The Impact of Modifying Food Service Practices in Secondary Schools Providing a Routine Meal Service on Student’s Food Behaviours, Health and Dining Experience: A Systematic Review and Meta-Analysis
Abstract
:1. Introduction
2. Materials and Methods
2.1. Search Strategies
2.2. Study Selection
2.3. Eligibility Criteria
2.4. Data Extraction and Management
2.5. Risk of Bias and Quality Criteria
2.6. Data Analysis
2.6.1. Classification of Intervention Strategies
2.6.2. Grouping of Outcomes Measured
2.6.3. Impact of Interventions
Meta-Analysis
Vote-Counting Based on the Direction of Effect
Narrative Summary
3. Results
3.1. Search Results
3.2. General Characteristics of Included Studies
3.3. Risk of Bias and Quality Assessment
3.4. Data Analysis
3.4.1. Intervention Strategies
3.4.2. Outcomes Measured
- Student selection of a meal component: measured as either (i) percent of students selecting, (ii) numbers of serves selected, or (iii) amount selected using weight or fluid measurements; assessed in n = 26 interventions (62%) and included fruit (n = 17), vegetables (n = 18), entrée (n = 11), milk (n = 11), grains (n = 4), protein foods (n = 3), energy (n = 2), and desserts, overall meal, healthier foods, sides and saturated fat (each, n = 1).
- Student consumption of a meal component: measured as either (i) percent of serve consumed, (ii) number of serves consumed, or (iii) amount consumed using weight of fluid measurements; assessed in n = 24 interventions (57%) and included measures of fruit (n = 14), vegetables (n = 15), milk (n = 10), entrée and energy (each, n = 5), protein foods and saturated fat (each, n = 4), grains, calcium, iron, sodium, total fat, vitamin A and vitamin C (each, n = 3), fibre and sodium (each, n = 2), overall meal, healthier foods, sides, carbohydrates, folate and zinc (each, n = 1).
- Health status: Blood pressure (BP) was measured in n = 1 intervention to assess the impact of reduced sodium in school meals. Body mass index (BMI) was measured in n = 1 intervention to assess the impact of interactive kiosks to guide student lunch choices.
- Knowledge: One study (n = 2 intervention arms) measured knowledge about fish before and after an intervention that aimed to increase students’ intake of fish at school and included classroom education about fish preparation in the school kitchen.
- Meal program participation rate: assessed in n = 5 studies and represents the proportion of enrolled students that participated in the school meal program pre-and post-intervention, reflecting population level selection/acceptance of the school meal program without separating components of the meal program or reflect consumption.
- Attitudes and perceptions related to changes to the meal service: assessed in n = 15 interventions (n = 13 with before and after measurements) to assess students’ attitude toward school lunch and the cafeteria, acceptability of modified or new menu items, or feedback on intervention components.
3.4.3. Impact of Interventions
Meta-Analysis
- Number of students selecting a meal component (Supplementary Materials Figure S1): Four separate meta-analyses were prepared for fruit (n = 7 studies), vegetables (n = 8 studies), entrée (n = 6 studies; 7 interventions) and milk (n = 6 studies). The pooled effect showed interventions increased the proportion of students selecting vegetables (OR: 1.39; 95% CI: 1.12, 1.73; p = 0.002), with no change in the proportion of students selecting fruit (OR: 1.03; 95% CI: 0.84, 1.27; p = 0.774), entrée (OR: 1.03; 95% CI: 1.00, 1.06; p = 0.076) or milk (OR: 0.96; 95% CI: 0.91, 1.01; p = 0.088).
- Percent of serve consumed of a meal component by students (Supplementary Materials Figure S2a): Four separate meta-analyses were prepared for fruit (n = 5 studies), vegetables (n = 6 studies), entrée (n = 4 studies) and milk (n = 5 studies). The pooled effect found no change in the percent of serve consumed by students who selected fruit (mean difference MD: 2.99; 95% CI: −2.24, 8.21; p = 0.262), vegetables (MD: 8.64; 95% CI: −4.67, 21.94; p = 0.203), entrée (MD: 4.46; 95% CI: −0.93, 9.84; p = 0.105) or milk (MD: 0.88; 95% CI: −5.61, 7.36; p = 0.791). Supplementary Materials Figure S2b presents a sensitivity analysis excluding Wansink et al. [95] (1 day intervention measuring vegetable consumption) and an improved pooled effect for vegetables (MD: 13.69; 95% CI: 6.09, 21.28; p < 0.001).
- Mean number of serves of a meal component selected per student per day (Supplementary Materials Figure S3a): Two separate meta-analyses were prepared for fruit (n = 4 studies) and vegetables (n = 4 studies). The pooled effect showed interventions increased the number of fruit serves selected per student per day (MD: 0.09; 95% CI: 0.09, 0.09; p < 0.001), with no change in vegetable serves selected (p = 0.977). The pooled estimate for both fruit and vegetable serves selected per student per day is not a good representation due to the large sample size for one study (Bogart et al., 2014 [88]; n = 102,262) that highly influenced the pooled estimate (weighting > 99%). A sensitivity analysis excluded this study (Supplementary Materials Figure S3b). The pooled effect of remaining three studies showed an increase in serves selected per student per day of fruit (MD: 0.14; 95% CI: 0.08, 0.20; p < 0.001) and vegetables (MD: 0.11; 95% CI: 0.05, 0.18; p = 0.001).
