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Wide release date: December 2, 2025.

Topics Discussed:

* Epidemiology basics: Studies disease influences using observational designs like case-control and prospective cohorts, plus trials, to identify patterns and test hypotheses.

* Hierarchy of evidence critique: Rejects rigid pyramids favoring RCTs, as all studies can be biased; advocates triangulation integrating varied data types for robust conclusions.

* RCT strengths & weaknesses: Randomization balances confounders, but issues like poor blinding, attrition, or subversion can undermine results; large samples may yield spurious precision if biased.

* Confounding & reverse causation: Examples include yellow fingers and lung cancer (both from smoking) or early atherosclerosis inflating CRP-disease links; hard to fully control statistically.

* Nutrition epidemiology pitfalls: Observational studies often overstate benefits (e.g., vitamin E for heart disease), leading to failed trials; incentives favor new findings over revisiting errors.

* Mendelian randomization: Uses genetic variants as proxies for exposures (e.g., ALDH2 for alcohol metabolism) to mimic randomization; reveals no heart benefits from alcohol, unlike observational data.

* Negative controls for validation: Tests implausible outcomes (e.g., smoking and murder) or exposures (e.g., paternal smoking in pregnancy) to check for confounding artifacts.

* Evidence triangulation: Combines diverse studies with different biases (e.g., cross-cultural comparisons) for causality; applied to dismiss HDL-raising drugs despite initial promise.

Practical Takeaways:

* Scrutinize health claims by checking for negative controls or variety in evidence sources to avoid mistaking correlation for causation.

* For personal decisions like alcohol intake, consider genetic studies showing risks at all levels, and aim for moderation or abstinence based on overall evidence.

* When evaluating supplements or diets, prioritize trials over observational data, and question media hype that ignores confounding factors.

* Use symmetrical analysis in reading studies: Treat exposures and confounders equally to assess true effects.

About the guest: Dr. George Davey Smith, MD, DSc is a professor of clinical epidemiology at the University of Bristol and director of the MRC Integrative Epidemiology Unit, where he focuses on causal inference in health.

Reference Paper:

* Paper: Evidence triangulation in health research

Related Episode:

* M&M 212: How Science Really Works: Meta-Research, Publishing, Reproducibility, Peer Review, Funding | John Ioannidis

*Not medical advice.

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* Episode transcript below.

Episode Chapters:00:00:00 Intro

00:06:01 Hierarchy of Evidence

00:12:54 Sample Size & Precision

00:18:41 Vitamin E Supplements

00:25:05 Nutrition Epidemiology Pitfalls

00:32:01 Preclinical vs Clinical

00:38:04 Negative Controls

00:45:16 Negative Control Exposures

00:52:21 Alcohol Consumption Effects

00:59:00 Mendelian Randomization Example

01:05:16 MR Limitations & Pleiotropy

01:11:20 HDL Cholesterol Myths

01:18:21 Evidence Triangulation

01:23:36 Final Thoughts & Resources

Full AI-generated transcript below. Beware of typos & mistranslations!