Florent Vieux

Lisa Privet

Louis Georges Soler

Xavier Irz

Marika Ferrari

Stefania Sette

Susanna Raulio

Heli Tapanainen

Ruben Hoffmann

More sustainable European diets based on self-selection do not require exclusion of entire categories of food

Keywords: More sustainable European diets based AHC: agglomerative hierarchical clustering ANOVA Nutrition, greenhouse gas emissions, multicriteria analysis, meat, environment, flexitarian Highlights

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

In response to the growing evidence that food consumption patterns, due to negative health and environmental impacts, are fundamentally unsustainable globally the Food and Agriculture Organization of the United Nations (FAO) defined sustainable diets as environmentally respectful, nutritionally adequate and healthy, economically fair and affordable and culturally acceptable (FAO, 2010). In the process of establishing the food content of such diets, the compatibility between environmental impact and healthiness has received increasing attention, especially in European countries [START_REF] Aleksandrowicz | The Impacts of Dietary Change on Greenhouse Gas Emissions, Land Use, Water Use, and Health: A Systematic Review[END_REF][START_REF] Mertens | Operationalising the health aspects of sustainable diets: a review[END_REF][START_REF] Perignon | Improving diet sustainability through evolution of food choices: review of epidemiological studies on the environmental impact of diets[END_REF]. Most studies are based on comparisons between current and theoretical diets [START_REF] Aleksandrowicz | The Impacts of Dietary Change on Greenhouse Gas Emissions, Land Use, Water Use, and Health: A Systematic Review[END_REF][START_REF] Mertens | Operationalising the health aspects of sustainable diets: a review[END_REF][START_REF] Nelson | Alignment of Healthy Dietary Patterns and Environmental Sustainability: A Systematic Review[END_REF], with the latter derived based on either simulations or mathematical optimization.

Simulations have included scenarios based on adherence to dietary guidelines [START_REF] Tukker | Environmental impacts of changes to healthier diets in Europe[END_REF][START_REF] Wolf | Do healthy diets in Europe matter to the environment? A quantitative analysis[END_REF], traditional food patterns (e.g. Mediterranean, Nordic) [START_REF] Sáez-Almendros | Environmental footprints of Mediterranean versus Western dietary patterns: beyond the health benefits of the Mediterranean diet[END_REF][START_REF] Saxe | The global warming potential of two healthy Nordic diets compared with the average Danish diet[END_REF][START_REF] Tukker | Environmental impacts of changes to healthier diets in Europe[END_REF], exclusion of entire food categories (e.g. pescatarian, vegetarian, vegan diets) [START_REF] Baroni | Evaluating the environmental impact of various dietary patterns combined with different food production systems[END_REF][START_REF] Berners-Lee | The relative greenhouse gas impacts of realistic dietary choices[END_REF][START_REF] Kim | Country-specific dietary shifts to mitigate climate and water crises[END_REF][START_REF] Springmann | Health and nutritional aspects of sustainable diet strategies and their association with environmental impacts: a global modelling analysis with country-level detail[END_REF][START_REF] Tilman | Global diets link environmental sustainability and human health[END_REF], and replacement of specific food items (e.g. meat/dairy being replaced by plant-based products) [START_REF] Seves | Are more environmentally sustainable diets with less meat and dairy nutritionally adequate?[END_REF][START_REF] Temme | Replacement of meat and dairy by plant-derived foods: estimated effects on land use, iron and SFA intakes in young Dutch adult females[END_REF]van de Kamp et al., 2018avan de Kamp et al., , 2018b;;[START_REF] Vieux | Greenhouse gas emissions of self-selected individual diets in France: Changing the diet structure or consuming less?[END_REF]. A limitation of simulation studies is that they are based on preconceived views concerning the food content of a sustainable diet. Another limitation is that nutritional and environmental indicators are outputs of the scenarios, meaning that they do not necessarily improve and may even worsen in some scenarios [START_REF] Payne | Do low-carbon-emission diets lead to higher nutritional quality and positive health outcomes? A systematic review of the literature[END_REF][START_REF] Seves | Are more environmentally sustainable diets with less meat and dairy nutritionally adequate?[END_REF][START_REF] Vieux | Greenhouse gas emissions of self-selected individual diets in France: Changing the diet structure or consuming less?[END_REF]. In contrast, mathematical optimization integrates nutritional and environmental constraints in the model thereby guaranteeing that the diets modeled are both nutritionally adequate and reduce environmental impacts [START_REF] Donati | Towards a sustainable diet combining economic, environmental and nutritional objectives[END_REF][START_REF] Green | The potential to reduce greenhouse gas emissions in the UK through healthy and realistic dietary change[END_REF][START_REF] Horgan | Achieving dietary recommendations and reducing greenhouse gas emissions: modelling diets to minimise the change from current intakes[END_REF]Macdiarmid et al., 2012a;Perignon et al., 2016b;[START_REF] Van Dooren | Combining Low Price, Low Climate Impact and High Nutritional Value in One Shopping Basket through Diet Optimization by Linear Programming[END_REF][START_REF] Vieux | Dietary changes needed to improve diet sustainability: are they similar across Europe?[END_REF].

By deriving optimized diets which are as close as possible to observed population averages (Macdiarmid et al., 2012b;Perignon et al., 2016b) or individual diets [START_REF] Horgan | Achieving dietary recommendations and reducing greenhouse gas emissions: modelling diets to minimise the change from current intakes[END_REF] the cultural dimension is taken into account. However, the findings remain theoretical as the modeled diets are never tested in the real word and hence it is questionable whether consumers would accept these diets.

Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. (2020). More sustainable European diets based on self-selection do not require exclusion of entire categories of food. Journal of Cleaner Production, 248, 1-10. , DOI : 10.1016/j.jclepro.2019.119298 4 Thus, there is a need to more directly take into account the notion of cultural acceptability and consumer preferences [START_REF] Irz | Welfare and sustainability effects of dietary recommendations[END_REF]. It seems reasonable to assume that self-selected diets are more culturally appropriate than theoretical diets as, by definition, they are already consumed by at least some individuals [START_REF] Aleksandrowicz | The Impacts of Dietary Change on Greenhouse Gas Emissions, Land Use, Water Use, and Health: A Systematic Review[END_REF][START_REF] Perignon | Improving diet sustainability through evolution of food choices: review of epidemiological studies on the environmental impact of diets[END_REF].

