The environmental footprint of in silico-designed vegan, lacto-ovo-vegetarian and omnivorous diets complying with Mediterranean diet standards and essential amino-acid requirements

The environmental footprint of in silico-designed vegan, lacto-ovo-vegetarian and omnivorous diets complying with Mediterranean diet standards and essential amino-acid requirements | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The environmental footprint of in silico-designed vegan, lacto-ovo-vegetarian and omnivorous diets complying with Mediterranean diet standards and essential amino-acid requirements Paolo Tessari, Giuliano Mosca, Giovanni Bittante, Anna Lante This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2005120/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : The relationships between environmental variables, diet-type, and nutritional parameters are incompletely known. Objective : To estimate the environmental footprint and selected nutritional parameters of in silico-designed vegan (VEG), lacto-ovo-vegetarian (LOV) and omnivorous (OMN) weekly menus (n=7 for each type) complying with Mediterranean-Diet (MD) standards and satisfying Essential-Amino- Acids (EAA) requirements. Methods : Land-Use (LU), Water-Footprint (WF), Green-House-Gas-Emission (GHGE), sodium, saturated-fat, calorie, protein contents, and food weight, were calculated. A global EAA-based Nutritional and Environmental Score (EAA-NES) was developed. Key findings : Average LU, WF, GHGE, calories, protein and food weight, and EAA-NES scores, were similar among menu-types. In LOV menus, sodium and saturated fat were greater (by ≈140%, p<0.006, and by ≈60%, p<0.006), than in VEG or in VEG and OMN menus, respectively. However, the LU, GHGE and WF allocation of VEG menus fell predominantly into the first two quartiles (with lower environmental impact), whereas that of LOV and OMN menus was more scattered. No difference was found in the EAA-NES distribution among menu-types, by combining the two lower or the two higher quartiles. Conclusions : In silico-designed VEG diets might not exhibit a lower environmental impact, nor a better EAA-NES score, than LOV or OMN diets at safe EAAs requirements. Energy Environmental footprint Food production Nutrition Environment Green-House-Gas-Emission Mediterranean Diet Land use Saturated fat Sodium Water Footprint Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction The steadily-growing global population requiring appropriate nutrition, the increase of global warming and the shifts in land use and water consumption, constitute serious risks to the planet’s environmental sustainability [1, 2]. An optimal balance between peoples’ healthy nutritional requirements [for health maintenance and chronic disease prevention], and the food-associated global environmental footprint, is strongly felt to be pursued nowadays. There are growing ethical implications about food choice & quality and the associated environmental footprint [3-7]. Common indexes of the environmental footprint linked to food production are land use (LU), the water footprint (WF) and the Green House Gas Emission (GHGE) [8-11]. Many studies have investigated these indexes of environmental footprint in respect to the food industry [7-14], also by comparing animal and vegetal foods, type of meat, common menus etc. [11, 13, 14]. Generally speaking, crop-based diets are usually associated to a lower environmental footprint than that of animal or mixed ones [12-14], and many have hypothesized that producing (and eating) more vegetables and fruit than animal-derived foods, could result in a better environmental impact. Some key methodological issues should however be considered in these investigations. The comparisons among foods or diets have been usually based on either food raw weight [11], energy density [7], average daily menu(s) [11], or nutritional quality [13], but normally they did not consider the quality of the protein consumed based on their amino acid profile. As a matter of fact, a healthy diet should provide all the essential nutrients as well as the energy required daily [15, 16]. The essential amino acids (EAAs) are key, indispensable substrates that need to be introduced in sufficient amounts, i.e. at the recommended daily allowances (RDAs) to guarantee optimal growth, health, recovery from disease, etc., along with other essential nutritional elements [16, 17]. Therefore, in the light of the growing interest in the complex and important relationships between food consumption and the environmental footprint [18-27], also the nutritional availability of all the EAAs should be taken into consideration. From an investigational standpoint, both “bottom-up” and “top-down” methods can be employed. The former are based on data collection on existing eating habits, that need to be associated to estimates of the environmental footprint of the eaten foods. Conversely, the latter could examine the theoretical footprint of either single foods or in silico -designed diets, on the environmental parameters. Using the latter approach, we recently reported that the environmental footprint of selected, staple vegetal and animal-origin foods, at an edible food weight guaranteeing the RDA of all EAAs, does not show any consistent, clear-cut advantage of vegetal over animal foods [28]. Such a somehow-unexpected conclusion was apparently due, besides their specific footprint values, also to the greater edible fraction, the higher protein concentration, and the richer and more balanced EAA content, of animal than vegetal foods. In other words, a smaller quantity of animal than vegetal food was required to satisfy human EAA requirements. Therefore, from our as well as from other reports, it may be suggested that the choice between vegetal and animal foods should be based on a more-in-depth consideration of nutritional and environmental variables, under an integrated perspective [28-31]. Our initial investigation was however limited almost exclusively to single foods, i.e. it did not consider complex diets, nor it compared different diet-types [28]. In addition, the water footprint and the energy content of the foods were not considered [28]. Generally speaking, no food guarantees the ideal proportion and/or quantity of amino acids to meet their requirements in humans, although some are closer than others. Such a target could rather be better achieved with mixed diets, where the deficiency in some EAA(s) and the excess in some other EAAs of a given food, could be compensated by different, complementary proportions of EAAs from other foods. In other words, the statements formulated from the analysis of single foods [28] couldn’t be applied directly to complex diets. Moreover, the nutritional adequacy of the diets should include other nutritional elements besides the EAAs. Given these premises, the current study was designed to analyze, under the driving perspective of EAA requirement(s), the effects of food combinations in sample, in-silico designed, applicable diets, on the environmental footprint. The diets were divided into vegan, lacto-ovo vegetarian and omnivorous ones. A variety of daily meal choices were assembled, to end up into seven different one-week menus for each diet-type, all complying with Mediterranean-Diet (MD) standards [32, 33]. The environmental footprint data (LU, WF and GHGE) of foods were retrieved from the literature and re-calculated. Some relevant nutritional parameters (sodium, saturated fat, energy and protein, in addition to food weight) were determined too. A global “EAA-Nutritional and Environmental Score” (EAA-NES) was proposed, to enable a simple comparisons among the menu types. Results The calculated MD Index score [33] was (9/11) in all menus, but (10/11) in the two fish-containing OMN menus, showing a good/excellent overall compliance with the MD (See Methods). As reported above, despite the addition of extra foods, the average total caloric content of the menus resulted to be between ≈8% and ≈25% lower ( Table 1 ) than that recommended in sedentary middle-age female and male subjects] [34]. The total content of starch-rich foods (excluding legumes) in OMN menus (283 ± 29 g) was greater than that in VEG menus (183 ± 25 g, p0.17). The content of legumes of OMN menus (36 ± 4 g) was > 3-fold lower than that of both VEG (101 ± 16 g) and LOV menus (105 ± 16 g) (p<0.007 and p<0.005 respectively, by ANOVA followed by the Tukey’s post-hoc test). The data of the environmental footprint, i.e. the LU, total WF and GHGE, associated to the different menus calculated to comply with the RDA of all the EAAs, are visually reported on Figures 1-3 , ranking the diets from the lowest (i.e. with a more favorable impact) to the highest value (=less favorable impact). In regard of LU ( Figure 1 ), the different diets of the three menu-types are not clearly clustered, although all VEG menus fell within middle-to-low positions of the ranking, indicating a tendency for a lower land requirement. In the case of the total WF, an overlap in the ranking of the three menu-types was more evident, the VEG menus occupying both the first and the last position ( Figure 2 ). Also GHGE ranking of the individual menus of the three menu types was quite scattered ( Figure 3 ), showing no preferential menu-associated distribution. In respect to GHGE, OMN menus occupied both the first two and the last two positions. These visual impressions were confirmed by quartile analysis (Figure 4) , although the LU, GHGE and total WF allocation of VEG menus fell predominantly into the first two quartiles. The aggregated values (as Means ± SE) of the environmental footprint data, of sodium, saturated fat, calories, protein menu content, food weight, and of the global EAA-based, Nutritional and Environmental score (EAA-NES), are reported on Table 1. Despite the apparent trend(s) depicted on Figure 1, no statistical difference in any of the environmental parameters was observed among the mean values of the three menu-types, except for a borderline lower (by ≈15%) Land Use in VEG than LO menus (p=0.052 by 1-way ANOVA and the Tukey’s post-hoc test). In contrast, in LOV menus, sodium content was ≈60% greater than in VEG menus (p<0.006, by 1-way ANOVA and the Tukey’s post-hoc test), whereas saturated-fat content was greater by ≈70% (p<0.006) and ≈60% (p<0.025) than in VEG and OMN menus respectively. Total energy, protein and food weight were not significantly different among the three menu types. The EAA-NES was not different among the menu types too (Table 1), also when the mean differences from the median were calculated (VEG: -38 ± 28; LOV: 40 ± 18; OMN: -11 ± 26) (F: 2,54, p = 0.106, by 1-way ANOVA). The menus’ distribution of the global EAA-NES score, (calculated as the sum of the percent values of each variable vs. the corresponding maximum) is reported in Figure 5 . First, it can be observed that the maximum difference between the highest and the lowest value was by < 50%, showing a relatively small variation among menus. Although the five lowest positions (indicating a better combined Nutritional and Environmental score) are occupied by four VEG and one OMN menus, as opposed to three LOV and two OMN menus placed in the highest five ones, there is no apparent, consistent trend or pattern associated to any menu type. As a matter of fact, the menus are scattered anywhere in the panel, irrespective of their types. This impression is supported also by the quartile distribution analysis of the data (Figure 4). Although four out of the seven VEG menus are allocated within the first quartile vs. none in the fourth one (at variance with what observed for LOV and OMN menus), by combining the data of the two lowest (i.e. 1 and 2) and the two highest (3 and 4) quartiles, the distribution of the three menu types into the combined low and high quartiles was virtually the same. Discussion We report here estimates of the environmental footprint and of some key nutritional variables, of in-silico designed vegan, lacto-ovo-vegetarian and omnivorous menus, calculated on food amounts satisfying the daily requirements of all the essential amino acids, and complying with Mediterranean diet standards. This study represents a step-forward over our previous one [28] focused on the environmental footprint of selected, staple vegetal and animal-origin foods, here extended to a larger variety of popular foods included into complex meals and structured into vegan, lacto-ovo-vegetarian and omnivorous menus. The meal design intentionally was not based on epidemiologically-derived, statistically-calculated food frequencies, nor on schematic diets and/or menus proposed by official and public agencies (predominantly because of the enormous amount of choices). Rather, it was based on the unbiased assembly of some popular foods providing the RDAs of all the essential amino acids and complying with the “Mediterranean” diet and custom. Nevertheless, it represents a theoretical exercise both to calculate “ in silico ” the environmental footprint and some nutritional parameters of sampled diets/menus, and to show the technical feasibility of designing diets with a specific environmental impact. We also propose here a global EAA-based, environmental-nutritional (EAA-NES) score, to rank menus by combining their environmental footprint and few nutritional variables. This study shows that vegan, lacto-ovo-vegetarian and omnivorous sample diets, analyzed as separate groups, could result to be not different in any of the environmental variables (Table 1), nor in the calculated global nutritional & environmental score (Figure 5). Thus, on the basis of these in-silico-designed menus, it cannot be concluded that VEG diets, as a group, are per se better than LOV and OMN diets from an environmental & nutritional standpoint. Overall diet ranking apparently depends at large on which diet within each group is chosen, i.e. on within-group diet variability and, possibly, also on the limited number of diets here designed for each group. Therefore, although our diet design and choice may appear somehow subjective, our study demonstrate a potentially ample choice within VEG, LOV and OMN diets, complying with different degrees of environmental footprint. The ranking of the menus in respect of the environmental variables appeared randomly scattered, and included a rather limited range too, irrespective of menu type (Figures 1-3). Although VEG menus apparently exhibited lower LU, GHGE and total WF values than LOV and OMN