Why do nutritionists' recommendations differ?

Or Why is the science of nutrition so confusing, and healthy eating is not as simple as we would like?

There are many articles by various nutritionists on a wide variety of topics of healthy nutrition. Lots of competing theories. One study confirms a hypothesis, and another completely refutes it.

And, from the outside, nutrition science can seem like something very complicated and/or confusing.

I often hear questions like:

  • Why so much conflicting information?
  • Why so much nonsense?
  • Why can't everything be said clearly and simply?
 

That is - people who are interested in a healthy diet and fitness are often confused - who to believe? And in general, what is really healthy and what is not?

 

Why so many contradictory recommendations?

This tangle of many competing ideas shows the true beauty of science because the scientific approach means considering/testing all ideas and assumptions. Because at the moment of their occurrence it is not known whether they are right or wrong, good or bad.

And each check takes time.

And that's why nutrition science is sometimes so confusing. It hasn't had enough time yet:

  • The presence of macronutrients (fats, carbohydrates and proteins) was detected only in In the middle of the 19th century;
  • Vitamins were discovered only early 20th century;
  • Studies on the effects of nutrition in a world with a sedentary lifestyle and an abundance of tasty, ultra-processed, and "enriched" foods were started only about 20 years ago.
 

Science always begins with confusion, dead ends, disappointments, and stupidities — before studying natural phenomena, people believed that hurricanes were caused by angry gods of wind.

A good example of a misconception of initial assumptions/findings in the field of nutrition is "good" and "bad" cholesterol. It turns out that high cholesterol does not cause atherosclerosis, but that the development of atherosclerosis depends on the relationship between "good" and "bad" cholesterol.

And despite the fact that this issue has been clarified, we still hear "expert" stories about bad cholesterol based on outdated research.

 

Nutrition science is evolving

Maybe not as fast as we would like. However, over time, the scientific method will distinguish grains from chaff and there will be fewer and fewer foolish claims.

In the meantime, a brief summary of the main reasons why nutrition science can sometimes be confusing and which should be considered when evaluating expert claims.

 

Nutrition science is still very new

Compared to chemistry, nutrition is still in its infancy:

  • 1842 - The first successful treatment of Scurvy;
  • Mid-19th century - it is discovered that the body gets energy from fats and carbohydrates;
  • 1902 - "Atwater factors" - a system for calculating the amount of available energy in food - was published;
  • Early 20th century - vitamins A, B, C, D, E, B5, B6, B3, K, and folic acid discovered;
  • 1970s - A link is found between mortality from coronary heart disease and HDL cholesterol.
 

If we continue the comparison with chemistry - the science of nutrition is still in the period of alchemy.

 

Insufficient research funding

Most of the funding goes to research into the treatment of various diseases, not prevention.

That is, research is being done to answer the question, "How can we treat this disease?", rather than, "How should we change our diet/lifestyle to proactively reduce the risk of the disease?".

For example, according to the US National Institute of Health, in 2016, only 4.6% of the total health research budget was devoted to nutrition research.

Of course, cardiovascular disease is statistically one of the leading causes of premature death. But obesity is a major risk factor for cardiovascular disease, which in turn is caused by an unhealthy diet.

And we can say with some certainty that an unhealthy diet shortens lives more than smoking!

 

Nutrition research is often funded by stakeholders

The source of funding may influence the results of the study. For example, to the question - Can sweetened drinks promote weight gain?

  • “Yes” is answered by 16.6% of studies funded by manufacturers of sweetened beverages;
  • “Yes” is answered by 83.3% of studies funded by independent sources.
 

This does not mean that researchers are cheating, ie the data obtained are correct in themselves, but the design of the research (selection of participants, methodology, data processing, and interpretation…) is such that it presents a result that meets the expectations of the particular funder.

 

Too many variables

Our health is affected by a myriad of factors and it is virtually impossible to determine the effects of each particular factor because even in the best-controlled study, it is difficult to isolate the effects of other factors that affect health.

As a result, it is also difficult to prove exactly how each specific factor affects health.

In some cases, even participation in a study can be a confusing variable in itself. For example, scientists asked people who usually had breakfast not to have breakfast anymore. And people who usually didn't have breakfast - start having breakfast.