However, epidemiological studies analyzing the sustainability of self-selected diets have found that lower greenhouse gas emissions (GHGE) are not necessarily associated with higher nutritional quality and vice versa [START_REF] Biesbroek | Does a better adherence to dietary guidelines reduce mortality risk and environmental impact in the Dutch sub-cohort of the European Prospective Investigation into Cancer and Nutrition?[END_REF][START_REF] Payne | Do low-carbon-emission diets lead to higher nutritional quality and positive health outcomes? A systematic review of the literature[END_REF]Perignon et al., 2016a;[START_REF] Sjors | Adherence to dietary recommendations for Swedish adults across categories of greenhouse gas emissions from food[END_REF]Vieux et al., 2013a). Investigating the impact of dietary recommendations based on a behavioral consumer choice model [START_REF] Irz | Welfare and sustainability effects of dietary recommendations[END_REF] reached a similar conclusion. This can be explained by a quantity vs quality dichotomy, with the environmental impact being closely and positively linked to both physical quantities and calories ingested [START_REF] Vieux | Greenhouse gas emissions of self-selected individual diets in France: Changing the diet structure or consuming less?[END_REF]. At a given level of caloric intake, low quality diets, due to high energy density, are consumed in smaller quantities and thus often have low GHGE (Vieux et al., 2013a). Furthermore, some foods, such as high-sugar foods and refined cereals, display both low GHGE and low nutritional quality (Masset et al., 2014a;[START_REF] Payne | Do low-carbon-emission diets lead to higher nutritional quality and positive health outcomes? A systematic review of the literature[END_REF].

As sustainability dimensions may not be compatible with one another, one-dimensional analyses are inappropriate in identifying more sustainable food choices.

Multicriteria analyses applied to self-selected diets, overcoming the quantity vs quality dichotomy, are urgently needed in order to identify realistic sustainable diets that are culturally acceptable. The objective of the present study was therefore to apply such energyadjusted multicriteria approaches, without ex ante assumptions concerning the food content, to identify which current self-selected diets are relatively more sustainable in five European countries, namely Finland, France, Italy, Sweden and the UK. Our contribution is both methodological and empirical. We develop and test a new method for identification of sustainable diets and the results have broad policy implications. We conclude that significantly lower GHGE from diets with high nutritional quality and already adopted by a large share of the European population is possible. The relatively more sustainable diets do not exclude entire categories of foods (e.g. meat), which suggests that flexitarian diets should be promoted in order to improve the sustainability of European diets.

Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. (2020 (NatCen Social Research et al., 2015). Detailed information of each survey is available in supplementary data. Individuals younger than 18 years old and older than 64 years old, consumers of dietary supplements and one outlier [START_REF] Franklin | Robust multivariate outlier detection using Mahalanobis' distance and modified Stahel-Donoho estimators[END_REF] were excluded. The final sample consisted of 8302 individuals including 568 men and 679 women in Finland, 930 men and 1323 women in France, 967 men and 1105 women in Italy, 588 men and 764 women in Sweden and, 627 men and 751 women in the UK. Age, and socio-demographics information of each selected sample are available in supplementary data.

Individual dietary intakes

Each national institute provided individual energy and nutrient intakes as well as the consumed quantities of 151 food items. The food items were derived from the FoodEx food classification system (European Food Safety Authority, 2011) and grouped into 6 food groups and 27 food sub-groups. Information on folates was not available in the Italian survey and was assumed to be the same as for the corresponding French food items (The French Information Center on Food Quality, 2013). Information on free sugars (monosaccharides and disaccharides added to foods by the manufacturer, cook or consumer, plus the sugars that are naturally present in honey, syrups and fruit juices) was not available in the Swedish, Finish and Italian surveys. It was assumed that the content of intrinsic sugar (naturally present in food)

was the same as for the corresponding French food items [START_REF] Lluch | Individual Diet Modeling Shows How to Balance the Diet of French Adults with or without Excessive Free Sugar Intakes[END_REF] and the level of free sugars was calculated as the difference between total sugar content (according to the national surveys) and intrinsic sugar content.

Nutritional quality indicators

Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. ( 2020 2007;World Health Organization, 2003) to prevent obesity and obesity-related diseases [START_REF] Ledikwe | Dietary energy density is associated with energy intake and weight status in US adults[END_REF].

GHGE associated with food consumption

A GHGE coefficient, expressed in grams of CO 2 equivalents (g CO 2 eq), derived from life cycle assessment (LCA) literature studies was assigned to each of the 151 food items as described by [START_REF] Hartikainen | Summary of the chosen methodologies and practices to produce GHGE-estimates for an average European diet[END_REF]. The reader should be aware that there are major uncertainties related to GHGE coefficients aggregated from the LCA literature (Clune et al., 2017;Kendall and Chang, 2009) but that it is still the best available alternative. For each individual, the consumption of 151 food items was matched to their respective GHGE in order to calculate dietary GHGE, i.e. the GHGE related to the daily food consumption of the individual. Dietary GHGE were used as indicators of the environmental impacts of diets.

Identification of "More-Sustainable" cluster and class

We hypothesized that some diets combine cultural acceptability (because they are selfselected), good nutritional quality and low environmental impact. Diets that relative to other diets were more sustainable were identified using two approaches: a new clustering approach

Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. ( 2020 specifically developed for this study (described in 2.2.1) and a previously described classification approach (Masset et al., 2014b). The methods were used to identify a collection of self-selected diets called the "More-Sustainable" cluster and the "More-Sustainable" class, respectively.

