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

Area of Science:

• Nutrition Science
• Public Health
• Computational Modeling

Background:

• Dietary patterns significantly impact human health through complex interactions at nutrient, food group, and overall pattern levels.
• Food-based dietary guidelines (FBDGs) aim to translate this complex information for public use.
• Previous FBDGs often simplified the intricate relationships between diet and health outcomes.

Purpose of the Study:

• To describe a novel, enhanced optimization method for establishing French healthy eating patterns (HEPs).
• To integrate multiple data types including nutrients, food contaminants, and epidemiological health relations.
• To develop realistic dietary patterns that minimally deviate from existing dietary habits.

Main Methods:

• Utilized an enhanced optimization method for in-depth food pattern modeling.
• Gathered data on nutrients, food contaminants, and long-term health effects.
• Incorporated objectives for realistic dietary patterns and minimal deviation from prevailing diets.

Main Results:

• Modeled HEPs demonstrate the importance of food grouping and considering dietary habits.
• The method accounts for food contaminant exposure and integrates varied health-related outcomes.
• The approach provides a rationalized framework for establishing HEPs with multiple, competing objectives.

Conclusions:

• The enhanced optimization method offers a versatile and rationalized approach to developing comprehensive FBDGs.
• Flexibility in dietary reference values and health-based guidance values is crucial for identifying viable HEPs.
• The methodology can be expanded to include additional dimensions, promoting both human and planetary health.