to move during recess. Because of differences in maturation and growth, and body composition, children’s metabolic rates may vary; therefore, their energy intake needs may differ. The finding that students
consumed fewer calories when recess followed lunch may mean that some students did not receive adequate nutritional intake. Because the study did not assess body composition (ie, percentage body fat) in the school setting, this finding warrants further study. That participants consumed fewer calories when recess was offered after lunch despite the length of time given is consistent with previous research.16,17 The authors observed that children who received lunch after recess accumulated an additional energy surplus of about 50 kcal after accounting for estimated energy expenditure during recess. Although this energy differential may seem numerically trivial, it is known that even small differences in energy surplus over extended periods can have significant implications for longterm weight regulation.30,31 Conversely, it is possible that students who consume less food at lunch may become hungry throughout the day and consume more at other times of the school day and after school. This raises questions regarding the degree to which appetite regulation had a role in the behaviors observed in this study. Furthermore, provision of school lunches through the NSLP can offset food insecurity, particularly among low-income communities.32,33 Therefore, because a fairly large proportion of students were
Journal of Nutrition Education and Behavior Volume 51, Number 5, 2019 eligible for free or reduced-price lunch, and early evidence suggesting students partaking in NSLP reported more favorable nutritional intake,34 it is important to consider the role of mealtime as an important component of nutrient consumption. The main differences observed pertained to consumption of milk and entrees, which suggests that these students may have consumed more calcium and protein than did their counterparts who received recess after lunch. Furthermore, because the main differences were observed in milk consumption, it is possible that students were thirstier after recess. Although water fountains were present in the cafeteria, the researchers could not study water intake because many students did not use water bottles. Unlike prior research,18 no differences were observed in fruit or vegetable consumption between lunch and recess timing groups. Nevertheless, the study by Price and Just18 did not control for demographic variables such as age, sex, or weight status, and therefore caution must be taken when comparing the current findings with previous investigations. Strengths of the current study included the use of objective assessment of PA and quantification of food choices within the school for the entire school week. However, several limitations are worth considering. Although this acute component (ie, lunch and recess) of the school day indicates lifestyle nutrition intake and PA, it cannot be assumed that behaviors observed reflected those throughout the day. In relation to energy expenditure, the researchers also recognize the limitation of assessing calories expended at recess alone; they did not measure energy expenditure outside this time and realize that other times of the school day, such as physical education and classroom activities, may provide students with ways to use energy. Therefore, future research might track activity, energy expenditure, and nutritional intake throughout the day and outside school to achieve an accurate depiction of children’s lifestyles. Furthermore, participants were selected through convenience sampling and limited to 1 geographical location in the US, which provided a relatively small sample from
which to draw conclusions. Considering the efforts put forth by the USDA and the NSLP to provide consistency in nutritional choices to schools throughout the country, it is important to gather data from several geographically dispersed schools. Finally, establishing the direct cause-and-effect relationship between nutritional intake at lunch and PA during recess will require randomized, controlled or crossover trials.
McLoughlin et al
3.
4.
IMPLICATIONS FOR RESEARCH AND PRACTICE The findings of the current study offer empirical support for the benefits of scheduling lunch after recess to limit total plate waste and increase consumption; nevertheless, accounting for PA-related energy expenditure revealed a more complex relationship between recess timing and health behavior that warrants further study. Alternatively, these findings indicate that beverages offered at lunch, such as milk, are more likely to be consumed if lunch is offered after recess. Collectively, these findings provide a rationale for considering overall food consumption, quality of nutritional intake, PA behaviors, and the accumulation of residual energy in the development of future policies affecting school health environments. Additional experimental and longitudinal research is needed to confirm the findings observed here, as well as the long-term consequences of lunch timing policies on children’s eating behaviors.
5.
6.
7.
8.
9.
10.
ACKNOWLEDGMENTS Sources of financial support for this study were provided by the Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, and the Illinois Association for Health, Physical Education, Recreation, and Dance.
11.
12.
REFERENCES 1. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in the United States, 20112012. JAMA. 2014;311:806-814. 2. Herman KM, Craig CL, Gauvin L, Katzmarzyk PT. Tracking of obesity
13.
14.