menus (Figures 1, 2), these differences were not confirmed by comparing the three menus’ groups (Table 1). Furthermore, the relative difference between the lowest and the highest value(s) (irrespective of menu type), was approximately 0.6 fold for LU (Figure 1), 1.0-fold for total WF (Figure 2), and ≈1.2-fold for GHGE (Figure 3). These ranges are either close to, or lower than, those previously reported for environmental footprint parameters of vegetal and animal single foods [9, 11, 14], as well as of dietary regimens [4, 9, 10, 14, 26]. Also the global EAA-NES did not cluster around any specific menu type (Figures 4 and 5), the relative difference between the lowest and the highest value being approximately by 50%. Although omnivorous diets are usually associated with worse carbon, water and ecological footprints, than those of both lacto-ovo-vegetarian and vegan diets [9,11-14, 26], a large intragroup variability within OMN diets was reported by others too [26]. These observations support the view that the difference(s) in the average environmental footprint among VEG, LOV and OMN diets could be both quite limited, and affected by a large within-diet variability, enabling an imaginative approach in the design of vegan, vegetarian and omnivorous regimens with the best environmental footprint. In other words, adequate food combinations may optimize the nutritional and environmental parameters irrespective of the diet type. In regard of the impact of meat in the comparison between OMN, and either LOV or VEG diets, it may be argued that the amount of meat in OMN diets was modest (i.e. ≈150 g and 120 g of red and white meat, respectively, per week) (Supplementary Table 1), as opposed to greater amounts commonly reported for omnivorous diets [26, 35-37]. Although the relatively low meat amount included in our OMN diets was primarily due to the constraint of our approach (i.e. the focus on EAA requirements), a moderate intake of meat [preferably white, but not excluding small amounts of red and/or processed meat], is considered by recent dietary indications [3, 32, 38]. LOV menus as a group were associated to greater sodium and saturated fat content than the two other menu types (Table 1), although well below the maximum recommended intakes [16]. This was mostly due to the presence in LOV menus of dairy products, particularly of cheese, rich in [natural] saturated fat, as well as in salts [39-42]. Both sodium and saturated fat had been positively associated to cardiovascular disease [33, 38, 43, 44, 45]. In regard of saturated fat, its health-related effects should however be reconsidered in the light of recent meta-analyses and large prospective cohort studies [46, 47], outlining the inconsistency of the common claims about a negative role of saturated fatty acids on cardio-vascular diseases. In a State-of-the-Art review, the American College of Cardiology recently stated the absence of “beneficial effects of reducing saturated fat intake on cardiovascular disease (CVD) and total mortality”, rather the presence of “a protective effects against stroke” [47]. Substitution of the current nutrients-based guidelines for food-group based macronutrient indications was recommended [47], and no available evidence from a large body of current studies would support a restriction in the intake of “whole-fat dairy, unprocessed meat, and dark chocolate” to prevent cardiovascular disease [48, 49]. The acceptance of such a recent position on saturated fat would obviously question the validity of including saturated fat among “the lower, the better” variables considered in the NES score (see Methods and Results). Therefore, waiting for an updated, unanimously-accepted position about the role of saturated fat on cardiovascular disease(s), our results should be taken with caution. All menus were intentionally designed to provide approximately the same energy to avoid a significant bias in menu comparisons (see the Method section and Supplementary details of methods). Furthermore, since the “focal” variable of our approach was the satisfaction of EAA RDAs rather than energy provision, the calculated total food amounts, irrespective of menu type, resulted into an (unexpected) total caloric content by ≈20%-25% lower than reference intakes even in sedentary individuals [34, 50]. While we acknowledge such a limitation, an increase of the caloric content of the diet(s), approaching the “minimum” requirement of ≈2000 kcal/day, could be easily and freely attained at the consumer’s choice, by adding sucrose (not considered in our diets), either as such and/or as sucrose-containing soft drinks, sweets or cakes, as well as by increasing vegetal oil in the menus. These additional nutrients, if added at the same amount to all menus, will not modify the (relative) differences among the menus in the environmental footprint. We did not report here the calculated provision of other essential nutritional elements (oligo elements, vitamins, essential fatty acids etc.) in respect to their individual RDAs (Tessari et al, unpublished results). The abundance of fruit and vegetables could anyway guarantee consistent amounts of some of these elements, that however need to be accurately determined. The design of an “ideal food system” requires an integrated approach, combining health science(s), food technologists, the food production system(s) and their environmental footprint, and else [12, 14]. Regional, income-related factors can condition the effects of replacement of animal-source foods with vegetal-based diets [10]. Energy-balanced, plant-based dietary regimens are associated with both healthy nutritional habits and a low environmental impact particularly in high-income and middle-income countries [10]. Conversely, their impact would be of lower magnitude in low-income countries, because of less efficient production systems and increase demand for environmental resources [10]. In our in silico , theoretical study, we did not aim at either examining these complex relationships, nor at analyzing extensive epidemiological data; rather we present here theoretical estimates of the environmental impact of some sample, in silico -designed, although applicable, dietary regimens. The conclusion(s) of our work should be placed in the context of many other social-economic variables, as well as applied and/or adapted to specific populations. The study of the association between the type of food production/consumption, and the environmental footprint is at the core of current debates. The agricultural system accounts for relevant fractions of the earth’s cultivable land (≈40%), of freshwater use (≈70%) and of the total greenhouse gas emission (≈20%) [49, 51]. The growing use of land and water, and the worsening of the greenhouse effect for food production, represent serious challenges to the earth’s sustainability [51, 52]. Therefore, dietary choices could represent key lifestyle-related factors capable of modifying and/or minimizing the environmental footprint due to agriculture and food production. Any intervention upon the agricultural food system should however be weighed in respect of the provision of adequate nutrition to people. High quality proteins are distinctly found in many animal foods, besides (red) meat. The heavy environmental impact of an [excessive] production of bovine meat [8, 9, 11, 49, 51], as well as the risk conveyed by an exaggerated consumption particularly of processed red meat on human health are well established [43]. The shift from current consumption patterns to “sustainable diets” rich in vegetal foods, could be associated to both human health protection and a reduced GHGE [52]. While keeping in mind these key observations, a comprehensive, unbiased and thoughtful analysis of all the variables involved in dietary planning, based on objective data, would nevertheless be advisable. From our data, balanced mixtures of vegetal and animal proteins, the latter including not only egg or dairy foods, but also poultry, fish, and/or moderate amounts of (preferably unprocessed) red meat, appear to be both feasible and recommended, from an environmental and a nutritional standpoint. In addition, food combinations would positively interact to end up into proportionally lower total amounts of food(s), thus contributing to the reduction of the environmental footprint. The conclusions of this study are based on published, peer-reviewed, often multiple, estimates of environmental parameters. From a methodological standpoint, these kind of data are per se quite difficult to be calculated, and often show a large variability, in particular those of beef meat and fish (seabass), largely because of differences between [semi]intensive and extensive production systems (see Supplementary Methods, Tables 2 and 3, and References). Indeed, when the gross means of these two different systems are compared, LU can differ by up to ≈20-fold for beef meat, and by up to ≈5-fold for seabass, whereas those of GHGE differ by ≈3-fold for beef meat (Supplementary Table 3 and References). In our study, we arbitrarily chose to use the (semi)-intensive system data for both beef and seabass, because of the following reasons. First, the “large” environmental footprint due to extensive beef meat production systems would not necessarily imply a “worse” LU and GHGE footprint, because: a) the extensive land surface used for grazing wouldn’t often be used for other purposes; b) the GHGE effect [due to methane released by rumination], reportedly ≈3-fold greater with extensive than intensive systems [53], would be almost entirely balanced by CO 2 fixation in the grassland (used by grazing animals) through the Calvin-Benson cycle, since CO 2 fixation exceeds by ≈10% the CO 2 produced from the released methane [54]; and: c) the half-life of methane in the atmosphere is at least 10-fold faster than that of CO 2 , although a precise estimate of the latter is difficult because the processes involved have different time scales [51]. Secondly, intensive and (semi)-intensive systems, if properly developed, efficiently applied and with consideration for animal welfare too, may lead to an optimized production of high quality protein food while minimizing the environmental impact [54, 55 ]. The dietary requirement of protein is inversely associated to its quality, as reflected by an adequate and balanced content of essential amino acids. Similarly, also the required food weight would be inversely proportional to its content of protein, as well as of other essential substrates (i.e. the greater the protein content, the lower the food amount needed). Since protein content and quality are higher in animal than in vegetal foods (except for soybeans), less animal than vegetal protein (and food) amounts would be required to guarantee the RDAs of all the EAAs. Such a reduction would affect the LU, GHGE and WF too. In addition, protein complementation attained by adequate mixing of foods of any source, reciprocally compensating for opposite EAA deficiencies [57], could lead to lower amounts of both vegetal or animal foods, thus reducing the overall environmental impact, as outlined above. The results of this theoretical study could be relevant in respect of the need to feed the world’s population healthy food without further wasting the planet’s resources. The double burden of malnutrition (both undernutrition and over-nutrition) affects >3.500 million people, of whom ≈850 million by undernutrition, vs. ≈2500 million, (≈35% of the current world population) by over nutrition [58]. Another billion of people suffer from “hidden hunger”, i.e. they have sufficient energy intake but are deficient in key nutrients, particularly of high-quality proteins, therefore of EAAs [59]. Appallingly, the number of “malnourished” individuals in the world is steadily rising [58]. Both undernutrition and over-nutrition are associated to altered growth, reduced life expectancy, and poor health, not to mention devastating psychological effects. Since malnutrition is frequently linked to poor food quality [59], the availability of high quality foods and suitable combinations would retain a significant impact on human health. In the calculation of the global EAA-NES score we roughly considered energy intake as a variable to be kept at a minimum to prevent overweight and obesity. However, energy intake should also be proportional to the actual needs of a given human being as well as of a population, and, more importantly, sufficient to prevent malnutrition. This considerations should be taken into account in specific conditions. It could be argued that any nutrient deficiency, including that of the EAAs themselves, could be replaced by appropriate supplements. While this possibility is logic and should be carefully considered, the cost and the feasibility of this approach should be balanced against both the effective in vivo availability of the supplemented nutrient(s), and the environmental impact and cost(s) associated to their production. As a matter of fact, the goal of food-based dietary guidelines is to consume the full complement of essential nutrients from natural foods (i.e. not supplements). In conclusion, in silico -designed vegan diets do not necessarily rank better than lacto-ovo-vegetarian and omnivorous ones, when key environmental and nutritional parameters, such the EAA RDAs, are considered. More detailed analyses on the relationships between the nutritional quality of foods and their environmental footprint are warranted to guarantee both human health and the planet’s future. Methods Food choice, composition, and data source Popular, staple foods utilized worldwide, but preferentially based on western countries traditions, included into the MD frame, and with a specific reference to Italy, were considered [32, 33, 35, 36, 37, 43] Among vegetal ones, we selected nuts (almond, hazelnut, pistachio, walnut), legumes (bean, pea, soybean, lentil), cereals as either flour (maize, wheat) or a refined food (rice), a pseudo-cereal (quinoa), a tuber (potato), a cucurbita (zucchini), a solanale (eggplant), lettuce, and cultivated mushroom type (pleurotus). Among animal ones, we selected: beef (and beef-derived bresaola); pork (and bacon); chicken egg; dairy products (milk, yogurt, ricotta, gorgonzola and parmesan); fish (cod and seabass); and poultry (chicken and turkey). Each meal also contained extra virgin olive oil [EVO], fruit (both fresh and dried), coffee and/or chocolate, and one serving of an alcoholic