A methodological framework for deriving the German food-based dietary guidelines 2024: a multi-objective function including human health, the environment, and observed dietary intakes

BackgroundFood-based dietary guidelines (FBDGs) provide recommendations on diets that aim to decrease disease risk and environmental impact, while remaining culturally acceptable for the population. Using mathematical optimization to define such diets, these objectives can be operationalized as components of the objective function. ObjectivesTo develop a framework for (i) deriving an indicator that quantifies diet-related disease burden and (ii) evaluating different weighting schemes within a three-dimensional diet optimization model. MethodsTo address objective (i), disability-adjusted life years (DALYs) from the Global Burden of Disease Study (GBD) and a diet-specific burden estimate based on observational data were transformed into a model-compatible indicator using linear interpolation. To address objective (ii), a linear diet optimization model was developed. It included constraints on nutrients and acceptability, and a three-objective function that minimized disease burden (DALYs), environmental impact (greenhouse gas emissions and land use), and, as a proxy for cultural acceptability, deviation from the observed diet. Forty-two model variations with different weighting schemes were computed and compared regarding component outcomes. ResultsIn proof-of-concept analyses, the derived health indicator aligned closely with values reported in the literature: 90% (based on GBD) and 99% (based on the observational data) of diet-related DALYs were captured. Among the 42 model variations, strong synergies were observed between health and environmental outcomes. Optimizing exclusively for disease burden or environmental impact resulted in substantial deviations from the observed diet, underscoring the importance of considering cultural acceptability. Model stability improved with the inclusion of all three components. ConclusionThe proposed methodology enables the integration of DALYs and provides insights about various weighting schemes to establish a diet optimization model that minimizes disease burden, environmental impact, and deviation from the observed diet, and serves as the basis to derive FBDG for Germany.