Systems Science and Data Science in Nutrition

Dietary patterns reflect the frequency, amounts, diversity, and mix of various foods, drinks, and nutrients in a person's diet. Nutrition interventions are any set of strategies aimed at encouraging and facilitating the adoption of nutrition-related habits that promote health and happiness. Systems thinking is a way of thinking at how objects are related to one another and how they fit into a bigger system. A system is a collection of organized and interconnected pieces or factors that cause complex and dynamic behaviours that can change over time. Many components of systems thinking and systems science methodologies are informed by important concepts like dynamic, complex, and linked. The application of systems science methodologies to explain or forecast real-world results of large-scale actions is becoming more common. The application of systems science to nutrition implementation research is gaining popularity.

The fields of nutritional research and data science are colliding. Because of statistical limits and poor data quality, the subject of nutrition has been plagued with perplexing signals to the public, both of which can be improved by data science and the collective power of new technology. Data science is being used to analyse billions of chemicals found in daily foods that have the potential to give a wide range of health advantages, benefiting millions of people around the world.

• AI and Machine Learning
• Data-Driven Diets
• Implementation Science in Nutrition
• Nutrition Behaviours
• The Future of Food