Both approaches were applied without ex ante assumptions concerning the food content of sustainable diets. Adjustments were made for energy intakes to take into account the welldocumented and strongly positive relationship between dietary GHGE and energy intakes [START_REF] Monsivais | Greater accordance with the Dietary Approaches to Stop Hypertension dietary pattern is associated with lower diet-related greenhouse gas production but higher dietary costs in the United Kingdom[END_REF][START_REF] Saxe | The global warming potential of two healthy Nordic diets compared with the average Danish diet[END_REF][START_REF] Vieux | Greenhouse gas emissions of self-selected individual diets in France: Changing the diet structure or consuming less?[END_REF].

Clustering of diets and identification of the "More-Sustainable" cluster

The "More-Sustainable" cluster was identified as the cluster with the best compromise between high nutritional quality and low dietary GHGE. Clustering was conducted in two consecutive steps. In a first step, multiple factorial analysis (MFA) [START_REF] Tucker | Dietary patterns, approaches, and multicultural perspectiveThis is one of a selection of papers published in the CSCN-CSNS 2009 Conference, entitled Can we identify culture-specific healthful dietary patterns among diverse populations undergoing nutrition[END_REF] was applied to the 8302 individual diets, using nutrient intakes (representing the nutritional dimension)

and dietary GHGE (representing the environmental dimension) as active variables and intake by food sub-group, diet quality indicators (SED, MAR and MER), number of food items consumed and other characteristics (total energy, total quantity, age) as illustrative variables.

The illustrative variables are useful in interpreting the results but do not influence the principal component analysis. Because the environmental dimension was represented by only one variable while the nutritional dimension included 28 nutrients, dietary GHGE were weighted to be as important as nutritional intakes. All variables included in the MFA were adjusted for total energy intake (using residuals of each linear regression between the variable considered and the total energy intake) and scaled to the standard deviation in order to avoid bias due to different units. In a second step, a partition of diets was carried out by agglomerative hierarchical clustering (AHC) using Euclidean distances between individuals, based on their coordinates on the first component, i.e. the new variables derived by the MFA which summarize the largest variability of the raw data [START_REF] Contreras | Handbook of Cluster Analysis-Chapter 6 -Hierarchical clustering, 1st ed, Handbook of Cluster Analysis[END_REF][START_REF] Cornillon | R for Statistics, R for Statistics[END_REF]. Individuals were in this second step grouped into clusters. The number of clusters was chosen using two criteria: the gain of inter/intra cluster inertia ratio and the interpretability of clusters. Comparisons of characteristics across clusters, especially regarding dietary GHGE and nutritional quality indicators, were used to name clusters and to identify which of the clusters defined by AHC that was the "More-Sustainable".

Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. ( 2020

Classification of diets and identification of the "More-Sustainable" class

The approach used to identify a class of more sustainable diets was based on the methodology suggested by Masset et al (Masset et al., 2014b). Briefly, this approach was used to define individual diets as belonging to "More-Sustainable" class if the diet had a MAR above, a MER below, and dietary GHGE (all being adjusted for energy) below the energy-adjusted genderspecific median.

Statistical analysis

Correlations between the first two components from the MFA and the active and illustrative variables were computed and represented on a correlation circle. Each cluster was described in terms of individual characteristics (nationality, gender, age) and diet characteristics.

Differences of means between clusters were tested by analysis of variance (ANOVA) adjusted as appropriate [START_REF] Fisher | Statistical methods for research workers[END_REF]. Post-hoc comparisons between means using Tukey correction were performed. Differences in the distribution of nationalities across the different clusters were analyzed with a chi-squared test. The "More-Sustainable" cluster was isolated and nutritional intakes as well as consumption (in percentage of total diet weight) of food groups and sub-groups were compared to the rest of the sample by ANOVA after adjusting for total energy intake. The "More-Sustainable" class was similarly compared to the rest of the sample.

This made it possible to qualitatively identify the main differences between the "More-Sustainable" cluster and the "More-Sustainable" class.

Statistical softwares SAS version 9.4 (SAS Institute, Cary, NC, USA) and R version 3.3.0 (Base and FactoMineR packages) were used to perform the statistical analysis. A 5% level of statistical significance was used for all tests.

Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. ( 2020

Results

The two first components of the MFA accounted for 23% and 15% of the variability (Figure 1).

The MFA showed that dietary GHGE were inversely correlated with carbohydrates and sugar intakes, including free sugars (Figure 1, panel A). Vitamins and minerals were highly correlated with each other but not with dietary GHGE. Graphically representing consumption of food groups in the map defined by MFA (Figure 1, panel B) revealed that consumption of livestock meat was strongly correlated with dietary GHGE while consumption of fruits and vegetables as well as dairy were positively correlated with vitamins and minerals.

Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. ( 2020 1 Only illustrative variables with an Euclidean distance from the center higher than 0.05 were represented.

Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. ( 2020 The "Highest-GHGE" cluster (Cluster 5) was characterized by a high intake of livestock meat, animal fats and alcoholic beverages and low intakes of meat imitates, vegetable fats and plantbased composite dishes (Table 2). The "Lowest-GHGE" cluster (Cluster 1) had the highest consumption of soft drinks, sugar/confectionaries, and snack/desserts. The "Others" cluster (Cluster 6) was characterized by high intakes of offal/other meats.

The diets in the "More-Sustainable" cluster included all food groups and sub-groups. Figure 2 compares the "More-Sustainable" cluster to the rest of the sample. Individuals from the cluster consumed a larger total quantity which can be explained by the relatively low energy density of plant foods representing half of the quantity consumed (Figure 2 panel A).

Among drinks (Figure 2 panel B), alcoholic beverages and soft drinks were the only sub-groups consumed in smaller quantities than in the rest of the sample.

Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. ( 2020 both animal-and plant-based composite dishes were lower in the "More-Sustainable" cluster resulting in a statically significant lower share of total composite dishes in this cluster than in the rest of the sample. In the classification approach, however, the "More-Sustainable" class had a larger share of plant-based and a smaller share of animal-based composite dishes compared to the rest of the sample. As a result the share of total composite dishes was not statistically different between the class and the rest of the sample. 1 The "More-Sustainable" cluster was obtained by applying agglomerative hierarchical clustering on principal components of energy-adjusted multiple factor analysis with individual nutrient intakes and dietary GHGE as active variables.