And - both groups lost weight. Respectively, weight loss was caused by dietary changes, not by eating or not eating breakfast.

 

Most nutrition studies are conducted using an observation/questionnaire method

Participants complete questionnaires about their lifestyle and eating habits. This is a problem because:

  • Questionnaires are filled in late and people usually do not remember what and how much they ate. Can you tell me what you ate last Tuesday? Exactly what? Exactly how much?
  • People tend to pretend to be more "correct" than they really are.
 

The result is strange (and often pointless) correlations. For example, the sale of organic food is associated with autism.

It should also be noted that a finding of a connection is not a finding of a cause. For example - Does red meat cause heart disease and cancer, or do people with these diseases eat more red meat?

It is not possible to account for all variables in an observational study, so such a study cannot answer this question.

 

Measurements always have limitations

Even to a question as simple as, "How do calories affect our weight?" it is difficult to get an exact answer because:

  • The number of calories listed on food labels and databases is inaccurate. The error can reach up to 25%, there are even recorded cases with a 50% error;
  • Our body does not absorb all the energy that is contained in food. And there is no exact standard of how much energy each of us absorbs because we are all unique/different;
  • Calorie consumption/burn calculations are inaccurate. The error can range from 3-45%;
  • Your dietary history (previously followed fad diets) and body composition affect how much energy you consume.
 

Your diet does not affect your health right away

For example, to find out if red meat causes cancer, study participants would have to live in hermetically sealed cells for 30 years (to exclude the effects of other factors) and eat different types and amounts of red meat.

Do you know anyone who would sign for something like that in the name of science?

 

It is difficult to determine to what extent the results of the study apply to you

Even if there were people who agreed to 30-year isolation in the name of science, we still would not be completely sure that the results of the study apply to us - to all the rest.

Because participants in nutrition studies generally do not fit into the general population.

They are often:

  • Young and completely healthy students because they live close to research laboratories, they have time and they need money;
  • Sick people who suffer from problems such as obesity, metabolic disorders, and/or hypertension, as these are the diseases most commonly studied;
  • Elite athletes whose excellent physical condition reduces the number of variables and allows them to "pedal" for hours in the laboratory;
  • Animals with a relatively short lifespan - so they are easy and cheap to study.
 

And even if the study participants were fully representative of a population, the results would still not be applicable to everyone because:

  • Most people do not match with the average results of the study (at least not completely);
  • Averages are generalized. For example, if half of the study participants show a positive result and the other half a negative result, then the average score is 0. But can we ignore the response of the 50% of study participants?
 

Research is not easy, but interpreting its results is even more difficult

We first learn about the latest discoveries in nutrition science, as well as about current fashion diets, from the media.

Journalists are usually not engaged in scientific research, do not have professional knowledge and are not trained to interpret research results.

This means that:

  • They may misunderstand the results of the study;
  • They may exaggerate the results of individual studies;
  • They are not able to see the big picture — how individual studies fit together.
 

Each individual study is interesting, but not always relevant and essential. They usually reveal only one tiny piece of a giant puzzle, and without seeing the rest, the conclusions can be misleading.

 

In conclusion

As you can see, research is a rather complex field. Experience and in-depth study are needed to draw the right conclusions and find causation. It is not enough to read the conclusions section.

Trust nutrition professionals - preferably with extensive experience and able to present the results of their recommendations in the long term.

 

Sources:

National Institutes of Health: History of Congressional Appropriations, Fiscal Years 2000-2016

Financial Conflicts of Interest and Reporting Bias Regarding the Association between Sugar-Sweetened Beverages and Weight Gain

A Short History of Nutritional Science: Part 1 (1785–1885)

A short history of nutritional science: part 2 (1885-1912)

A short history of nutritional science: part 3 (1912-1944)

A Short History of Nutritional Science: Part 4 (1945–1985)

Gender, racial, and ethnic disclosure in the NIH K-Award funded diabetes and obesity clinical trials

Metabolizable energy of macronutrients

Discrepancy between the Atwater factor predicted and empirically measured energy values of almonds in human diets

Adaptive thermogenesis in humans

Indirect calorimetry: methodological and interpretative problems

Validity of the assessment of dietary intake: problems of misreporting

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