A recently published study presents a surprising claim: consuming more than two servings of red meat each week dramatically increases the risk of type 2 diabetes.

In this article, we’ll delve into the details of the study to examine how its authors came to this conclusion and why their methods and results are fundamentally flawed.

After debunking the study, we will explore a more reasonable perspective on how red meat can be part of a bone-healthy diet.

New Study Raises Red Flags

Unfortunately, the publication of a study does not guarantee its quality. Despite the standard of peer-review, studies that produce flashy headlines sometimes turn out to be built on shaky ground– and bad science.

A study recently published in The American Journal of Clinical Nutrition falls into this infamous category. The authors claim to have identified an association between red meat consumption and an increased risk of type 2 diabetes.¹

Right away, this conclusion should give us pause. Type 2 diabetes is a metabolic disorder caused by the body’s resistance to insulin, a hormone that allows the body to use glucose to produce energy. It results in elevated blood sugar levels that can cause widespread health problems, including heart disease, vision loss, and kidney disease.

When considering risks for diabetes, we typically focus on foods containing high levels of sugar and simple carbohydrates that are quickly broken down into glucose. Meat does not contain sugar or carbohydrates.

Immediately, it seems that something is missing from this study. On closer inspection, there are a number of resounding issues that undermine the supposed conclusions of the paper.

Synopsis

A new study claims it found an association between type 2 diabetes and red meat consumption. This conclusion is immediately suspect, given that type 2 diabetes is a metabolic disorder concerning how the body processes glucose. Meat doesn't contain glucose or the carbohydrates that are broken down into sugars.

Prospective Cohort Studies Can’t Claim Causation

A prospective cohort study, like the one we're analyzing, analyzes a bank of data previously collected from a large population. The study that collected the data is called an epidemiological study, or a population study. These types of studies gather a large amount of information about each participant at baseline and then follow up with the participants over a certain number of years.

Then, other researchers take that data and look for patterns and associations. The prospective cohort study we're analyzing used data from three population studies:

• The Nurses’ Health Study I (NHS I), started in 1980, including 84,315 women
• The Health Professionals Follow Up Study (HPFS), started in 1986, including 42,163 men
• The Nurses’ Health Study II (NHS II), started in 1991, including 90,217 women

In total, this encompasses 216,695 participants, all based in the US, and predominantly women. Looking at such a large number of participants' data allows researchers to identify trends and patterns.

However, this approach does not enable researchers to draw conclusions about the causes of any observed trends or patterns. In fact, these large population studies were intended to be a way for research to develop hypotheses, not draw conclusions.

To draw a conclusion about causation requires a randomized controlled trial, designed and executed by the researchers to test a hypothesis.

The authors of this prospective cohort study did not conduct such a trial. Therefore they cannot draw conclusions about causation. However, that hasn't stopped them from doing so. Shamefully, their peer reviewers and publication did not intervene.

Even when prospective cohort studies provide a measured analysis of trends, the media often presents associations from these studies uncritically, misrepresenting the science. The attention that these headlines bring encourages researchers to make unjustifiable claims based on population studies.

As you can see, from the very beginning, no definitive conclusion was possible for a study of this kind.

Synopsis

This study was based on large population studies that gathered data about participants. This data is useful for analyzing trends and associations, but cannot be used to draw conclusions about causation. However, these researchers have published unsupportable conclusions about the link between red meat and type 2 diabetes.

Food Frequency Questionnaire And Omissions

The population studies that provided the data for this prospective cohort study gathered information about their participants' diets using the Food Frequency Questionnaire (FFQ). This raises another enormous red flag about the legitimacy of the study.

The FFQ is inherently unreliable because it relies on participants to self-report their diets. Furthermore, it asks them to report how often they've eaten certain types of foods over the past year. This method might offer a general overview of someone’s eating habits , but it's unlikely that anyone could accurately recall everything they've eaten over the past year.

In addition to this baseline problem with using data from the FFQ, in 1980 it wasn’t even the same FFQ we use now. The questionnaire has changed as our understanding of nutrition and official serving sizes changed.

The study authors reported that they “adjusted” for those changes. This alteration of the data is questionable, especially because their adjustments dramatically increased the association between red meat consumption and type 2 diabetes.

However, perhaps the most glaring problem is the exclusion of relevant dietary data. The study excluded the FFQ results on participants' sugar and grain consumption. Even with all of its faults, if we were going to look at the relationship between FFQ answers and type 2 diabetes, the first food types we would look at are sugar and grains. These are the two types of food that we would expect to have the biggest impact on diabetes risk.

We cannot assess associations between diet and type 2 diabetes risk without looking at the foods that we already know are most closely related to the development of type 2 diabetes.

This glaring omission alone undermines the claims of the study and renders the paper useless.

