In our study, we measured the effects of food intake by focusing on blood glucose responses, which are crucial for understanding how different foods affect individuals differently.

Individual responses to dietary interventions vary significantly, suggesting that personalized nutrition could be key to effective weight management and health outcomes.

Participants logged their food intake using an app, allowing us to analyze their dietary habits alongside their glucose responses for a comprehensive understanding of personalized nutrition.

In our study with 26 participants, we designed diets to either reduce or increase blood glucose levels, demonstrating that personalized diets can effectively manage glucose responses.

We found that people's glucose responses to the same food can vary significantly, indicating that individual responses to foods are not categorically good or bad but depend on the person.

Choosing the right foods based on individual responses can help manage blood glucose levels and potentially prevent pre-diabetes without drastic dietary changes.

We developed an algorithm that predicts people's glucose responses to meals based on their microbiome composition and other health metrics, achieving a correlation of 0.68, which is significantly better than previous methods.

I started working on personalized nutrition because of the alarming statistics on metabolic disease, where currently 4 out of 10 US adults are obese, and diabetes affects 1 in 10 Americans, leading to significant suffering and healthcare costs.

We standardized our study by providing participants with the same breakfast over a week to measure variability in their glucose responses to food intake.