Identification and modelling of risk factors for food waste generation in school and pre-school catering units

Abstract Public sector food service is a major contributor to food waste generation in Sweden, with schools, pre-schools, elderly care homes, hospitals etc., producing approximately 70,000 tons of food waste each year. Sweden has appropriate infrastructure for handling food waste in place, recycling nutrients and energy, but there is still great potential to move upwards in the waste hierarchy and prevent waste. An important step in designing waste reduction measures is to identify and quantify the importance of different risk factors, in order to start by solving the problems with the greatest potential benefit and the lowest cost. This study sought to identify and quantify risk factors for food waste generation in public sector canteens by correlation analyses and statistical modelling. The empirical material comprised food waste quantification data for 177 kitchens in the Swedish municipalities of Falun, Malmo, Sala, Uppsala and Orebro, supplemented with quantifiable information about the kitchens obtained using a questionnaire. According to the findings, plate waste in schools and pre-schools increases with children's age. Schools with older children could potentially reduce plate waste by introducing more structured lunch breaks. Plate waste also increases with dining hall capacity, potentially due to rising stress and noise levels. Both plate waste and serving waste increase with greater overproduction, as indicated by calculated portion size, and could be reduced by schools and pre-schools estimating their daily number of diners and their diners’ food intake more accurately. As serving waste was significantly higher in satellite units (which bring in cooked food), due to lack of cooling and storage possibilities, than in production units (which cook, serve and sometimes deliver hot food), satellite units in particular would benefit from more accurate quantification of the food required on a daily basis. These findings were confirmed by multiple linear regression models, which explained >85% of the variation in plate, serving and total waste per portion. When used for quantification after changing the value of different factors, these models confirmed that the main factors influencing serving waste and total waste per portion were type of kitchen and rate of overproduction, while plate waste was mainly influenced by children’s age and factors indicating a stressful dining environment.