- Mean number of serves of a meal component consumed per student per day (Supplementary Materials Figure S4): Two separate meta-analyses were prepared for fruit (n = 4 studies) and vegetables (n = 4 studies). The pooled effect showed interventions increased the number of serves consumed per student per day of fruit (MD: 0.10; 95% CI: 0.04, 0.15; p < 0.001) and vegetables (MD: 0.06; 95% CI: 0.01, 0.10; p = 0.024).
Vote Counting Based on the Direction of Effect
- Intervention duration: there was evidence that shorter interventions (≤2 months) had greater impact on selection and consumption of a meal component compared to longer interventions (≥3 months): selection, 12 of 15 short interventions favoured the intervention (80%; 95% CI: 55% to 93%, p = 0.003) compared to 3 of 10 longer interventions (30%; 95% CI: 11% to 60%, p = 0.625); consumption, 8 of 13 short interventions favoured the intervention (62%; 95% CI: 36% to 82%, p = 0.109) compared to 6 of 11 longer interventions (55%; 95% CI: 28% to 79%, p = 0.125).
- NOURISHING framework domains: there was evidence that interventions targeting three domains had a greater impact on selection and consumption of a meal component compared to interventions targeting less (≤2): selection, 10 of 15 targeting three domains favoured the intervention (67%; 95% CI: 42% to 85%, p = 0.012), compared to 5 of 10 targeting ≤2 domains (50%; 95% CI: 24% to 76%, p = 0.219); consumption, 9 of 15 targeting three domains favoured the intervention (60%; 95% CI: 36% to 80%, p = 0.065), compared to 5 of 9 targeting ≤2 domains (56%; 95% CI: 27% to 81%, p = 0.219).
- NOURISHING framework action areas: there was evidence that interventions targeting more action areas (≥3) had a greater impact on selection and consumption of a meal component compared to interventions that targeted less (≤2): selection, 11 of 16 with more action areas favoured the intervention (69%; 95% CI: 44% to 86%, p = 0.006), compared to 4 of 9 with less (44%; 95% CI: 19% to 73%, p = 0.375); consumption, 11 of 17 with more action areas favoured the intervention (65%; 95% CI: 41% to 83%, p = 0.022), compared to 3 of 7 with fewer (43%; 95% CI: 16% to 75%, p = 0.625).
- Student engagement: there was evidence that interventions that engaged students in development and/or implementation had a greater impact on selection and consumption of a meal component compared to interventions without student engagement: selection, 7 of 9 with student engagement favoured the intervention (78%; 95% CI: 45% to 94%, p = 0.016), compared to 8 of 16 without student engagement (50%; 95% CI: 28% to 72%, p = 0.109); consumption, 5 of 6 with student engagement favoured the intervention (83%; 95% CI: 44% to 97%, p = 0.063), compared to 9 of 18 without student engagement (50%; 95% CI: 29% to 71%, p = 0.146).
Narrative Summary
# | Author, Year of Publication | Study Design, Study Duration + (Dates) | Setting | Sample Characteristics | Study Aims | Intervention Duration + (Dates), Components * | Intervention Detail |
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1 | Askelson et al., 2019 [117] | Before-after Pilot 1 y (2016) | USA, Iowa, rural and urban areas | 6 middle schools (5 rural and 1 urban); 1 intervention Grades served by schools K-12; 5–8; 6–8 and 7–8 Enrolment across all schools, n = 3326, range n = 341–1140 per school; all students exposed to intervention; age NR; eligible for FRP lunch, range 18% to 42% | To improve the lunchroom environment to promote healthy food choices and empower food service staff with the knowledge, skills, and ability to communicate with students about making healthy choices in the lunchroom | 1 y (2016)
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2 | Bean et al., 2019 [102] | Before-after 2 y (2014–2016) | USA, Virginia | 16 schools: 8 middle, 8 high; 1 intervention Demographic data: student sample size or age NR School district demographics: 75% African American, 13% Hispanic, 9% white, 1% Asian, 2% other ethnicity; 83% of schools with >90% NSLP participation rate | To examine the impact of food service staff training on Smarter Lunchroom adherence in school cafés | 2 y (2014–2016)
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3 | Bhatia et al., 2011 [44] | Before-after Pilot 2 y (2008–2010) | USA, San Francisco, California | 3 schools: 1 middle school, 2 high schools; 1 intervention Demographic data: enrolment across all schools, n = 4304; student age NR | To examine the impact of removing competitive a la carte lunch offerings and providing greater diversity of meal offerings for all students, on NSLP participation rates | 5 m (January–May 2010)
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4 | Boehm et al., 2020 [96] | Controlled before-after (random allocation of schools) Pilot 9 m (September 2013–May 2014) | USA, Northeast USA, urban area | 3 high schools; 2 interventions 2 I-schools: (1) Choices school, n = 1177 enrolled students, (2) Nudging school, n = 2140 enrolled students 1 C-school: n = 1297 enrolled students Demographics: student age NR; ethnic diversity (NS differences across schools); >95% students eligible for FRP meals, therefore free meals provided to all students | To compare federally reimbursable meals served when competitive foods are removed and when marketing and nudging strategies are used in school cafeteria operating the NSLP | 4 w (April–May 2014)
