Educationwhy is research so hard to read?

why is nutrition so complicated

Why research is so tricky!

This article is not based on any one particular study, it is more so a commentary and glance at the reality of nutrition research, how it’s conducted and why it is difficult to draw conclusions from it. Nutrition has long been a misunderstood topic and has long been at the centre of public debate & disagreement, if you have a particular belief about food, you will find a paper to back it up, I almost guarantee it. This is one of the reasons as to why there is much confusion and debate over topics relating to nutrition, and one of the main reasons that we decided to put research bites together, as it is incredibly easy to misinterpret nutritional research and draw inappropriate conclusions. So why is this the case? Let’s take a look.


Not as clear cut as it may seem..

It is important to note that a lot of nutritional research is based on models designed for the pharmaceutical industry, think about it, lot’s of research has to compare a compound, drug or food in question against a placebo (a benign substance with no therapeutic value). This is easy to do with drugs such as chemotherapy agents or certain antibiotics, as you don’t encounter them in your day to day life, and almost certainly don’t ingest them, compare this to foods, imagine we are making a study looking at the effects of eating vegetables on eyesight, if we try and do this study, how do we find a placebo group? A group of individuals who never have or rarely eat vegetables – best of luck with that. This strange example is to point out the fact that with nutrition, it’s very difficult to compare a group who has been exposed to a compound, to those who have not, as we eat foods and recipes – complex matrixes of macronutrients, micronutrients, antioxidants etc. – with this in mind, there is an increased reliance on correlation studies, observational studies and mechanistic data to all come together to paint a picture and build the case for something like vegetable intake and eyesight, as we cannot rely on one paper alone.


This inability to rely on the results of a single paper is frustrating, and it can be tempting to simply say you read your research and to draw a conclusion, especially if you have an a priori hypothesis on the topic that you are looking to validate, but here’s the thing – everything is correlated, think about that for a second and then think about why it might not be ideal to simply take a piece of research correlating a nutrient and an outcome at face value. If we peel back further into this, if we are looking at a correlation, we want to know if it is a true relationship or if it simply an observation (more toys are sold around Christmas when the flu rates are highest, does this mean that toys cause the flu, or is it an observation?). One way to assess this is to find and allow for confounding factors, things that will have an effect on the result outside of the study itself, sometimes a study design might allow for this by removing people with vulnerable immune systems from studies such as the flu example, as they are already more likely to get sick already. The importance of how a paper is put together in terms of the methods is vital in this context, as this is where much of the nuance arises.


An example..

A good example is some papers look at carbohydrate mouth rinsing in exercise to see if it improves performance, there is one particular paper that conducted such an inquiry, but all the subjects were fasted going into the trial, it goes without saying that the group receiving any form of nutritional intervention will perform better, I heard a researcher discuss this paper years ago claiming that if they licked a postage stamp instead of mouth rinsing, that it would have had still been better than placebo – this is anecdotal and based off of a memory, but you get my point.


At research bites, we want to peel through these layers, which is why we intend to explain how a study was done, what was looked at, the results and most importantly, we want to put every piece of research into context and give you a bit sized takeaway point from it, hence the name.


Looking forward to bringing science to your fingertips.

Evan Lynch


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