Blood sugar levels in response to foods are highly individualized.
The need for personalized dietary recommendations has been affirmed in the largest study of its kind.
Which is more likely to raise blood sugar levels: sushi or ice cream?
A study conducted at the Weizmann Institute of Science that appeared in Cell (Nov.19,2015), found that the answer varies from one person to another. The study, which for one week continuously monitored blood sugar levels in over a thousand people, revealed that the bodily response to all foods was highly individual.
The study, called the Personalized Nutrition Project, was led by Prof. Eran Segal of the Computer Science and Applied Mathematics Department and Dr. Eran Elinav of the Immunology Department.
Segal said: “We chose to focus on blood sugar because elevated levels are a major risk factor for diabetes, obesity and metabolic syndrome. The huge differences in the rise of blood sugar levels among different people who consumed identical meals highlights why personalized eating choices are more likely than universal dietary advice to help people stay healthy.”
Personalized Nutrition/ Cell November 19, 2015 (Vol. 163 issue 5)
- High interpersonal variability in post-meal sugar observed in an 800-person cohort
- Using biometric and microbiome features enables accurate sugar response prediction
- Prediction is accurate and superior to common practice in an independent cohort
- Short-term personalized dietary interventions successfully lower post-meal sugar
Taking these multiple factors into account, the scientists generated an algorithm for predicting individualized response to food based on the person’s lifestyle, medical background, and the composition and function of his or her microbiome. In a follow-up study of another 100 volunteers, the algorithm successfully predicted the rise in blood sugar in response to different foods, demonstrating that it could be applied to new participants. The scientists were able to show that lifestyle also mattered. For example, the same food affects blood sugar levels differently in the same person if its consumption had been preceded by exercise or sleep.
In the final stage of the study, the scientists designed a dietary intervention based on their algorithm; this was a test of their ability to prescribe personal dietary recommendations for lowering blood sugar level responses to food. Volunteers were assigned a personalized “good” diet for one week, and a “bad” diet – also personalized – for another. Both “good” and “bad” diets were designed to have the same number of calories, but they differed between participants. Thus, certain foods in one person’s “good” diet were part of another’s “bad” diet. The “good” diets indeed helped to keep blood sugar at steadily healthy levels, whereas the “bad” diets often induced spikes in sugar levels – all within just one week of intervention. Moreover, as a result of the “good” diets, volunteers experienced consistent changes in the composition of their Gut Bacteria, suggesting that the microbiome may be influenced by the personalized diets while also playing a role in each participant’s blood sugar responses.