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5 | Bogart et al., 2011 [109] | Controlled before-after (non-random allocation of schools) Pilot 15 w (dates NR) | USA Los Angeles, California | 2 middle schools, 1 intervention 1 I-school, 1 C-school Similar demographic data for ethnicity and 77% students eligible for FRP lunch I-school: n = 399 7th grade students completed pre and post surveys (50% female, mean age 13, SD 0.5); n = 140 7th grade student advocates; enrolled students or student sample size NR | To pilot a community-based intervention for adolescents, Students for Nutrition and eXercise (SNaX) to translate school obesity-prevention policies into practice through peer leader advocacy of healthy eating and school cafeteria changes | 5 w (dates NR)
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6 | Bogart et al., 2014 [88] | Cluster randomised trial (controlled) 3.5 y (January 2009–June 2012) | USA Los Angeles, California | 10 middle schools, 1 intervention Similar demographic data for ethnicity; >83% students eligible for FRP lunch; student age and gender NR 5 I-schools, n = 1515 mean number of students enrolled per school (SD = 323) 5 C-schools, n = 1524 mean number of students enrolled per school (SD = 266) n = 2997 7th grade students from I-school completed B and FU surveys | To conduct an RCT of SNaX, and examine effect on cafeteria participation, student eating behaviours and cafeteria attitudes | 5 w per school (during spring semester each y; January to June)
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7 | Bogart et al., 2018 [110] | Cluster non-randomised trial (controlled) 2 y (2013–2015) | USA Los Angeles, California | 65 middle schools, 1 intervention n = 17 I-schools, n = 22311 enrolled students, 70% students in NSLP; n = 47 C-schools, n = 56,120 enrolled students, 86% students in NSLP n = 242 student advocates at end of I-year (student grade NR) n = 187 students completed student advocate surveys n = 154 student advocates participated in post-I focus groups | To disseminate an evidence-based middle-school obesity-prevention program, SNaX | 5 w per school (1 y across all schools; 2014–2015)
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8 | Chu et al., 2011 [118] | Non-randomised trial (controlled, crossover) 1 y (spring and fall semesters 2009) | USA, Minnesota, Texas, urban and suburban areas | 5 schools, 2 interventions 3 middle schools (1 Minnesota, 2 Texas), 2 high schools (1 Minnesota, 1 Texas) Demographics: Hispanic students, Texas range 25.7% to 54.5%, Minnesota range 1.4% to 35.6%; non-Hispanic, Texas range 1.7% to 47.3%, Minnesota range 26% to 94.7%; students eligible for FRP meals, range 30.5% to 100% across all schools; student age not reported | To compare student acceptance of whole-wheat vs. refined tortillas in school meals according to sensory attribute ratings | 30 w (2 school semesters, 2009)
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9 | Cohen et al. 2012 [89] 2013 [119] | Cluster non-randomised trial (controlled, parallel arm) Pilot 2 y (2007–2009) | USA, MA, Boston | 4 middle schools, 1 intervention 2 I-schools: 88% eligible for FRP meals, 78% participation in NSLP, n = 1609 student participants 2 C-schools, 86% eligible for FRP meals, 70% participation in NSLP, n = 1440 student participants Students in grades 6–8, most aged 12–14 years | 2012: To evaluate the impact of chef-based model on student’s selection and consumption of school lunches 2013: To assess the impact of food waste on nutrient consumption, if school foods served could be valid proxies for food consumed, and costs associated with food waste | 2 y (2007–2009)
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10 | Cullen et al., 2007 [114] | Before-after Pilot 1 y (spring 2003–spring 2004) | USA, California, North Carolina, Texas | 6 middle schools, 1 intervention 2 California, n = 2873 students 2 North Carolina, n = 1565 students 2 Texas, n = 1810 students Student age NR; baseline differences in ethnicity and eligibility for FRP meals (range, 55–97%) between schools | To examine the feasibility of instituting school food environment changes during a 6-week pilot in school foodservice programs | 6 w (winter/spring 2004)
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11 | Cullen et al., 2008 [103] Mendoza et al., 2010 [104] | Before-after 5 y (2001–2006) | USA, Texas | 3 middle schools, 1 intervention Students in grades 6–8; n = 2690 enrolled students across all schools (2001–2002 school year), and n = 3306 (2005–2006 school year) FRP eligibility, range 26–68% in 2001–2002, and 38–75% in 2005–2006 | To assess the effect of the Texas Public School Nutrition Policy on middle school student lunchtime food consumption | 2 y (2004–2006)
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12 | Cullen et al., 2015 [90] | Cluster randomised trial (controlled, parallel arm) Pilot 15 w (fall 2011) | USA, TX, Houston | 4 intermediate schools, 1 intervention 2 I-schools, 2 C-schools Student age or enrolment numbers NR; Sample size for observations, n = 427 students (I-schools, n = 212; C-schools, n = 215) | To investigate changes in student food selection and consumption in response to the new NSLP meal patterns during fall 2011 | 15 w (fall 2011)
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13 | D’Adamo et al., 2021 [113] | Non-randomised trial (controlled, crossover) 2 y (dates NR) | USA, Maryland, Baltimore, urban area | 1 high school, 1 intervention I-group (herbs and spices), C-group (typical recipe) n = 273 enrolled students Demographics: 57% female, African American 76% Hispanic 10%, ≥2 races 10%, White 4%, Asian < 1%, 100% eligible for FRP meals All students provided lunch trays for veg plate waste assessment | To determine whether stakeholder-informed addition of spices and herbs to NSLP veg would increase intake | 4 school semesters (dates NR)