drink (either wine or beer). The composition of each food, including their amino acid concentration, was largely retrieved from the public, free database of the Italian National Research Institute of Food and Nutrition (INRAN, renamed CREA[1] in 2015) [39]. For foods not considered by CREA/INRAN, we relied on additional sources, i.e. the ANSES Ciqual French database [40], that of the USDA [41], or that of the European Institute of Oncology [42]. For some foods, additional selected publications were retrieved, as reported in part previously [28] (See also the complete Reference list in the Supplementary material). The edible parts [e.p.] of the foods, i.e. the food fraction effectively viable for nutrition, were derived and/or calculated from the references. The WHO/FAO/UNU amino acid requirements [17], recalculated to a standard 70-kg young male subject, were used. Food combinations Food combinations were mainly designed following Italian common, traditional recipes and proportions. In order to quantitate food amounts in respect to “servings”, that notoriously vary among national tradition and uses, we referred to Italian portion/serving values, as reported in [60]. Therefore, no specific, statistically-determined food frequency, was applied in the assembly of these combinations, although it was intentionally unbiased, except for the choice of “reasonable” food amounts and proportions in the meals. The chosen foods were combined to provide a variety of daily menus, each composed by three main meals (breakfast, lunch and dinner), according to three diet types containing either only vegetal foods, i.e. complying with a “vegan” [VEG] diet, or mixed vegetal and animal foods, according to both “lacto-ovo” vegetarian [LOV] and omnivorous [OMN] diet-types. The list and the detailed food composition and amounts of each of the resulting twenty-one different daily menus, divided into the three types, are reported in Supplementary Table 1. Each daily menu was designed to contain at least one legume and one cereal, with the aim to reciprocally compensate the (relative) lysine deficiency of cereals, and that of sulfur amino acids (methionine and cysteine) of legumes [57]. No added sucrose, salt, other dressings, sweeteners, or sauces, were considered in food design. Menu assembly was also intentionally developed to furnish approximately the same calories with all menus. This target was quite complex to be achieved, for several reasons. First, the initial step was to design just the three main daily meals complying with the reference daily value of the EAAs (Supplementary Information). However, under this premise all menus resulted quite hypocaloric (between ≈700 and ≈1000 kcal, data not reported), i.e. below recommended standards [34]. Therefore, in order to increase both the menus’ total calories and their variety, we included into all menus additional foods (potato, extra bread), as well as olive oil, fruit (both fresh and dried), chocolate, coffee, lettuce. An alcoholic beverage (either red wine or beer) was added to all but one menu of each type. The quantities of these added foods were identical in all menus, except for bread and potato, titrated in each menu in the effort to match their total caloric content (Supplementary Table 1). Following these further additions, the food amounts of the main meals, satisfying the reference daily requirements of the EAAs had obviously to be recalculated. Despite these adjustments however, the resulting total caloric content of the menus was still (mildly) below (by ≈8-25%, depending on either female or male sex, respectively), that recommended in middle-age human individual of either sex with a sedentary lifestyle (≈1800-2200 kcal/day) [34]. While such a limitation should be considered, it nevertheless left open the possibility to each consumer, to add other nutrients (such as sucrose or vegetal fat, see also the Discussion) at his/her choice, albeit at the same amount(s), to avoid a bias among the menus in the calculated footprint data. Seven options were designed for each VEG, LOV and OMN menu type, with the aim both to provide a different daily choice for one week-periods, and to allow a statistical comparison among the menu types. A Mediterranean Diet index, based on both the type and the amount of foods, was calculated for each menu. Although the type of vegetal and animal-based food products is variable in the MD as well as among Mediterranean countries [31], we used the “Italian Mediterranean Index” as proposed by Agnoli et al [33], that includes eleven items, recommended at amounts either equal or above a given threshold value. These items are: complex carbohydrates (except potato), “MD” vegetables, fruit, nuts & legumes, olive oil and fish. Conversely, the items to be consumed in “low” amounts are potato, red & processed meat, butter, whereas soft drinks are totally excluded. Although for most items, the Mediterranean Diet Pyramid [32] and Agnoli’s index [33] are concordant, they are instead discordant about the amount of potatoes, allowed to a maximum of 1-2 servings (included in the starch-rich foods) at each main meal in the former [32], but surprisingly limited to <17 g/day in the latter [33] (Supplementary details on methods). Nevertheless, for the sake of simplicity, we followed the latter index to calculated the Mediterranean score, thus rating with a “zero” point the presence of potatoes (included in all our menus at more than 17 g/day] (See the Discussion section for further comments). Method of calculations of food amounts A spreadsheet was developed to finely calibrate the food amounts and proportions of each daily menu, focused on the satisfaction of the RDAs of all the EAAs. Therefore, the essential amino acid, resulting the lowest one by combining all the foods included in each daily menus, was set as the “limiting” one, whereas the contents of all other amino acids were consequently up-graded, as described in detail in [28]. A compliance by ±5% of the total amount of the “limiting” EAA in respect to its target RDAs was tolerated. The limiting EAA was lysine (in all the seven VEG and in five LOV menus), valine (in one LOV menu) and leucine (in one LOV and all OMN menus). Calculation of the environmental impact of each menu The three environmental variables here considered were the Land Use (LU, in m 2 for kg of food product), the Green House Gas Emission (GHGE, in g of CO 2-equivalents produced per kg food) and the Water Footprint (WF, in Liter, L, of water consumed per kg food) [8-11, 51]. The latter was the sum of three main components, i.e. the green (=rainwater, either evaporated or incorporated into the product], blue (=surface and groundwater) and grey (=the water needed to dilute pollutants and restore the water reserve) ones [8, 27, 29]. These data were retrieved through a systematic literature search [unpublished data], reported only in61art previously [28], but here updated and extended to additional foods, and applied to more complex one-week mixed food regimens rather than those of single foods. Multiple estimates for the same food are often reported by the scientific literature (Supplementary Tables 2 and 3, and Supplementary References), thus increasing the complexity of data retrieval, reporting and analysis. For the sake of simplicity, the data here used are the calculated mean(s) derived from multiple estimates, except for red meat and fish (seabass) (See the Discussion for further comments). Only publications based on Life Cycle Assessment [LCA][2] methodology were taken into consideration [61] (Supplementary Tables 2 and 3). Calculation of land use, GHGE, water footprint, total calories, protein, sodium, saturated fat, and other nutritional elements, associated to meals satisfying the EAA RDAs. In the above-reported food combinations (see Supplementary Table 1 ) , including the three main meals and the added foods, we first calculated the three environmental parameters, i.e. LU, GHGE and WF, as well as the content of sodium, saturated fat, calories, total protein, and food weight, derived from the databases and the accessed publications. We assumed that the above-listed five nutritional variables, together with the three environmental ones, should be minimized in order to ensure an optimal, balanced, combined nutritional and environmental profile. As a matter of fact, sodium (to prevent hypertension, mortality and disability-adjusted life-years, DALYs), saturated fat (to minimize cardiovascular risk, but see also additional comments in the Discussion), calories (to prevent overweight and obesity, albeit approximating minimum energy requirements) [34, 38, 44], protein(s) (i.e. the higher the quality, the lower the quantity required), and food weight (to minimize the environmental footprint for food production), all should be maintained at the lowest-possible, although safe, intake level. Ranking the mixed foods menus The further step was to rank the food combinations of each menu type separately for GHGE, land use, WF, sodium, saturated fat, calories, protein, and food weight. Lower rankings would thus reflect healthier, more sustainable profiles, whereas higher rankings less healthy, less sustainable ones. To this aim, we used two methods. One was to transform each variable into the percent of the highest value of the group, with the aim to respect the relative distribution of the menus in respect to each parameter. Such a calculation is however highly sensitive extremely high values (i.e. “outliers”). Therefore, another method was to calculate the deviation of each value from the group median. We did not directly compare the values with either standard reference(s) or a recommended minimum, because for some of them there is no accepted, clearly-established, desirable limits, for instance for the three environmental variables. Only for sodium and saturated fat there are accepted recommendations [38, 44, 62]. In regard of protein intake, the protein quantity in either a food or a food combination, needed to satisfy the reference daily value of the EAAs, could be even below that of the recommended average protein intake [17], should the protein quality be particularly “high”. It should also be considered that the resulting ranked values obviously depend on both the number and the type of the selected foods, as well as on their relative amount(s) in the combinations. Therefore, the relative proportion, as well as the position(s) of the combinations, would change their rank within each variable group, should additional foods and/or different quantities or proportions be used in the menus. Taking into account these consideration and limitations, we calculated a “global EAA-based, Nutritional and Environmental Score” [EAA-NES], by summing up the percent values attained by each menu in the separate ranking of each of the eight variables. As anticipated, we also compared the menu types in respect to their deviations from median values. Therefore, lower values reflected nutritionally-healthier, more environmentally-sustainable characteristics, whereas higher values less healthy/sustainable ones. The LU, GHGE and WF data, as well as the percentualized global EAA-NES of the three menu types, were also analyzed as quartiles, using the built-in formulas of the Excel® software (version 10) (Microsoft Co, Redmond, Washington, USA). Statistical analysis The statistical comparison among the three menu-types, in regard of the three environmental parameter (i.e. LU, GHGE, total and green+blue WF), as well as sodium, saturated fat, total calories, protein and food weight, was performed using the 1-way Analysis of Variance [ANOVA] for independent groups, followed by the Tukey’s post-hoc text in the head-to-head group comparison. The normal distribution of the data, as well as absence of difference in variances among the three menu groups, were verified for each parameter. The Statistica® Software (StatSoft Inc, TIBCO Sofware Inc. Palo Alto, CA, USA, version 10) was employed. A p value <0.05 was considered as statistically significant. Data availability statement . The data used to calculate the food composition and their environmental footprint were derived from published peer-reviewed articles, internet sites and other publicly-available material, as detailed in the References of the main text, and in the Supplementary references list. [1] CREA stands for: Il Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economica Agraria , i.e. the Council for Agriculture Research and Analysis of Agrarian Economics. [2] The term LCA was introduced in 1979-1980, and was increasingly adopted in the last decade of the last century in particular following the 1997 publication of ISO standard 14040. Source: ECOINVEN database. Found in: www.ecoinvent.ch Abbreviations DALY: Disability-Adjusted Life-Years; EAA: Essential Amino Acids; e.p.: edible part; EVO: Extra Virgin Olive oil; GHGE: Green-House-Gas-Emission; LCA: Life Cycle Assessment; LOV: Lacto-Ovo-Vegetarian; LU: Land Use; MD: Mediterranean Diet; NES: Nutritional and Environmental Score; OMN: Omnivorous; RDA: Recommended Daily Allowance; VEG: Vegan; WF: Water Footprint. Declarations ACKNOWLEDGEMENTS The authors wish to acknowledge Ms. Linda Inverso for her excellent assistance in the correcting and proof-editing the manuscript. ETHICS DECLARATIONS Not applicable. COMPETING INTERESTS The author(s) declare no competing interests. AUTHORS’ CONTRIBUTION P. T. designed and conducted the research, wrote paper and had primary responsibility for final content. G. M. contributed to methodology, supervision, validation. G. B. contributed to data analysis, animal data critical assessment, the discussion section and manuscript revision. A. L. contributed to study conceptualization, methodology, paper writing, funding acquisition, investigation. All authors have read and approved the final manuscript. DECLARATIONS OF INTEREST : All authors disclose no conflict of interest. FUNDING SOURCES : The language editing of this manuscript was supported by an institutional Grant of the University of Padova, Italy (Grant n. DOR 2032990/20). References Hoekstra, A.Y., & Wiedmann, T.O. Humanity's unsustainable environmental footprint. Science 344 , 6188; 1114-7. https://doi.org10.1126/science.1248365 (2014). GBD 2017. Risk Factor Collaborators. Global EAA, regional, and national comparative risk assessment of 84 behavioral, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories,1990–2017: a systematic analysis for the Global EAA Burden of Disease Study. Lancet 392 , 1923-94 (2018). Willett, W. et al. 