621
and physical activity from childhood to adulthood: the physical activity longitudinal study. Int J Pediatr Obes. 2009;4:281-288. Jung CH, Kang YM, Jang JE, et al. Fatty liver index is a risk determinant of incident type 2 diabetes in a metabolically healthy population with obesity. Obesity (Silver Spring). 2016;24:1373-1379. Saydah S, Bullard KM, Cheng Y, et al. Trends in cardiovascular disease risk factors by obesity level in adults in the United States, NHANES 1999-2010. Obesity (Silver Spring). 2014;22:18881895. De Pergola G, Silvestris F. Obesity as a major risk factor for cancer. J Obes. 2013;2013:291546. Sun JW, Zhao LG, Yang Y, Ma X, Wang YY, Xiang YB. Obesity and risk of bladder cancer: a dose-response meta-analysis of 15 cohort studies. PLoS One. 2015;10:e0119313. Vidal AC, Howard LE, Moreira DM, Castro-Santamaria R, Andriole GL, Freedland SJ. Obesity increases the risk for high-grade prostate cancer: results from the REDUCE study. Cancer Epidemiol Biomarkers Prev. 2014;23:2936-2942. Swinburn BA, Jolley D, Kremer PJ, Salbe AD, Ravussin E. Estimating the effects of energy imbalance on changes in body weight in children. Am J Clin Nutr. 2006;83:859-863. Clark MA, Fox MK. Nutritional quality of the diets of US public school children and the role of the school meal programs. J Am Diet Assoc. 2009;109(suppl 2):S44-S56. Ralston KL, Buzby JC, Guthrie JF. A Healthy School Meal Environment: Food Assistance Research Brief. Washington, DC: US Department of Agriculture, Economic Research Service; 2003. Poitras VJ, CE, Borghese MM, et al. Systematic review of the relationships between objectively measured physical activity and health indicators in school-aged children and youth. Appl Physiol Nutr Metab. 2016;41:197-239. Warburton DER, Nicol CW, Bredin SSD. Health benefits of physical activity: the evidence. Can Med Assoc J. 2006;174:801-809. Ramstetter CL, Murray R, Garner AS. The crucial role of recess in school. Pediatrics. 2013;131:183-188. Ridgers ND, Timperio A, Crawford D, Salmon J. Five-year changes in school
622
15.
16.
17.
18.
19.
20.
21.
McLoughlin et al recess and lunchtime and the contribution to children’s daily physical activity. Br J Sports Med. 2012;46:741-746. Fenton Communications. Recess Rules —Why the Undervalued Playtime May Be America’s Best Investment for Healthy Kids and Healthy Schools. Plainsboro Township, NJ: Robert Wood Johnson Foundation; 2007. Getlinger MH, Laughlin VT, Bell E, Akre C, Arjmandi BH. Food waste is reduced when elementary-school children have recess before lunch. J Am Diet Assoc. 1996;96:906-908. Hunsberger M, McGinnis P, Smith J, Beamer BA, O’Malley J. Elementary school children’s recess schedule and dietary intake at lunch: a communitybased participatory research partnership pilot study. BMC Public Health. 2014;14:156. Price J, Just DR. Lunch, recess and nutrition: responding to time incentives in the cafeteria. Prev Med (Baltim). 2015;71:27-30. Illinois State Board of Education. Illinois Report Card. https://www.illinoisreportcard.com/. Accessed August 5, 2017. Kuczmarski RJ, Ogden CL, Guo SS, et al. 2000 CDC growth charts for the United States: methods and development. Vital Health Stat. 2002;11:1-190. 11. Ptomey LT, Willis EA, Honas JJ, et al. Validity of energy intake estimated by digital photography plus recall in overweight and obese young adults. J Acad Nutr Diet. 2015;115:1392-1399.
Journal of Nutrition Education and Behavior Volume 51, Number 5, 2019 22. Food and Nutrition Service, US Department of Agriculture. National School Lunch Program and School Breakfast Program: Nutrition standards for all foods sold in school as required by the Healthy, Hunger-Free Kids Act of 2010. 78 FR 39067. https://www.federalregister.gov/documents/2013/06/28/ 2013-15249/national-school-lunch-program-and-school-breakfast-programnutrition-standards-for-all-foods-sold-in. Published June 28, 2013. Accessed July 17, 2018. 23. Pulsford RM, Cortina-Borja M, Rich C, Kinnafick FE, Dezateux C, Griffiths LJ. Actigraph accelerometer-defined boundaries for sedentary behaviour and physical activity intensities in 7 year old children. PLoS One. 2011;6:e21822. 24. Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Med Sci Sport Exerc. 2008;40:181-188. 25. Ridgers ND, Stratton G, Fairclough SJ. Assessing physical activity during recess using accelerometry. Prev Med. 2005;41:102-107. 26. US Department of Health and Human Services. 2008 Physical Activity Guidelines for Americans. https://health. gov/paguidelines/guidelines/. Accessed September 21, 2017. 27. Treuth MS, Schmitz K, Catellier DJ, et al. Defining accelerometer thresholds for activity intensities in adolescent girls. Med Sci Sports Exerc. 2004;36:1259-1266.