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14 | Elbel et al., 2015 [107] | Cluster non-randomised trial (controlled) 11 m (November 2010–September 2011) | USA, New York, NYC | 17 schools (includes elementary, middle and high schools; split between school type unknown), 1 intervention 8 I-schools, 9 C-schools I-schools: n = 1091 mean number of students/school, 55% female, 54% eligible for FRP meals, 21% African American, 41% Hispanic, 25% White, 11% Asian C-schools: n = 1175 mean number of students/school, 52% female, 47.1% eligible for FRP meals, 13% African American, 33% Hispanic, 33% White, 20% Asian Sub-set of larger study separated survey data for middle and high school (8th and 11th grade; n = 1759 students). | To determine the influence of water-jets on observed water and milk taking and self-reported fluid consumption in NYC public schools | 10 m (December 2010–September 2011)
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15 | Ellison et al. 1989 a [115] 1989 b [100] 1990 [116] | Controlled before-after (non-randomised) 4 y (1984–1988) | USA, NH and MA | 2 boarding high schools, 2 interventions (phase 1 and 2) Student mean age 15 years, almost none obese, 77% white 1989a: Sodium intake from food diary assessment, at B n = 674 (I-group n = 340, C-group n = 334), at FU n = 431 (I-group n = 221, C-group n = 210); 1700 ballots for food acceptability rating 1989b: BP assessment, n = 650 students (I-group n = 309, C-group n = 341) 1990: Fat intake from food diary assessment, at B n = 774 (I-group n = 389, C-group n = 385), at FU n = 467 (I-group n = 228, C-group n = 239) | To measure the effects of changes in food purchasing and preparation practices on student acceptability of modified foods, sodium and fat intake, and BP | 6 m/phase (phase 1: reduced sodium; phase 2: modified fat; years unclear)
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16 | Fritts et al., 2019 [120] | Phase 1: Non-randomised trial (controlled, crossover) Phase 2: Before-after 10 m (March–December 2017) | USA, Pennsylvania, rural area | 1 middle/high school, 2 interventions (phase 1 and 2) I-group (herb and spice veg), C-group (lightly salted veg); approx. 75% students participate in the NSLP, and 44% received FRP lunch; 600–700 students aged 11–18 years were served lunch daily across 3 lunch periods School district demographics: 97% Caucasian | To test whether adding herbs and spices to school lunch veg increases selection and consumption compared with lightly salted veg among rural adolescents | 10 m (March–December 2017)
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17 | Greene et al., 2017 [91] | Cluster randomised trial (controlled) 9 w (February–April 2014) | USA, New York, urban and rural districts | 7 middle schools, 1 intervention 4 I-schools (2 urban, 2 rural) and 3 C-schools (2 urban, 1 rural) I-schools: n = 1258 enrolled students, 1–97% white, 55–92% economic disadvantage C-schools: n = 850 enrolled students, 5–90% white, 49–92% economic disadvantage All students in grades 5–8, age NR | To evaluate the impact of fruit-promoting Smarter Lunchroom interventions on middle school students’ selection and consumption of fruit | 6 w (March–April 2014)
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18 | Hackett et al., 1990 [121] | Controlled before-after (non-randomised) 1 y (July 1987–July 1988) | UK, Northum-berland county | 4 middle schools, 2 interventions 2 ‘dish of day free-choice’ I-schools; 2 ‘2 course fixed price’ I-schools 2 ‘affluent’ and 2 ‘less well-off’ schools (each allocated 1 free-choice I-school and 1 fixed-price I-school); Approx. n = 830 students aged 11–12 years across all schools Completion of surveys with school meal participation data: survey 1, n = 674 (n = 301 from free-choice I-schools, n = 373 from fixed-price I-schools); survey 2, n = 692 students (n = 333 from free-choice I-schools, n = 359 from fixed-price I-schools) | To improve the quality of school meals and their up-take via a healthy eating campaign | 10 m (October–December 1987)
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19 | Hanks et al., 2012 [122] | Before-after 4 m (February–May 2011) | USA, New York, Corning | 1 high school, 1 intervention | To examine the application of the principle that healthier foods are more likely to be consumed if they were more convenient than less convenient less healthy foods | 2 m (April–May 2011)
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20 | Hanks et al., 2013 [97] | Before-after Pilot 4 m (March–June 2011) | USA, New York | 2 high schools, 1 intervention Grades 7–12, student numbers, age and other demographics NR | To investigate how small changes to school cafeterias can influence the choice and consumption of healthy foods | 2 m (May–June 2011)
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21 | Hunsberger et al., 2015 [123] | Before-after 4 m (January–April 2010) | USA, Oregon, rural area | 1 middle school, 1 intervention Students in grades 6–8, aged 11–15 years, 64.6% of ethnic minority, 32.5% have BMI >95th percentile (obese), 79% eligible for FRP meals, n = 531 average number of students/day that participated in the NSLP (78%) during study period | To investigate the impact of POS calorie information | 17 d (February 2010)
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22 | Just et al., 2014 [93] | Before-after Pilot 3 m (February–April 2012) | USA, New York | 1 high school, 1 intervention n = 370 enrolled students, aged 13–18 years; School district demographics: ethnicity primarily white (93.9%), eligibility for FRP meals 19.8% | To conduct a pilot test to gauge the feasibility of the Chef Moves To School program, and measure student response through lunch selection and consumption | 2 d (April 2012)
