Does reducing saturated fat actually prevent heart attacks?For decades, saturated fat from foods like butter, red meat, cheese, coconut oil, and full-fat dairy has been treated as something to reduce. But the new USDA/HHS dietary guidelines and the inverted food pyramid have made the message a lot less clear.In part two of this series, we look into three of the major randomized controlled trials behind the meta-anlayses: the Minnesota Coronary Experiment, the Sydney Diet Heart Study, and the LA Veterans Trial. Along the way, we also discuss relative risk vs absolute risk, what an ideal saturated-fat trial would look like, why these old trials are so hard to interpret, and how issues like trans fats, adherence, short duration, and missing data complicate the conclusions.Hopefully, there’s also something useful here about how to think through studies, evidence, and nutrition claims when the answer is not as clean as it first seems.This is the second in a series of videos on the subject. Slides:https://www.jsdatascience.com/saturated_fat_meta-analyses_RCTs/Papers:Steen et al. 2025 https://pubmed.ncbi.nlm.nih.gov/41397264/Yamada et al. 2025 https://pubmed.ncbi.nlm.nih.gov/40416032/Frantz et al. 1989 https://pubmed.ncbi.nlm.nih.gov/2643423/Ramsden et al. 2016 https://pubmed.ncbi.nlm.nih.gov/27071971/Woodhill et al. 1978 https://pubmed.ncbi.nlm.nih.gov/727035/Ramsden et al. 2013 https://pubmed.ncbi.nlm.nih.gov/23386268/Dayton et al. 1968 https://pubmed.ncbi.nlm.nih.gov/4176868/Dayton et al. 1969 https://www.ahajournals.org/doi/10.1161/01.cir.40.1s2.ii-1Wilkins et al. 2012 https://pubmed.ncbi.nlm.nih.gov/23117780/

Does cutting saturated fat actually prevent heart attacks?For decades, saturated fat from foods like butter, red meat, cheese, coconut oil, and full-fat dairy has been treated as something to reduce. But the new USDA/HHS dietary guidelines and the inverted food pyramid have made the message a lot less clear.In this episode, Calvin and John look closely at two 2025 meta analyses of randomized controlled trials: Yamada 2025 and Steen 2025. One says there is no clear benefit to reducing saturated fat. The other says there may be a benefit, but mostly depending on your cardiovascular risk and what you replace saturated fat with.We don’t just read the abstracts. We go deep into the studies, recreate some of the charts, check the reported metrics, look at the forest plots, compare odds ratios and risk ratios, and dig into where the conclusions seem strong, weak, or a little too confident.Hopefully, there’s also something useful here about how to think through studies, evidence, and nutrition claims when the answer is not as clean as it first seems.

In this episode, we look at how Americans die at different ages using U.S. mortality data from the CDC. John walks through an interactive mortality data tool he built with multiple interactive charts showing broad causes of death by overall rank, age at death, and over time, along with detailed subcauses.The charts have filters for sex, age range, time period, and metric. We discuss the patterns that stand out and why the tool is useful.

A recent government announcement claimed Tylenol use during pregnancy causes autism, sparking widespread concern. We dissect the controversial study behind this claim, uncovering major flaws and conflicts of interest, and reveal what higher-quality evidence actually says about the risk.

Critical analysis of the popular anti-aging supplement fatty15, dissecting its "science-backed" claims and deceptive marketing tactics.Is fatty15 a “new essential fatty acid” that’s “3× better than omega-3”?Is fatty15 GRAS "certified'?Does fatty15 have any health benefits in humans?We review the evidence, including all the human randomized controlled trials on fatty15.Slides: https://www.jsdatascience.com/fatty15/

In this episode, we revisit the controversial Keto-CTA study about cholesterol, and arterial plaque progression. After the authors released some of their raw data, our analysis reveals the study's flaws are far worse than first thought. John breaks down the egregious errors, from published charts that incorrectly cut plaque progression in half, to statistical models that violate their own assumptions, directly contradicting the authors' claims and invalidating their conclusions.

In this episode, we dive into five statistical concepts everyone should know. We cover regression to the mean, how to evaluate model performance, what medical diagnostic tests really tell you, the Hawthorne effect, and what causation actually means in research.

In part 2 of How to Read Scientific Studies Series, we focus on interpreting the data and conclusions.We break down how results are reported, what statistical significance actually means, and how to spot confounding factors. We also highlight the common tricks and manipulations that influencers use to misrepresent research findings and media headlines.