28. Puyau MR, Adolph AL, Vohra FA, Butte NF. Validation and calibration of physical activity monitors in children. Obes Res. 2002;10:150-157. 29. Huberty JL, Beets MW, Beighle A, Saint-Maurice PF, Welk G. Effects of ready for recess, an environmental intervention, on physical activity in third-through sixth-grade children. J Phys Act Health. 2014;11:384-395. 30. Hill JO. Can a small-changes approach help address the obesity epidemic? A report of the Joint Task Force of the American Society for Nutrition, Institute of Food Technologists, and International Food Information Council. Am J Clin Nutr. 2009;89:477-484. 31. Hill JO, Peters JC. Environmental contributions to the obesity epidemic. Science. 1998;280:1371-1374. 32. Nguyen BT, Ford CN, Shuval K, Drope J, Yaroch AL. Food security and weight status in children: interactions with food assistance programs. Am J Prev Med. 2017;52(suppl 2):S138-S144. 33. Gundersen C, Kreider B, Pepper J, Tarasuk V. Food assistance programs and food insecurity: implications for Canada in light of the mixing problem. Empir Econ. 2017;52:1065-1087. 34. Au LE, Gurzo K, Gosliner W, Webb KL, Crawford PB, Ritchie LD. Eating school meals daily is associated with healthier dietary intakes: the Healthy Communities Study. J Acad Nutr Diet. 2018;118:1474-1481.
INTRODUCTION Over 30% of US children are classified as being overweight.1 Obesity during childhood often tracks into adulthood,2 leading to exacerbated risks for type 2 diabetes,3 cardiovascular disease,4 and cancer.5−7 A principal cause of overweight and obesity is a chronic energy imbalance, such that energy expended is less than that consumed over extended periods of time.8 Because the majority of school-aged children consume at least 1 meal in the school setting via the National School Lunch Program (NSLP), increasing children’s opportunities to consume fruits and vegetables and reasonably well-balanced meals is a priority.9 Another vital component of a healthy school
1
environment is the promotion of physical activity (PA) to help students accrue the recommended 60 min/d of moderate to vigorous physical activity (MVPA).10 The benefits of regular PA for children include enhanced cognitive functioning, positive psychosocial behavior, increased bone density, and gains in physical fitness.11,12 School recess may have an important role in providing children with opportunities to make progress toward their daily PA.13,14 Indeed, most schoolaged children spend more time per week in recess than they do in physical education or after-school programs.15 Therefore, optimizing recess represents an excellent opportunity for children to improve their daily PA.
Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL 2 Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL Conflict of Interest Disclosure: The authors have not stated any conflicts of interest. Address for correspondence: Naiman A. Khan, PhD, RD, Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, 317 Freer Hall, 906 South Goodwin Ave, Urbana, IL 61801; E-mail: [email protected] Ó 2019 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved. https://doi.org/10.1016/j.jneb.2019.01.006
616
Although school lunch and recess are often provided consecutively, their interactive relationships are seldom studied together. Indeed, there is a dearth of knowledge pertaining to the influence of lunch timing on the level of PA during recess. Regarding lunch timing (ie, before vs after recess), the US Department of Agriculture (USDA) recommended that to reduce plate waste, schools should schedule lunch after recess.10 This reflects prior work suggesting that children consume more food when recess is offered before lunch.16,17 However, little is known regarding food-specific consumption patterns as a consequence of lunch timing. One study examined the impact of lunch and recess timing on the consumption of fruits and vegetables and found an increase in fruit and vegetable intake when the timing of recess was changed to before lunch in intervention schools.18 However no research examined timing factors on other aspects of school lunch consumption. Furthermore, the extent to which lunch timing influences the degree of the residual or energy surplus that children accumulate based on
Journal of Nutrition Education and Behavior Volume 51, Number 5, 2019
Journal of Nutrition Education and Behavior Volume 51, Number 5, 2019
McLoughlin et al
617
Table 1. School Demographic Characteristics and Participant Weight Status School 1 Variable Age, y Sex (M, F) BMI-for-age percentile Underweight, n (%) Healthy weight, n (%) Overweight, n (%) Obese, n (%) Racea White or Caucasian Black or African American Hispanic Asian American Indian ≥2 races Pacific Islander
School 2
Lunch After Recess (n = 21)
Lunch Before Recess (n = 33)
Lunch After Recess (n = 30)
Lunch Before Recess (n = 19)
10.5 § 0.5 9, 12 69.4 § 28.2 0 13 (62) 2 (9) 6 (29)
9.6 § 0.4 13, 20 69.0 § 24.9 0 20 (61) 5 (15) 8 (24)
9.5 § 0.4 11, 19 63.8 § 33.4 2 (7) 17 (57) 4 (13) 7 (23)
10.6 § 0.3 7, 12 73.7 § 22.8 0 12 (63) 1 (5) 6 (32)
43.7 20.0
13.6 59.8
12.4 12.0 0.2 11.7 0
11.4 9.3 0.2 5.7 0
F indicates female; M, male. Data are based on school-wide information provided by the Illinois State Board of Education. Note: Data are presented as mean § SD.
a
lunch timing policy is unknown. Accordingly, the current exploratory study aimed to understand differences in lunch intake and PA between children receiving different lunch timing policies (ie, lunch before or after recess). The central hypothesis was that PA during recess and children’s nutritional intake at lunch would be interrelated and influenced by recess timing.