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23 | Koch et al., 2020 [124] | Before-after 2 y (2017–2018) | USA, New York City, NY | 7 high schools, 1 intervention All students eligible to participate; n = 5719 enrolled students across all schools, 74% eligible for FRP lunch, age NR | To measure the effects of major changes to school cafeterias (STARCafe) on school lunch consumption and factors that may influence consumption (i.e., seated time, attitudes towards school lunch, perception of cafeteria noise, school lunch participation) | 1 y per school (2017–2018)
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24 | Madden et al., 2013 [105] | Before-after 3 w (2005) | UK, London | 1 secondary school, 1 intervention Student participants aged 12–16 years, n = 378 lunch observations, pre-I n = 180 (38.9% female), post-I n = 198 (26.3% female) 63% students eligible for free school lunch | To examine the effect of a short, low-budget kitchen-based intervention on energy, nutrient, and fruit and veg intakes | 1 w (2005)
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25 | McCool et al., 2005 [108] | Non-randomised trial (controlled, crossover) Pilot 12 w (dates NR) | USA, metropolitan area | 1 middle school, 3 interventions (phase 1–3) Enrolled students, n = 1234, age NR, 87.4% eligible for FRP meals | To compare the amount of apple consumed by students when they were offered whole versus sliced ready-to-eat packaged apples | 12 w (dates NR; phase 1 = 6 weeks, phase 2 = 4 weeks, phase 3 = 2 weeks)
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26 | Pope et al., 2018 [94] | Before-after Pilot 3 m (September–November 2015) | USA, Vermont, rural area | 1 middle school, 1 intervention n = 587 eligible students in grades 4–8 eligible to participate; average NSLP participation rate = 66% Student age NR; numbers who participated in taste-testing NR | To investigate whether providing samples of a veg-focused lunch entrée the day before it appeared on the lunch menu ↑ NSLP participation | 1 m (October 2015)
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27 | Prell et al., 2005 [101] | Controlled before-after (randomised) 5 w (1998–1999 school year) | Sweden, Göteborg | 3 secondary schools: 2 interventions (1) C-group, no intervention, n = 83 students (63% participation) (2) SL-group (school lunch intervention), n = 58 students (51% participation) Grade 8, aged approx. 14 years (3) SLHE-group (SL + home economics intervention), n = 87 students (60% participation) | To examine the effectiveness of 2 school-based interventions aimed at increasing adolescents’ intake of fish at school | 5 w
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28 | Prescott et al., 2019 [99] | Controlled before-after (non-random allocation of schools) 6 m (November 2017–April 2018) | USA, Colorado | 2 middle schools, 1 intervention (1) I-group (poster + education), n = 268 grade 6 students across 2 schools (2) C-group (poster only), n = 426 students in grades 7–8 across 2 schools | To examine the impact of a student-driven sustainable food systems education and promotion intervention on adolescent school lunch selection, consumption and waste behaviours, particularly for fruit and veg, during school lunch | 12–16 classes (from December 2017) + 2 weeks (April 2018)
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29 | Quinn et al., 2018 [98] | Controlled before-after (non-random allocation of schools) 1 y (2013–2014 school year) | USA, Washington, King County | 11 schools, 1 intervention 6 I-schools (3 middle and 3 high schools; n = 1026 mean number students enrolled per school), 5 C-schools (3 middle and 2 high schools; n = 1219 mean number students per school) n = 2309 tray observations across all schools and time points Student age not reported | To evaluate whether a year-long choice architecture intervention implemented by school cafeteria managers changed student selection and consumption of healthy foods | 1 y (2013–2014)
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30 | Schwartz et al., 2015 [92] | Before-after 3 y (2012–2014) | USA, Connecticut, New Haven, low-income urban area | 12 middle schools, 1 intervention Approx. n = 680 enrolled students in grade 5 (all schools); Sample population followed over 3 years, n = 502 in grade 5 (2012), n = 465 in grade 6 (2013) and n = 373 in grade 7 (2014) School district demographics: >70% eligible for free-lunch, 13% for reduced-price; 47% African American, 38% Hispanic, 15% white | To examine food component selection and consumption data pre- and post- revisions to the NSLP nutrition standards and policies | 2 y (2012–2014)
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31 | Sharma et al., 2018 [106] | Non-randomised trial (controlled, parallel arm) 4 w (November–December, y NR) | USA | 1 middle-high school, 1 intervention I-group, 1 fast service lane (FSL) C-group, 2 regular service lanes (RSL) Approx. n = 650 enrolled students in grades 6–12 | To investigate whether middle and high school students are averse to loss of time and to assess feasibility of a fast food service lane intervention that would serve limited choices of pre-plated lunch meals | 4 w (November–December, year NR)
