Diet (nutrition) | EPFL Graph Search

In nutrition, diet is the sum of food consumed by a person or other organism. The word diet often implies the use of specific intake of nutrition for health or weight-management reasons (with the two often being related). Although humans are omnivores, each culture and each person holds some food preferences or some food taboos. This may be due to personal tastes or ethical reasons. Individual dietary choices may be more or less healthy. Complete nutrition requires ingestion and absorption of vitamins, minerals, essential amino acids from protein and essential fatty acids from fat-containing food, also food energy in the form of carbohydrate, protein, and fat. Dietary habits and choices play a significant role in the quality of life, health and longevity. Healthy diet A healthy diet can improve and maintain health, which can include aspects of mental and physical health. Specific diets, such as the DASH diet, can be used in treatment and management of chronic conditions. Dietary recommendations exist for many different countries, and they usually emphasise a balanced diet which is culturally appropriate. These recommendation are different from dietary reference values which provide information about the prevention of nutrient deficiencies. Exclusionary diets are diets with certain groups or specific types of food avoided, either due to health considerations or by choice. Many do not eat food from animal sources to varying degrees (e.g. flexitarianism, pescetarianism, vegetarianism, and veganism) for health reasons, issues surrounding morality, or to reduce their personal impact on the environment (e.g. environmental vegetarianism). People on a balanced vegetarian or vegan diet can obtain adequate nutrition, but may need to specifically focus on consuming specific nutrients, such as protein, iron, calcium, zinc, and vitamin B12. Raw foodism and intuitive eating are other approaches to dietary choices. Education, income, local availability, and mental health are all major factors for dietary choices.

Computational Approaches for Studying Dietary Behaviors with Digital Traces

Kristina Gligoric

Human nutrition and dietary habits shape our health, daily life, societies, the environment, and life on earth in general. However, it remains challenging to understand and attempt to change dietary behaviors using traditional methods due to measurement and causal identification challenges.In this thesis, we contribute computational and causal approaches leveraging large-scale passively sensed digital traces to shed new light on our dietary behaviors and derive novel scientific insights. We study dietary behaviors in two types of contexts: campus-wide and worldwide. Based on digital traces capturing behaviors of tens of thousands of people on campus and millions of internet users, we develop observational study designs that enable the isolation of causal effects of implicit behavioral interventions, including forming social ties, being exposed to the food choice of others, and stay-at-home interventions. The thesis is organized into three parts.The first part presents studies based on situated on-campus food purchase logs. In the first study, we show how, when a person acquires a new eating partner on campus, the healthiness of their food choice shifts significantly in the direction of their new eating partner's dietary patterns. In the second study, we identify purchasing mimicry, i.e., copying the food choices of others in the purchasing queue, as a specific behavioral mechanism for how similarities in dietary behaviors between individuals occur on campus. The second part of the thesis leverages online information-seeking traces (Google search query logs). Studying worldwide dietary behaviors, we identify and describe global shifts in dietary interests during the first wave of the COVID-19 pandemic, larger and longer-lasting than the typical changes during the end-of-year holidays in Western countries.In the third part, we critically investigate the limits to how much computational approaches can reveal about dietary behaviors in the general population. We contribute a framework for reasoning about biases of digital traces and present a case study of food consumption in Switzerland. The bias estimates derived in the case study imply that researchers should aim to establish evidence of validity before relying on social media and tracking apps---two frequently used digital traces---as proxies for true food consumption in the general population.The novel scientific findings and methodological advances presented here contribute to the existing knowledge about human dietary behaviors and inform the design of future food systems, policies, and behavioral interventions.

EPFL2022

Computational Approaches for Studying Dietary Behaviors with Digital Traces

Kristina Gligoric

EPFL2022