WP 7: Modelling SHARP diets for EU-consumers

General information

The overall aim is to operationalize “SHARP diets” for EU consumers in sub-regions based on individual-level data; such diets are environmentally Sustainable, Healthy (nutritionally adequate), Affordable (accessible yet also supporting the EU agri-food sector), Reliable (stable in their supply), and Palatable (consistent with cultural norms and preferences):

  • To characterise the diversity and nutritional adequacy of diets in different EU regions, overall and in relevant population subgroups;
  • To obtain insight into the sustainability of diets of EU consumers;
  • To develop the consumer-based SHARP model that delivers options for sustainable food and nutrition security (FNS) diets by combining real-life individual-level food intake data with sustainability metrics;
  • To enrich the SHARP model with demographic factors (e.g. age, sex), biological factors (e.g. weight status), regional circumstances (e.g. cultural preferences), and socio-economic factors
  • To apply the SHARP model under restrictions of nutritional, environmental, and economic factors and to translate SHARP model output to consumer-oriented food intakes in EU regions.

Latest Publication

Deliverable 7.5: The SHARP diet model and its application to different EU regions Working document including preliminary results

-This deliverable has not yet been published - The SHARP diet model makes use of individual-level dietary intake data of different EU countries to derive diets that are more environmentally Sustainable, Healthy, Affordable, Reliable, and Preferred by consumers. Options for dietary change are derived from existing efficient diets, hence within the boundaries of current dietary practices and realistic. The SHARP diet model proposes future EU diets that are both healthy and sustainable, and likely to be accepted by consumers #SHARP #die

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Deliverable 7.4: Toward modelling SHARP diets, based on nutritional adequacy, sustainability metrics and population diversity parameters

Diet modelling has been dominated by linear programming models for many years, however their success has been limited, while their inability to extract value from data in our information-driven world has become readily apparent. Increasing consumers’ diet healthiness has been the primary task of almost all diet models, however to actually change patterns of consumers’ purchasing behavior, models have to learn their preferences, so as to recommend diet alternatives that are both healthy, and appealing. We present our data-driven approach that leverages food item similarities as the main building blocks of diet recommendations, which arguably represents a paradigm shift in the way we optimize diets. Furthermore, we switch from exploiting what is known to be preferable (i.e. what we observe in a consumer’s diet), to exploring what is likely preferable, thereby allowing our diet model to “think outside the box”.

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Deliverable 7.3: Initial model for designing SHARP diets

Designing healthier diets is a complex process which can have substantial public health benefits.The intakes, but also the requirements of multiple important nutrients for different population groups should be taken into account. Moreover, the current dietary preferences of individuals should be considered to promote the acceptability of the diet. Diet models have been developed and used for designing suchhealthier and acceptable diets. The main objective of these models is to determine the optimal quantities of available food items that should be included in a diet to optimize a specific indicator (e.g. maximize a dietary quality index). Additional constraints are defined to improve the acceptability of the calculated diets. These constraints are either in the form of upper and lower limits to the intake of specific food-items or in the form of fixed combinations of food-items in meals. Defining such constraints explicitly is challenging and involves expert knowledge and a substantial degree of arbitrariness. To avoid defining such acceptability constraints we propose a DEA based diet model that benchmarks existing complete diets of a certain population and in our case identifies healthier alternatives. However, the model's flexibility allows for additional dimensions to be included, such as sustainability indicators and prices. The method was applied successfully to benchmark alternative diets of a group of individuals in the Netherlands.

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Deliverable 7.1: The initial model to design SHARP diets, based on nutritional adequacy and preliminary sustainability metrics

This paper collates food and nutrient intake data from Denmark, Czech Republic, Italy and France. Nutritional adequacy of the diets will be assessed using a protocol developed in WP2. This is the basis for the initial model to design SHARP diets, based on nutritional adequacy and preliminary sustainability metrics.

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