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32 | Turnin et al., 2016 [112] | Before-after 1 y (dates NR) | France, Toulouse, suburban and urban areas | 3 middle schools (1 suburban, 2 urban), 1 intervention n = 350 students for analysis, mean age 13.3 years (range, 11.5 to 16.4 years) School A, B and C; n = 84, 88 and 178 students respectively | To evaluate the impact of interactive Nutri-Advice kiosks on children’s nutritional skills and their ability to apply it to food choices in a middle school cafeteria menu (food choice competencies) | 6 m (November–May, year NR)
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33 | Wansink et al., 2015 [95] | Before-after Pilot 2 m (March–April 2012) | USA, New York, Lansing | 1 high school, 1 intervention n = 370 enrolled students in grades 9–12; age not reported School district demographics: 93.9% white, 2% African American; 19% students eligible for FRP lunch | To examine the potential impact that a school garden intervention, independent of corresponding educational materials, has on students veg selection and intake | 1 d (24 April 2012)
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34 | Wansink et al., 2013 [111] | Cluster randomised trial (controlled) Duration unclear (2011) | USA, New York, Wayne County | 6 middle schools, 1 intervention 3 I-schools, 3 C-schools n = 2150 enrolled students across all schools | To determine the effect of offering pre-sliced fruit in schools on selection and intake | 1 m (November 2011)
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35 | Witschi et al. 1985 [125] | Before-after Pilot 9 w (Oct-Nov 1982) | USA, New Hampshire | 1 boarding high school, 1 intervention Approx. n = 1000 enrolled students; To monitor sodium intake: n = 228 students aged 15–18 years Palatability survey responses: n = 1036 (pre-I) and 748 (during-I) | To test the effects of dietary modification on total sodium intake of students and assess palatability for adolescents | 5 w (October–November 1982)
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Domain * | Action Areas * | Sub-Action Areas Relevant to the Current Review * | Classification of Intervention Strategies from Included Studies | |
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Food environment | N | Nutrition label standards and regulations on use of claims and implied claims on food |
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O | Offer healthy food and set standards in public institutions and other specific settings |
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U | Use economic tools to address food affordability and purchase incentives |
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R | Restrict food advertising and other forms of commercial promotion |
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I | Improve nutritional quality of the whole food supply |
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S | Set incentives and rules to create a healthy retail and food service environment |
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Food system | H | Harness food supply chain and actions across sectors to ensure coherence with health |
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Behaviour change communication | I | Inform people about food and nutrition through public awareness |
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N | Nutrition advice and counselling in health care settings |
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G | Give nutrition education and skills |
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Food Environment | Food System | Behavior Change Communication | |||||||
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N | O | U | I | S | H | I | G | ||
Author | Number of Action Areas Targeted | Nutrition Label Standards and Regulations on Use of Claims and Implied Claims on Food | Offer Healthy Food and Set Standards in Public Institutions or Other Settings | Use Economic Tools to Address Food Affordability and Purchase Incentives | Improve Nutritional Quality of the Whole Food Supply | Set Incentives and Rules to Create a Healthy Retail and Food Service Environment | Harness Food Supply Chain and Actions Across Sectors to Ensure Coherence with Health | Inform People about Food and Nutrition through Public Awareness | Give Nutrition Education and Skills |
Interventions that include strategies across three domains: | |||||||||
Bhatia et al., 2011 [44] | 6 | • | • | • | • | • | • | ||
Bogart et al., 2011 [109] | 6 | • | • | • | • | • | • | ||
Bogart et al., 2014 [88] | 6 | • | • | • | • | • | • | ||
Bogart et al., 2018 [110] | 6 | • | • | • | • | • | • | ||
Askelson et al., 2019 [117] | 5 | • | • | • | • | • | |||
Greene et al., 2017 [91] | 5 | • | • | • | • | • | |||
Madden et al., 2013 [105] | 5 | • | • | • | • | • | |||
Prell et al., 2005 1. SL [101] | 5 | • | • | • | • | • | |||
Prell et al., 2005 2. SLHE [101] | 5 | • | • | • | • | • | |||
Quinn et al., 2018 [98] | 5 | • | • | • | • | • | |||
Fritts et al., 2019 1. Phase 1 [120] | 4 | • | • | • | • | ||||
Fritts et al., 2019 2. Phase 2 [120] | 4 | • | • | • | • | ||||
Hanks et al., 2013 [97] | 4 | • | • | • | • | ||||
Koch et al., 2020 [124] | 4 | • | • | • | • | ||||
Pope et al., 2018 [94] | 4 | • | • | • | • | ||||
Prescott et al., 2019 [99] | 4 | • | • | • | • | ||||
Wansink et al., 2015 [95] | 4 | • | • | • | • | ||||
Cullen et al., 2007 [114] | 3 | • | • | • | |||||
D’Adamo et al., 2021 [113] | 3 | • | • | • | |||||
Ellison et al., 1989a [115], 1989b [100] | 3 | • | • | • | |||||
Ellison et al., 1990 [116] | 3 | • | • | • | |||||
Just et al., 2014 [93] | 3 | • | • | • | |||||
Interventions that include strategies across two domains: | |||||||||
Bean et al., 2019 [102] | 4 | • | • | • | • | ||||