Synopsis

The study is based on data from Food Frequency Questionnaires, which are notoriously inaccurate due to self-reporting and the limitations of human memory. Additionally, the FFQ has changed over the years, and the study authors adjusted the data for those changes in ways that supported their hypothesis. The study also excluded the two food types that are most likely to be related to type 2 diabetes, which undermines their results.

The Healthy User Bias

The data from the population studies highlights one of the major issues with prospective cohort studies: healthy user bias.

People who make one unhealthy choice, such as eating a highly unbalanced diet, frequently engage in other unhealthy behaviors, such as leading a sedentary lifestyle, smoking, excessive drinking, or others.

Conversely, people who make one intentional healthy choice, such as eating red meat in moderation, are likely to make other healthy choices as well.

This fact makes it very difficult to separate these linked choices from each other.

Imagine you're trying to determine if wearing a particular brand of sneakers, let's call them Brand X, affects running speed. At the local park, you observe that many of those wearing Brand X seem to run slower.

Upon closer inspection, you notice that many wearing Brand X appear to be out of shape, frequently stopping for breaks, and breathing heavily. In contrast, a majority of those wearing another brand, Brand Y, seem fitter, running continuously and with ease.

If you only compared the running speeds based on the shoes they wore and concluded that Brand X wearers are slower, you'd miss the bigger picture. The slower speed may not be due to the shoes but rather the overall fitness level of the individuals choosing each brand.

This is similar to the study on red meat: attributing an outcome to one factor without considering other significant variables can be misleading.

Synopsis

Healthy user bias is a problem in population studies arising from the difficulty of isolating one healthy behavior from another in participants. Healthy people tend to make many different healthy choices, and unhealthy people make many unhealthy choices. It's nearly impossible to credit any one behavior as the cause of a particular outcome.

The Facts On Red Meat

Red meat has become a subject of intense debate, with proponents and opponents pushing their views towards increasingly entrenched extremes. Outliers on both ends are financially invested in their position, and unfortunately, it seems that this is true of one of the authors of this study.

The nonprofit organization Food And Behavior Research issued a report on study author Dir. Walter Willett. Dr. Willett has published more than 200 papers based on large population studies, all proposing that red meat is bad for your health, or that a plant-based diet is superior. He rarely, if ever, discloses conflicts of interest, even though institutions he worked for accepted funding from groups that promote vegetarian and vegan products.²

There is no shortage of sources attempting to sell you on the idea that only a vegan diet is healthy. Other sources will insist, bizarrely, that people should eat nothing but meat!

Common sense and historical perspective suggest that, while extreme diets are feasible, people typically achieve better health by consuming a variety of foods in moderation.

This includes red meat. Animal products contain important nutrients. If you enjoy eating meat, you absolutely can, and your health can benefit from it. Here are some of the vitamins and nutrients found in beef:

• Vitamin B12 – Animal-derived foods are an excellent dietary source of Vitamin B12, an essential nutrient for blood formation, brain function, and the nervous system.
• Zinc – Beef is rich in zinc, a mineral that plays a critical role in the immune system. It can accelerate wound healing, aid sleep, and provide antioxidant protection.
• Selenium – Selenium protects your bones, balances your thyroid, and boosts your immune system.
• Iron – The iron in meat is highly bioavailable, making animal-based foods an efficient source of a mineral responsible for oxygen transport, DNA synthesis, and energy production.
• Vitamin B3 – Also known as niacin, this vitamin supports heart health and releases energy from carbohydrates, fats, and proteins.
• Vitamin B6 – Vitamin B6 supports blood formation and energy metabolism.

Choose unprocessed and lean meats, and remember that moderation is key. Eating too much of any one food will have negative consequences. Variety is essential for getting all of the nutrients you need to stay healthy and strong.

The Save Institute's 80/20 pH-balanced diet provides an easy visual tool for balancing your diet, meal by meal. Instead of weighing, measuring, and counting, you simply look at the balance of acidifying and alkalizing foods on your plate. It's one of many simple strategies employed by the Osteoporosis Reversal Program.

What This Means To You

Don’t take every headline at face value, particularly when they make significant claims about common foods. You can include red meat in your bone-healthy diet… or not! That’s the beauty of a dietary plan built around inclusion, enjoyment, and good health.

The Save Institute even created a special cookbook and meal planner to help you unlock the joys of a bone-healthy diet. Bone Appétit isn’t a cookbook that restricts your diet, it’s one that expands it! You’ll be amazed by how easy and fun these recipes are to make, and how delicious and satisfying the dishes are.

Choosing a healthy lifestyle should be both rewarding and enjoyable. After all, staying healthy and having strong bones is about living more of the independent and robust life we want to live.

References

¹ https://ajcn.nutrition.org/article/S0002-9165(23)66119-2/fulltext

² https://www.fabresearch.org/viewItem.php?id=12377#:~:text=Conclusion%3A,of%20the%20vegetarian%2Fvegan%20diet