February 7, 2020

Why you should Keep your Health Advice to Yourself.

When it comes to health and fitness, there is so much information out there that we are literally drowning in it.

Every day, I notice people both asking for and receiving well-meaning advice on Facebook, Reddit, and Quora.

This crowd may share similar struggles and may have opinions. They may be supportive and responsive. But few answers are provided by clinicians, journalists, doctors, trainers, nutritionists, or experts of any kind.

Instead, the responses are from a set of people who read something or tried something and because it “worked” (however briefly), or it “makes sense,” it becomes proof enough to recommend it to someone else. There is no follow-up on results, what measures success, what other elements were changed, how long the plan or program was effective, or what the long-term results were.

Crowdsourcing diet and workout plans is functionally getting drive-by advice, and it’s usually getting advice that mirrors the common cultural norm du jour for what constitutes a socially acceptable diet.

When giving advice: you are an anecdote, not an evidence-based conclusion.

When getting advice: the advice giver is an anecdote, not an evidence-based conclusion.

Here are two examples of information sources I personally trust when it comes to reliable conclusions about health: Harvard Public Health and Stanford Public Health.

If it’s coming from the public health department of a respected university, plus it’s been published in a peer-reviewed journal (particularly if it contains hundreds of people and/or it’s a longitudinal study), that’s an evidence-based conclusion. The opinion of someone on Facebook is an anecdote.

The public health agencies I noted above reveal their methodologies (not always perfect methodologies) and use statistically significant volumes of test subjects. So it’s as close to rock-solid as it’s going to get when it comes to health data that you can believe and create successful health habits around.

But there are always going to be people who believe that they know best and apply more weight to that than to science.

Example: Harvard Public Health recently published the results of a 30-year study to determine the impact of a low-carb diet. One of the conclusions was that those who cut carbs fared slightly worse on outcomes related to heart health due to a lower intake of grains. Before I go further, this single fact bears repeating: this study was for 30 years. Thirty.

I shared this with a paleo-friendly friend, who debated that study, because she personally thinks everyone should be on a grain-free diet. She told me that grains are bad because her skin breaks out and she gets bloated. Therefore, grains are bad and nobody should eat them.

Okay. This doesn’t invalidate her personal experience.

But it’s not an evidence-based conclusion. Harvard did a 30-year study on this. So I’m not going to recommend an anecdote-based conclusion over a published paper from Harvard when it comes to advising my clients, or giving advice on Facebook.

She told me she likes Dr. Axe’s opinion.

Okay. This doesn’t invalidate her personal experience.

But it’s not an evidence-based conclusion. Dr. Axe is not Harvard. Dr. Axe is not a medical doctor: he’s a chiropractor and a nutrition practitioner. That doesn’t make him wrong. But I place significantly more merit on a peer-reviewed longitudinal study, myself.

Removing grains from your diet for 30 years means you have a slightly higher mortality risk of heart disease than someone who didn’t. That’s a clinical conclusion, and it unfortunately doesn’t matter what Dr. Axe or my friend thinks or believes.

Do I think everyone should eat grains? Not necessarily. But if the goal is heart health, then I don’t think someone should remove them. Because there’s a 30-year study that generated statistically significant conclusions.

Here’s another thing I trust: meta-analysis. Meta-analysis takes dozens of studies (or more) on similar topics and combines data points to draw conclusions based on larger data pools than individual studies. They can include data from one million or more test subjects over the course of literally decades.

Generally, the reason we eat well and exercise relates to longevity. None among us want to die.

So we are cutting carbs to be skinnier now so that we don’t die later.

We are drinking water so that we don’t die later.

We choose to not smoke so that we don’t die.

It’s all about not dying.

But we are all going to die. And the meta-studies can track the factors that are the highest risk to mass volumes of people when it comes to dying.

I debated with the same friend about a meta-study that involved 1.6 million people (using 13 different studies). That study found that high red meat consumption had a 22 percent higher mortality from any cause and 18 percent higher from cardiovascular disease. My friend says that she discarded the study because she felt like it didn’t take into account if the meat was “grass-fed.” Because the book she read by Mark Sisson assured her that grass-fed meat was healthy in unlimited quantities. So she feeds her family meat at every meal and snack, because it’s grass-fed and organic.

I’ve truthfully never read The Primal Blueprint by Mark Sission. So I’m not here to debate specifics of what he, in particular, said. I’m not here to debate the merits of eating meat (so don’t send me nasty notes).

I’m simply saying that a meta-study of 1.6 million people, published in a peer-reviewed journal and authored by the public health department of a major university, is more likely to have meaningful conclusion-based data about the relative merits and dangers of “heavy” meat consumption than her personal household or even a popular diet book.

So remember that you are one person. Your opinion actually (sorry) doesn’t matter. A book you read about how and why everyone’s been eating wrong this year doesn’t matter. Quit posting it on Facebook and quit asking for help on Facebook.

And definitely quit listening to people who are posting stuff, believing they are an evidence-based conclusion.

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