METHODS Institutional Review Board All procedures were approved by the Institutional Review Board at the University of Illinois at UrbanaChampaign after a full board review.
Study Design The researchers employed a cross-sectional study design in 2016. The protocols were implemented over 5 days in the school setting. Participants’ school lunch intake and activity levels during outdoor recess were assessed. Data collection occurred from September through October, 2016.
Participants and Setting Fourth- and fifth-grade children attending 2 elementary schools participated in this study. Demographic characteristics were obtained from school-wide data provided by the Illinois Board of Education.19 The researchers provided informed consent forms to parents of students. Of the total number of fourth- and fifth-grade students in both schools (n = 235), 158 provided consent to participate. Among those who consented, complete data were available for 103 children. Reasons for excluding participants from the final sample analyses included absences and/or voluntary dropout (n = 8), <3 days’ participation in the study (n = 22), and consuming packed lunches (n = 25). Regarding lunch timing, 51 participants had recess before lunch and 52 had recess afterward. Table 1 lists demographic characteristics (ie, age, sex, grade, body mass index [BMI] percentile) of the final sample.
Weight Status Participants’ height and weight were measured using a combination weighing scale (calibrated using a
known weighted item and weighing twice) and stadiometer (model 769, Seca, Hamburg, Germany) to determine BMI (in kg/m2). The researchers took measurements in schools in a private area to maintain confidentiality and comfort. Participants were asked to remove their shoes before the assessment. Calculations were based on the average of 2 measurements of height and weight. The BMI percentiles for age and sex were determined based on raw BMI data and Centers for Disease Control and Prevention age- and sex-specific growth charts.20 Children’s weight status was subsequently bifurcated across the cutoff for overweight as either non-overweight (<85th percentile BMI-for-age) or overweight/obese (≥85th percentile BMI-for-age).
Lunch Assessment Each child’s lunch intake was assessed for 5 consecutive school days and averaged before analyses. Menu items for each school for the 5day period are displayed in Table 2. All data were collected in the cafeteria; school 1 scheduled lunch over a 30-minute session (immediately followed or preceded by a 30-minute
618
McLoughlin et al
recess period) and school 2 over a 15minute period session (immediately followed or preceded by a 15-minute recess period). Therefore, certain classes in each school had either recess before or recess after lunch. Table 3 represents average food consumption by lunch and recess timing. A total of 51 children received lunch after recess (30 children had 15-min lunch and 15-min recess and 21 children had 30-min lunch and 30-min recess) whereas 52 children received lunch before recess (19 children had 15-min lunch and 15-min recess and 33 children had 30-min lunch and 30-min recess). Nutritional intake was measured using a modified weighted plate waste technique assisted by digital photography.21 Both schools participated in the NSLP, adopting an offer vs serve system; options included a prepackaged or portioned serving of fruits and vegetables, a choice of 2 entrees, and milk. As per rules set by the USDA,22 children receiving school lunches had to select at least 3 of the 5 options (1 grain, 1 milk, 1 protein, and 1 vegetable and/or 1 fruit). One of each prepackaged food item available for lunch each day was weighed at the beginning of the lunch period to establish a standard baseline/preconsumption weight. For items that were not prepackaged (chicken tenders, corn dogs, and hot dogs), 3 samples were weighed and the average was used as the standard or premeal weight. During the meals, trained research assistants stood next to food disposal bins to prevent the loss of food items owing to disposal. After the meals, children returned the trays and each item was weighed using a food-weighing scale (digital food scale, The Sharper Image, Farmington Hills, MI). The differential between the standard and established food item weight and the weight of food items at postmeal and tray return was calculated to index the degree of consumption for each food item. In addition, digital photographs of lunch trays were taken before and after the meal to facilitate recording and confirmation of items selected and returned. Students were given a tray identification number at the beginning of the study; to ensure accurate depiction of what each student took and brought back to the researchers after
Journal of Nutrition Education and Behavior Volume 51, Number 5, 2019
Activity Energy Expenditure
consumption, research staff wrote the identification number on students’ trays. To determine the proportions of items consumed (ie, fruits, vegetables, entree, milk), the remaining or wasted item weight was calculated as a percentage of the total item weight determined before lunch. Photographs were used to identify what students chose for lunch that day; in the case of discrepancies in weight or an item not weighed at the end (ie, one without packaging), the researchers were able to check what students chose, to discern accurately what they consumed. If students did not choose an item (ie, milk, entree, fruit, vegetable), this was a missing data point for the day and was not counted as 0 consumption. Average percent consumption of each item was calculated by dividing the total consumption of each item by the number of days of data collected for each student (variation owing to student absences). Nutrient content of all foods available on the menu was analyzed with NUTRIKIDS Menu Planning and Nutritional Analysis software (Lunchbyte Systems, Inc, Rochester, NY, 2001).
