In this WP we aim to review food and nutrition policy measures across Europe to support the identification of possible future food scenarios. Relevant health effects and environmental impacts associated with shifts between scenarios will be described and quantified using a risk-benefit approach. We will combine data on exposure to foods, food components or dietary patterns in the several scenarios with dose-response associations between exposure and beneficial or detrimental health effects. Multiple environmental impacts associated with each potential scenario will be assessed. The comparison of the health risks and benefits and environmental impacts of each scenario will allow prioritizing the most effective interventions to promote human health and sustainable environments. Finally, a graph database in RDF (Resource Description Framework) format will be delivered as one of the outputs to FAIR share the reviewed policies and the inferred future food scenarios. The WP will be focused on five main tasks.
TASK 5.1. Review of food and nutrition policy measures across Europe
Aim: Evaluate the evidence for the effectiveness of intervention policies undertaken in EU countries in terms of promoting, supporting and improving nutritional behaviour at population and population groups level. Identify gaps i.e. what is missing in the actions that are taken in charge for public health related to climate change and malnutrition. Also, we will discuss peculiar aspects related to population minorities/immigration towards/across Europe with the idea of harmonizing the conclusions of this survey.
Methods: Collect and compile information on public health nutrition activities/programs:
a. Literature search on consensus documents for public health and the different policies in Europe.
b. Identify databases and collect data on food allergy prevalence.
c. Identification of national official authorities in Public Health in each country of the Knowledge Hub, and the respective focal points that will provide data on the different policies. d. Develop a graph database to store the findings of the review, which can be read by humans and processed by computer. By developing the graph database, we aim to i) integrate the identified policies; ii) clarify the relationships between the policies and evidence, datasets, etc. and iii) indicate the gaps in the semantic network.
Source: Literature review and secondary data sources.
TASK 5.2. Identification of future food scenarios
Aim: From the results obtained in the other WPs, food consumption scenarios will be defined,
based on identified public health policies and from ongoing discussion topics in European/global health authorities.
Method: Different case studies will be considered. These may include the studies of selected foods, nutrients/ bioactive content, or a more comprehensive integrated approach through the definition of dietary patterns. Possible examples include the substitution of different food sources of proteins; the substitution of conventional plants with unconventional edible plants that may provide health benefits; the substitution of conventional foods with novel/enriched food in nutrients or in bioactive molecules; the change from standard current diets to a scenario of healthier patterns of eating by certain population groups. Specifically, individual dietary intake data will be used to measure the adherence to an a priori dietary pattern, recently proposed by the EAT-Lancet Commission (Willett et al., 2019), where the scientific targets for healthy diets and sustainable food systems were integrated into a common framework. Dietary patterns represent the set of foods and nutrients that are consumed together, thus they allow to study the role of multiple dietary exposures and their association with health benefits/risks. They take advantage of the collinearity between dietary variables to examine their cumulative effects instead of looking at individual nutrients or foods, with smaller effects (Tucker, K. L., 2010). From the available data regarding the dietary habits of the population, and from the gaps identified in WP1, alterations in the eating behaviours will be carried out and proposed in order to provide the population, not only with enriched foods in nutrients, but also with matrices that are rich sources of bioactive ingredients able to provide important health-promoting effects, thus having a strong impact on the population ́s well-being.
Source: Literature review and secondary data sources.
TASK 5.3. Relevant health effects and environmental impacts
Aims: Identification, prioritization, and selection of relevant health effects and environmental impacts associated with foods, food components and/or dietary patterns.
Method: Gather information on health effects associated with food/dietary patterns shifts proposed in the scenarios defined on task 5.2, regarding the domains of nutrition, toxicology, and microbiology. Collect consolidated information of multiple environmental impacts (land use, GHG emissions, acidifying emissions, atrophying emissions, freshwater use) of different food groups (Poore J and Nemecek T, 2018), in collaboration with WP1. Prioritization of beneficial and detrimental health effects to be included in the risk-benefit assessment (RBA) by evaluating the degree of evidence of the association between the health effects and exposure to food component/food or dietary pattern. The health risks associated with new potential sources of food allergens in each scenario will also be evaluated.