2 The "More-Sustainable" class consists of individual diets having simultaneously a Mean Adequacy Ratio above the median, a Mean Excess Ratio below the median and dietary greenhouse gas emissions below the median.

3 Energy adjusted p-value of difference in means between the "More-Sustainable" cluster and the rest of the sample.

4 Energy adjusted p-value of difference in means between the "More-Sustainable" class and the rest of the sample.

Discussion

The new clustering method used to identify the relatively more sustainable diets avoids several shortcomings of previous studies, such as working with theoretical diets, adopting preconceived views on the sustainability of specific food choices or adopting one-dimensional approaches to embrace a fundamentally multi-dimensional concept. Examining diets of adults from national food consumption surveys in five European countries (Finland, France, Italy, Sweden, the UK), this study found a cluster of 18 % of diets that were relatively more sustainable because they combined low dietary GHGE (21 % reduction vs average of all observed diets) and high nutritional quality. All categories of foods were represented in these diets, but compared to the rest of the sample they contained significantly larger quantities of plant-based products and smaller quantities of meat, soft drinks and alcoholic beverages.

Dietary GHGE was found to be strongly and positively associated with livestock meat consumption but negatively associated with the intake of free sugars. That consumption of livestock meat drives the level of GHGE in the diet is well known [START_REF] Garnett | Livestock-related greenhouse gas emissions: impacts and options for policy makers[END_REF][START_REF] Gerber | Tackling Climate Change Through Livestock: A Global Assessment of Emissions and Mitigation Opportunities, Food and Agriculture Organization of the United Nations[END_REF]. It is less known that high consumption of free sugars is related to low environmental impact, although evidence of this relation can be found in the literature [START_REF] Payne | Do low-carbon-emission diets lead to higher nutritional quality and positive health outcomes? A systematic review of the literature[END_REF].

For instance, a study assessing the environmental impact of several dietary scenarios in the UK found that the diet with the lowest dietary GHGE was a vegan diet with a large share of confectionaries and soft drinks [START_REF] Berners-Lee | The relative greenhouse gas impacts of realistic dietary choices[END_REF]. Furthermore, the results in this study suggest that dietary GHGE is practically unrelated to the intake of beneficial nutrients such as vitamins, minerals and fiber, thereby confirming results found in previous studies (Vieux et al., 2013a).

Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. ( 2020 Due to the complicated relationships between different dimensions of sustainability, unidirectional approaches (e.g. splitting one metric, either nutritional or environmental, into quantiles) are not suitable for studying diets. Such approaches explain why most epidemiological studies on the environmental impact of self-selected diets have found a weak correlation, or even a divergence between the nutritional and environmental dimensions [START_REF] Perignon | Improving diet sustainability through evolution of food choices: review of epidemiological studies on the environmental impact of diets[END_REF]. For instance, diets from the lowest GHGE quintile in the French Nutrinet cohort of healthy volunteers were neither the diets with the least amount of nonbeneficiary nutrients nor the diets closest to French dietary guidelines [START_REF] Seconda | Comparing nutritional, economic, and environmental performances of diets according to their levels of greenhouse gas emissions[END_REF].

In fact, adherence to dietary guidelines is not necessarily associated with a lower environmental impact. The recommended DASH dietary pattern has for example been found to be associated with lower GHGE in the UK [START_REF] Monsivais | Greater accordance with the Dietary Approaches to Stop Hypertension dietary pattern is associated with lower diet-related greenhouse gas production but higher dietary costs in the United Kingdom[END_REF] but higher GHGE in the Netherlands [START_REF] Biesbroek | Does a better adherence to dietary guidelines reduce mortality risk and environmental impact in the Dutch sub-cohort of the European Prospective Investigation into Cancer and Nutrition?[END_REF].

Six clusters were identified based on the nutritional and environmental characteristics of the diets. The relatively more sustainable of these clusters was characterized by large amounts of plant-based products and small amounts of animal-based products. Livestock meat and processed meat represented around 300 grams per week in this cluster which is less than the maximum of 500 grams recommended by international bodies (World Cancer

Research/American Institute for Cancer Research, 2007). The presence of non-negligible amounts of animal-based foods in the relatively more sustainable diets implies that excluding entire categories of foods is not necessary in order to move towards more sustainable diets.

The same conclusion can be drawn from results obtained with the classification approach. The results is also supported by a previous study which found that the diets of omnivores are not always those with the largest environmental impacts, and that some vegetarians and vegans can have diets with even higher impacts [START_REF] Rosi | Environmental impact of omnivorous, ovo-lacto-vegetarian, and vegan diet[END_REF]. Our results suggest that policies intended to improve the sustainability of European diets should promote flexitarian diets, e.g.

by reformulating dietary recommendations. The 21% GHGE reductions in the more sustainable cluster provides a useful reference for the development of sustainable food systems which requires that both demand-and supply-side aspects are considered.

In identifying sustainable food choices, multicriteria methods are preferable to unidirectional

approaches. An important contribution of the present study was the original method used to identify more sustainable self-selected diets. Whereas MFA has been widely used in epidemiological studies to derive dietary patterns [START_REF] Bertin | Dietary patterns of French adults: associations with demographic, socio-economic and behavioural factors[END_REF][START_REF] Gazan | Dietary patterns in the French adult population: a study from the second French national crosssectional dietary survey (INCA2) (2006-2007)[END_REF],

Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. ( 2020 [START_REF] Drewnowski | Energy and nutrient density of foods in relation to their carbon footprint[END_REF][START_REF] Masset | Which functional unit to identify sustainable foods?[END_REF].