Energy expenditure during recess in terms of metabolic equivalent scores was calculated.27 To estimate caloric expenditure based on the duration of recess (in minutes) and participant body weight (in kilograms), the regression equation developed by Puyau et al28 was applied to accelerometer counts (average counts per minute). This provided activity energy expenditure (AEE) expressed as AEE (kcal kg−1 min−1). To calculate total AEE for the duration of recess, AEE was multiplied by participant body weight (in kilograms) and the average amount of wear time per school (to account for day-to-day differences for when students entered and left the recess playground). To calculate energy balance, a separate variable was created based on the differential between total caloric intake at lunch and total AEE during recess to provide residual caloric intake or surplus for the duration of the lunch or recess period.
Physical Activity Assessment
Data Analysis
The researchers measured PA objectively during recess over each of the 5-day period using accelerometry and averaged it before analyses. Each participant was fitted with an ActiGraph wGT3X+ accelerometer (Actigraph, LLC, Pensacola, FL) worn around the waist during lunch and recess. Accelerometers were validated for use with children, as well as to measure recess PA.23−25 ActiLife software was used to analyze accelerometry data using previously validated cut points to calculate MVPA.22 The researchers chose to examine MVPA because current PA recommendations aim to improve activity within the moderate and vigorous PA range.26 Two trained research assistants were positioned at the entrance to the school playground to record the exact time that classes left and returned to the school building for recess, providing a time window for analysis. The accelerometers were retrieved once children returned to the classrooms.
All data were analyzed using the SPSS software (version 24, IBM Corporation, Armonk, NY). After descriptive analysis, Pearson bivariate correlations were run to investigate relations between demographic and behavioral variables. One-way ANOVA was conducted to determine the effect of lunch timing (before vs after recess) on primary nutrition (ie, energy intake and food items) and activity (percent time spent in MVPA range and raw/absolute time spent in MVPA) variables, after adjusting for sex, age, and duration of lunch or recess (to account for school differences). Because weight status was strongly correlated with energy intake (r = .29; P < .01), activity-related energy expenditure (r = .45; P < .01), and energy balance (r = .22; P = .01), the researchers controlled for it in the primary analyses. Any significant effects were subsequently examined using independent t tests. Data were analyzed with an a threshold of P = .05.
Journal of Nutrition Education and Behavior Volume 51, Number 5, 2019
McLoughlin et al
619
Table 2. Food Items Offered During Study for Each School Variable
e Items Entre
Side Items
Drink Options
School 1
Bosco cheese sticks Hot dog Walking taco Ham salad Chicken and waffles Corn dog Beef and cheese nachos Soft taco
Milk (1%) Milk (skim) Milk (chocolate 1%) Apple mango juice
School 2
Pizza Chicken strip wrap Hot dog Turkey and cheese sub Chicken strips Pretzel and cheese sauce Bosco cheese sticks
Peach cup Broccoli Charro beans Raspberry lemon Slushie Apple slices French fries Pineapple Grapes Green beans Orange wedges Mashed potatoes Blue raspberry applesauce Banana Watermelon Celery sticks Broccoli (bag) Grape tomatoes Pineapple Peach cup Applesauce Baby carrots Mashed potatoes Refried beans Orange
Milk (1%) Milk (skim) Milk (chocolate 1%)
Note: Menus were different for schools 1 and 2; each school had students who received lunch either before or after recess.
RESULTS Table 2 lists lunch menu items that were offered. The mean percentage of children who selected fruits, vegetables, entree, and milk over the data collection period was 57%, 26%, 68%, and 64%, respectively. Therefore,
vegetables were the least selected food item. Descriptive data and 1-way ANOVA results for the sample, bifurcated by lunch timing, are displayed in Table 3. After controlling for age, sex, recess or lunch duration, and BMI percentile, significant main effects for lunch timing were found
for energy intake, milk consumption, and energy balance. No significant main effects for recess timing were observed on activity variables such total MVPA (minutes) and percentage of time spent in MVPA. Nonsignificant findings were also found for fruit, vegetable, and entr ee consumption.
