To summarize:

- 3 of the 5 meta-analyses reviewed support the consensus on red meat's health dangers

- The other 2 are irrelevant and shouldn't have been considered at all

- The paper handwaves away the conclusions of the 3 by raising reliability issues that could be applied to any meta-analysis of nutrition, since it's impossible to perform nutritional research as rigorously as drug research

I think it was not so much to give advice as to answer the question.

Is that one thing that we are eating bad for us?

The sheer chutzpah of handwaving away the only paper that matters - the one meta-analyzing the randomized experiments - by counting a bunch of different confounded correlational approaches as each equal in value to it.

Here is the only sentence you need to read:

https://annals.org/aim/fullarticle/2752326/effect-lower-vers...

'Of 12 eligible trials, a single trial enrolling 48 835 women provided the most credible, though still low-certainty, evidence that diets lower in red meat may have little or no effect on all-cause mortality (hazard ratio [HR], 0.99 [95% CI, 0.95 to 1.03]'

Experiments introduce control at the expense of generalizability, and some types of experiments more so than others.

Observational studies aren't perfect but they do have advantages, and in nutrition I wouldnt trust experiments more (maybe not less either to be fair).

We have plenty of experiments in animals for example and those arent much more interpretable, at least in nutrition.

Nothing is simple.

What blinding do you need for all-cause mortality? Do you think people are lying on the form where the coroner says they are dead?

> How do you ensure they're following protocol? For how long? And who is adhering? How do you know you're manipulating what you think?

Every single problem here is far, far, far worse for all those observational studies you cite.

> Observational studies aren't perfect but they do have advantages

Their only advantages are that they make it cheap and easy to get the wrong answer precisely and churn out lots of papers and meta-analyses. Fortunately, here we have the more expensive, hard, but correct results. Guess what the second set of results say?

> We have plenty of experiments in animals for example and those arent much more interpretable, at least in nutrition.

Indeed. Because most nutrition research, especially the ones based on correlational results, are wrong. That's why the randomized experiments aren't 'interpretable': because the theories are wrong. You will indeed have trouble "interpreting" the results which keep showing all the theories are wrong. This is a feature, not a bug.

Harvard, unfortunately, has doubled-down on this style of science.

It's not helpful that the press supports these methods, without skeptical commentary.

For myself, until you can tell me by what means a particular food produces the claimed outcome, I dismiss your epidemiological nutrition study.

It wasn't that long ago that the role of microbiome was recognized, for example, and even now it's contentious. Conversely, scores of epidemiological findings have had nice physiological explanations that turned out to be much more complicated, like those involving saturated fat, cholesterol, and carbohydrates. DHA, omega fatty acids, etc. are similar. Physiology is complex enough that you can accommodate just about any finding.

To carry this a bit further, it can be problematic going in the other direction too, from physiology to populations. Some of the anti-sugar advocacy, for example, was rooted in lab studies that neglected the effect of fiber in digestion of fruit, so you had people advocating that whole fruit consumption be avoided based on incomplete understanding. It's hard to argue that unprocessed whole fruit is undesirable on the basis of observational nutrition studies. Someone looking at the wet lab data and advocating abandonment of whole fruits might have done well to look at those observational studies to see why different trends were occurring.

I'm not saying that tying one level to the other at some point isn't necessary. I just think one or the other level can't be dismissed out of hand just because things don't map onto each other initially. It's possible that one level provides clues that the other is missing; it's also possible to come up with plausible but wrong bridges between the two levels.

I think the depth of knowledge is very uneven. We're not sure how Tylenol works. (Disclaimer: I work in software, not bioscience)

At least, placebos don't harm the user. There's evidence paracetamol is harmful. https://ard.bmj.com/content/75/3/552

And dosages higher than 4g/day are known to destroy the liver. Paracetamol overdose is one of the most painful way to kill yourself. Its abuse being freely sold over the counter makes it the number one cause of liver failure in the US and UK. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1403265/

>Paracetamol’s toxicity is also the single biggest cause of acute liver failure in the United States. Cases have been rising for six years, according to a study published in December (Hepatology 2005;42:1364-72). By 2003, the drug accounted for just over half the cases of acute liver failure, and about half of these cases were the result of unintentional overdose.

It boggles the mind the substance has not been put under harsher control yet.

Sounds like someone is optimizing for the number of papers written per grant dollar, as opposed to generating quality science.

Why do expensive research when you can just print a few questionnaires, get a few underpaid grad students to administer them, then trawl the data for acceptable p-values for publication?

Perspective: Limiting Dependence on Nonrandomized Studies and Improving Randomized Trials in Human Nutrition Research: Why and How https://academic.oup.com/advances/article/9/4/367/5055939

Implausible results in human nutrition research https://www.bmj.com/content/347/bmj.f6698

His most famous paper, Why Most Published Research Findings Are False https://journals.plos.org/plosmedicine/article?id=10.1371/jo...

Here's a talk on nutrition science methods, along with a specific audience moment with Walter Willet, former head of Harvard Nutrition dept, and advocate for his questionnaires. https://www.youtube.com/watch?v=KTAbx4i8Dyg -- https://youtu.be/KTAbx4i8Dyg?t=23m40s

He seems to be in favor of large randomized-controlled comprehensive diet protocols, for example, where many aspects of diets are manipulated simultaneously. He dismisses them too, though, for very good reasons. Given that there were additional reasons to be skeptical of such studies he didn't mention, I was left wondering if his pleas for study designs should be heeded very much (as opposed to his criticism of specific flaws). I love his work, but am wondering if it's best approached as worst-case criticism rather than an inspiration for what to do.

He's listed as an author in a number of nutritional and other studies. One might see those as leaning in his direction, if he's willing to be mentioned.

You might contact him if you have additional doubts.

It isn't wrong, but it seriously calls into question whether the aim of the recommendation against red meat purely accurate nutrition science or a broader agenda.