Principal Investigator: Dr Sachin Banker
University of UtahTags: 32466, cognition, decision-making, exercise, featured, health
This research aims to understand the genetic variants associated with healthy food preferences and physical activity. Touchscreen Questionnaire (WP items) and Diet Questionnaire data from UK Biobank will be merged with additional data on perceived health of the items collected from an independent participant sample. Econometric modeling and machine learning methods will be applied to determine the association between genetic variants and healthy decisions. Understanding the links between healthy decision making and genetic variation can help to uncover biological and neurobiological processes involved in making deleterious choices. This insight will allow policy makers to design improved `nudges` that can promote healthy decisions and prevent unhealthy decisions particularly within populations displaying genetic variants associated with greater risk. Phenotype data on healthy decisions (including dietary choices & fitness) will be transformed into scores using additional data collected from independent participant samples. Genome-wide association studies will be conducted to identify links between healthy decision making and genetic variations. Furthermore, machine learning methods (e.g., classification algorithms) will be applied to predict risks of deleterious choices based on genetic information. The subset of UK Biobank participants with availability of (1) Diet Questionnaire and/or Touchscreen Questionnaire, and (2) genotype data.