Back in 1987, the United Nations (UN) defined sustainability or sustainable development as “the one that meets the needs of the present without compromising the needs of future generations” [1
]. At present, food systems are showing a major environmental impact worldwide, accounting for 19–29% of overall greenhouse gas emissions [2
], and therefore compromising the sustainability concept and principles. Specifically, food waste (FW) is a major problem that must be tackled and minimized in order to achieve a more sustainable food supply chain [3
]. According to the Food and Agriculture Organization (FAO), “food waste” can be defined as food that, although suitable for human consumption, is discarded as a result of negligence or the deliberate choice to throw it away [4
]. The later a food product is lost or wasted in the supply chain, the higher the environmental cost, as more inputs are invested (processing, transport, cooking, etc.), and greenhouse gas emissions build up as the product moves through the supply chain [5
]. Therefore, preventing the avoidable generation of FW in the supply chain represents the most beneficial approach to avoid food wastage [6
]. It is difficult to know precisely how many foods that are suitable for consumption end up being discarded. Even though data on FW from European member states (EU) still have a high uncertainty level, the Fusions Project estimated that by 2012 an annual FW of 88 million tons in EU-28 member states would be produced, of which about 53% occur at household level and 12% at the food service or catering sector [7
]. According to the 2014 FAO estimates, 1.3 billion tons of food was wasted annually (1/3 of the world’s production) [8
The main source of FW in catering or food services (restaurants, bars, etc.) and institutions is the food that is not consumed, left on the plate, or leftovers [9
]. There is a consensus in the literature on the definition of plate waste (PW) that is expressed as the quantity of an edible portion of served food that is discarded [11
] or the fraction of FW represented by leftovers [12
]. Specifically, in Sweden, Engström et al. [9
] observed that PW was the major source of food loss, with about 11% to 13% of the amount of food served in food service institutions being thrown away.
Elimelech et al. [13
] quantified a household food waste that accounted for 45% of total waste (573 g/day per capita), and importantly, they stated that 54% was identified as avoidable. There are many causes that can lead consumers to leave food on the plate [14
]. For instance, in the catering sector, it was observed that up to 59% of clients could not eat all of what they were served, as serving sizes and portions were very large; and in this regard, 23% of plate leftovers (PL) were side dishes that consumers were unaware of when choosing their menus [15
]. Furthermore, a number of studies have shown that reducing portion sizes is an effective measure toward decreasing FW. In a study by Freedman and Brochado [16
], the authors indicated that decreasing the serving size of French fries by 50% resulted in a 31% reduction in PW per consumer. Moreover, Vermote et al. [17
] showed that a downsizing of 20.9% in French fries portion resulted in a total intake reduction of 9.1% and a relative decrease of 66.4% of PW. This study did not only change portion size, but also the material and shape of the serving ware, as serving material has been previously shown to affect the quantity of PW [18
]. In a study conducted by Kallbekken and Sælen [19
] in hotel restaurants, they found that very simple measures, such as reducing plate size and informing guests they were allowed to help themselves more than once, reduced the amount of FW by 20%.
The latest report conducted in Spain by the Ministry of Agriculture, Fisheries and Food (MAPA) estimated a waste production, between January and December 2018, of 1339 million kg of food and drinks, which translates into and average FW production of 24.7 kg per capita/year. These data indicate that FW in Spanish households has increased by 8.9%, compared to data from 2017, a curious fact considering that most households state that they avoid throwing away food products [20
] and in spite of the past and current economic crisis. At the household level, the latest data from the Panel of FW Quantification from Spanish Households developed by MAPA [20
] showed that Spanish families discarded about 4.6% of purchased foods, a similar quantity of that reported by the “Food and society decision in 21st century Spain” study in adult population by CEU San Pablo University [21
]. The latter indicates that, in relation to the measures undertaken by consumers to reduce FW, 85% of participants declared trying to reduce plate leftovers by planning their menus in advance, 84% planning their grocery shopping, and only 66% declared buying less amounts of food [21
]. These data do not seem to confirm the ones from the Ministry report, in which 8 out of every 10 homes acknowledge discarding food and beverages. Namely, 81.5% of consumers discarded food products just as they were acquired, without any further processing or elaboration [20
]; the main reasons for disposal were spoilage due to mold presence (29%), products past their “best before” or “use by” date (19%), leftovers from dining (14%), and preparation of food dishes above their actual needs (13%) [22
]. The typical Spanish meal structure has changed over the last few years, and many traditions have been lost as dietary habits drift away from the Mediterranean Diet [23
]. A regular daily menu mainly consists of a first course (legumes, vegetables, salads, soups, etc.), followed by a second course (fish, meat, pasta, etc.), a piece of bread, beverage, dessert, and coffee or infusion. Alternatively, main courses accompanied by side dishes (salads, vegetables, potatoes, etc.) can be consumed.
