Making sense of conflicting claims from diet gurus - Dr. Guyenet and Dr. Kratz

The Energy Blueprint Podcast

In this episode, I’m re-releasing an episode with Dr. Stephan Guyenet and Dr. Mario Kratz, two impressively experienced nutrition researchers with a wide range of expertise, about their organization Red Pen Reviews, a non-profit dedicated to publishing unbiased, scientifically accurate reviews for current nutrition books hitting the market.

Today, we focus on two popular but controversial books—Dr. Steven Gundry’s The Plant Paradox and Carnivore Code from Dr. Paul Saladino.

This podcast was originally published on August 27 2022

In this podcast, Dr. Guyenet, Dr. Kratz, and I discuss:

• How difficult it is to parse out accurate versus inaccurate and biased information and the regulated and systematic role of Red Pen Reviews in clearing up the confusion

• The 3 focus areas Dr. Guyenet and Dr. Kratz use to score the books they review and the importance of each

• How the health claims made in Carnivore Code compare to research AND anecdotal reports of people eating the diet…and how the main claim that humans evolved to be carnivores compares to evolutionary evidence

• Possible downsides or even dangers of the carnivore diet and if these caveats are discussed in the book

• The full truth of the claim that elevated LDL is not a cardiovascular concern if a person has excellent metabolic health

• Does a nose-to-tail carnivore diet provide all the nutrients you need each day?

• The Plant Paradox’s primary claim that certain plant lectins lead to approximately 50 diseases…plus, what a lectin actually is!

• What current research tells us about lectins triggering leaky gut, inflammation, and autoimmune disease

• The health status of people who eat large amounts of lectin-rich legumes, tomatoes, and other nightshade vegetables

• Could lectins and other plant foods be stressful BUT ALSO beneficial at the same time?

• Practical ways to evaluate the nutrition information you take in every day so you can more easily consider what’s accurate and what’s likely not