Table 3. Descriptive Information and 1-Way ANOVA Results Regarding Activity and Nutrition Variables Based on Timing of Recess and Lunch
Variable MVPA (%) MVPA, min es (%) Entre Vegetables (%) Milk (%) Fruit (%) Energy intake, kcal Activity-related energy expenditure, kcal Residual energy, kcal
Lunch After Recess (n = 30 [15 min L and R]; n = 21 [30 min L and R])
Lunch Before Recess (n = 19 [15 min L and R]; n = 33 [30 min L and R])
F
P
Partial h2
29.4 § 9.7 5.0 § 1.6 70.8 § 21.6 57.0 § 43.7 57.5 § 29.9 58.2 § 27.0 355.6 § 88.3 36.4 §16.5
27.6 § 8.5 6.1 § 3.0 71.4 § 21.3 69.5 § 37.5 47.0 § 26.2 52.1 § 29.7 314.5 § 97.2 40.6 § 15.0
0.08 2.32 0.93 2.54 4.46 2.53 10.15 1.23
.78 .13 .34 .11 .03** .11 .001** .27
.00 .02 .01 .02 .04 .02 .09 .01
319.2 § 82.6
273.8 § 94.7
9.34
.001**
.08
% indicates percentage of recess time spent in MVPA; L, lunch; MVPA, moderate to vigorous physical activity; R, recess. Note: Data are presented as mean § SD.
620
McLoughlin et al
Journal of Nutrition Education and Behavior Volume 51, Number 5, 2019
Figure. Effects of lunch timing (after vs before recess) on energy intake and residual energy. *Significant (P < .05) difference between groups receiving recess before vs after lunch.
Although significant main effects of lunch timing were observed for energy intake, such effects were not apparent for energy expenditure. Subsequent independent t tests revealed significant differences in milk consumption, in which children who received lunch before recess consumed less milk (11.4%; 95% confidence interval [CI], 0.70−22.1; P = .04), expended less energy (55 kcal; 95% CI, 21−90; P < .01), and accumulated lower residual energy (53 kcal; 95% CI, 19−88; P < .01). The Figure illustrates differences in energy intake and residual energy.
DISCUSSION This exploratory study revealed that differences in lunch intake and energy balance were observable in children according to different lunch timing policy. Children who received lunch before recess had lower residual energy than did their counterparts who received lunch after recess. However, specific food item analyses indicated that children who received lunch after recess consumed a greater proportion of milk. To the authors’ knowledge, the current work provides new insights regarding nutrition at lunch and objectively measured PA patterns during recess as a function of timing of lunch periods over the course of a school week.
That participants consumed significantly more calories when receiving lunch after recess is consistent with previous studies conducted among schools that followed USDA guidelines to schedule recess before lunchtime to increase food consumption and reduce waste.10,17,29 However, to understand the health implications of lunch timing comprehensively, it is important also to account for its influence on quality of nutritional intake. Although food consumption was higher after recess, the researchers observed differential patterns of intake for specific food items and energy balance in relation to timing policy. Based on the report from the USDA,10 it may seem that children rush eating and consume fewer calories to leave the cafeteria quickly for recess. However, this explanation did not pertain to the current study because of the fixed amount of time children were given to eat lunch at each school. Alternatively, providing meals before recess may provide adequate nourishment for children to optimize activity during subsequent recess in a manner consistent with the expectation that children may need to be nourished to move during recess. Because of differences in maturation and growth, and body composition, children’s metabolic rates may vary; therefore, their energy intake needs may differ. The finding that students
consumed fewer calories when recess followed lunch may mean that some students did not receive adequate nutritional intake. Because the study did not assess body composition (ie, percentage body fat) in the school setting, this finding warrants further study. That participants consumed fewer calories when recess was offered after lunch despite the length of time given is consistent with previous research.16,17 The authors observed that children who received lunch after recess accumulated an additional energy surplus of about 50 kcal after accounting for estimated energy expenditure during recess. Although this energy differential may seem numerically trivial, it is known that even small differences in energy surplus over extended periods can have significant implications for longterm weight regulation.30,31 Conversely, it is possible that students who consume less food at lunch may become hungry throughout the day and consume more at other times of the school day and after school. This raises questions regarding the degree to which appetite regulation had a role in the behaviors observed in this study. Furthermore, provision of school lunches through the NSLP can offset food insecurity, particularly among low-income communities.32,33 Therefore, because a fairly large proportion of students were