Sources: Literature search on systematic reviews and meta-analysis and on official reports/opinions of international research organizations and regulatory agencies.
TASK 5.4. Risk-benefit characterization of future food scenarios
Aim: Quantification of individual health effects and individual environmental impacts of food scenarios.
Method: Combination of exposure data in the several scenarios with dose-response associations between the risk-benefit factor and the health effects (beneficial or detrimental) identified in task 5.3. Individual consumption data in national representative samples (from task 3.4) will be used to assess exposure to foods or dietary patterns in the current scenario. Combining individual consumption data with information on food composition (from task 3.1) will allow assessing individual exposure to specific nutrients or other bioactive compounds. The dose-response study can be based on two approaches: i) the bottom-up approach, which estimates the incidence of disease due to exposure via dose-response models (if the biological mechanisms are known and transcribed into a mathematical model), or ii) the top-down approach, that starts from epidemiological data (relative risks) and incidence data and estimates the number of attributable cases of a certain disease due to an exposure. If the association between the risk/benefit factors and the health effects cannot be quantified (lack of dose-response data) the effects will be considered through a qualitative or semi-quantitative approach (e.g. comparison with Dietary Reference Values). Environmental impacts will be calculated by combining food consumption data in current and alternative scenarios and environmental impacts (land use, GHG emissions, acidifying emissions, atrophying emissions, freshwater use) of different food groups (from task 5.3).
Source. Literature review and/or other sources of epidemiological data.
TASK 5.5. Health effects and environmental impacts: scenarios comparison
Aim: Quantification of health effects using common metrics and environmental impacts of the substitutions proposed in the scenarios and integration of results.
Method: To quantify beneficial and detrimental health effects, we will use composite metrics such as the Disability-Adjusted Life Years (DALYs), in order to consider both mortality and morbidity in the assessment. DALYs can be estimated using the following equation: DALYs=YLL+YLD, where YLL refers to the years of life lost because of the disease (YLL=Number of deaths×Remaining life expectancy) and the YLD refers to the years of life lived with disability (YLD=Incident cases×Disability weight×Average duration of the symptoms or the disease). Comparison of DALYs and environmental impacts between scenarios will be performed. The differences between the current/reference scenario and the alternatives provide a measure of the change in the burden of disease and in the environment if the substitutions proposed are effectively implemented (Nauta MJ et al, 2018; Thomsen ST et al, 2018; Thomsen ST et al, 2019).
Source: Data needed for DALYs calculations, includes the disability weights, duration of each stage, the probability of death, age of onset of the disease and life expectancy. This data will be used to develop a schematic tree for each health effect. Integration of all health effects, by adding the all DALYs estimated, in each scenario.
Description of the activities (networking and scientific)
Effective public health policies need to address a wide variety of complex issues, ranging from individual lifestyle choices to environmental exposure factors. This WP5 will develop new expertise to tackle these challenges. WP5 tasks are strongly interconnected and connected with other tasks from other WPs. Regular networking activities (face-to-face or via internet, teleconferences) will take place to promote harmonization between tools used during the RBA process. Existing scientific literature will be collected to identify and summarize current knowledge on the effectiveness of policy measures to decrease nutrition related diseases and environmental impacts of food consumption. Harmonizing existing food composition databases and individual food intake will allow estimating exposure to diets, foods, nutrients (and other bioactive compounds) and food hazards. Health effects associated with exposure changes between scenarios will be reviewed by literature search allowing to quantify beneficial and detrimental health effects. Harmonizing databases on environmental impacts of different food groups will allow assessing changes in environmental impacts between scenarios. Applying this holistic approach, a clearer consensus about the knowledge gaps and research needs can emerge.