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Livelli di assunzione di riferimento di nutrienti ed energia per la popolazione italiana. IV Revision. https://sinu.it/tabelle-larn-2014/ Caffrey, K.R., & Veal, M.W. Conducting an agricultural life cycle assessment: challenges and perspectives. Sci. World J. (2013). Article ID 472431. https://doi.org/10.1155/2013/472431. NCBI. Dietary Reference Intakes. Food and Nutrition Board, Institute of Medicine, National Academies. (Tables 2,3,4). https://www.ncbi.nlm.nih.gov/books/NBK56068/table (2011) Tables Table 1: The absolute values of the environmental and nutritional variables considered in the three menu types. Land Use GHGE Total WF Green & Blue WF Na Saturated Fat Energy Total Protein Food Weight EAA-NES Score n m 2 g CO 2eq L L mg g kcal g kg Sum of % VEG 7 4.32 2.75 3247 2929 143 a 9.0 a 1695 75 1.6 541 ±0.21 ±0.15 ±260 ±236 ±35 ±1.5 ±56 ±4 ±0.1 ± 25 LOV 7 5.07 2.93 3587 3309 343 b 15.4 c 1636 71 1.5 624 ±0.23 ±0,11 ±185 ±182 ±40 ±1.4 ±57 ±5 ±0,1 ±16 OMN 7 4.90 2.82 3695 3526 200 a 9.6 a 1606 73 1.6 563 ±0.21 ±0.33 ±176 ±208 ±20 ±0.8 ±39 ±1 ±0.1 ±23 ANOVA F 2.845 0.134 1.061 1.850 6.551 7.635 0.294 0.148 2.544 2.863 p 0.084 0.876 0.337 0.186 0.007 0.004 0.749 0.863 0.106 0.833 Legend of the table: Values are Mean ± SEM. The (n) indicates the number of choices of daily menus in each group. Abbreviations: GHGE: Green House Gas Emission; WF: Water footprint; EAA-NES: Essential Amino Acid-Nutritional and Environmental Score. The EAA-NES is calculated the sum of the percent-transformed scores of the environmental and the nutritional parameters (see the Method section). Labeled means without the common letter ( a ) differ by: b p<0.006 vs VEG by the Tukey’s post hoc test. c p<0.006 vs VEG, and p<0.025 vs OMN, by the Tukey’s post hoc. Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterialmergedfile.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2005120","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":132434910,"identity":"c958a6f5-2e7c-481e-946a-d9f80d1e153e","order_by":0,"name":"Paolo Tessari","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYHACxgNwZkIFAwMbA4MBQwIBPQdAiiBazsC0ENCD0MLYBqaAPDxazNkPHzjwgeGPnHz/4WcfHs47nMcn3byB4eEP3Fose9ISDs5gMDA2uJFmPCNx2+FiNpljBXgdZnAgx+AwD4NB4gYJBmMGoJbENokc/H4xOP8GrKV+fv/xzwyJc4jRcgNiSwLDgRygLQ1EaLGc8QzoFwNjww03cooZEo6lJ7YB/XIgIQ23FnP+5IMPPlTIycv3H9/M+KPGOnH+7OaND3/Y4HEYEgkFEuCYIqQFBUjgUz8KRsEoGAUjEQAAYHxT4K/pdOYAAAAASUVORK5CYII=","orcid":"","institution":"University of Padua","correspondingAuthor":true,"prefix":"","firstName":"Paolo","middleName":"","lastName":"Tessari","suffix":""},{"id":132434912,"identity":"e309598a-6588-4467-a520-05b965aa0fa8","order_by":1,"name":"Giuliano Mosca","email":"","orcid":"","institution":"University of Padua","correspondingAuthor":false,"prefix":"","firstName":"Giuliano","middleName":"","lastName":"Mosca","suffix":""},{"id":132434914,"identity":"c021b5b2-8235-47ca-9300-f84df2f33e00","order_by":2,"name":"Giovanni Bittante","email":"","orcid":"","institution":"University of Padua","correspondingAuthor":false,"prefix":"","firstName":"Giovanni","middleName":"","lastName":"Bittante","suffix":""},{"id":132434916,"identity":"51b095b8-bea5-4a63-a2b8-c73a9ac0952a","order_by":3,"name":"Anna Lante","email":"","orcid":"","institution":"University of Padua","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Lante","suffix":""}],"badges":[],"createdAt":"2022-08-27 17:14:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2005120/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2005120/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":25953761,"identity":"fc01c663-4528-4484-a369-bee9cdf9923b","added_by":"auto","created_at":"2022-09-01 20:51:00","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":114238,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLand Use.\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThe land use (reported in the x axis as m\u003csup\u003e2\u003c/sup\u003e) associated to daily menus calculated to satisfy the RDA of all the EAAs of a 70-kg subject. The menu numbers [in the y axis] correspond to the mixed meals listed in Supplementary Table 1. Menus 1-7 (green bars) correspond to vegan meals [VEG]. Menus 8-14 (yellow bars) correspond to lacto-ovo-vegetarian meals [LOV]. Menus 16-21 (red bars) correspond to omnivorous meals [OMN], i.e. including also meat or fish.\u0026nbsp;\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2005120/v1/6b5aac41ecb2186be34c1b74.jpg"},{"id":25953762,"identity":"4fc64f05-3dd2-4a62-b8f5-ca76345f93ec","added_by":"auto","created_at":"2022-09-01 20:51:00","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":111760,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTotal Water Footprint.\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThe total water footprint (WF, reported in the x axis as Liters) associated to daily menus calculated to satisfy the RDA of all the EAAs of a 70-kg subject. The menu numbers (in the y axis) correspond to the mixed meals listed in Supplementary Table 1. Menus 1-7 (green bars) correspond to vegan meals [VEG]. Menus 8-14 (yellow bars) correspond to lacto-ovo-vegetarian meals [LOV]. Menus 16-21 (red bars) correspond to omnivorous meals (OMN), i.e. including also meat or fish.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2005120/v1/0f9d86aa560da56fab16c1bd.jpg"},{"id":25954272,"identity":"cc6d71f2-657b-4a60-bbae-62d9655436e5","added_by":"auto","created_at":"2022-09-01 20:56:01","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":102388,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGHGE.\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThe Green House Gas Emission (GHGE), reported in the x axis as g CO\u003csub\u003e2-eq\u003c/sub\u003e, i.e. including CO\u003csub\u003e2\u003c/sub\u003e, and other gases such as Methane, Nitrous Oxide, Fluorinated gases, all contributing to the Green House Gas Emission effect], associated to daily menus calculated to satisfy the RDA of all the EAAs of a 70-kg subject. The menu numbers (in the y axis) correspond to the mixed meals listed in Supplementary Table 1. Menus 1-7 (green bars) correspond to vegan meals [VEG]. Menus 8-14 (yellow bars) correspond to lacto-ovo-vegetarian meals [LOV]. Menus 16-21 (red bars) correspond to omnivorous meals [OMN], i.e. including also meat or fish.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2005120/v1/d8f32e7a0de4101719c1eac6.jpg"},{"id":25954271,"identity":"59aae120-a333-43d1-a5b1-897f34ae3743","added_by":"auto","created_at":"2022-09-01 20:56:00","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":88247,"visible":true,"origin":"","legend":"\u003cp\u003eQuartile distribution of the environmental footprint data of VEG, LOV and OMN menus. The panels on the left show the menus’ distribution of Land Use (top panel), GHGE (middle panel) and Total Water Footprint (bottom panel), also by combining the distribution of [1+2] quartiles, and that of [3+4] ones, as indicated. On the right, the quartile distribution of the Global EAA Nutritional and Environmental Score (EAA-NES) is reported. \u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2005120/v1/e15bd18ac58dcc5bda68935d.jpg"},{"id":25954903,"identity":"32619412-ae2e-404a-b99e-cadcde783bb9","added_by":"auto","created_at":"2022-09-01 21:01:00","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":133032,"visible":true,"origin":"","legend":"\u003cp\u003eThe figure reports the distribution of the menus’ associated values of the Global EAA-NES (Nutritional and Environmental) score, i.e. the sum of the percent-transformed values of each variable (see Methods for details on calculation). The variables are the environmental ones (Land Use, GHGE, Total Water Fooprint), and the “nutritional” ones (Sodium, Saturated Fat, Calories, Total Protein and Food Weight), calculated to satisfy the RDA of all the EAAs of a 70-kg subject. The percent values of each variable are reported in different colors. The total length of the horizontal bars is the sum of the percent-transformed values of the variables in each menu. The menu numbers (in the y axis) correspond to the mixed meals listed in Supplementary Table 1. Menus 1-7 correspond to vegan meals (VEG). Menus 8-14 correspond to lacto-ovo-vegetarian meals (LOV). Menus 16-21 correspond to omnivorous meals (OMN), i.e. including also meat or fish.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2005120/v1/c464adc2ac90e24277b482fb.jpg"},{"id":29789254,"identity":"e2455bd0-6dad-4c71-89ee-6fadc6698d99","added_by":"auto","created_at":"2022-12-01 19:14:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":803028,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2005120/v1/fd911aca-bd40-498c-a1e4-b26958515eab.pdf"},{"id":25953766,"identity":"57d27478-c152-45dc-ade7-c2782fdbdfdd","added_by":"auto","created_at":"2022-09-01 20:51:01","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2108704,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterialmergedfile.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2005120/v1/2ba684c528957fc47b544a19.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The environmental footprint of in silico-designed vegan, lacto-ovo-vegetarian and omnivorous diets complying with Mediterranean diet standards and essential amino-acid requirements","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe steadily-growing global population requiring appropriate nutrition, the increase of global warming and the shifts in land use and water consumption, constitute serious risks to the planet\u0026rsquo;s environmental sustainability [1, 2]. An optimal balance between peoples\u0026rsquo; healthy nutritional requirements [for health maintenance and chronic disease prevention], and the food-associated global environmental footprint, is strongly felt to be pursued nowadays. There are growing ethical implications about food choice \u0026amp; quality and the associated environmental footprint [3-7].\u003c/p\u003e\n\u003cp\u003eCommon indexes of the environmental footprint linked to food production are land use (LU), the water footprint (WF) and the Green House Gas Emission (GHGE) [8-11]. Many studies have investigated these indexes of environmental footprint in respect to the food industry [7-14], also by comparing animal and vegetal foods, type of meat, common menus etc. [11, 13, 14]. Generally speaking, crop-based diets are usually associated to a lower environmental footprint than that of animal or mixed ones [12-14], and many have hypothesized that producing (and eating) more vegetables and fruit than animal-derived foods, could result in a better environmental impact.\u003c/p\u003e\n\u003cp\u003eSome key methodological issues should however be considered in these investigations. The comparisons among foods or diets have been usually based on either food raw weight [11], energy density [7], average daily menu(s) [11], or nutritional quality [13], but normally they did not consider the quality of the protein consumed based on their amino acid profile. As a matter of fact, a healthy diet should provide all the essential nutrients as well as the energy required daily [15, 16]. The essential amino acids (EAAs) are key, indispensable substrates that need to be introduced in sufficient amounts, i.e. at the recommended daily allowances (RDAs) to guarantee optimal growth, health, recovery from disease, etc., along with other essential nutritional elements [16, 17]. Therefore, in the light of the growing interest in the complex and important relationships between food consumption and the environmental footprint [18-27], also the nutritional availability of all the EAAs should be taken into consideration.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFrom an investigational standpoint, both \u0026ldquo;bottom-up\u0026rdquo; and \u0026ldquo;top-down\u0026rdquo; methods can be employed. The former are based on data collection on existing eating habits, that need to be associated to estimates of the environmental footprint of the eaten foods. Conversely, the latter could examine the theoretical footprint of either single foods or \u003cem\u003ein silico\u003c/em\u003e-designed diets, on the environmental parameters.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUsing the latter approach, we recently reported that the environmental footprint of selected, staple vegetal and animal-origin foods, at an edible food weight guaranteeing the RDA of all EAAs, does not show any consistent, clear-cut advantage of vegetal over animal foods [28]. Such a somehow-unexpected conclusion was apparently due, besides their specific footprint values, also to the greater edible fraction, the higher protein concentration, and the richer and more balanced EAA content, of animal than vegetal foods. In other words, a smaller quantity of animal than vegetal food was required to satisfy human EAA requirements. Therefore, from our as well as from other reports, it may be suggested that the choice between vegetal and animal foods should be based on a more-in-depth consideration of nutritional and environmental variables, under an integrated perspective [28-31].\u003c/p\u003e\n\u003cp\u003eOur initial investigation was however limited almost exclusively to single foods, i.e. it did not consider complex diets, nor it compared different diet-types [28]. In addition, the water footprint and the energy content of the foods were not considered [28]. Generally speaking, no food guarantees the ideal proportion and/or quantity of amino acids to meet their requirements in humans, although some are closer than others. Such a target could rather be better achieved with mixed diets, where the deficiency in some EAA(s) and the excess in some other EAAs of a given food, could be compensated by different, complementary proportions of EAAs from other foods. In other words, the statements formulated from the analysis of single foods [28] couldn\u0026rsquo;t be applied directly to complex diets. Moreover, the nutritional adequacy of the diets should include other nutritional elements besides the EAAs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGiven these premises, the current study was designed to analyze, under the driving perspective of EAA requirement(s), the effects of food combinations in sample, \u003cem\u003ein-silico\u003c/em\u003e designed, applicable diets, on the environmental footprint. The diets were divided into vegan, lacto-ovo vegetarian and omnivorous ones. A variety of daily meal choices were assembled, to end up into seven different one-week menus for each diet-type, all complying with Mediterranean-Diet (MD) standards [32, 33]. The environmental footprint data (LU, WF and GHGE) of foods were retrieved from the literature and re-calculated. Some relevant nutritional parameters (sodium, saturated fat, energy and protein, in addition to food weight) were determined too. A global \u0026ldquo;EAA-Nutritional and Environmental Score\u0026rdquo; (EAA-NES) was proposed, to enable a simple comparisons among the menu types.