It should be underlined that, so far, most studies conducted in the Spanish population have focused on the overall waste generated by the Spanish consumers. However, to date, there are no studies that quantify and describe the food groups left by Spaniards per se on the plate. Hence, the present study aims to provide the information about the amount of household and out-of-home PW, accounting for relevant socioeconomic factors (habitat size, educational level, and family income), eating occasions, and different types of dishes consumed amongst different age groups of participants from the ANIBES study (“anthropometric data, macronutrients and micronutrients intake, practice of physical activity, socioeconomic data and lifestyles in Spain”) as a representative sample of the Spanish population.
2. Materials and Methods
Design, protocol, and methodology of the ANIBES study have been previously published [24
], and full references can be found at the repository from the Spanish Nutrition Foundation (FEN) (http://www.fen.org.es/anibes/es/biblioteca
). The design of the ANIBES study was cross-sectional, and stratified multistage sampling was used. Fieldwork was achieved at 128 sampling points across Spanish territory, aiming to include a sample size representative of all people living in Spain aged 9–75 years and living in municipalities of at least 2000 residents. The initial potential sample included 2634 individuals, and the final comprised 2009 (1013 men, 50.4%; 996 women, 49.6%). The youngest age groups (9–12, 13–17, and 18–24 years) included a “boost sample” to deliver n
= 200 per age group (error ± 6.9%). Random plus boost sample involved 2285 subjects in total. Sample quotas were age groups (9–12, 13–17, 18–64, and 65–75 years), gender (male/female), and locality or habitat size (rural population: 2000 to 30,000 inhabitants; semi-urban population: 30,000 to 200,000 inhabitants; and urban population: >200,000 inhabitants). Additional factors considered for sample adjustment were education and monthly family income (0–1000 €, 1001–2000 €, and > 2000 €). The statistical description of the ANIBES population sample is included in Table 1
Two pilot studies were completed before the main research period (mid-September 2013 to mid-November 2013), and participants were involved for two working-week days and one weekend day. The final protocol was accepted by the Ethical Committee for Clinical Research of the Region of Madrid, Spain. Subjects were provided a tablet (Samsung Galaxy Tab 27.0, Samsung Electronics; Suwon, Gyeonggi-do, South Korea), to facilitate recording all foods and drinks consumed over the course of those three days, by taking photographs of their meals, in their household and outside. It is described that self-report of dietary intake could be biased by the social desirability or social approval given to diet, and this might affect estimates in epidemiological studies [25
]. In order to avoid self-report biases, no specific instructions were given to subjects regarding food consumption, so that they would eat as customarily as possible. Instructions given to participants can be found in Appendix A
. Pictures of the dishes or food products were freely taken by participants, before and after each eating occasion, and these were used for performing comparisons within each participant’s plate. A fit-for-purpose software was developed to collect information from the tablets every two seconds, and comprised a database that was updated every 30 min. Food consumption was assessed with the use of the photographs (Figure 1
), descriptions, and information collected, by a team of 14 dieticians/nutritionists, who codified foods and beverages and assigned portion weights (g). Our method is considered to be sound but still awaits proper validation.
Statistical analysis was performed as a descriptive analysis of the sample, with the main quantitative variables expressed through centralization and dispersion parameters. Results are reported as median (interquartile range) per group or as percentage. Variables were tested for normality, using a Kolmogorov–Smirnov test. Non-parametric data were analyzed by the Mann–Whitney U test, Wilcoxon test or the Kruskal–Wallis test, and when it resulted in differences, multiple comparisons between medians were studied by the Dunn test, to adjust for multiple comparisons and adjusted p-value with Bonferroni correction. Differences were considered significant at p < 0.05. Data analysis was performed with the SPSS 24.0 software package (IBM Corp., Armonk, NY, USA).