Boehm et al., 2020 2. Nudges [96] | 3 | • | • | • | |||||
Hackett et al., 1990 2. Fixed price [121] | 3 | • | • | • | |||||
Sharma et al., 2018 [106] | 3 | • | • | • | |||||
Chu et al., 2011 1. 66% wholewheat [118] | 2 | • | • | ||||||
Chu et al., 2011 2. 100% wholewheat [118] | 2 | • | • | ||||||
Cohen et al., 2012 [89], 2013 [119] | 2 | • | • | ||||||
Cullen et al., 2015 [90] | 2 | • | • | ||||||
Hackett et al., 1990 1. Dish of day [121] | 2 | • | • | ||||||
Witschi et al., 1982 [125] | 2 | • | • | ||||||
Interventions that include a strategy or strategies in one domain only: | |||||||||
McCool et al., 2005 1. Phase 2 vs. 1 [108] | 3 | • | • | • | |||||
McCool et al., 2005 2. Phase 3 [108] | 3 | • | • | • | |||||
Elbel et al., 2015 [107] | 2 | • | • | ||||||
Hanks et al., 2012 [122] | 2 | • | • | ||||||
Boehm et al., 2020 1. Choices [96] | 1 | • | |||||||
Cullen et al., 2008 [103]; Mendoza et al., 2010 [104] | 1 | • | |||||||
Hunsberger et al., 2015 [123] | 1 | • | |||||||
Schwartz et al., 2015 [92] | 1 | • | |||||||
Turnin et al., 2016 [112] | 1 | • | |||||||
Wansink et al., 2013 [111] | 1 | • | |||||||
3 | 26 | 4 | 19 | 21 | 25 | 22 | 18 |
Outcome Domain | Interventions, n | Positive Impact, n (%) | Negative Impact, n | No Change or Mixed Effects | Sign Test, p-Value * | 95% CI ** | |
---|---|---|---|---|---|---|---|
Selection of a meal component | |||||||
Study quality | Positive rating | 8 | 5 (63%) | 0 | 3 | 0.063 | 31% to 86% |
Neutral rating | 17 | 10 (59%) | 2 | 5 | 0.039 | 36% to 78% | |
Study design | Pre-post assessment | 22 | 15 (68%) | 2 | 5 | 0.002 | 47% to 84% |
Parallel arm or crossover | 3 | 0 (0%) | 0 | 3 | NA | NA | |
Intervention duration | ≤2 months | 15 | 12 (80%) | 1 | 2 | 0.003 | 55% to 93% |
3+ months | 10 | 3 (30%) | 1 | 6 | 0.625 | 11% to 60% | |
NOURISHING domains | Three domains | 15 | 10 (67%) | 1 | 4 | 0.012 | 42% to 85% |
One or two domains | 10 | 5 (50%) | 1 | 4 | 0.219 | 24% to 76% | |
NOURISHING action areas | Three to six action areas | 16 | 11 (69%) | 1 | 4 | 0.006 | 44% to 86% |
One to two action areas | 9 | 4 (44%) | 1 | 4 | 0.375 | 19% to 73% | |
Stakeholder engagement | Student engagement | 9 | 7 (78%) | 0 | 2 | 0.016 | 45% to 94% |
Without | 16 | 8 (50%) | 2 | 6 | 0.109 | 28% to 72% | |
Behaviour change communication | Promotion and/or training | 18 | 11 (61%) | 1 | 6 | 0.006 | 39% to 80% |
Without | 7 | 4 (57%) | 1 | 2 | 0.375 | 25% to 84% | |
Consumption of a meal component | |||||||
Study quality | Positive rating | 3 | 0 (0%) | 0 | 3 | NA | NA |
Neutral rating | 21 | 14 (67%) | 3 | 4 | 0.013 | 45% to 83% | |
Study design | Pre-post assessment | 18 | 11 (61%) | 2 | 5 | 0.022 | 39% to 80% |
Parallel arm or crossover | 6 | 3 (50%) | 1 | 2 | 0.625 | 19% to 81% | |
Intervention duration | ≤2 months | 13 | 8 (62%) | 2 | 3 | 0.109 | 36% to 82% |
3+ months | 11 | 6 (55%) | 1 | 4 | 0.125 | 28% to 79% | |
NOURISHING domains | Three domains | 15 | 9 (60%) | 2 | 4 | 0.065 | 36% to 80% |
One or two domains | 9 | 5 (56%) | 1 | 3 | 0.219 | 27% to 81% | |
NOURISHING action areas | Three to six action areas | 17 | 11 (65%) | 2 | 4 | 0.022 | 41% to 83% |
One to two action areas | 7 | 3 (43%) | 1 | 3 | 0.625 | 16% to 75% | |
Stakeholder engagement | Student engagement | 6 | 5 (83%) | 0 | 1 | 0.063 | 44% to 97% |
Without | 18 | 9 (50%) | 3 | 6 | 0.146 | 29% to 71% | |
Behaviour change communication | Promotion and/or training | 17 | 9 (53%) | 2 | 6 | 0.065 | 31% to 74% |
Without | 7 | 5 (71%) | 1 | 1 | 0.219 | 36% to 92% | |
Meal program participation rate | |||||||
Study quality | Positive rating | 0 | 0 (0%) | 0 | 0 | NA | NA |
Neutral rating | 5 | 3 (60%) | 2 | 0 | NA | 23% to 88% | |
Study design | Pre-post assessment | 5 | 3 (60%) | 2 | 0 | NA | 23% to 88% |
Parallel arm or crossover | 0 | 0 (0%) | 0 | 0 | NA | NA | |
Intervention duration | ≤2 months | 1 | 1 (100%) | 0 | 0 | NA | NA |
3+ months | 4 | 2 (50%) | 2 | 0 | NA | 15% to 85% | |
NOURISHING domains | Three domains | 3 | 3 (100%) | 0 | 0 | 0.250 | 44% to 100% |
One or two domains | 2 | 0 (0%) | 2 | 0 | NA | 0% to 66% | |
NOURISHING action areas | Three to six action areas | 4 | 3 (75%) | 1 | 0 | 0.625 | 30% to 95% |
One to two action areas | 1 | 0 (0%) | 1 | 0 | NA | NA | |
Stakeholder engagement | Student engagement | 2 | 2 (100%) | 0 | 0 | 0.500 | 34% to 100% |
Without | 3 | 1 (33%) | 2 | 0 | NA | 6% to 79% | |
Behaviour change communication | Promotion and/or training | 5 | 3 (60%) | 2 | 0 | NA | 23% to 88% |
Without | 0 | 0 (0%) | 0 | 0 | NA | NA | |
Attitudes and perceptions related to changes to the meal service | |||||||
Study quality | Positive rating | 3 | 3 (100%) | 0 | 0 | 0.250 | 44% to 100% |
Neutral rating | 10 | 6 (60%) | 4 | 0 | 0.754 | 31% to 83% | |
Study design | Pre-post assessment | 9 | 8 (89%) | 1 | 0 | 0.039 | 57% to 98% |
Parallel arm or crossover | 4 | 1 (25%) | 3 | 0 | 0.625 | 5% to 70% | |
Intervention duration | ≤2 months | 4 | 4 (100%) | 0 | 0 | 0.125 | 51% to 100% |
3+ months | 9 | 5 (56%) | 4 | 0 | NA | 27% to 81% | |
NOURISHING domains | Three domains | 8 | 6 (75%) | 2 | 0 | 0.289 | 41% to 93% |
One or two domains | 5 | 3 (60%) | 2 | 0 | NA | 23% to 88% | |
NOURISHING action areas | Three to six action areas | 9 | 7 (78%) | 2 | 0 | 0.180 | 45% to 94% |
One to two action areas | 4 | 2 (50%) | 2 | 0 | NA | 15% to 85% | |
Stakeholder engagement | Student engagement | 3 | 3 (100%) | 0 | 0 | 0.250 | 44% to 100% |
Without | 10 | 6 (60%) | 4 | 0 | 0.754 | 31% to 83% | |
Behaviour change communication | Promotion and/or training | 9 | 7 (78%) | 2 | 0 | 0.180 | 45% to 94% |
Without | 4 | 2 (50%) | 2 | 0 | NA | 15% to 85% |