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe calculated MD Index score [33] was (9/11) in all menus, but (10/11) in the two fish-containing OMN menus, showing a good/excellent overall compliance with the MD (See Methods). As reported above, despite the addition of extra foods, the average total caloric content of the menus resulted to be between \u0026asymp;8% and \u0026asymp;25% lower (\u003cstrong\u003eTable 1\u003c/strong\u003e) than that recommended in sedentary middle-age female and male subjects] [34]. \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe total content of starch-rich foods (excluding legumes) in OMN menus (283 \u0026plusmn; 29 g) was greater than that in VEG menus (183 \u0026plusmn; 25 g, p\u0026lt;0.04 by ANOVA followed by the Tukey\u0026rsquo;s post-hoc test), whereas that of LOV menus (214 \u0026plusmn; 29 g) menus was intermediated (p \u0026gt;0.17). The content of legumes of OMN menus (36 \u0026plusmn; 4 g) was \u003cu\u003e\u0026gt;\u003c/u\u003e3-fold lower than that of both VEG (101 \u0026plusmn; 16 g) and LOV menus (105 \u0026plusmn; 16 g) (p\u0026lt;0.007 and p\u0026lt;0.005 respectively, by ANOVA followed by the Tukey\u0026rsquo;s post-hoc test).\u003c/p\u003e\n\u003cp\u003eThe data of the environmental footprint, i.e. the LU, total WF and GHGE, associated to the different menus calculated to comply with the RDA of all the EAAs, are visually reported on \u003cstrong\u003eFigures 1-3\u003c/strong\u003e, ranking the diets from the lowest (i.e. with a more favorable impact) to the highest value (=less favorable impact). In regard of LU (\u003cstrong\u003eFigure 1\u003c/strong\u003e), the different diets of the three menu-types are not clearly clustered, although all VEG menus fell within middle-to-low positions of the ranking, indicating a tendency for a lower land requirement. In the case of the total WF, an overlap in the ranking of the three menu-types was more evident, the VEG menus occupying both the first and the last position (\u003cstrong\u003eFigure 2\u003c/strong\u003e). Also GHGE ranking of the individual menus of the three menu types was quite scattered (\u003cstrong\u003eFigure 3\u003c/strong\u003e), showing no preferential menu-associated distribution. In respect to GHGE, OMN menus occupied both the first two and the last two positions. These visual impressions were confirmed by quartile analysis \u003cstrong\u003e(Figure 4)\u003c/strong\u003e, although the LU, GHGE and total WF allocation of VEG menus fell predominantly into the first two quartiles.\u003c/p\u003e\n\u003cp\u003eThe aggregated values (as Means \u0026plusmn; SE) of the environmental footprint data, of sodium, saturated fat, calories, protein menu content, food weight, and of the global EAA-based,\u0026nbsp;Nutritional and Environmental score (EAA-NES), are reported on Table 1. Despite the apparent trend(s) depicted on Figure 1, no statistical difference in any of the environmental parameters was observed among the mean values of the three menu-types, except for a borderline lower (by \u0026asymp;15%) Land Use in VEG than LO menus (p=0.052\u0026nbsp;by 1-way ANOVA and the Tukey\u0026rsquo;s post-hoc test). In contrast,\u0026nbsp;in LOV menus, sodium content was\u0026nbsp;\u0026asymp;60% greater than in VEG menus (p\u0026lt;0.006, by 1-way ANOVA and the Tukey\u0026rsquo;s post-hoc test), whereas saturated-fat content was greater by\u0026nbsp;\u0026asymp;70% (p\u0026lt;0.006) and\u0026nbsp;\u0026asymp;60% (p\u0026lt;0.025) than in VEG and OMN menus respectively.\u0026nbsp;Total energy, protein and food weight were not significantly different among the three menu types. The EAA-NES was not different among the menu types too (Table 1), also when the mean differences from the median were calculated (VEG: -38 \u0026plusmn; 28; LOV: 40 \u0026plusmn; 18; OMN: -11 \u0026plusmn; 26) (F: 2,54, p = 0.106, by 1-way ANOVA). \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe menus\u0026rsquo; distribution of the global EAA-NES score, (calculated as the sum of the percent values of each variable vs. the corresponding maximum) is reported in \u003cstrong\u003eFigure 5\u003c/strong\u003e. First, it can be observed that the maximum difference between the highest and the lowest value was by \u003cu\u003e\u0026lt;\u003c/u\u003e50%, showing a relatively small variation among menus. Although the five lowest positions (indicating a better combined Nutritional and Environmental score) are occupied by four VEG and one OMN menus, as opposed to three LOV and two OMN menus placed in the highest five ones, there is no apparent, consistent trend or pattern associated to any menu type. As a matter of fact, the menus are scattered anywhere in the panel, irrespective of their types. This impression is supported also by the quartile distribution analysis of the data (Figure 4). Although four out of the seven VEG menus are allocated within the first quartile vs. none in the fourth one (at variance with what observed for LOV and OMN menus), by combining the data of the two lowest (i.e. 1 and 2) and the two highest (3 and 4) quartiles, the distribution of the three menu types into the combined low and high quartiles was virtually the same.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe report here estimates of the environmental footprint and of some key nutritional variables, of \u003cem\u003ein-silico\u003c/em\u003e designed vegan, lacto-ovo-vegetarian and omnivorous menus, calculated on food amounts satisfying the daily requirements of all the essential amino acids, and complying with Mediterranean diet standards. This study represents a step-forward over our previous one [28] focused on the environmental footprint of selected, staple vegetal and animal-origin foods, here extended to a larger variety of popular foods included into complex meals and structured into vegan, lacto-ovo-vegetarian and omnivorous menus. The meal design intentionally was not based on epidemiologically-derived, statistically-calculated food frequencies, nor on schematic diets and/or menus proposed by official and public agencies (predominantly because of the enormous amount of choices). Rather, it was based on the unbiased assembly of some popular foods providing the RDAs of all the essential amino acids and complying with the \u0026ldquo;Mediterranean\u0026rdquo; diet and custom. Nevertheless, it represents a theoretical exercise both to calculate \u0026ldquo;\u003cem\u003ein silico\u003c/em\u003e\u0026rdquo; the environmental footprint and some nutritional parameters of sampled diets/menus, and to show the technical feasibility of designing diets with a specific environmental impact. We also propose here a global EAA-based, environmental-nutritional (EAA-NES) score, to rank menus by combining their environmental footprint and few nutritional variables.\u003c/p\u003e\n\u003cp\u003eThis study shows that vegan, lacto-ovo-vegetarian and omnivorous sample diets, analyzed as separate groups, could result to be not different in any of the environmental variables (Table 1), nor in the calculated global nutritional \u0026amp; environmental score (Figure 5). Thus, on the basis of these in-silico-designed menus, it cannot be concluded that VEG diets, as a group, are \u003cem\u003eper se\u003c/em\u003e better than LOV and OMN diets from an environmental \u0026amp; nutritional standpoint. Overall diet ranking apparently depends at large on which diet within each group is chosen, i.e. on within-group diet variability and, possibly, also on the limited number of diets here designed for each group. Therefore, although our diet design and choice may appear somehow subjective, our study demonstrate a potentially ample choice within VEG, LOV and OMN diets, complying with different degrees of environmental footprint. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe ranking of the menus in respect of the environmental variables appeared randomly scattered, and included a rather limited range too, irrespective of menu type (Figures 1-3). Although VEG menus apparently exhibited lower LU, GHGE and total WF values than LOV and OMN menus (Figures 1, 2), these differences were not confirmed by comparing the three menus\u0026rsquo; groups (Table 1). Furthermore, the relative difference between the lowest and the highest value(s) (irrespective of menu type), was approximately 0.6 fold for LU (Figure 1), 1.0-fold for total WF (Figure 2), and \u0026asymp;1.2-fold for GHGE (Figure 3). These ranges are either close to, or lower than, those previously reported for environmental footprint parameters of vegetal and animal single foods [9, 11, 14], as well as of dietary regimens [4, 9, 10, 14, 26]. Also the global EAA-NES did not cluster around any specific menu type (Figures 4 and 5), the relative difference between the lowest and the highest value being approximately by 50%. Although omnivorous diets are usually associated with worse carbon, water and ecological footprints, than those of both lacto-ovo-vegetarian and vegan diets [9,11-14, 26], a large intragroup variability within OMN diets was reported by others too [26]. These observations support the view that the difference(s) in the average environmental footprint among VEG, LOV and OMN diets could be both quite limited, and affected by a large within-diet variability, enabling an imaginative approach in the design of vegan, vegetarian and omnivorous regimens with the best environmental footprint. In other words, adequate food combinations may optimize the nutritional and environmental parameters irrespective of the diet type.\u003c/p\u003e\n\u003cp\u003eIn regard of the impact of meat in the comparison between OMN, and either LOV or VEG diets, it may be argued that the amount of meat in OMN diets was modest (i.e. \u0026asymp;150 g and 120 g of red and white meat, respectively, per week) (Supplementary Table 1), as opposed to greater amounts commonly reported for omnivorous diets [26, 35-37]. Although the relatively low meat amount included in our OMN diets was primarily due to the constraint of our approach (i.e. the focus on EAA requirements), a moderate intake of meat [preferably white, but not excluding small amounts of red and/or processed meat], is considered by recent dietary indications [3, 32, 38].\u003c/p\u003e\n\u003cp\u003eLOV menus as a group were associated to greater sodium and saturated fat content than the two other menu types (Table 1), although well below the maximum recommended intakes [16]. This was mostly due to the presence in LOV menus of dairy products, particularly of cheese, rich in [natural] saturated fat, as well as in salts [39-42]. Both sodium and saturated fat had been positively associated to cardiovascular disease [33, 38, 43, 44, 45]. In regard of saturated fat, its health-related effects should however be reconsidered in the light of recent meta-analyses and large prospective cohort studies [46, 47], outlining the inconsistency of the common claims about a negative role of saturated fatty acids on cardio-vascular diseases. In a State-of-the-Art review, the American College of Cardiology recently stated the absence of \u0026ldquo;beneficial effects of reducing saturated fat intake on cardiovascular disease (CVD) and total mortality\u0026rdquo;, rather the presence of \u0026ldquo;a protective effects against stroke\u0026rdquo; [47]. Substitution of the current nutrients-based guidelines for food-group based macronutrient indications was recommended [47], and no available evidence from a large body of current studies would support a restriction in the intake of \u0026ldquo;whole-fat dairy, unprocessed meat, and dark chocolate\u0026rdquo; to prevent cardiovascular disease [48, 49]. The acceptance of such a recent position on saturated fat would obviously question the validity of including saturated fat among \u0026ldquo;the lower, the better\u0026rdquo; variables considered in the NES score (see Methods and Results). Therefore, waiting for an updated, unanimously-accepted position about the role of saturated fat on cardiovascular disease(s), our results should be taken with caution. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll menus were intentionally designed to provide approximately the same energy to avoid a significant bias in menu comparisons (see the Method section and Supplementary details of methods). Furthermore, since the \u0026ldquo;focal\u0026rdquo; variable of our approach was the satisfaction of EAA RDAs rather than energy provision, the calculated total food amounts, irrespective of menu type, resulted into an (unexpected) total caloric content by \u0026asymp;20%-25% lower than reference intakes even in sedentary individuals [34, 50]. While we acknowledge such a limitation, an increase of the caloric content of the diet(s), approaching the \u0026ldquo;minimum\u0026rdquo; requirement of \u0026asymp;2000 kcal/day, could be easily and freely attained at the consumer\u0026rsquo;s choice, by adding sucrose (not considered in our diets), either as such and/or as sucrose-containing soft drinks, sweets or cakes, as well as by increasing vegetal oil in the menus. These additional nutrients, if added at the same amount to all menus, will not modify the (relative) differences among the menus in the environmental footprint.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe did not report here the calculated provision of other essential nutritional elements (oligo elements, vitamins, essential fatty acids etc.) in respect to their individual RDAs (Tessari et al, unpublished results). The abundance of fruit and vegetables could anyway guarantee consistent amounts of some of these elements, that however need to be accurately determined.