Both household and out-of-home PW from total population and different gender and age groups are shown in Table 2
(and Supplementary Materials Figure S1
). Female participants showed a significantly higher PW (11.7 (0.0–46.2) g/day) than males (4.0 (0.0–31.4) g/day) when the total population was analyzed (p
< 0.05). However, by dividing population by age, we only observed that PW was significantly higher in women during adolescence and adulthood when compared to men. Moreover, household and out-of-home PW was highest among children aged 9 to 12 years (20.3 (4.3–59.7) g/day), followed by adolescents aged 13 to 17 years (12.7 (0.0–48.7) g/day), adults aged 18–64 years (8.3 (0.0–38.0) g/day), and elders aged 65–75 years (0.0 (0.0–13.3) g/day). Similarly, significant differences (p
< 0.01) were observed amongst children, adolescent, adults, and the elderly. Furthermore, 19% of children, 28% of adolescents, 35% of adults, and 64% of elderly did not leave any PW (0 g/day) during the three-day record.
shows the grams per day of PW that a person leaves a day on the plate, considering if food consumption is either at home or outside. Leftover quantities are greater when eaten at home than when eaten away from home. In addition, if we segment the places where people eat outside home, it can be seen that there is a slight tendency to leave a little more food on the plate when eating in institutions (schools, universities, jobs, etc.) than when eating at food service emplacements (restaurants, bars, etc.). It should be noted that out-of-home observations (n
= 1407) do not add up when segmented into “Institutions” (n
= 732) and “Food services” (n
= 1144), because one participant might have lunch in an institution and then dinner at a restaurant (food service) on the same day, therefore increasing the number of observations.
shows the distribution of food discarded over different eating occasions and the main meals that contributed to household and out-of-home PW across all groups were lunch (40%), dinner (27%), breakfast (11%), and afternoon (8%), with mid-morning and other occasions accounting for 7% each. Significant differences (p
≤ 0.001) were found between the central meals (breakfast, lunch, and dinner) and snacks (mid-morning, snack, and other occasions). However, the amount of waste generated between collations was very similar.
In Table 4
, we can observe that there is more PW over working days than on weekends (p
≤ 0.001). In addition, average household and out-of-home PW over lunch was significantly higher (p
≤ 0.001) in children (9.3 (0.0–31.0) g/day) than in adults (0.3 (0.0–16.7) g/day) and elderly (0.0 (0.0–3.3) g/day), while adolescent females (8.7 (0.0–43.7) g/day) and adult females (2.0 (0.0–18.4) g/day) had a significantly higher PW than adolescent males (1.0 (0.0–17.7) g/day) and adult males (0.0 (0.0–13.3), (p
≤ 0.05 and p
≤ 0.01, respectively) (Table 5
displays the total PW generated by the ANIBES participants, accounting for the different menu components consumed throughout the day. The highest PW amounts corresponded to bread and similar products (25%), followed by main courses (16%), first and second courses (each 15%), and starters (8%), which were among the main contributors.
In addition, the largest amounts of leftovers attributable to children (4.8%) and adolescents (3.7%) were main courses, while adults and elders produced greater PW as bread and similar products, with 3.2% and 2.2%, respectively (Figure 4
The main food groups that contributed to PW across all age and gender groups were vegetables (12%), ready-to-eat meals (10%), cereals and grains (10%), oils and fats (10%), and pulses (10%), followed by meat and meat products (8%) and sauces and condiments (8%), as shown in Figure 5
. On the other hand, groups such as fruits (6%), appetizers (salted snacks, olives, and pickles) (6%), eggs (5%), sugars and sweets, and alcoholic and non-alcoholic beverages (2% each) are less frequently discarded.
illustrates household and out-of-home PW studied by socioeconomic factors. There were significant differences by habitat size, as higher leftover amount was observed in urban or rural zones when compared to semi-urban zones (p
≤ 0.01). Likewise, educational level (Table 6
) did seem to influence population’s PW, as there was a significant difference between lower educational level compared to superior educational levels (p
≤ 0.01). Similarly, we did find a statistical difference in PW between lower (≤1000€ per month) and higher (≥2000€ per month) population income levels (Table 6