Predictive Health: Navigating Dietary Dynamics and BMI Trajectories for Chronic Condition Prevention
Principal Investigator
Name
Yao-Chi Yu
Degrees
Ph.D.
Institution
Tarleton State University
Position Title
Research Data Scientist
Email
About this CDAS Project
Study
IDATA
(Learn more about this study)
Project ID
IDATA-70
Initial CDAS Request Approval
Apr 11, 2024
Title
Predictive Health: Navigating Dietary Dynamics and BMI Trajectories for Chronic Condition Prevention
Summary
The escalating prevalence of obesity-related chronic diseases, including heart disease, diabetes, and cancer, underscores the need for advanced predictive tools that identify risk factors associated with dietary habits and body mass index (BMI). Adopting the Interactive Diet and Activity Tracking in AARP (IDATA), this project aims to use a dynamic BMI simulation model to create a comprehensive framework for assessing the risk of obesity-related chronic diseases. Our novelty in the methodology is based on an examination of comprehensive data on dietary consumption as well as temporal data on BMI. Therefore, the objective of the study is to discover connections between dietary habits, fluctuations in BMI, which is a good measure for predicting obesity, and the subsequent risk of chronic illnesses. We will employ machine learning algorithms in order to examine intricate sets of data, guaranteeing the precise categorization of eating habits' effects on BMI fluctuations and, ultimately, the prediction of various chronic health outcomes and their implications for long-term health. This method will not only augment our comprehension of the complex connections between nutrition, BMI, and health results but can also serve as a practical tool for providers to predict the likelihood of chronic disease development and execute preventive measures.
Aims
1. Cluster different dietary patterns and identify the corresponding BMI change (weekly/monthly basis) through machine learning techniques
2. Derive the cluster-specific BMI model, stratified by age/sex/gender
3. Evolve the BMI model and observe long-term BMI change to discover the relation between disease risks and dietary patterns
Collaborators
Dr. Subi Gandhi, Ph.D., MPH (Associate Professor, College of Health Sciences, Tarleton State University)