Journal of Nutrition Education and Behavior Volume 51, Number 5, 2019 eligible for free or reduced-price lunch, and early evidence suggesting students partaking in NSLP reported more favorable nutritional intake,34 it is important to consider the role of mealtime as an important component of nutrient consumption. The main differences observed pertained to consumption of milk and entrees, which suggests that these students may have consumed more calcium and protein than did their counterparts who received recess after lunch. Furthermore, because the main differences were observed in milk consumption, it is possible that students were thirstier after recess. Although water fountains were present in the cafeteria, the researchers could not study water intake because many students did not use water bottles. Unlike prior research,18 no differences were observed in fruit or vegetable consumption between lunch and recess timing groups. Nevertheless, the study by Price and Just18 did not control for demographic variables such as age, sex, or weight status, and therefore caution must be taken when comparing the current findings with previous investigations. Strengths of the current study included the use of objective assessment of PA and quantification of food choices within the school for the entire school week. However, several limitations are worth considering. Although this acute component (ie, lunch and recess) of the school day indicates lifestyle nutrition intake and PA, it cannot be assumed that behaviors observed reflected those throughout the day. In relation to energy expenditure, the researchers also recognize the limitation of assessing calories expended at recess alone; they did not measure energy expenditure outside this time and realize that other times of the school day, such as physical education and classroom activities, may provide students with ways to use energy. Therefore, future research might track activity, energy expenditure, and nutritional intake throughout the day and outside school to achieve an accurate depiction of children’s lifestyles. Furthermore, participants were selected through convenience sampling and limited to 1 geographical location in the US, which provided a relatively small sample from
which to draw conclusions. Considering the efforts put forth by the USDA and the NSLP to provide consistency in nutritional choices to schools throughout the country, it is important to gather data from several geographically dispersed schools. Finally, establishing the direct cause-and-effect relationship between nutritional intake at lunch and PA during recess will require randomized, controlled or crossover trials.
McLoughlin et al
3.
4.
IMPLICATIONS FOR RESEARCH AND PRACTICE The findings of the current study offer empirical support for the benefits of scheduling lunch after recess to limit total plate waste and increase consumption; nevertheless, accounting for PA-related energy expenditure revealed a more complex relationship between recess timing and health behavior that warrants further study. Alternatively, these findings indicate that beverages offered at lunch, such as milk, are more likely to be consumed if lunch is offered after recess. Collectively, these findings provide a rationale for considering overall food consumption, quality of nutritional intake, PA behaviors, and the accumulation of residual energy in the development of future policies affecting school health environments. Additional experimental and longitudinal research is needed to confirm the findings observed here, as well as the long-term consequences of lunch timing policies on children’s eating behaviors.
5.
6.
7.
8.
9.
10.
ACKNOWLEDGMENTS Sources of financial support for this study were provided by the Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, and the Illinois Association for Health, Physical Education, Recreation, and Dance.
11.
12.
REFERENCES 1. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in the United States, 20112012. JAMA. 2014;311:806-814. 2. Herman KM, Craig CL, Gauvin L, Katzmarzyk PT. Tracking of obesity
13.
14.
621
and physical activity from childhood to adulthood: the physical activity longitudinal study. Int J Pediatr Obes. 2009;4:281-288. Jung CH, Kang YM, Jang JE, et al. Fatty liver index is a risk determinant of incident type 2 diabetes in a metabolically healthy population with obesity. Obesity (Silver Spring). 2016;24:1373-1379. Saydah S, Bullard KM, Cheng Y, et al. Trends in cardiovascular disease risk factors by obesity level in adults in the United States, NHANES 1999-2010. Obesity (Silver Spring). 2014;22:18881895. De Pergola G, Silvestris F. Obesity as a major risk factor for cancer. J Obes. 2013;2013:291546. Sun JW, Zhao LG, Yang Y, Ma X, Wang YY, Xiang YB. Obesity and risk of bladder cancer: a dose-response meta-analysis of 15 cohort studies. PLoS One. 2015;10:e0119313. Vidal AC, Howard LE, Moreira DM, Castro-Santamaria R, Andriole GL, Freedland SJ. Obesity increases the risk for high-grade prostate cancer: results from the REDUCE study. Cancer Epidemiol Biomarkers Prev. 2014;23:2936-2942. Swinburn BA, Jolley D, Kremer PJ, Salbe AD, Ravussin E. Estimating the effects of energy imbalance on changes in body weight in children. Am J Clin Nutr. 2006;83:859-863. Clark MA, Fox MK. Nutritional quality of the diets of US public school children and the role of the school meal programs. J Am Diet Assoc. 2009;109(suppl 2):S44-S56. Ralston KL, Buzby JC, Guthrie JF. A Healthy School Meal Environment: Food Assistance Research Brief. Washington, DC: US Department of Agriculture, Economic Research Service; 2003. Poitras VJ, CE, Borghese MM, et al. Systematic review of the relationships between objectively measured physical activity and health indicators in school-aged children and youth. Appl Physiol Nutr Metab. 2016;41:197-239. Warburton DER, Nicol CW, Bredin SSD. Health benefits of physical activity: the evidence. Can Med Assoc J. 2006;174:801-809. Ramstetter CL, Murray R, Garner AS. The crucial role of recess in school. Pediatrics. 2013;131:183-188. Ridgers ND, Timperio A, Crawford D, Salmon J. Five-year changes in school
622
15.
