Fostering Sustainable Dietary Habits Through Optimized School Meals - an Intervention Study
Phase: NA
Conditions: Food Habits
Sponsor: Karolinska Institutet

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Study protocol with statistical analysis plan 
Fostering sustainable dietary habits through optimized school meals – 
OPTIMAT 
 
Date: November 14, 2019 
 
 
 

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Introduction 
 
Public school meals have been highlighted as a suitable setting for children to internalize sustainable 
dietary habits, which may persist throughout life [1, 2]. Radical changes to food production and 
consumption are needed to ensure the attainment of Agenda 2030 for Sustainable Development [3], and 
fulfillment of the Paris Agreement [4]. Planning of school meals must take many aspects into account: 
health promotion, environmental impact, acceptability by the consumers and affordability to those 
paying for the meals. Currently many schools use organic products, recycle food packaging and aim to 
reduce food waste, but environmental impacts like greenhouse gas emissions (GHGE) have so far not 
received much attention.  
In Sweden, fully subsidized lunches are served daily in primary schools to all 1.3 million children aged 
6 to 15 [5]. Due to their reach and scale (approximately 230 million meals/year at an annual cost of 
around 5.6 billion SEK), school meals have enormous potential to increase children’s knowledge about 
health and sustainability, foster sustainable dietary habits and to enable sustainable public procurement.  
This study aimed to: a) apply linear programming to develop a GHGE-reduced, nutritionally adequate, 
and affordable four-week lunch menu plan optimized for minimum deviation from the current food 
supply;  and b) evaluate  the climate impact of the menu, effects on food waste, food consumption, and 
pupils’ satisfaction with school lunches. Our hypothesis is that school meals can be optimized to be 
nutritious and more climate friendly, without negatively affecting acceptance, food waste and cost.  
 
Methods 
 
Design 
An interrupted time series (ITS) analysis design will be used to compare the effect of an optimized menu 
to the baseline menu on daily food waste and consumption at school level. For a baseline period of four 
weeks children in primary schools will receive a baseline menu. After a two-week break, the optimized 
four-week menu will be served (intervention period).  
 
Recruitment of schools 
During the fall of 2018, public meal managers in three municipalities of Stockholm, Sweden, were 
invited to information meetings about the intervention. The public meal managers were asked to attend 
the meeting together with school chefs from primary schools had shown interest in sustainability issues. 
To be eligible for the intervention, schools were required to have on-site kitchens. They also needed to 
be able to provide previously used recipes for a standard four-week menu electronically.  
Optimization  
Recipes for an original (baseline) four-week school lunch menu plan previously served at the recruited 
schools, will be obtained through the municipality's electronic meal planning system. The foods included 
and amounts are considered as the baseline food supply. Each food item included has a code that can be 
coupled to the Swedish national food database and a national climate database for foods containing life 
cycle data for each food item [6]. This baseline food supply will be optimized using linear programming. 

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The optimized food list, not including new foods or excluding foods from the baseline list, will be 
handed to a professional meal planner who develops a new menu plan for the intervention using all 
foods on the optimized list. 
Outcomes 
To assess the effect of the new menu plan, data on food waste and consumption will be collected in each 
intervention school four weeks before (baseline) as well as during the four-week intervention with a 2-
week brake in between measurement periods. A tool for measuring food waste in school restaurants 
developed by the National Food Agency in Sweden will be used. The tool requires weighting (using 
school kitchen scales) of all kitchen waste (both preparation waste and cooking waste); all food prepared 
in the kitchen; the share of the prepared food that is not eaten and has to be thrown away (serving waste); 
the share that can be saved; and plate waste. The number of plates used daily by the pupils in the school 
restaurant will also be recorded. These measurements will be made daily by the personnel in the school 
kitchens during the baseline as well as during the intervention period. Based on these measurements, the 
total food consumption (kg) will be calculated as the total amount of food prepared in the kitchen (kg) 
minus the total amount of prepared food that is not eaten and has to be thrown away (overall waste in 
kg), the total amount of plate waste (kg), and the total amount of food that could be saved (kg). Plate 
waste per pupil (g) will be calculated for each day by dividing the total amount of plate waste by the 
total number of plates used. Similarly, the consumption per pupil (g) will calculated for each day by 
dividing the total consumption by the total number of plates used. 
Data on school meal satisfaction will be collected at each intervention school through an online 
questionnaire at baseline and during the last week of the intervention period. Pupils in grades 5 and 8 
answer the questionnaire containing ten questions related to the school lunch. Five of the ten multiple-
choice questions specifically cover their general (i.e. not for that specific day of week) sense of 
satisfaction with the school lunch. The questions include how often they consider that the school lunch 
tastes good, how many days per week that they tend to eat from the school lunch, how often they usually 
feel full after having eaten lunch, and how often they tend to throw away food in the school restaurant. 
They are also asked to provide an overall rating of the school lunch. 
 
