There’s a reason some diets are called ‘fad diets.’ They rise quickly on a wave of popularity, sure. And some people have enough success with them that they become advocates to spread the word and increase the popularity even more. But before that initial wave hits, there is usually some sort of research, study, or datapoint shared that reveals a new dietary secret of some kind.
But we all know when something is too good to be true, right?
We live with a constant stream of information in all aspects of our lives. That includes information about nutrition. Here are two simple questions to illustrate the deeper point: Is butter healthy? Are fats good or bad?
The fact is, ‘experts’ disagree on even very basic dietary principles, and oftentimes we are left to figure things out for ourselves (and our families). We say ‘experts’ in quotation marks because nutritional scientists often disagree, but there are also many self-proclaimed experts on social media who spread dangerous, unfounded advice (alongside beach-body photos that clearly say “listen to me, and you can look like this”).
All of this means we — as parents and adults in general — must be able to distinguish reliable research from weak studies that are riding on a sensational headline. Fortunately, there are a few simple, key features you should look for in any dietary data.
Look for the statistic, and apply a few basic principles to ask what it really tells you.
If you remember nothing else from this piece, remind yourself whenever you see data that correlation does NOT imply causation. Two things trending in the same direction can have different root causes. For example, data shows us that summer months see an increase in ice cream sales and bicycle accidents. But you know it would be silly to imply that eating ice cream causes more accidents.
Not all example are so simple and obvious. Here’s one that’s a little closer to health news you might see online: A new study finds that people who ate fish were less likely to develop Alzheimer’s Disease. So…does that mean eating fish prevents the disease?
It doesn’t. The study merely found two observations. It never said the word “prevents,” but your brain naturally leaps to that conclusion. There are many more factors to consider. Maybe there are additional patterns or lifestyle choices shared by people who just happen to also eat fish. Maybe they spend more time at the ocean, with natural air and sunshine. Or perhaps they are more likely to exercise regularly. Any number of factors could all be linked back to the observation that this group has a lower likelihood of developing a certain disease.
So we must look for the data points and read explicitly what the data tells us. We can’t fill in the blanks or jump to conclusions ourselves. In many cases, a study actually can’t tell the scientist the answer they truly want to know, so they are looking for other signs or indicators called “surrogate endpoints” or surrogate markers to make assumptions about an outcome. An easy example of this is looking at risk of heart attack. It’s impossible to predict real rates of heart attacks, but scientists can look at related factors — like high or low blood pressure — to make inferences about the larger outcomes.
Once you have find the actual data, look at the study design.
Scientists use data to look for new insights. But the scientific method requires multiple rounds of testing and results to validate even the simplest hypothesis. So first ask yourself: Was this a single study or the result of multiple tests?
In addition to the number of studies that support the claim, it’s also helpful to look at the sample size (e.g., how many participants were observed). Generally, large sample sizes are crucial to provide reliable results that support big conclusions. Think about it this way: If we told you that we know a guy, Gerry, who lost 25 pounds in 3 weeks by only eating Weetabix and walking on the treadmill, you might be skeptical. It would be hard to assume that Gerry’s secret would work for everyone.
But we do that all the time. We are used to using anecdotes and personal testimonies to justify grand conclusions about dieting. We have something called “confirmation bias,” which means we will more easily believe something we want to believe.
A final question to ask about the study design is whether or not it was performed on animals or humans. Obviously, any study that does not use humans will provide results that we should question and explore further.
Once you understand the study itself, look at who conducted or funded it.
Data science is not a hard science. It is easy to manipulate numbers and get them to tell a certain story (remember confirmation bias?). While we want to believe that scientists are all seeking truth to help the greater good, there are many studies that are commissioned and paid for by companies who want to find a datapoint that will influence their customers.
Look at this headline: Children and adolescents who eat pasta have better overall diet quality, new research shows.
Wow! Does this mean we should go out and buy pasta for our kids? That’s what the study is hoping will happen; it was paid for by the National Pasta Association.
This happens all the time. A Sugar Association funded a study with Duke University researchers. What did they find? Numerous adverse health effects from the consumption of sucralose (e.g., artificial sweeteners like Splenda).
It can be sneakier, too. A well-known fast-food chain funds a study showing that physical activity is critical for maintaining a healthy weight. This may be true, but by emphasizing exercise they are also diverting attention away from nutrition, and the negative impacts of their food.
Research is an investigation. So our knowledge is always evolving.
Hopefully these three simple tips can help you think just a little more critically as you read news studies, online blogs, and even food labels. And ideally, even questioning the study for a brief minute will help you ask some important questions about your own health.
Our bodies all react differently to our dietary choices. Let’s go back to the simple questions we started with: Is butter healthy? Are fats good or bad? Of course, it depends. It is the job of scientists to question and analyse everything they can to find different opinions and points of view. Good scientists find a primary conclusion and then do everything they can to prove the opposite to be true as well. Everything adds to the body of evidence so that more studies (and increasingly large sample sizes) can begin to validate hypotheses. It would be ideal to discover direct causation between two factors (like the example of fish and Alzheimer’s disease), but that process is immensely difficult.
What is less difficult is spotting the scams. Magic pills or cheat-superfoods are fake, or using a small subset of unfounded data. Most highly restrictive diets should be questioned, as they increase the risk of cutting out key nutrients your body needs. The world is a tough enough place; the last thing we need is more fear-mongering and food shaming about our diets.
Unless allergies restrict certain foods from your diet, there are no reasons to cut out entire food groups or macro nutrients like carbohydrates or fat. Good nutrition is about balance and paying attention to your own unique body. Whole foods, especially fruits and vegetables, make a great foundation, but even sugars and saturated fats are okay in moderation. Physical activity helps to ensure the fuel we are putting into our bodies is really helping us perform at our best.
If you are considering making dietary decisions, talk to your doctor or seek help from experienced nutritionists. As this article points out, the first step is thinking critically and asking questions. Don’t leap to any conclusions.