#393 ‒ AMA #85: A guide to medications and supplements: determining what to take, what to skip, and how to know if they're working for you

May 25, 2026 Episode Page ↗
Overview

In this AMA, Peter Attia discusses critically evaluating medications and supplements. He emphasizes defining problems with actionable metrics, classifying interventions by purpose, and adjusting evidence thresholds and risk tolerance accordingly to avoid common pitfalls.

At a Glance
9 Insights
13m 6s Duration

Deep Dive Analysis

1. Prioritize Problem Over Intervention

Before considering any medication or supplement, define the specific problem tightly with actionable metrics, thresholds, and timelines. This prevents vague goals from leading to ineffective or harmful interventions.

2. Define Problems Actionably

Reframe vague health goals like ‘more energy’ into measurable metrics (e.g., ApoB 130 to <60 in 6 months, sleep latency 60 mins to <10 mins in 2 months). This allows for objective measurement of success or failure.

3. Assess Counterfactual Consequences

Before starting an intervention, ask what happens if you do nothing; does the problem meaningfully increase risk, reduce quality of life, or create downstream consequences? This helps distinguish real problems from those that merely feel actionable, preventing false positives.

4. Classify Intervention’s Purpose

Categorize the intervention’s ‘job’ into disease treatment, symptom relief, risk reduction, or optimization, as each requires different evidence standards and risk tolerance. Applying the wrong standard can lead to poor decisions.

5. Approach Optimization with Skepticism

For ‘optimization’ interventions, maintain high skepticism, especially regarding safety, as these often start from a healthy baseline with small expected effects and mechanistic claims. This reduces the risk of self-deception due to the lack of objective measurement.

6. Longevity Interventions are Optimization

Understand that many ’longevity interventions’ are often speculative optimizations masquerading as risk reductions, borrowing language of prevention but lacking strong evidence. This distinction should increase your skepticism and lower your risk tolerance.

7. Demand High Evidence for Disease

For disease treatment, require strong evidence like hard outcome trials or well-validated surrogate endpoints, and be willing to accept more downside. This is because the underlying problem is serious, and the counterfactual of doing nothing is strong.

8. Require High Evidence for Risk

For interventions aimed at risk reduction, demand high evidence, typically hard outcomes or very validated surrogate markers (like ApoB). This is crucial because you are treating something a person cannot feel.

9. Prioritize Lived Benefit for Symptoms

When seeking symptom relief, prioritize whether you actually feel or function better, and be willing to tolerate placebo risk if the downside is low. However, remain aware of the placebo effect and unknown safety factors.