This study has some limitations. Using large, representative and multi-cultural samples was valuable but aggregating different dietary surveys into one sample introduced a potential bias due to methodological differences in the data collection (e.g. dietary records based on varying number of days) (European Food Safety Authority, 2011). In order to minimize this potential bias, all variables included in the MFA were centered, scaled and adjusted for total energy intake. In the future it would be interesting to apply country-specific clustering to see if the results would differ from the results obtained in this study. Another limitation was that the cost of diets was not considered. However, previous studies have found that increasing sustainability does not necessarily increase the cost as it implies a lower consumption of meat which is a costly part of the diet [START_REF] Fischer | Plates, pyramids, planet Developments in national healthy and sustainable dietary guidelines: a state of play assessment[END_REF]. That European average GHGE coefficients were used is another limitation of this study. Using coefficients reflecting country averages would be preferable but are unfortunately available only for some food items in some countries. Furthermore, using only one environmental indicator, dietary GHGE, and only one average value per food item, is a simplification as environmental performance is represented by a diversity of highly variable and possibly uncorrelated metrics [START_REF] Poore | Reducing food's environmental impacts through producers and consumers[END_REF][START_REF] Ridoutt | Dietary Strategies to Reduce Environmental Impact: A Critical Review of the Evidence Base[END_REF].

Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. ( 2020

Conclusion

As data on the multiple metrics needed to address the sustainability of diet is becoming increasingly available (Gazan et al., 2018a;[START_REF] Johnston | Understanding sustainable diets: a descriptive analysis of the determinants and processes that influence diets and their impact on health, food security, and environmental sustainability[END_REF], multicriteria analyses such as the multiple factor analysis developed in the present study or more complex mathematical optimization models [START_REF] Gazan | Mathematical optimization to explore tomorrow's sustainable diets: a narrative review[END_REF][START_REF] Van Dooren | A Review of the Use of Linear Programming to Optimize Diets, Nutritiously, Economically and Environmentally[END_REF] are becoming ever more relevant. In particular, we think that the novel clustering method suggested in this paper would benefit from being generalized and that the results can be used to promote more sustainable dietary patterns adapted to specific populations. Recommendations originating from the actual preferences and choices of consumers have a greater potential to be adopted by consumers than is currently the case. The diets identified with this method can inform policy makers when specifying more sustainable dietary recommendations.

Using a multidimensional approach to identify self-selected diets with the best compromise between environmental and nutritional objectives, the present study suggests that diets with moderate amounts of animal-based products in the short-run is the most realistic path towards more sustainable diets, as it is already adopted by nearly one in five adults in Europe. was part of the SUSDIET research project (https://www6.inra.fr/sustainablediets) launched in the framework of the second ERANET-SUSFOOD call. The objective was to identify sustainable diets compatible with consumers'

preferences in Europe and to analyze how public and private policies can promote sustainable diets. The authors wish to thank the DN Carasso foundation, the French Environment & Energy Management Agency (ADEME), the Finnish Ministry of Agriculture and Forestry (MMM-Makera) and the FORMAS agency for funding the French, Finnish and Swedish components of the SUSDIET project.

Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. (2020). More sustainable European diets based on self-selection do not require exclusion of entire categories of food. Journal of Cleaner Production, 248, 1-10. , DOI : 10.1016/j.jclepro.2019.119298

Figure 1 :

 1 Figure 1: Correlation circles derived from the Multiple Factorial Analysis (MFA) PANEL A: Active variables

Table 1 .

 1 Individuals were grouped into six clusters by applying hierarchical clustering and studying the inertia gain and the interpretability of clusters. The characteristics of the overall sample and the six clusters are shown in Table1. Mean energy intake varied from 1916 kilocalories (kcal) per day, in cluster 3, to 2152 kcal per day, in cluster 4. Cluster 1 had the lowest dietary GHGE (3551 g CO 2 eq/d) and low nutritional quality, as indicated by the highest SED (191 kcal/100g), the lowest MAR (77 %) and the second highest MER (133 %). It was also characterized by the lowest mean age. Cluster 5 had the highest dietary GHGE (7034 g CO 2 eq/d) and nutritional quality similar to the overall sample average. Clusters 4 and 6 also had high dietary GHGE (>5000 g CO 2 eq/d). Cluster 4 was characterized by the lowest SED (141 kcal/100g) and the highest MAR (93 %) but the highest MER (140 %). Cluster 6 was the smallest cluster (<1 % of the sample) and had the highest mean age. Cluster 3, representing 33% of the whole sample, Characteristics of the overall sample and the six clusters 1 Solid foods are all foods except liquids; liquids were defined as hot drinks, sugary and non-sugary beverages, milk, juices, water, and alcoholic beverages. a,b,c,d,e Non-significant 2 by 2 post-hoc comparisons (using Tukey correction) have the same letter. * This cluster was characterized by the highest mean intake of Offals/Other meats (see table2).

		All	Cluster 1	Cluster 2	Cluster 3	Cluster 4	Cluster 5	Cluster 6
	N (%)	8302	2020 (24.33%)	1498 (18.04%)	2749 (33.11%)	809 (9.74%)	1151 (13.86%)	75 (0.90%)
	Age (y)	42.57 (12.77)	38.51 (12.94)	45.78 (12.21) a	42.55 (12.52) b	46.29 (11.63) a	42.53 (12.50) b	48.72 (11.47) a
	Women (%)	55.67%	57.77%	61.95%	58.86%	49.32%	41.18%	48.00%
	Energy (kcal/d)	2003.91 (634.4)	2059 (680.4) a	1939 (579.1) b	1916 (599.3) b	2152 (659.2) c	2091 (638.5) ac	2084 (697.3) abc
	Energy from solid foods 2	1797 (579.6)	1827 (636.5) a	1742 (532.3) b	1752 (547.0) b	1900 (594.9) c	1851 (577.0) ac	1868 (653.4) abc
	Total quantity (g/d)	2587.80 (878.5)	2352 (800.6) a	2886 (783.0) b	2327 (790.2) a	3359 (837.8)	2676 (882.2) c	2876 (1076) bc
	Solid quantity	1083 (349.7)	969.0 (326.2) a	1236 (339.1) b	984.1 (282.3) a	1375 (388.3)	1109 (320.0) c	1202 (380.8) bc
	GHGE (g CO2 eq/d)	4516 (1789)	3551 (1315)	3834 (1188)	4327 (1254)	5187 (1538) a	7034 (1891)	5191 (1794) a
	SED (kcal/100g)	170.3 (380.0)	191.0 (360.0)	142.8 (310.0) a	179.4 (320.0)	140.9 (320.0) a	169.2 (330.0) b	158.8 (380.0) b
	MAR (%)	82.84 (12.37)	77.36 (13.89)	88.55 (8.04) a	79.92 (12.34)	93.02 (5.49) b	84.34 (9.91)	90.37 (7.08) ab
	MER (%)	128.08 (33.01)	132.74 (36.96) a	121.42 (28.27) b	124.43 (28.9) c	139.7 (39.68) d	129.0 (32.14) e	128.99 (32.43) abcde
	Distinguishing of cluster features		Lowest GHGE, 2 nd highest MER Lowest MAR, Highest SED	2 nd lowest GHGE Lowest MER High MAR (88%) 2 nd lowest SED	2 nd lowest MAR	Lowest SED Highest MER Highest MAR	Highest GHGE	Highest intakes of offals*
	Cluster Name		«Lowest-GHGE»	«More-Sustainable» «Smallest-Quantity» «Largest-Quantity»	«Highest-GHGE»	« Others »

