<p class="p1"><span class="s1"><a href="https://peterattiamd.com/davidallison/?utm_source=podcast-feed&utm_medium=referral&utm_campaign=220228-pod-davidallison&utm_content=220228-pod-davidallison-podfeed"> View the Show Notes Page for This Episode</a></span></p> <p class="p1"><span class="s1"><a href="https://peterattiamd.com/subscribe/?utm_source=podcast-feed&utm_medium=referral&utm_campaign=220228-pod-davidallison&utm_content=220228-pod-davidallison-podfeed"> Become a Member to Receive Exclusive Content</a></span></p> <p class="p2"><strong>Episode Description:</strong></p> <p class="p2">David Allison is an award-winning scientific writer who has been at the forefront of obesity research for the last 20 years. Currently the Dean of the Indiana University School of Public Health, he has also authored many publications on statistical and research methodology and how to improve research rigor and integrity. David's focus on evidence and data brings forth an interesting discussion of what we know (and don't know) about the science of obesity. He provides an insightful and unemotional explanation of the potential impact of nutritional epidemiology in public health while also explaining its many pitfalls and limitations. He offers his take on the path forward in addressing the obesity epidemic, and he closes with a lucid explanation for the evident lack of credibility in science and the steps we can take to change that. </p> <p class="p2"><strong>We discuss:</strong></p> <ul class="ul1"> <li class="li2">David's background, interest in obesity, and focus on evidence [5:00];</li> <li class="li2">The moment when the obesity crisis was recognized, and the sloppy science that ensued [13:00];</li> <li class="li2">What twins studies tell us about the genetics of obesity [20:30];</li> <li class="li2">How doctors and scientists have historically approached obesity treatment [23:45];</li> <li class="li2">Do surgical procedures for obesity prolong life? [32:00];</li> <li class="li2">The 'Obesity Paradox' [36:00];</li> <li class="li2">Interpreting BMI and mortality data and considering confounders [43:15];</li> <li class="li2">How body composition and ethnicity factor into consideration of BMI data [50:30];</li> <li class="li2">Superior tools for measuring obesity at the individual level [57:15];</li> <li class="li2">Using BMI data for actionable steps to combat obesity [1:02:00];</li> <li class="li2">Why maintaining weight loss is more challenging than losing weight [1:06:00];</li> <li class="li2">Differing perspectives on the utility of nutritional epidemiology [1:16:30];</li> <li class="li2">A mouse study illustrating the impossibility of fully controlling for confounds in observational studies [1:22:15]; </li> <li class="li2">Limitations of nutritional epidemiology and how it can improve [1:26:30];</li> <li class="li2">Addressing the obesity epidemic—the path forward and obstacles to overcome [1:37:15];</li> <li class="li2">What David believes to be the most promising interventions we could take to address obesity and improve public health [1:47:30];</li> <li class="li2">Reproducibility in science, normative and non-normative errors explained [1:51:30];</li> <li class="li2">Rebuilding trust in science and differentiating between science and advocacy [1:59:00];</li> <li class="li2">More.</li> </ul> <p class="p1"><span class="s1"><a href="https://peterattiamd.com/newsletter/?utm_source=podcast-feed&utm_medium=referral&utm_campaign=220228-pod-davidallison&utm_content=220228-pod-davidallison-podfeed"> Sign Up to Receive Peter's Weekly Newsletter</a></span></p> <p class="p2">Connect With Peter on <a href="https://twitter.com/PeterAttiaMD"><span class="s3">Twitter</span></a>, <a href="https://www.instagram.com/peterattiamd/"><span class="s3">Instagram</span></a>, <a href="https://www.facebook.com/peterattiamd/"><span class="s3">Facebook</span></a> and <a href="https://www.youtube.com/channel/UC8kGsMa0LygSX9nkBcBH1Sg"><span class="s3">YouTube</span></a></p>
Actionable Insights
1. Distinguish Science & Advocacy
Always be self-aware of whether you are speaking as a scientist (delivering nuanced, hard truth without regard for listener’s feelings) or as an advocate (aiming to change behavior for perceived best interest). This clarity is crucial for maintaining public trust and fostering honest dialogue.
2. Practice Epistemic Humility
When presenting scientific findings, honestly acknowledge all the ways your conclusions might be wrong and suggest further tests. Avoid systematically dismissing competing explanations to genuinely advance knowledge.
3. Prioritize Causal Evidence
When evaluating claims, especially about health interventions, prioritize evidence from randomized controlled trials over observational studies. Recognize that even pristine observational studies can yield associations opposite to causal effects due to confounding.
4. Demand Evidence for Claims
When presented with a claim about a treatment or intervention, reliably ask critical questions: Was there a study? Was it in humans? Was it randomized? Did it measure the actual outcome? Was it long enough? Was the result statistically significant and large enough to matter? Was the dose realistic?
5. Avoid Body Shaming
Refrain from shaming individuals about their body habitus, regardless of the direction (e.g., too thin, too heavy). This is a moral issue of denigrating people, not an empirical one tied to whether it causes weight loss or gain.
6. Utilize Effective Obesity Treatments
For individuals suffering from obesity, consider bariatric surgery and pharmaceutical interventions (like GLP-1 agonists or SGLT2 inhibitors) as they are the most effective, life-saving, and life-changing treatments available, with demonstrated benefits on longevity.
7. Invest in General Education
To improve public health outcomes related to obesity and diabetes, prioritize general education, especially for girls and women. Provocative data suggests this leads to lower BMIs and reduced rates of these conditions.
8. Reduce Wealth Disparities
Consider policies that reduce disparities in wealth and living environments, as studies suggest moving families to less poor neighborhoods can lead to less obesity and diabetes. Confucius’s wisdom highlights concern for disparity, not just absence of wealth.
9. Fund Key Obesity Research Areas
Allocate resources strategically across four areas: providing and studying surgery, providing and studying pharmaceuticals, investing in general education for well-being and reducing disparities, and funding basic research into senescence (e.g., senolytics, microchimerism) related to metabolism.
10. Question Everything Critically
Cultivate a habit of asking ‘Are you sure? How do you know? Where did that come from? What makes you think that’s true?’ to foster critical thinking and avoid taking information at face value.
11. Apply Rigorous Scientific Thinking
Approach all variables, whether in human behavior or physical phenomena, with the same laws of probability, physics, and mathematics. Avoid sloppy thinking that separates behavior from biology or applies different standards to human-related fields.
12. Consider Multiple Angles
When studying complex problems like obesity, examine them from many different angles (e.g., physiology, genetics, anatomy, clinical medicine, behavior, culture, environment). No single factor or perspective is likely to provide a complete solution.
Demand and implement significant reformation in nutritional epidemiology to address issues like confounding, measurement error (especially with food frequency questionnaires), and the overstatement of weak associations. The status quo is unacceptable and requires greater honesty and rigor.
14. Analyze Cluster Trials Correctly
For researchers conducting cluster randomized trials, ensure data analysis correctly accounts for clustering and nesting effects. Failure to do so leads to invalid results and distorted evidence.
15. Embrace Scientific Non-Complacency
Recognize that while science is likely more rigorous than ever, there is no cause for complacency. Continuously strive for improvement, addressing flaws and non-normative errors to elevate the quality and trustworthiness of scientific endeavors.