World Health Organization recently advised people who avoid the use of artificial sweeteners to lose weight or to reduce the risk of health problems such as heart disease and diabetes. This was based on the agency’s review of available research on artificial sweeteners to date.
Unfortunately, people cannot trust those findings. That’s because existing studies on artificial sweeteners are plagued with methodological problems. Even the WHO knows this, as it ultimately described its certainty on the existing evidence as “low”. It may be true that artificial sweeteners don’t help you lose weight, but we really don’t know for sure.
This is not a problem reserved for artificial sweeteners alone. The state of nutrition research is poor, with issues plaguing much of the research on dietary and lifestyle claims around things like coffee, came, dark chocolate, fad dietshe amount of exercise – You say it. This partly explains other recent changes around whether moderate alcohol consumption is good for you: A recent review found that the research methods used in many previous studies on the benefits of alcohol consumption are flawed.
Diet and exercise are clearly important parts of a healthy lifestyle, but it is challenging to accurately estimate the specific effect of making any one change based on how most nutrition and lifestyle research is currently conducted. .
Take the case of artificial sweeteners. Randomized studies, in which people are randomly assigned to one treatment or another to ensure that other factors do not interfere, are considered the gold standard. But randomized trials of sweeteners are often small and brief, making it difficult to draw reliable conclusions about their long-term effects. The way sweeteners are studied in trials is also often very different from the way people use them in the real world. For example, some trials had participants consume artificial sweeteners in addition to their typical diets rather than replace some real sugars in their diets with artificial sweeteners, the intervention researchers are most interested in, often for only a few months.
Many studies, both of sweeteners and of other dietary and lifestyle behaviors, ‌‌are not randomized. For example, several sweetener studies simply look at people over time, tracking their use of sweeteners and their health outcomes, such as rates of diabetes or heart attacks. These observational studies, as they are called, have their own problems, many of which are so serious that they are hard to take seriously.
The most significant of these problems is well known: correlation does not imply causation. If people who consume more sweeteners are more likely to have type 2 diabetes, did the sweeteners cause the diabetes? Or are people who use more sweeteners also more likely to get diabetes due to other aspects of their diet or health? Investigators can try to account for obvious differences between groups, but it is impossible to account for everything.
If the typical randomized trials and observational studies of dietary and lifestyle research present so many challenges, how can we get reliable answers?
Reliability still starts with randomization. Randomization is key to establishing cause and effect; It helps to make sure that two groups are similar before considering what happens to people who consume different amounts of artificial sweeteners, red wine, or dark chocolate.
In randomized trials, researchers intentionally randomize people to one group or another, but it is difficult to do trials like this that are large and long enough to be useful. (Would you let a scientist tell you what to eat every day for the next decade?)
But there are other ways to credibly study the cause-and-effect relationships of dietary and lifestyle behaviors: by identifying situations in which people are exposed to those behaviors not by the random hands of researchers but by accident. So-called natural experiments, commonly used in economics, are extraordinarily powerful but vastly underused in medical research.
Consider, for example, that in 1953, Great Britain ended the rationing of sugar and sweets that had been in place since World War II. Interested in studying The Effect of Early Childhood Sugar Intake Economists Paul Gertler and Tadeja Gracner noted that children born in the years immediately before rationing ended spent their infancy and childhood with limited sugar in their diets due to rationing.
Children born a few years later had infant diets higher in sugar. When these children became adults, their sugar intake remained higher than that of similar children born during the sugar rationing.
Measuring the health of these two groups more than 50 years later — far longer than any clinical trial could reasonably follow people — the economists found that extra sugar intake led to higher rates of diabetes, elevated cholesterol, arthritis and measures of chronic inflammation.
Another way that people can be accidentally randomly assigned to health behaviors is through their genes. Consider the much-studied question of whether alcohol, in moderation, is good or bad for your health. In a study of more than 500,000 Chinese adults, researchers took advantage of genetic variations that cause some random adults to enzymatically process alcohol differently, leading to unpleasant effects. symptoms like redness. Because such people tend to drink less alcohol, researchers can study the causal relationship between alcohol use and health outcomes by examining similar people with and without specific genetic variants, an approach called Mendelian randomization.
While the jury is still out, some research wearing these methods suggests that even small amounts of alcohol can lead to increased risks of cardiovascular disease and cancer.
Here are some untested ideas in nutrition research that, using methods found more often in economics than medicine, could take advantage of naturally occurring randomization.
Returning to the question of how sugar intake in early childhood affects health, let’s say that researchers could trace families with three children in which the middle child was diagnosed with diabetes. The eldest child in these families may have gone several years without special attention to sugar intake in the home, until the middle sibling was diagnosed with diabetes. Meanwhile, the youngest child in those families might have grown up in a particularly sugar-conscious household.
One could study these families and compare the long-term health outcomes between the first and third siblings who happened to be exposed to different sugary environments. And if they were concerned (as we would be) that the oldest and youngest children in families might differ in other ways besides their sugar exposure, they could explain it by comparing first and third siblings in similar families where the middle child did not have diabetes. This is not a perfect study, as siblings do not grow up in identical environments, but it is better than simple observational studies because it takes advantage of the random nature of sibling birth order.
We understand why so many simple observational studies are published; The impacts of diet are difficult to study by traditional means in medical research, and there is a great desire to better understand the health effects of the foods we eat.
But filling the research gap with studies that do little to help us understand the cause-and-effect relationships of our real-life dietary choices does little to advance understanding; in fact, it sows confusion.
Medical researchers professionally pressured to publish or perish are often incentivized to publish simple observational studies that lack empirical rigor. Medical journals, responding to public interest in information on nutrition, in turn encourage this research despite knowing its important limitations. Media coverage can simply add to the confusion.
The now decades old credibility revolution in economics promoted the use of high-quality, often creative, research designs in empirical economic work, so much so that in 2021 a group of economists received an award Nobel for his work with natural experiments.
Although medical researchers are increasingly taking advantage of natural experiments, thanks in part to the vast increase in digital data in recent years, these methods remain poorly understood and unused, especially with regard to diet. This important investigation needs a credibility revolution of its own.