). More sustainable European diets based on self-selection do not require exclusion of entire categories of food. Journal of Cleaner Production, 248, 1-10. , DOI : 10.1016/j.jclepro.2019.119298 11 MAR denotes Mean Adequacy Ratio, GHGE denotes greenhouse gas emissions. had intermediate dietary GHGE (4327 g CO 2 eq/d) but the second lowest MAR (80 %). Finally, cluster 2, representing 18 % of the sample, displayed the second lowest dietary GHGE (3834 g CO 2 eq/d, 21 % less than the sample average), the lowest MER (121 %), the second lowest SED (143 kcal/100g), and its MAR was relatively high (88 %). This cluster was therefore considered to be relatively more sustainable because none of the other clusters featured a better combination of low dietary GHGE and high nutritional quality. Names were also attributed to the other clusters according to their main specific characteristics. The percentage of individuals belonging to the "More-sustainable" cluster was 25.1 % in Finland, 11.6 % in France, 16.6 % in Italy, 19.7 % in Sweden and 23.4 % in the UK (data not shown). Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. (2020). More sustainable European diets based on self-selection do not require exclusion of entire categories of food. Journal of Cleaner Production, 248, 1-10. , DOI : 10.1016/j.jclepro.2019.119298 12 1 Results are presented as means (standard deviation) or percentages; statistical tests of differences in means between clusters, based on ANOVA and chisquare, were all statistically significant (p<0.01). 2 Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. (2020). More sustainable European diets based on self-selection do not require exclusion of entire categories of food. Journal of Cleaner Production, 248, 1-10. , DOI : 10.1016/j.jclepro.2019.119298 13

Table 2 .

 2 Mean consumption, grams per day, by food group and sub-group in the overall sample and in the six clusters 1 301 302

		All	"Lowest-GHGE"	"More-	"Smallest-	"Largest-	"Highest-	"Others"
				Sustainable"	Quantity"	Quantity"	GHGE"
	Plant foods	519.9 (241.8) 478.85 (215.37) 691.48 (250.1)	431.58 (181.8)	631.91 (284.6)	496.2 (219.5)	587.75 (285.4)
	Grains	209.83 (119.0)	221.97 (117.85)	229.27 (122.7)	182.02 (96.29)	259.67 (156.6)	194.97 (115.0)	204.55 (126.7)
	Vegetables	102.29 (91.55)	77.49 (71.74)	146.11 (113.2)	88.77 (71.4)	119.45 (108.0)	106.88 (93.62)	134.57 (142.6)
	Starchy roots	49.00 (59.66)	46.50 (53.71)	56.54 (69.57)	41.81 (49.47)	54.13 (80.52)	56.67 (58.50)	55.93 (57.70)
	Legumes/Nuts/Oilseeds	16.16 (28.4)	15.20 (27.79)	20.90 (35.13)	13.71 (22.86)	12.83 (29.26)	19.68 (29.87)	18.92 (27.83)
	Fruits	142.60 (142.7)	117.69 (116.7)	238.66 (180.4)	105.27 (97.61)	185.83 (175.3)	118.02 (125.8)	173.77 (180.1)
	Meat/Fish/Eggs	121.44 (74.19)	88.10 (56.7)	102.25 (60.82)	124.07 (62.2)	148.24 (101.9)	177.57 (78.08)	155.93 (83.15)
	Livestock meat	33.43 (38.57)	17.74 (23.0)	19.22 (25.19)	33.10 (28.75)	25.39 (40.61)	86.20 (47.26)	29.52 (36.88)
	Poultry	21.26 (32.9)	19.41 (28.94)	19.68 (29.63)	21.71 (31.65)	24.82 (45.44)	23.29 (35.63)	15.98 (31.58)
	Processed meat	28.98 (35.11)	23.92 (28.31)	24.47 (30.43)	30.73 (32.29)	42.76 (60.02)	29.39 (30.59)	35.91 (41.47)
	Meat imitates	0.41 (4.81)	0.45 (5.15)	1.17 (7.97)	0.20 (3.42)	0.28 (3.49)	0.00 (0)	0.00 (0)
	Offals/Other meat	3.10 (13.19)	0.99 (5.57)	1.29 (6.97)	2.57 (8.76)	4.60 (17.35)	7.28 (24.56)	35.11 (25.47)
	Fish/Seafood	26.34 (34.69)	20.49 (27.2)	29.10 (34.11)	26.46 (32.11)	38.72 (53.85)	23.67 (33.08)	32.03 (37.93)
	Eggs	7.92 (16.2)	5.11 (11.44)	7.31 (15.11)	9.30 (16.33)	11.67 (24.92)	7.75 (15.86)	7.36 (14.64)
	Dairy products	217.2 (215.6)	149.4 (137.3)	251.0 (178.0)	167.3 (151.9)	532.8 (339.2)	188.1 (183.2)	244.3 (279.5)
	Milk and fresh dairy products 181.43 (211.3)	121.8 (135.0)	212.91 (178.4)	131.71 (149.4)	480.58 (338.3)	152.05 (181.2)	205.75 (275.4)
	Cheese	32.47 (38.61)	24.98 (27.26)	28.74 (30.85)	33.56 (35.21)	49.70 (66.78)	35.36 (40.23)	38.58 (50.2)
	Milk product imitates	3.33 (27.39)	2.62 (20.64)	9.35 (50.41)	1.99 (17.82)	2.50 (26.03)	0.75 (8.00)	0.00 (0)