\u003c/p\u003e\n\u003cp\u003eThe design of an \u0026ldquo;ideal food system\u0026rdquo; requires an integrated approach, combining health science(s), food technologists, the food production system(s) and their environmental footprint, and else [12, 14]. Regional, income-related factors can condition the effects of replacement of animal-source foods with vegetal-based diets [10]. Energy-balanced, plant-based dietary regimens are associated with both healthy nutritional habits and a low environmental impact particularly in high-income and middle-income countries [10]. Conversely, their impact would be of lower magnitude in low-income countries, because of less efficient production systems and increase demand for environmental resources [10]. In our \u003cem\u003ein silico\u003c/em\u003e, theoretical study, we did not aim at either examining these complex relationships, nor at analyzing extensive epidemiological data; rather we present here theoretical estimates of the environmental impact of some sample, \u003cem\u003ein silico\u003c/em\u003e-designed, although applicable, dietary regimens. The conclusion(s) of our work should be placed in the context of many other social-economic variables, as well as applied and/or adapted to specific populations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe study of the association between the type of food production/consumption, and the environmental footprint is at the core of current debates. The agricultural system accounts for relevant fractions of the earth\u0026rsquo;s cultivable land (\u0026asymp;40%), of freshwater use (\u0026asymp;70%) and of the total greenhouse gas emission (\u0026asymp;20%) [49, 51]. The growing use of land and water, and the \u0026nbsp;worsening of the greenhouse effect for food production, represent serious challenges to the earth\u0026rsquo;s sustainability [51, 52]. Therefore, dietary choices could represent key lifestyle-related factors capable of modifying and/or minimizing the environmental footprint due to agriculture and food production. Any intervention upon the agricultural food system should however be weighed in respect of the provision of adequate nutrition to people. High quality proteins are distinctly found in many animal foods, besides (red) meat. The heavy environmental impact of an [excessive] production of bovine meat [8, 9, 11, 49, 51], as well as the risk conveyed by an exaggerated consumption particularly of processed red meat on human health are well established [43]. The shift from current consumption patterns to \u0026ldquo;sustainable diets\u0026rdquo; rich in vegetal foods, could be associated to both human health protection and a reduced GHGE [52]. While keeping in mind these key observations, a comprehensive, unbiased and thoughtful analysis of all the variables involved in dietary planning, based on objective data, would nevertheless be advisable. From our data, balanced mixtures of vegetal and animal proteins, the latter including not only egg or dairy foods, but also poultry, fish, and/or moderate amounts of (preferably unprocessed) red meat, appear to be both feasible and recommended, from an environmental and a nutritional standpoint. In addition, food combinations would positively interact to end up into proportionally lower total amounts of food(s), thus contributing to the reduction of the environmental footprint.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe conclusions of this study are based on published, peer-reviewed, often multiple, estimates of environmental parameters. From a methodological standpoint, these kind of data are \u003cem\u003eper se\u003c/em\u003e quite difficult to be calculated, and often show a large variability, in particular those of beef meat and fish (seabass), largely because of differences between [semi]intensive and extensive production systems (see Supplementary Methods, Tables 2 and 3, and References). Indeed, when the gross means of these two different systems are compared, LU can differ by up to \u0026asymp;20-fold for beef meat, and by up to \u0026asymp;5-fold for seabass, whereas those of GHGE differ by \u0026asymp;3-fold for beef meat (Supplementary Table 3 and References). In our study, we arbitrarily chose to use the (semi)-intensive system data for both beef and seabass, because of the following reasons. First, the \u0026ldquo;large\u0026rdquo; environmental footprint due to extensive beef meat production systems would not necessarily imply a \u0026ldquo;worse\u0026rdquo; LU and GHGE footprint, because: a) the extensive land surface used for grazing wouldn\u0026rsquo;t often be used for other purposes; b) the GHGE effect [due to methane released by rumination], reportedly \u0026asymp;3-fold greater with extensive than intensive systems [53], would be almost entirely balanced by CO\u003csub\u003e2\u003c/sub\u003e fixation in the grassland (used by grazing animals) through the Calvin-Benson cycle, since CO\u003csub\u003e2\u0026nbsp;\u003c/sub\u003efixation exceeds by\u0026nbsp;\u0026asymp;10% the CO\u003csub\u003e2\u0026nbsp;\u003c/sub\u003eproduced from the released methane [54]; and: c) the half-life of methane in the atmosphere is at least 10-fold faster than that of CO\u003csub\u003e2\u003c/sub\u003e, although a precise estimate of the latter is difficult because the processes involved have different time scales [51]. Secondly, intensive and (semi)-intensive systems, if properly developed, efficiently applied and with consideration for animal welfare too, may lead to an optimized production of high quality protein food while minimizing the environmental impact [54, 55\u003cstrong\u003e].\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dietary requirement of protein is inversely associated to its quality, as reflected by an adequate and balanced content of essential amino acids. Similarly, also the required food weight would be inversely proportional to its content of protein, as well as of other essential substrates (i.e. the greater the protein content, the lower the food amount needed). Since protein content and quality are higher in animal than in vegetal foods (except for soybeans), less animal than vegetal protein (and food) amounts would be required to guarantee the RDAs of all the EAAs. Such a reduction would affect the LU, GHGE and WF too. In addition, protein complementation attained by adequate mixing of foods of any source, reciprocally compensating for opposite EAA deficiencies [57], could lead to lower amounts of both vegetal or animal foods, thus reducing the overall environmental impact, as outlined above.\u003c/p\u003e\n\u003cp\u003eThe results of this theoretical study could be relevant in respect of the need to feed the world\u0026rsquo;s population healthy food without further wasting the planet\u0026rsquo;s resources. The double burden of malnutrition (both undernutrition and over-nutrition) affects \u0026gt;3.500 million people, of whom \u0026nbsp;\u0026asymp;850 million by undernutrition, vs. \u0026asymp;2500 million, (\u0026asymp;35% of the current world population) by over nutrition [58]. Another billion of people suffer from \u0026ldquo;hidden hunger\u0026rdquo;, i.e. they have sufficient energy intake but are deficient in key nutrients, particularly of high-quality proteins, therefore of EAAs [59]. Appallingly, the number of \u0026ldquo;malnourished\u0026rdquo; individuals in the world is steadily rising [58]. Both undernutrition and over-nutrition are associated to altered growth, reduced life expectancy, and poor health, not to mention devastating psychological effects. Since malnutrition is frequently linked to poor food quality [59], the availability of high quality foods and suitable combinations would retain a significant impact on human health.\u003c/p\u003e\n\u003cp\u003eIn the calculation of the global EAA-NES score we roughly considered energy intake as a variable to be kept at a minimum to prevent overweight and obesity. However, energy intake should also be proportional to the actual needs of a given human being as well as of a population, and, more importantly, sufficient to prevent malnutrition. This considerations should be taken into account in specific conditions.\u003c/p\u003e\n\u003cp\u003eIt could be argued that any nutrient deficiency, including that of the EAAs themselves, could be replaced by appropriate supplements. While this possibility is logic and should be carefully considered, the cost and the feasibility of this approach should be balanced against both the effective \u003cem\u003ein vivo\u003c/em\u003e availability of the supplemented nutrient(s), and the environmental impact and cost(s) associated to their production. As a matter of fact, the goal of food-based dietary guidelines is to consume the full complement of essential nutrients from natural foods (i.e. not supplements).\u003c/p\u003e\n\u003cp\u003eIn conclusion, \u003cem\u003ein silico\u003c/em\u003e-designed vegan diets do not necessarily rank better than lacto-ovo-vegetarian and omnivorous ones, when key environmental and nutritional parameters, such the EAA RDAs, are considered. More detailed analyses on the relationships between the nutritional quality of foods and their environmental footprint are warranted to guarantee both human health and the planet\u0026rsquo;s future.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eFood choice, composition, and data source\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePopular, staple foods utilized worldwide, but preferentially based on western countries traditions, included into the MD frame, and with a specific reference to Italy, were considered [32, 33, 35, 36, 37, 43]\u0026nbsp;Among vegetal ones, we selected nuts (almond, hazelnut, pistachio, walnut), legumes (bean, pea, soybean, lentil), cereals as either flour (maize, wheat) or a refined food (rice), a pseudo-cereal (quinoa), a tuber (potato), a cucurbita (zucchini), a solanale (eggplant), lettuce, and cultivated mushroom type (pleurotus). Among animal ones, we selected: beef (and beef-derived bresaola); pork (and bacon); chicken egg; dairy products (milk, yogurt, ricotta, gorgonzola and parmesan); fish (cod and seabass); and poultry (chicken and turkey). Each meal also contained extra virgin olive oil [EVO], fruit (both fresh and dried), coffee and/or chocolate, and one serving of an alcoholic drink (either wine or beer).\u003c/p\u003e\n\u003cp\u003eThe composition of each food, including their amino acid concentration, was largely retrieved from the public, free database of the Italian National Research Institute of Food and Nutrition (INRAN, renamed CREA[1] in 2015) [39]. For foods not considered by CREA/INRAN, we relied on additional sources, i.e. the ANSES Ciqual French database [40], that of the USDA [41], or that of the European Institute of Oncology [42]. For some foods, additional selected publications were retrieved, as reported in part previously [28] (See also the complete Reference list in the Supplementary material).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe edible parts [e.p.] of the foods, i.e. the food fraction effectively viable for nutrition, were derived and/or calculated from the references. The WHO/FAO/UNU amino acid requirements [17], recalculated to a standard 70-kg young male subject, were used.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eFood combinations\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFood combinations were mainly designed following Italian common, traditional recipes and proportions. In order to quantitate food amounts in respect to \u0026ldquo;servings\u0026rdquo;, that notoriously vary among national tradition and uses, we referred to Italian portion/serving values, as reported in [60]. Therefore, no specific, statistically-determined food frequency, was applied in the assembly of these combinations, although it was intentionally unbiased, except for the choice of \u0026ldquo;reasonable\u0026rdquo; food amounts and proportions in the meals.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe chosen foods were combined to provide a variety of daily menus, each composed by three main meals (breakfast, lunch and dinner), according to three diet types containing either only vegetal foods, i.e. complying with a \u0026ldquo;vegan\u0026rdquo; [VEG] diet, or mixed vegetal and animal foods, according to both \u0026ldquo;lacto-ovo\u0026rdquo; vegetarian [LOV] and omnivorous [OMN] diet-types. The list and the detailed food composition and amounts of each of the resulting twenty-one different daily menus, divided into the three types, are reported in Supplementary Table 1. Each daily menu was designed to contain at least one legume and one cereal, with the aim to reciprocally compensate the (relative) lysine deficiency of cereals, and that of sulfur amino acids (methionine and cysteine) of legumes [57]. No added sucrose, salt, other dressings, sweeteners, or sauces, were considered in food design.\u003c/p\u003e\n\u003cp\u003eMenu assembly was also intentionally developed to furnish approximately the same calories with all menus. This target was quite complex to be achieved, for several reasons. First, the initial step was to design just the three main daily meals complying with the reference daily value of the EAAs (Supplementary Information). However, under this premise all menus resulted quite hypocaloric (between\u0026nbsp;\u0026asymp;700 and\u0026nbsp;\u0026asymp;1000 kcal, data not reported), i.e. below recommended standards [34]. Therefore, in order to increase both the menus\u0026rsquo; total calories and their variety, we included into all menus additional foods (potato, extra bread), as well as olive oil, fruit (both fresh and dried), chocolate, coffee, lettuce. An alcoholic beverage (either red wine or beer) was added to all but one menu of each type. The quantities of these added foods were identical in all menus, except for bread and potato, titrated in each menu in the effort to match their total caloric content\u0026nbsp;(Supplementary Table 1). Following these further additions, the food amounts of the main meals, satisfying the reference daily requirements of the EAAs had obviously to be recalculated. Despite these adjustments however, the resulting total caloric content of the menus was still (mildly) below (by \u0026asymp;8-25%, depending on either female or male sex, respectively), that recommended in middle-age human individual of either sex with a sedentary lifestyle (\u0026asymp;1800-2200 kcal/day) [34]. While such a limitation should be considered, it nevertheless left open the possibility to each consumer, to add other nutrients (such as sucrose or vegetal fat, see also the Discussion) at his/her choice, albeit at the same amount(s), to avoid a bias among the menus in the calculated footprint data.