Qualitative study 
Six focus group discussions (FGD) with pupils in grades 5 and 8 and three FGDs with meal staff will 
be conducted to explore their experiences with the intervention as well as the barriers and facilitators 
to scaling up.  
 
Statistical analysis plan 
In order to compare food waste and consumption between the two periods (baseline and intervention), 
interrupted time-series (ITS) analysis will be used [7]. ITS analysis will be implemented at school level 
to assess the difference between the two periods daily in the number of pupils consuming lunch (n), 
kitchen waste (kg), prepared food (kg), serving waste (kg), total plate waste (kg), plate waste per pupil 
(g), total consumption (kg), and consumption per pupil (g).  
The ITS analysis will based on linear regression models [7]. These models will be determined by three 
independent variables: (a) A time-variable, applied to adjust for a potential baseline trend; (b) A variable 
indicating whether the data point represented the baseline or intervention period to assess the level 
(mean) change resulting from the intervention; and c) an interaction term between (a) and (b) specifying 

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the slope change resulting from the intervention. Assumptions of normality, homoscedasticity, as well 
as absence of autocorrelation and partial autocorrelation will be assessed.  
The effect of the new menu plan on the five questions related to school meal satisfaction will be explored 
with Pearson’s chi-squared tests (χ2) within each intervention school.  
The software R (version 3.6.1) [8] will be used for statistical analysis. 
Qualitative content analysis [9] will be used to analyze the FGDs.  
References 
1.  Willett W, Rockström J, Loken B, et al (2019) Food in the Anthropocene: the EAT–Lancet 
Commission on healthy diets from sustainable food systems. The Lancet 393:447–492 
2.  Oostindjer M, Aschemann-Witzel J, Wang Q, et al (2017) Are school meals a viable and 
sustainable tool to improve the healthiness and sustainability of children´s diet and food 
consumption? A cross-national comparative perspective. Crit Rev Food Sci Nutr 57:3942–3958 
3.  UN General Assembly (2015) Transforming our world : the 2030 Agenda for Sustainable 
Development. UN General Assembly 
4.  (2015) Paris Agreement. UNFCCC 
5.  The National Food Agency (2013) Skolmåltiden – en viktig del av en bra skola. Swedish. (The 
school meal: an important part of a good school: support and inspiration for school leaders.). The 
National Food Agency; The Swedish National Agency for Education, Uppsala; Stockholm 
6.  Florén B, Amani P, Davis J (2017) Climate Database Facilitating Climate Smart Meal Planning 
for the Public Sector in Sweden. Int J Food Syst Dyn 8:72–80 
7.  Bernal JL, Cummins S, Gasparrini A (2017) Interrupted time series regression for the evaluation 
of public health interventions: a tutorial. Int J Epidemiol 46:348–355 
8.  R Core Team (2019) R: A language and environment for statistical computing. R Foundation for 
Statistical Computing, Vienna 
9.  Lundmark B (2002) Kvalitet som utsaga och praktik: kvalitetsaspekter med fokus på skolmåltiden 
i Sverige. Institutionen för hushållsvetenskap, Uppsala universitet