). More sustainable European diets based on self-selection do not require exclusion of entire categories of food. Journal of Cleaner Production, 248, 1-10. , DOI : 10.1016/j.jclepro.2019.119298 14

Composite dishes 271.7 (184.3) 256.94 (185.5) 253.87 (171.9) 275.39 (182.2) 317.24 (191.3) 278.71 (191.4) 293.2 (190.9)

	Plant-based dishes	208.84 (174.6)	207.55 (182.8)	205.39 (168.2)	207.10 (169.4)	229.27 (181.4)	203.08 (174.6)	244.23 (177.1)
	Animal-based dishes	62.88 (73.2)	49.40 (58.59)	48.48 (59.84)	68.29 (70.52)	87.97 (95.01)	75.64 (90.99)	48.96 (55.99)

Drinks 1385 (721.0) 1299 (692.9) 1518 (689.2) 1260 (681.1) 1652 (744.1) 1465 (783.9) 1534 (866.7)

  Results are presented as means (standard deviation); statistical tests of differences in means between the clusters, based on ANOVA and chi-square, were 303 all significant (<0.01), with and without adjustment for individual energy intakes, age and gender.

	Snacks/Desserts/Others	19.69 (35.75)	23.10 (36.69)	18.08 (36.06)	18.14 (30.55)	19.19 (40.18)	20.35 (41.64)	11.67 (24.42)
	Fruit & vegetable juices	65.13 (131.1)	74.45 (138.7)	99.26 (161.4)	37.16 (77.37)	79.91 (160.3)	61.11 (139.7)	59.38 (115.3)
	Tea/Coffee/Cocoa	434.20 (377.34)	364.06 (343.7)	497.84 (379.7)	382.75 (347.8)	656.87 (422.7)	435.54 (391.9)	515.31 (373.8)
	Soft drinks	95.30 (205.5)	167.89 (274.9)	76.99 (199.1)	68.95 (151.4)	43.24 (115.0)	93.32 (204.5)	64.20 (147.7)
	Alcoholic beverages	147.61 (295.0)	167.81 (357.4)	118.62 (248.8)	128.48 (213.4)	94.53 (196.8)	230.18 (411.2)	188.88 (314.1)
	Drinking water	642.93 (544.9)	525.03 (471.3)	724.89 (546.7)	642.78 (550.7)	777.37 (614.2)	644.95 (546.9)	706.35 (670.3)
	Miscellaneous	72.37 (58.54)	79.58 (63.25)	69.57 (56.55)	68.27 (54.96)	77.35 (59.7)	70.37 (59.16)	61.10 (48.72)
	Sugar/Confectionaries	18.06 (22.79)	26.73 (29.78)	16.63 (20.94)	14.85 (17.89)	13.70 (20.89)	15.42 (18.75)	17.92 (17.38)
	Animal fats	3.80 (8.6)	3.38 (7.36)	1.91 (5.38)	4.85 (9.81)	2.89 (9.52)	5.13 (9.71)	3.38 (6.22)
	Vegetable fats	11.60 (13.93)	9.28 (10.89)	13.16 (13.57)	11.04 (13.52)	20.10 (21.14)	8.89 (10.72)	13.50 (15.57)
	Herbs/Spices/Condiments	19.23 (28.45)	17.09 (25.44)	19.79 (28.67)	19.39 (29.0)	21.47 (29.68)	20.58 (30.98)	14.64 (21.89)
								15

Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. (

2020

). More sustainable European diets based on self-selection do not require exclusion of entire categories of food. Journal of Cleaner Production, 248, 1-10. , DOI : 10.1016/j.jclepro.2019.119298 1

Table 3 .

 3 Contribution (%) of food groups and sub-groups to total diet weight in the "More-sustainable" cluster 1 and in the "More-sustainable" class 2 compared with the corresponding overall rest of the sample