4. Discussion
4.1. Interpretation of Results
4.2. Limitations
4.3. Implications
- Engage the stakeholders who prepare the food (food service staff) and consume the food (adolescent students) through formative research, program development and/or implementation; recruit peer advocates to act as change agents;
- Explore novel approaches in the school dining room such as integrating technology which now forms part of adolescents daily lives;
- Ensure nutritional quality of school menus alongside assessment of palatability; they must go hand in hand to increase consumption, reduce waste, and improve students’ diet quality. Allow students to sample modified foods, and if feasible, engage experts in the field of food and nutrition (dietitians, school nutrition specialists or professional chefs) to inform recipe or menu reformulation;
- Healthy options must be accessible (front and centre), visually appealing (showcase them), and fast to access because time allowed for lunch at school is limited;
- Restrict the availability and portion size of less healthy options. Students can only make decisions based on the options placed in front of them;
- Include marketing strategies and positive health messaging to engage adolescents and promote positive changes to the meal service;
- Use short-and longer-term evaluations to monitor progress and build sustained change;
- Measure selection and consumption of meal components to assess intake and waste.
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Inclusion Criteria | Exclusion Criteria | |
---|---|---|
Population | Secondary (i.e., middle or high) schools that provide a routine main meal service (≥1 main meal/day) to most students (≥50%) on most days; students aged 10–19 years; generally well and independent of activities of daily living; upper-middle and high-income countries | Primary (i.e., elementary) schools; before or after school care; schools that only provide optional purchases that may supplement a meal provided from home or elsewhere; people aged <10 or >19 years; high-needs populations who are acutely or chronically unwell; selection of participants based on special nutritional needs (athletes, dance groups, high or at-risk of nutrient deficiency), specific disease state or weight status |
Intervention | Single or multi-strategy nutrition-related interventions that target and modify the practices of the routine meal service; includes nudging strategies, policy implementation, menu changes, staff training; may vary in method, duration, or mode of delivery | Interventions that focus on components outside the routine meal service, e.g., introduce a new routine meal service, or target the total school food environment without specific routine meal service strategies |
Comparison | Experimental studies with control or comparison groups (both classified as ‘controlled studies’ throughout review), not limited to parallel controls; single group experiments with comparison of before and after measurements | Experimental studies without control or comparison data; studies with comparative data but without an intervention (e.g., menu comparison across schools) |
Outcomes | Objective or subjective measures of students’ food behaviours and dining experience that reflect a change in practice within the routine meal service; includes selection or consumption of a meal component (a food item, food group or nutrient), qualitative feedback, attitudes or satisfaction scores, knowledge, school meal program participation rates | Measurements that do not reflect student outcomes (e.g., menu assessment) or the impact of strategies targeting the routine meal service (e.g., dietary intake from total diet, anthropometric measures for interventions that include physical activity or classroom education unrelated to the routine meal service) |
Study design | Randomised and non-randomised experimental trials, single group before-after studies; peer-reviewed publications; may be a pilot study | Non-peer-reviewed publications, reviews, observational studies, commentaries, editorials, conference proceedings, reports, PhD dissertations |
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Mingay, E.; Hart, M.; Yoong, S.; Palazzi, K.; D’Arcy, E.; Pursey, K.M.; Hure, A. The Impact of Modifying Food Service Practices in Secondary Schools Providing a Routine Meal Service on Student’s Food Behaviours, Health and Dining Experience: A Systematic Review and Meta-Analysis. Nutrients 2022, 14, 3640. https://doi.org/10.3390/nu14173640
Mingay E, Hart M, Yoong S, Palazzi K, D’Arcy E, Pursey KM, Hure A. The Impact of Modifying Food Service Practices in Secondary Schools Providing a Routine Meal Service on Student’s Food Behaviours, Health and Dining Experience: A Systematic Review and Meta-Analysis. Nutrients. 2022; 14(17):3640. https://doi.org/10.3390/nu14173640
Chicago/Turabian StyleMingay, Edwina, Melissa Hart, Serene Yoong, Kerrin Palazzi, Ellie D’Arcy, Kirrilly M. Pursey, and Alexis Hure. 2022. "The Impact of Modifying Food Service Practices in Secondary Schools Providing a Routine Meal Service on Student’s Food Behaviours, Health and Dining Experience: A Systematic Review and Meta-Analysis" Nutrients 14, no. 17: 3640. https://doi.org/10.3390/nu14173640
APA StyleMingay, E., Hart, M., Yoong, S., Palazzi, K., D’Arcy, E., Pursey, K. M., & Hure, A. (2022). The Impact of Modifying Food Service Practices in Secondary Schools Providing a Routine Meal Service on Student’s Food Behaviours, Health and Dining Experience: A Systematic Review and Meta-Analysis. Nutrients, 14(17), 3640. https://doi.org/10.3390/nu14173640