In this webinar, Dr. Richard Feinman and Bob Kaplan discuss critical issues in medical and nutritional research, focusing on flaws in scientific methodology, particularly in nutrition science. Dr. Feinman critiques the over-reliance on statistical significance in medical studies, arguing that statistical manipulations often lead to misleading conclusions rather than uncovering objective truth. He highlights how small sample sizes, conflicts of interest, and retrospective adjustments to hypotheses frequently distort findings.

A major focus of the discussion is the controversy surrounding dietary guidelines, particularly the demonization of red meat and the promotion of high-carbohydrate diets. Any claims linking red meat to diabetes lack scientific rigor and are based on weak epidemiological evidence. Studies like the Harvard-led research on red meat and diabetes risk were based on food frequency questionnaires and statistical adjustments that mask real-world implications.

Feinman also emphasizes the importance of considering absolute risk over relative risk when interpreting study results. He cites historical examples, such as the association between smoking and lung cancer, to illustrate the distinction between strong and weak epidemiological findings. Ultimately, he advocates for a return to biochemical principles in nutrition science and calls for better experimental design to uncover true causal relationships rather than relying on flawed statistical associations.

Professor Feinman is the former co-editor-in-chief of the journal Nutrition & Metabolism, as well as a professor of cell biology at SUNY Downstate Health Sciences University in New York. Dr. Feinman has long been a critic of the current state of medical nutrition and the associated literature.