AMA #76: Peter evaluates longevity drugs, aspirin for CVD, and strategies to improve muscle mass — proven, promising, fuzzy, noise, or nonsense?
Peter Attia
Oct 27, 2025
Mindsip insights from this episode:
Adopt investor mindset to evaluate health information effectively
To evaluate health information effectively, one should have 'strong convictions, loosely held,' a principle borrowed from hedge fund investing that prioritizes changing your mind based on new data.
Prioritize objective data over elegant theories in health claims
A beautiful hypothesis can be 'categorically slayed by ugly facts,' highlighting the importance of prioritizing objective data over elegant theories when evaluating health claims.
Categorize health interventions on five-tier scale
Health interventions can be categorized on a scale from 'Proven' (well-established) to 'Promising,' 'Fuzzy,' 'Noise' (no meaningful results), and 'Nonsense' (disproven by data).
Recognize 'nonsense' claims as actively disproven health assertions
A health claim is categorized as 'nonsense' not due to a lack of evidence, but because available data actively refutes the claim, making it as close to disproven as possible.
Recognize limits of 'proven' in biological claims
Unlike mathematics, nothing in biology is ever truly proven; the 'proven' category simply means a claim is supported by the most high-quality, consistent data available.
Investigate GLP-1s for unique anti-aging effects
A key question for drugs like Ozempic is whether they possess a unique anti-aging effect that improves lifespan beyond their known metabolic health benefits.
Prioritize data over ego to avoid costly investment mistakes
Unlike in science where being wrong may only damage your reputation, in investing, clinging to a bad idea costs real money, which enforces a stricter adherence to data over ego.
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