Personalised Nutrition – One Size Does Not Fit All

June 17th, 2019 | Posted in Info

Whilst we like to believe that food, exercise and medicines all have consistent and measurable effects on us it is becoming increasingly apparent that this is not the case. Research has shown that the effects of foods can vary, not only between individuals, but also within an individual from one day to the next. It’s also known that whilst most drug research on humans has historically used men, women respond very differently to many drugs, partly due to body size and composition as well as due to hormonal differences.

This month we’ll look at how individuals react differently to food, drugs and the environment and why this may be.

Personalised Nutrition

Glycaemic Index Variability

The idea of classifying foods according to their glycaemic index or glycaemic load has influenced food choices for many people for decades. The Glycaemic Index (GI) and Glycaemic Load (GL) of foods aim to indicate their effects on blood sugar after ingestion.

 

Variability Between People

However, a study of 800 people found that there was high variability in the glycaemic response to identical meals. Some people’s blood sugar rises after eating white bread but not after eating glucose. For some sushi caused a more rapid sugar spike than ice cream (1).

 

Variability Within an Individual

Not only can the glycaemic effect of a food vary between people it can also vary by 20% within an individual. This means that the same food can trigger a different response in the same individual at different times. A food that triggers a low glycaemic response in you at one time could trigger a high glycaemic response at another time.

For example, research into the glycaemic response to white bread found that within the an individual the glycaemic value could differ by more than 60 points between tests. The researchers took into account gender, BMI, blood pressure, physical activity levels and other characteristics. Most factors only had a minor effect on GI variability.

This means that the Glycaemic Index has limited use as an indicator of the effect of food on blood sugar levels, even under highly standardised conditions. In real life, because foods are not eaten in isolation, the variability is likely to be even greater. It seems that using the glycaemic index or glycaemic load as indicators of the effect of food on health needs to be reconsidered (2).

 

What is Causing the Variability?

There are a few things that can affect our response to food but it turns out that a key player is our old friend the microbiome. We all have a unique and changing colony of micro-organisms in our digestive tracts and the make up of your microbiome will have a big influence on how you respond to food. This is a two way street as the microbiome changes in response to what we eat as well as affecting our response to food. 

Other factors that influence the glycaemic response include:

  • Whether food is preceded by exercise
  • Sleep quality and quantity
  • Stress
  • Genetics – for more information see blog post: Are You Carb Adapted?

 

Individualised Diets

The idea of universal dietary recommendations appear to be of limited use. Instead personalized diets that change over time as needs change are likely to be more successful in improving many aspects of health. 

Whilst there may be no such thing as the perfect diet keeping a food and symptom diary can help to identify which foods make you feel good and which have negative effects. Things to monitor include:

  • Energy
  • Tiredness
  • Bloating
  • Indigestion
  • Bowel movements
  • Thirst
  • Headaches
  • Sleep
  • Mood

You may find that although you sometimes react differently to the same foods on different days there may be patterns in how your body reacts. Listen to the signals your body is giving you. It is never wrong!

See also blog post If the Drugs Don’t Work for information about how our microbiomes affect our response to medications.

 

References

1. Cell. 2015 Nov 19;163(5):1079-94. Personalized Nutrition by Prediction of Glycemic Responses. Zeevi D, Korem T, Zmora N et al.

2. Matthan NR, Ausman LM, Meng H et al.  Estimating the reliability of glycemic index values and potential sources of methodological and biological variability. A