\u003c/p\u003e\n\u003cp\u003eSeven options were designed for each VEG, LOV and OMN menu type, with the aim both to provide a different daily choice for one week-periods, and to allow a statistical comparison among the menu types.\u003c/p\u003e\n\u003cp\u003eA Mediterranean Diet index, based on both the type and the amount of foods, was calculated for each menu. Although the type of vegetal and animal-based food products is variable in the MD as well as among Mediterranean countries [31], we used the \u0026ldquo;Italian Mediterranean Index\u0026rdquo; as proposed by Agnoli et al [33], that includes eleven items, recommended at amounts either equal or above a given threshold value. These items are: complex carbohydrates (except potato), \u0026ldquo;MD\u0026rdquo; vegetables, fruit, nuts \u0026amp; legumes, olive oil and fish. Conversely, the items to be consumed in \u0026ldquo;low\u0026rdquo; amounts are potato, red \u0026amp; processed meat, butter, whereas soft drinks are totally excluded. Although for most items, the Mediterranean Diet Pyramid [32] and Agnoli\u0026rsquo;s index [33] are concordant, they are instead discordant about the amount of potatoes, allowed to a maximum of 1-2 servings (included in the starch-rich foods) at each main meal in the former [32], but surprisingly limited to \u0026lt;17 g/day in the latter [33] (Supplementary details on methods). Nevertheless, for the sake of simplicity, we followed the latter index to calculated the Mediterranean score, thus rating with a \u0026ldquo;zero\u0026rdquo; point the presence of potatoes (included in all our menus at more than 17 g/day] (See the Discussion section for further comments). \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eMethod of calculations of food amounts\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA spreadsheet was developed to finely calibrate the food amounts and proportions of each daily menu, focused on the satisfaction of the RDAs of all the EAAs. Therefore, the essential amino acid, resulting the lowest one by combining all the foods included in each daily menus, was set as the \u0026ldquo;limiting\u0026rdquo; one, whereas the contents of all other amino acids were consequently up-graded, as described in detail in [28]. A compliance by \u0026plusmn;5% of the total amount of the \u0026ldquo;limiting\u0026rdquo; EAA in respect to its target RDAs was tolerated. The limiting EAA was lysine (in all the seven VEG and in five LOV menus), valine (in one LOV menu) and leucine (in one LOV and all OMN menus).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eCalculation of the environmental impact of each menu\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe three environmental variables here considered were the Land Use (LU, in m\u003csup\u003e2\u003c/sup\u003e for kg of food product), the Green House Gas Emission (GHGE, in g of CO\u003csub\u003e2-equivalents\u003c/sub\u003e produced per kg food) and the Water Footprint (WF, in Liter, L, of water\u003csub\u003e\u0026nbsp;\u003c/sub\u003econsumed per kg food) [8-11, 51]. The latter was the sum of three main components, i.e. the green (=rainwater, either evaporated or incorporated into the product], blue (=surface and groundwater) and grey (=the water needed to dilute pollutants and restore the water reserve) ones [8, 27, 29]. These data were retrieved through a systematic literature search [unpublished data], reported only in61art previously [28], but here updated and extended to additional foods, and applied to more complex one-week mixed food regimens rather than those of single foods. Multiple estimates for the same food are often reported by the scientific literature (Supplementary Tables 2 and 3, and Supplementary References), thus increasing the complexity of data retrieval, reporting and analysis. For the sake of simplicity, the data here used are the calculated mean(s) derived from multiple estimates, except for red meat and fish (seabass) (See the Discussion for further comments). Only publications based on Life Cycle Assessment [LCA][2] methodology were taken into consideration [61] (Supplementary Tables 2 and 3).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eCalculation of land use, GHGE, water footprint, total calories, protein, sodium, saturated fat, and other nutritional elements, associated to meals satisfying the EAA RDAs.\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn the above-reported food combinations (see Supplementary Table 1\u003cem\u003e)\u003c/em\u003e, including the three main meals and the added foods, we first calculated the three environmental parameters, i.e. LU, GHGE and WF, as well as the content of sodium, saturated fat, calories, total protein, and food weight, derived from the databases and the accessed publications. We assumed that the above-listed five nutritional variables, together with the three environmental ones, should be minimized in order to ensure an optimal, balanced, combined nutritional and environmental profile. As a matter of fact, sodium (to prevent hypertension, mortality and disability-adjusted life-years, DALYs), saturated fat (to minimize cardiovascular risk, but see also additional comments in the Discussion), calories (to prevent overweight and obesity, albeit approximating minimum energy requirements) [34, 38, 44], protein(s) (i.e. the higher the quality, the lower the quantity required), and food weight (to minimize the environmental footprint for food production), all should be maintained at the lowest-possible, although safe, intake level.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eRanking the mixed foods menus\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe further step was to rank the food combinations of each menu type separately for GHGE, land use, WF, sodium, saturated fat, calories, protein, and food weight. Lower rankings would thus reflect healthier, more sustainable profiles, whereas higher rankings less healthy, less sustainable ones. To this aim, we used two methods. One was to transform each variable into the percent of the highest value of the group, with the aim to respect the relative distribution of the menus in respect to each parameter. Such a calculation is however highly sensitive extremely high values (i.e. \u0026ldquo;outliers\u0026rdquo;). Therefore, another method was to calculate the deviation of each value from the group median. We did not directly compare the values with either standard reference(s) or a recommended minimum, because for some of them there is no accepted, clearly-established, desirable limits, for instance for the three environmental variables. Only for sodium and saturated fat there are accepted recommendations [38, 44, 62]. In regard of protein intake, the protein quantity in either a food or a food combination, needed to satisfy the reference daily value of the EAAs, could be even below that of the recommended average protein intake [17], should the protein quality be particularly \u0026ldquo;high\u0026rdquo;. It should also be considered that the resulting ranked values obviously depend on both the number and the type of the selected foods, as well as on their relative amount(s) in the combinations. Therefore, the relative proportion, as well as the position(s) of the combinations, would change their rank within each variable group, should additional foods and/or different quantities or proportions be used in the menus.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTaking into account these consideration and limitations, we calculated a \u0026ldquo;global EAA-based, Nutritional and Environmental Score\u0026rdquo; [EAA-NES], by summing up the percent values attained by each menu in the separate ranking of each of the eight variables. As anticipated, we also compared the menu types in respect to their deviations from median values. Therefore, lower values reflected nutritionally-healthier, more environmentally-sustainable characteristics, whereas higher values less healthy/sustainable ones. The LU, GHGE and WF data, as well as the percentualized global EAA-NES of the three menu types, were also analyzed as quartiles, using the built-in formulas of the Excel\u0026reg; software (version 10) (Microsoft Co, Redmond, Washington, USA).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe statistical comparison among the three menu-types, in regard of the three environmental parameter (i.e. LU, GHGE, total and green+blue WF), as well as sodium, saturated fat, total calories, protein and food weight, was performed using the 1-way Analysis of Variance [ANOVA] for independent groups, followed by the Tukey\u0026rsquo;s post-hoc text in the head-to-head group comparison. The normal distribution of the data, as well as absence of difference in variances among the three menu groups, were verified for each parameter. The Statistica\u0026reg; Software (StatSoft Inc, TIBCO Sofware Inc. Palo Alto, CA, USA, version 10) was employed. A p value \u0026lt;0.05 was considered as statistically significant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eData availability statement\u003c/u\u003e. The data used to calculate the food composition and their environmental footprint were derived from published peer-reviewed articles, internet sites and other publicly-available material, as detailed in the References of the main text, and in the Supplementary references list.\u003c/p\u003e\n\u003cdiv id=\"ftn1\"\u003e\n \u003cp\u003e[1] CREA stands for: \u003cem\u003eIl Consiglio per la Ricerca in Agricoltura e l\u0026rsquo;Analisi dell\u0026rsquo;Economica Agraria\u003c/em\u003e, i.e. the Council for Agriculture Research and Analysis of Agrarian Economics.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"ftn2\"\u003e\n \u003cp\u003e[2] The term LCA was introduced in 1979-1980, and was increasingly adopted in the last decade of the last century in particular following the 1997 publication of ISO standard 14040. Source: ECOINVEN database. Found in: www.ecoinvent.ch\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eDALY: Disability-Adjusted Life-Years; EAA: Essential Amino Acids; e.p.: edible part; EVO: Extra Virgin Olive oil; GHGE: Green-House-Gas-Emission; LCA: Life Cycle Assessment; LOV: Lacto-Ovo-Vegetarian; LU: Land Use; MD: Mediterranean Diet; NES: Nutritional and Environmental Score; OMN: Omnivorous; RDA: Recommended Daily Allowance; VEG: Vegan; WF: Water Footprint.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to acknowledge Ms. Linda Inverso for her excellent assistance in the correcting and proof-editing the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eETHICS DECLARATIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCOMPETING INTERESTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTHORS\u0026rsquo; CONTRIBUTION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eP. T. designed and conducted the research, wrote paper and had primary responsibility for final content.\u003c/p\u003e\n\u003cp\u003eG. M. contributed to methodology, supervision, validation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eG. B. contributed to data analysis, animal data critical assessment, the discussion section and manuscript revision.\u003c/p\u003e\n\u003cp\u003eA. L. contributed to study conceptualization, methodology, paper writing, funding acquisition, investigation.\u003c/p\u003e\n\u003cp\u003eAll authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cb\u003eDECLARATIONS OF INTEREST\u003c/b\u003e: All authors disclose no conflict of interest. \u003c/p\u003e\n\u003cp\u003e\u003cb\u003eFUNDING SOURCES\u003c/b\u003e: The language editing of this manuscript was supported by an institutional Grant of the University of Padova, Italy (Grant n. DOR 2032990/20).\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eHoekstra, A.Y., \u0026amp; Wiedmann, T.O. Humanity\u0026apos;s unsustainable environmental footprint. \u003cem\u003eScience\u003c/em\u003e\u0026nbsp; \u003cstrong\u003e344\u003c/strong\u003e, 6188; 1114-7. https://doi.org10.1126/science.1248365 (2014).\u003c/li\u003e\n \u003cli\u003eGBD 2017. Risk Factor Collaborators. Global EAA, regional, and national comparative risk assessment of 84 behavioral, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories,1990\u0026ndash;2017: a systematic analysis for the Global EAA Burden of Disease Study. \u003cem\u003eLancet\u003c/em\u003e \u003cstrong\u003e392\u003c/strong\u003e, 1923-94 (2018).\u003c/li\u003e\n \u003cli\u003eWillett, W. et al. 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(Tables 2,3,4). https://www.ncbi.nlm.nih.gov/books/NBK56068/table (2011)\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1: The absolute values of the environmental and nutritional variables considered in the three menu types.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.929078014184396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.404255319148936%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLand Use\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.936170212765957%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGHGE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal WF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.51063829787234%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGreen \u0026amp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eBlue WF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.23404255319149%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.631205673758865%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSaturated Fat\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.078014184397164%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnergy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Protein\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFood Weight\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.085106382978724%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEAA-NES\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eScore\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.929078014184396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.404255319148936%\"\u003e\n \u003cp\u003e\u003cem\u003en\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u003cem\u003em\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.936170212765957%\"\u003e\n \u003cp\u003e\u003cem\u003eg CO\u003csub\u003e2eq\u003c/sub\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u003cem\u003eL\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.51063829787234%\"\u003e\n \u003cp\u003e\u003cem\u003eL\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.23404255319149%\"\u003e\n \u003cp\u003e\u003cem\u003emg\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.631205673758865%\"\u003e\n \u003cp\u003e\u003cem\u003eg\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.078014184397164%\"\u003e\n \u003cp\u003e\u003cem\u003ekcal\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u003cem\u003eg\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u003cem\u003ekg\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.085106382978724%\"\u003e\n \u003cp\u003e\u003cem\u003eSum of %\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.929078014184396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.404255319148936%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.936170212765957%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.51063829787234%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.23404255319149%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.631205673758865%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.078014184397164%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.085106382978724%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.929078014184396%\"\u003e\n \u003cp\u003eVEG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.404255319148936%\"\u003e\n \u003cp\u003e\u003cem\u003e7\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e4.