Perspective: Modeling Healthy Eating Patterns for Food-Based Dietary Guidelines-Scientific Concepts, Methodological Processes, Limitations, and Lessons.

The relations between dietary features and human health are varied and complex. Health-related variables are many and they have intricate relations at different and interrelated nutritional levels: nutrients, food groups, and the complex overall pattern. Food-based dietary guidelines (FBDGs) are principally designed to synthesize this information to make it available to the public. Here, we describe the method used to establish healthy eating patterns (HEPs) for the latest French FBDGs, which consists of in-depth food pattern modeling using an enhanced optimization method that gathered all aspects of HEPs. We present the novelty of this food modeling approach for FBDGs, which aims to gather information related to nutrients, food contaminants, and epidemiological relations with long-term health, and to be combined with the objective of realistic dietary patterns that deviate minimally from the prevailing diet. We draw lessons from stepwise implementation of the method and discuss its strengths, limitations, and perspectives. In light of the modeled HEPs, we discuss the importance of food grouping; of accounting for dietary habits while not precluding modeled diets that can be realistic/acceptable; and of taking into account the exposure to food contaminants. We discuss the tolerance and flexibility to be applied to certain dietary reference values for nutrients and health-based guidance values for contaminants so that HEPs can ultimately be identified, and how account can be taken of varied health-related outcomes applied to food groups. Although the approach involves all the peculiar uncertainties of numerous optimization model parameters and input data, its merit is that it offers a rationalized approach to establishing HEPs with multiple constraints and competing objectives. It is also versatile because it is possible to operationalize further dimensions of dietary patterns to favor human and planetary health.