Modeling Individual Differences in Food Metabolism through Alternating Least Squares. Academic Article uri icon

abstract

  • Understanding how macronutrients (e.g., carbohydrates, protein, fat) affect blood glucose is of broad interest in health and dietary research. The general effects are well known, e.g., adding protein and fat to a carbohydrate-based meal tend to reduce blood glucose. However, there are large individual differences in food metabolism, to where the same meal can lead to different glucose responses across individuals. To address this problem, we present a technique that can be used to simultaneously (1) model macronutrients' effects on glucose levels over time and (2) capture inter-individual differences in sensitivity to macronutrients. The model assumes that each macronutrient adds a basis function to the differences in macronutrient metabolism. The technique performs a linear decomposition of glucose responses, alternating between estimating the macronutrients' effect over time and capturing an individual's sensitivity to macronutrients. On an experimental dataset containing glucose responses to a variety of mixed meals, the technique is able to extract basis functions for the macronutrients that are consistent with their hypothesized effects on PPGRs, and also characterize how macronutrients affect individuals differently.

published proceedings

  • Annu Int Conf IEEE Eng Med Biol Soc

author list (cited authors)

  • Das, A., Mortazavi, B., Deutz, N., & Gutierrez-Osuna, R.

citation count

  • 0

complete list of authors

  • Das, Anurag||Mortazavi, Bobak||Deutz, Nicolaas||Gutierrez-Osuna, Ricardo

publication date

  • July 2022