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.936170212765957%\"\u003e\n \u003cp\u003e2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e3247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.51063829787234%\"\u003e\n \u003cp\u003e2929\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.23404255319149%\"\u003e\n \u003cp\u003e143\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.631205673758865%\"\u003e\n \u003cp\u003e9.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.078014184397164%\"\u003e\n \u003cp\u003e1695\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.085106382978724%\"\u003e\n \u003cp\u003e\u003cem\u003e541\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.929078014184396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.404255319148936%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u0026plusmn;0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.936170212765957%\"\u003e\n \u003cp\u003e\u0026plusmn;0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u0026plusmn;260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.51063829787234%\"\u003e\n \u003cp\u003e\u0026plusmn;236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.23404255319149%\"\u003e\n \u003cp\u003e\u0026plusmn;35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.631205673758865%\"\u003e\n \u003cp\u003e\u0026plusmn;1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.078014184397164%\"\u003e\n \u003cp\u003e\u0026plusmn;56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u0026plusmn;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u0026plusmn;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.085106382978724%\"\u003e\n \u003cp\u003e\u0026plusmn;\u003cem\u003e25\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.929078014184396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.404255319148936%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.936170212765957%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.51063829787234%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.23404255319149%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.631205673758865%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.078014184397164%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.085106382978724%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.929078014184396%\"\u003e\n \u003cp\u003eLOV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.404255319148936%\"\u003e\n \u003cp\u003e\u003cem\u003e7\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e5.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.936170212765957%\"\u003e\n \u003cp\u003e2.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e3587\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.51063829787234%\"\u003e\n \u003cp\u003e3309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.23404255319149%\"\u003e\n \u003cp\u003e343\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.631205673758865%\"\u003e\n \u003cp\u003e15.4\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.078014184397164%\"\u003e\n \u003cp\u003e1636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.085106382978724%\"\u003e\n \u003cp\u003e624\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.929078014184396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.404255319148936%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u0026plusmn;0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.936170212765957%\"\u003e\n \u003cp\u003e\u0026plusmn;0,11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u0026plusmn;185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.51063829787234%\"\u003e\n \u003cp\u003e\u0026plusmn;182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.23404255319149%\"\u003e\n \u003cp\u003e\u0026plusmn;40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.631205673758865%\"\u003e\n \u003cp\u003e\u0026plusmn;1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.078014184397164%\"\u003e\n \u003cp\u003e\u0026plusmn;57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u0026plusmn;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u0026plusmn;0,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.085106382978724%\"\u003e\n \u003cp\u003e\u0026plusmn;16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.929078014184396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.404255319148936%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.936170212765957%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.51063829787234%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.23404255319149%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.631205673758865%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.078014184397164%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.085106382978724%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.929078014184396%\"\u003e\n \u003cp\u003eOMN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.404255319148936%\"\u003e\n \u003cp\u003e\u003cem\u003e7\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e4.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.936170212765957%\"\u003e\n \u003cp\u003e2.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e3695\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.51063829787234%\"\u003e\n \u003cp\u003e3526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.23404255319149%\"\u003e\n \u003cp\u003e200\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.631205673758865%\"\u003e\n \u003cp\u003e9.6\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.078014184397164%\"\u003e\n \u003cp\u003e1606\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.085106382978724%\"\u003e\n \u003cp\u003e563\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.929078014184396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.404255319148936%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u0026plusmn;0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.936170212765957%\"\u003e\n \u003cp\u003e\u0026plusmn;0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u0026plusmn;176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.51063829787234%\"\u003e\n \u003cp\u003e\u0026plusmn;208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.23404255319149%\"\u003e\n \u003cp\u003e\u0026plusmn;20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.631205673758865%\"\u003e\n \u003cp\u003e\u0026plusmn;0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.078014184397164%\"\u003e\n \u003cp\u003e\u0026plusmn;39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u0026plusmn;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u0026plusmn;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.085106382978724%\"\u003e\n \u003cp\u003e\u0026plusmn;23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.929078014184396%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.404255319148936%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.936170212765957%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.51063829787234%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.23404255319149%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.631205673758865%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.078014184397164%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.085106382978724%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.929078014184396%\"\u003e\n \u003cp\u003e\u003cem\u003eANOVA \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;F\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.404255319148936%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e2.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.936170212765957%\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e1.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.51063829787234%\"\u003e\n \u003cp\u003e1.850\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.23404255319149%\"\u003e\n \u003cp\u003e6.551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.631205673758865%\"\u003e\n \u003cp\u003e7.635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.078014184397164%\"\u003e\n \u003cp\u003e0.294\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e0.148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e2.544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.085106382978724%\"\u003e\n \u003cp\u003e2.863\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"9.929078014184396%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; p\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"3.404255319148936%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.936170212765957%\"\u003e\n \u003cp\u003e0.876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.375886524822695%\"\u003e\n \u003cp\u003e0.337\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.51063829787234%\"\u003e\n \u003cp\u003e0.186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.23404255319149%\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.631205673758865%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.078014184397164%\"\u003e\n \u003cp\u003e0.749\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e0.863\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.21985815602837%\"\u003e\n \u003cp\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.085106382978724%\"\u003e\n \u003cp\u003e0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eLegend of the table: Values are Mean \u0026plusmn; SEM. The (n) indicates the number of choices of daily menus in each group.\u003c/p\u003e\n\u003cp\u003eAbbreviations: GHGE: Green House Gas Emission; WF: Water footprint; EAA-NES: Essential Amino Acid-Nutritional and Environmental \u0026nbsp;Score.\u003c/p\u003e\n\u003cp\u003eThe EAA-NES is calculated the sum of the percent-transformed scores of the environmental and the nutritional parameters (see the Method section).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLabeled means without the common letter (\u003csup\u003ea\u003c/sup\u003e) differ by:\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e p\u0026lt;0.006 vs VEG by the Tukey\u0026rsquo;s post hoc test.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u0026nbsp;\u003c/sup\u003ep\u0026lt;0.006 vs VEG, and p\u0026lt;0.025 vs OMN, by the Tukey\u0026rsquo;s post hoc. \u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Energy, Environmental footprint, Food production, Nutrition, Environment, Green-House-Gas-Emission, Mediterranean Diet, Land use, Saturated fat, Sodium, Water Footprint","lastPublishedDoi":"10.21203/rs.3.rs-2005120/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2005120/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: The relationships between environmental variables, diet-type, and nutritional parameters are incompletely known.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e: To estimate the environmental footprint and selected nutritional parameters of in silico-designed vegan (VEG), lacto-ovo-vegetarian (LOV) and omnivorous (OMN) weekly menus (n=7 for each type) complying with Mediterranean-Diet (MD) standards and satisfying Essential-Amino- Acids (EAA) requirements.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: Land-Use (LU), Water-Footprint (WF), Green-House-Gas-Emission (GHGE), sodium, saturated-fat, calorie, protein contents, and food weight, were calculated. A global EAA-based Nutritional and Environmental Score (EAA-NES) was developed.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eKey findings\u003c/strong\u003e: Average LU, WF, GHGE, calories, protein and food weight, and EAA-NES scores, were similar among menu-types. In LOV menus, sodium and saturated fat were greater (by ≈140%, p\u0026lt;0.006, and by ≈60%, p\u0026lt;0.006), than in VEG or in VEG and OMN menus, respectively. However, the LU, GHGE and WF allocation of VEG menus fell predominantly into the first two quartiles (with lower environmental impact), whereas that of LOV and OMN menus was more scattered. No difference was found in the EAA-NES distribution among menu-types, by combining the two lower or the two higher quartiles.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: In silico-designed VEG diets might not exhibit a lower environmental impact, nor a better EAA-NES score, than LOV or OMN diets at safe EAAs requirements.\u003c/p\u003e","manuscriptTitle":"The environmental footprint of in silico-designed vegan, lacto-ovo-vegetarian and omnivorous diets complying with Mediterranean diet standards and essential amino-acid requirements","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-09-01 20:50:59","doi":"10.21203/rs.3.rs-2005120/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9ca97b07-390b-488a-937b-711a20c01959","owner":[],"postedDate":"September 1st, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-12-01T19:14:30+00:00","versionOfRecord":[],"versionCreatedAt":"2022-09-01 20:50:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2005120","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2005120","identity":"rs-2005120","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}