Nutrition research plays an integral role in how we understand the impacts of various foods and/or behaviors on our health. In an ideal setting, researchers conduct experiments with the hope to draw conclusions based on direct interventions. These Randomized Controlled Trials (RCTs) are considered the “gold standard” of scientific research. In RCTs, participants are randomly placed into different groups. One group receives the hypothesized treatment (for example, a diet low in “processed” foods) and the other receives some kind of control intervention (for example, a diet high in “processed” foods). RCTs are usually performed in a controlled setting (such as in a lab) where external influences are limited. Though ideal, RCTs are too expensive and impractical to conduct long-term (plus, we can’t expect study participants to fully follow diet rules when we know that success rates with dieting are insanely low).
Quick note: Christy Harrison is a fellow dietitian who covers these facts and more in her book, Anti Diet: Reclaim Your Time, Money, Well-Being, and Happiness Through Intuitive Eating. I credit Christy to my own education on the subjects of detangling the confusion around nutrition research!
Why Is Nutrition Research Messy?
Because of the limitations with RCTs, most food- and diet-related research is observational. The goal of observational research is to observe patterns in behaviors over time (such as the impact of eating X amount of added sugar per day). From here, researchers can draw associations between levels of intake with various health outcomes, most notably the development of heart disease, diabetes, etc. When conducting observational studies, researchers often look back in time, using medical records, participant self-report, and sometimes even blood samples, to collect information. Observational studies are super interesting as they help to identify any potential associations between our behaviors and our health. Though helpful, there are four major limitations with observational research:
The first is time. For practical reasons, an observational period is usually short: from a couple of weeks to a few years. Short studies make it difficult to draw statistically significant conclusions. In other words, were the associations true or did they happen by chance? The second limitation is relying on study participants to self-report their food intake. Can you remember what you ate on a Tuesday 3 months ago? Drawing conclusions based on self-report is very unreliable! The third and most problematic limitation is the potential for confounding variables.
Confounding variables are anything that could impact what is observed in a study. Examples include alcohol consumption and cigarette smoking. While researchers often use statistical methods to try to control for these confounding variables (for example, separating the participants who smoke versus those who do not smoke), it’s impossible to control for everything. Other confounding variables that can have a huge impact on health outcomes include socioeconomic status, race, and even degree of disordered eating.
Last, we should also consider how various studies define their variables. In regards to added sugar, Christy Harrison says, “in many studies, participants grouped as consuming the “lowest [amount of] added sugar”… consume an amount equivalent to eating some sweetened foods at every meal and every snack, and having dessert every day.” This is wildly different from how my fellow perfectionists often translate the research: “According to the research, I should “AVOID” or “ELIMINATE” foods with added sugar!” Nope, dancers, even the research shows us that it’s not all-or-nothing!
The impact of disordered eating on nutrition research
Since the definition of “disordered eating” is so grey in a culture that normalizes food restrictions and praises over-exercising, it’s hard to define what “normal eating” even means. As I mention in this article, it took me years before I knew that my “clean eating lifestyle” was actually disordered! Interestingly, disordered eating behaviors and weight cycling (a common result of restrictive dieting) have been associated with negative health outcomes, including diabetes. So, it’s nearly impossible to draw conclusions between “eating foods high in X” with specific health outcomes when we know that disordered eating could impede results. For example, when looking at sugar consumption studies, any potential negative health outcomes could arguably be associated with excessive intakes of sugar during a “binge” cycle. And if that’s the case, then it’s safe to say that repairing one’s relationship with food might be a better takeaway.
How should we use nutrition research?
Systematic reviews and meta-analyses provide helpful tools in understanding the impact of various behaviors on health. These studies examine larger bodies of evidence in comparison to only looking at one study.
But even with these studies, results should be taken with a grain of salt since outcomes are oftentimes inconclusive. In regards to heart health, a 2018 review concluded, “to date, a lot of results obtained have produced few conclusions and sometimes, even contradictions.”
We need to remember that association doesn’t equate to causation. Any manipulation of the macronutrients is likely to result in some form of dieting/restriction or disordered eating. Eating “processed” foods or foods that contain saturated fat, added sugar, and/or high fructose corn syrup will not be the sole contributor to your overall health.
Nutrition research has played a major role in topics around fat, sugar, food addiction, and processed foods. Check out these articles to dive more into these topics:
- Is saturated fat bad for me?
- Is sugar bad for me?
- Is clean eating healthy?
- Are processed foods unhealthy?
- Can you be addicted to food (or sugar?)