		Clustering approach		Classification approach
		« More-	Rest of	P-	« More-	Rest of the	P-
	Food group % total	Sustainable »	the sample	value 3	Sustainable »	sample	value 4
	diet weight (sd)	cluster 1			class 2
	N	1498	6804		1125	7177
	Plant foods	24.79% (8.65)	19.86% (7.94)	0.0000	25.16% (8.12)	20.06% (8.1)	0.0000
	Grains	8.15% (4.23)	8.50% (4.54)	0.2431	8.81% (4.16)	8.38% (4.53)	0.0001
	Vegetables	5.28% (4.18)	3.82% (3.34)	0.0000	5.17% (3.85)	3.92% (3.48)	0.0000
	Starchy roots	2.01% (2.54)	1.98% (2.45)	0.1692	1.84% (2.5)	2.01% (2.46)	0.4332
	Legumes/Nuts/ Oilseeds	0.74% (1.24)	0.63% (1.16)	0.0017	0.67% (1.15)	0.65% (1.19)	0.4923
	Fruits	8.60% (6.47)	4.91% (4.67)	0.0000	8.68% (6)	5.09% (4.93)	0.0000
	Meat/Fish/Eggs	3.71% (2.26)	5.31% (3.27)	0.0000	3.92% (2.5)	5.19% (3.23)	0.0000
	Livestock meat	0.72% (0.96)	1.60% (1.93)	0.0000	0.54% (0.85)	1.58% (1.9)	0.0000
	Poultry	0.72% (1.11)	0.91% (1.42)	0.0000	0.81% (1.25)	0.89% (1.39)	0.4355
	Processed meat	0.85% (1.02)	1.21% (1.35)	0.0000	0.83% (0.92)	1.20% (1.35)	0.0000
	Meat imitates	0.04% (0.3)	0.01% (0.18)	0.0000	0.03% (0.24)	0.01% (0.2)	0.0016
	Offals/Other meat	0.05% (0.28)	0.14% (0.57)	0.0000	0.05% (0.26)	0.13% (0.56)	0.0000
	Fish/Seafood	1.08% (1.32)	1.10% (1.52)	0.1465	1.35% (1.54)	1.05% (1.47)	0.0000
	Eggs	0.26% (0.55)	0.33% (0.71)	0.0000	0.31% (0.74)	0.32% (0.68)	0.2586
	Dairy products	8.96% (6.45)	8.12% (7.55)	0.0000	8.97% (7.09)	8.16% (7.41)	0.0016
	Milk and fresh dairy products	7.62% (6.49)	6.67% (7.49)	0.0000	7.44% (7.13)	6.75% (7.36)	0.0030
	Cheese	1.03% (1.13)	1.36% (1.56)	0.0000	1.18% (1.21)	1.32% (1.54)	0.0000
	Milk product imitates	0.30% (1.56)	0.08% (0.78)	0.0000	0.35% (1.71)	0.09% (0.79)	0.0000
	Composite dishes	9.35% (6.75)	12.09% (9.18)	0.0000	11.74% (8.46)	11.58% (8.91)	0.0516
	Plant-based	7.61% (6.62)	9.28% (8.53)	0.0000	9.77% (7.89)	8.86% (8.3)	0.0001
	Animal-based	1.74% (2.23)	2.81% (3.36)	0.0000	1.97% (2.44)	2.72% (3.31)	0.0000
	Drinks	50.77% (12.39)	51.67% (13.5)	0.0067 47.97% (12.13) 52.06% (13.41) 0.0000
	Fruit & vegetable juices 3.45% (5.45)	2.21% (4.27)	0.0000	2.08% (3.42)	2.49% (4.68)	0.0609
	Tea/Coffee/Cocoa	16.96% (11.82)	16.14% (12.52) 0.3159 15.42% (10.56) 16.42% (12.66) 0.0000
	Soft drinks	2.52% (5.79)	4.12% (8.27)	0.0001	1.52% (3.7)	4.19% (8.31)	0.0000
	Alcoholic beverages	3.78% (6.67)	5.59% (8.98)	0.0000	3.70% (5.44)	5.51% (9.01)	0.0000
	Drinking water	24.06% (14.65)	23.62% (15.45) 0.5163 25.25% (13.49) 23.45% (15.56) 0.0030

Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. (

2020

). More sustainable European diets based on self-selection do not require exclusion of entire categories of food. Journal of Cleaner Production, 248, 1-10. , DOI : 10.1016/j.jclepro.2019.119298

  ). More sustainable European diets based on self-selection do not require exclusion of entire categories of food. Journal of Cleaner Production, 248, 1-10. , DOI : 10.1016/j.jclepro.2019.119298

	19

  of food consumption (nutrient intakes and GHGE) as input data, rather than food consumptions themselves, is novel. It is worth noting that this approach avoids the use of food categorization, which may differ between countries, in identifying clusters. As some databases include multidimensional information (e.g. nutritional content, contaminants, price, environmental impacts)(Gazan et al., 2018a), the use of MFA, a method designed to study data composed of variables structured in groups, seems adequate. Using nutrient intakes and dietary GHGE as input data, as opposed to intakes of food items or food groups, avoids ex ante assumptions regarding the sustainability of specific foods or diets. The fact that the relatively more sustainable cluster had the largest content of plant-based foods was in accordance with current national food-based dietary guidelines (FAO Departments and Offices, 2017) and most studies on sustainable diets[START_REF] Eupha | Healthy and sustainable diets for european countries[END_REF]. On the other hand, it may be surprising that diets in the cluster with lowest dietary GHGE had the lowest nutritional quality (highest SED, 2 nd highest MER, and lowest MAR). The reason is that these diets have

). More sustainable European diets based on self-selection do not require exclusion of entire categories of food. Journal of Cleaner Production, 248, 1-10. , DOI : 10.1016/j.jclepro.2019.119298 20 considering consequences the largest quantity of energy dense and nutrient poor foods (i.e., Sugar/Confectionaries, Soft drinks, Snacks/Desserts/Others) which have relatively low environmental impacts

Acknowledgements:

We thank all of the participants of the European dietary surveys used in this work, as well as the agencies that funded these surveys: National Institute for Health and Welfare in Finland, French Agency for Food, Environmental and Occupational health and safety in France, National Institute for Research on Food and Nutrition in Italy, National Food Administration in Sweden, and Department of Health and Food Standard Agency in the UK.

Funding:

This study

Comment citer ce document : Vieux, F., Privet, L., Soler, L. G., Irz, X., Ferrari, M., Sette, S., Raulio, S., Tapanainen, H., Hoffmann, R., Surry, Y., Pulkkinen, H., Darmon, N. ( 2020 In the classification approach, 1125 diets were identified as "More-Sustainable", 576 of which were also identified with the clustering approach. The "More-Sustainable" class contained a higher percentage of women (69.1 % vs 61.9 %) and displayed lower dietary GHGE (3485 vs 3834 g CO 2 eq/d) than the "More-Sustainable" cluster (data not shown).

Table 3 shows the average food composition (% of diet weight) of the individual diets in the "More-Sustainable" cluster and in the rest of the sample as well as p-values indicating statistically significant differences between the two. Corresponding statistics are shown with respect to the "More-Sustainable" class. Compared to the rest of the sample, the "More-Sustainable" cluster was characterized by considerably higher intake of plant foods, slightly higher intake of dairy, lower intake of meats, and lower intake of sugar/confectionaries, soft drinks and alcoholic beverages. Similar results were, with the exception of composite dishes, obtained with the classification approach. The only food sub-group for which the two approaches result in a difference in the internal comparison (i.e. between "More-Sustainable" class/cluster vs rest of sample) is plant-based composite dishes. In the clustering approach,