July 24, 2020
The problem with these guidelines is that food is complicated, and so are people. Even more importantly, these recommendations are based on what the ‘average person’ needs.
And that ‘average person’ doesn’t exist.
Meet Mary. She’s an ‘average’ US citizen.
Mary has white skin.
She is 38 years old.
Mary is 5’4 and weighs 168 pounds.
She wears size 9 shoes
She always has breakfast and drinks two cups of coffee per day
She eats one piece of fruit and two portions of vegetables each day
She earns $806 per week
Are you Mary? If not, congratulations – you’re not average! And neither is almost everyone else.
In the same way that buying size 9 shoes for every person in the population would leave most people unhappy and uncomfortable, a one-size-fits-all approach to nutrition is more like one-size-fits-almost-no-one.
In the US, healthy eating guidelines focus on reducing the number of people suffering from health conditions linked to poor nutrition, such as diabetes and heart disease. Every five years, the government issues guidelines that are designed to be easy to understand, simple to follow and applicable to the ‘average’ person.
At their most basic, the latest HHS/USDA guidelines recommend following a “healthy eating pattern” with an “appropriate calorie level”, including a variety of vegetables, fruits and whole grains, low-fat dairy, protein-rich foods and oils, and limiting saturated and trans fats, added sugars and salt.
Despite this good advice, something’s clearly not working.
The FDA bases its nutritional recommendations on scientific research, with a panel of experts systematically reviewing the latest studies every five years to create a report. This is then combined with feedback on previous guidelines to develop new ones.
This is a challenging task given that a single set of guidelines need to be produced, often using data from studies using average group results.
It’s also worth noting that participants in research tend to be mostly white and male and there are few mandates for research subjects to be representative of populations. Only in the early 1990s did the NIH suggest a policy that women and minorities should be included in medical research. Even after the new policy was created, much research continued to be over-represented with white male study subjects.
Looking at the ‘average’ within unrepresentative populations in research also leads to generalized headlines such as ‘cutting calorie intake by 300 calories can protect your heart’.
However, hidden within this data are participants who are ‘non-responders.’ In other words, people who reduce their food intake by 300 calories and find it has no effect on their health at all. Some people may buck the trend entirely and discover that cutting 300 calories from their nutrition plan actually has a negative impact on their health.
What’s more, nutritional research often focuses on people with specific health problems. For example, studies that measure the effect of salt on blood pressure tend to recruit people with high blood pressure. This is understandable, because decreasing the salt intake of healthy people with normal blood pressure is much harder to detect.
Research results in nutrition may seem to be contradictory, confusing or change in the light of new evidence. This may be because food is complex, the methods used to collect, analyze and interpret data vary from study to study, or simply because our bodies and the food that we eat are complicated!
There are foundational healthy eating principles that should apply to most people within the broad scope of current nutritional recommendations – such as eating more fibre, and more plant-based and fewer ultra-processed foods – but expecting one-size-fits-all average guidelines to fit you perfectly is overly simplistic.
What the ‘average person’ needs to eat may not be exactly the same as what you need to eat to stay healthy. We are all different, our responses to food are all different, and what works for one person isn’t necessarily the right choice for another.
Nutritional science is now advancing at a rapid pace, however due to the complexity of our bodies (with our thousands of biochemical pathways) and of the foods that we eat, we are only starting to scratch the surface in understanding how food impacts our health at a personalized level.
The good news is that developments in nutritional monitoring, microbiome analysis and machine learning mean that we’re finally getting the data and the tools we need to truly measure, analyze and even predict responses to food on an individual level.
Our PREDICT 1 study, which measured individual responses to food in more than 1,000 people, shows how different we all are. Even identical twins – who share all their genes and much of their environment – have very different nutritional responses.
So although our genes do influence how our bodies break down and use food, their influence is limited: PREDICT showed that genetics explains very little of the variation in nutritional responses between people.
Some of the differences are due to the particular blend of billions of bacteria living in our guts, known as the microbiome, while the rest are down to a complex mix of genetics, diet, activity, sleep, age and more.
Even so, whatever is responsible for the variation certainly isn’t random – we also found that individual people have regular, predictable responses to the same foods.
Our at-home test kit, personalized insights report, and action plan will enable you to test your biology and choose the foods that best support your health. We believe that there is no one right way to eat, and that good nutrition can’t be condensed into simple guidelines. With ZOE's at-home test kit you can discover exactly how your body works, so that you can make the best decisions for your unique biology.
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