16.
17.
18.
19.
20.
21.
McLoughlin et al recess and lunchtime and the contribution to children’s daily physical activity. Br J Sports Med. 2012;46:741-746. Fenton Communications. Recess Rules —Why the Undervalued Playtime May Be America’s Best Investment for Healthy Kids and Healthy Schools. Plainsboro Township, NJ: Robert Wood Johnson Foundation; 2007. Getlinger MH, Laughlin VT, Bell E, Akre C, Arjmandi BH. Food waste is reduced when elementary-school children have recess before lunch. J Am Diet Assoc. 1996;96:906-908. Hunsberger M, McGinnis P, Smith J, Beamer BA, O’Malley J. Elementary school children’s recess schedule and dietary intake at lunch: a communitybased participatory research partnership pilot study. BMC Public Health. 2014;14:156. Price J, Just DR. Lunch, recess and nutrition: responding to time incentives in the cafeteria. Prev Med (Baltim). 2015;71:27-30. Illinois State Board of Education. Illinois Report Card. https://www.illinoisreportcard.com/. Accessed August 5, 2017. Kuczmarski RJ, Ogden CL, Guo SS, et al. 2000 CDC growth charts for the United States: methods and development. Vital Health Stat. 2002;11:1-190. 11. Ptomey LT, Willis EA, Honas JJ, et al. Validity of energy intake estimated by digital photography plus recall in overweight and obese young adults. J Acad Nutr Diet. 2015;115:1392-1399.
Journal of Nutrition Education and Behavior Volume 51, Number 5, 2019 22. Food and Nutrition Service, US Department of Agriculture. National School Lunch Program and School Breakfast Program: Nutrition standards for all foods sold in school as required by the Healthy, Hunger-Free Kids Act of 2010. 78 FR 39067. https://www.federalregister.gov/documents/2013/06/28/ 2013-15249/national-school-lunch-program-and-school-breakfast-programnutrition-standards-for-all-foods-sold-in. Published June 28, 2013. Accessed July 17, 2018. 23. Pulsford RM, Cortina-Borja M, Rich C, Kinnafick FE, Dezateux C, Griffiths LJ. Actigraph accelerometer-defined boundaries for sedentary behaviour and physical activity intensities in 7 year old children. PLoS One. 2011;6:e21822. 24. Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Med Sci Sport Exerc. 2008;40:181-188. 25. Ridgers ND, Stratton G, Fairclough SJ. Assessing physical activity during recess using accelerometry. Prev Med. 2005;41:102-107. 26. US Department of Health and Human Services. 2008 Physical Activity Guidelines for Americans. https://health. gov/paguidelines/guidelines/. Accessed September 21, 2017. 27. Treuth MS, Schmitz K, Catellier DJ, et al. Defining accelerometer thresholds for activity intensities in adolescent girls. Med Sci Sports Exerc. 2004;36:1259-1266.
28. Puyau MR, Adolph AL, Vohra FA, Butte NF. Validation and calibration of physical activity monitors in children. Obes Res. 2002;10:150-157. 29. Huberty JL, Beets MW, Beighle A, Saint-Maurice PF, Welk G. Effects of ready for recess, an environmental intervention, on physical activity in third-through sixth-grade children. J Phys Act Health. 2014;11:384-395. 30. Hill JO. Can a small-changes approach help address the obesity epidemic? A report of the Joint Task Force of the American Society for Nutrition, Institute of Food Technologists, and International Food Information Council. Am J Clin Nutr. 2009;89:477-484. 31. Hill JO, Peters JC. Environmental contributions to the obesity epidemic. Science. 1998;280:1371-1374. 32. Nguyen BT, Ford CN, Shuval K, Drope J, Yaroch AL. Food security and weight status in children: interactions with food assistance programs. Am J Prev Med. 2017;52(suppl 2):S138-S144. 33. Gundersen C, Kreider B, Pepper J, Tarasuk V. Food assistance programs and food insecurity: implications for Canada in light of the mixing problem. Empir Econ. 2017;52:1065-1087. 34. Au LE, Gurzo K, Gosliner W, Webb KL, Crawford PB, Ritchie LD. Eating school meals daily is associated with healthier dietary intakes: the Healthy Communities Study. J Acad Nutr Diet. 2018;118:1474-1481.