A Quick Warning About Biotin Supplements (aka Numbers Still Aren’t Magic)

Now that I have my new shiny “Numbers Aren’t Magic” tag, I thought I’d use it for a bit of a PSA. I’m on a lot of laboratory testing related email lists for work, and I recently got a notification from the College of American Pathologists with a rather intriguing headline “Beauty Fad’s Ugly Downside: Test Interference“.

The story was about biotin (also called Vitamin H) a supplement widely touted as a beauty aid because it (allegedly) makes your hair and nails look better (example here). Unfortunately, it turns out that quite a few widely used immunoassays actually use biotin  to capture their target antibodies during testing, and unusually high levels in the blood interfere with this. In other words, high doses of biotin in your supplement could interfere with your lab results. Uh oh.

The news of this first broke in January, when it was discovered that some patients were getting bad thyroid test results that had resulted in an incorrect diagnosis of Graves’ disease. Since then, the awareness among endocrinologists has grown, but there’s concern that other potentially affected tests are being missed. Apparently cardiac markers, HIV and HCV tests could also be affected.

The problem here is really megadoses. These assays were designed to work with normal blood levels of biotin. The recommended daily amount is only 30 micrograms, but supplements like the one I linked to above actually give doses of 5000 micrograms….166 times higher, and in to the range of test interference. You only have to stop taking it for a day or two before the interference issues go away, but most people and doctors don’t know this.

I’m bringing this up for two reasons:

  1. I didn’t know it, and I think more people should be aware of this.
  2. It’s a good reminder that almost every number ever generated is based on a certain set of assumptions that you may or may not be aware of.

Numbers don’t often spring out of the head of Zeus fully formed, they are almost always assessed and gathered in ways that have vulnerabilities. For anyone attempting to make sense of those numbers, recognizing vulnerabilities is critical. If even lab tests (some of the most highly regulated medical products we have) can have issues like this, imagine what numbers with less stringent requirements could fall prey to.

PS: I couldn’t find biotin on the Information is Beautiful Supplement Visualization, but here’s the link anyway because it’s still pretty cool.

On Clothing Sizes (aka Numbers Aren’t Magic)

Last week I wrote a post that was sort of about denominators and sort of about abortion. At the end of that post I touched briefly on the limits of data, what the data will never tell us, and how often people attempt to use data to bolster beliefs they already have. That’s been a bit of a running theme on this blog, and it’s something I think about a lot. People seem to give numbers almost a magical power at times, and I’m not entirely sure why. It seems to get down to the  idea that numbers and statistics are objective information and that as long as their on your side, you can’t be too wrong. Now, I really wish this sort of confidence was well founded, but quite frankly anyone who’s spent any time with numbers knows that they’re a little too easily influenced to be trusted without some investigation.

I was thinking about that this week when I got in a discussion with a coworker about one of the worst examples of “numbers are magic when they tell me what I want to hear”: vanity sizing.

For those of you not aware of this phenomena, vanity sizing is when clothing manufacturers increase the size of their clothes, but keep the number of the smaller size on it.  The theory is that people like to say/believe they are a certain size, so they will gravitate towards brands that allow them to stay in that size even as they gain weight.

This is not a small problem. The Washington Post ran an article on this last year that showed the trend with women’s clothes:

Keep that in mind next time someone tells you Marilyn Monroe was a size 12.

While individual clothing manufacturers vary, my friends and I have definitely noticed this. Most of us are in smaller sizes than we were a decade ago, despite the fact that it’s really not supposed to work like that.

Anyway, this makes discussing women’s clothing a little difficult. It was recently reported that the average American woman wears a size 16 , but which size 16 is it?  A size 16 from 2011 has a waist size 4 inches bigger than the 16 from 2001. Tim Gunn recently wrote an op-ed in which he blasted the fashion industry for not designing for anyone over a size 12, but he never mentions this trend. If you look at that chart again, you realize that any retailer accommodating a size 12 today is covering would would have been a size 16 a decade ago. Weirdly, this means the attempt to cater to vanity means the fashion industry isn’t getting credit for what they are actually doing.

And lest you think this is a women only problem men, sorry, that “36 inch” waist thing? Not at all accurate unless you’re shopping high end retail. Here’s what a “36 inch” waist can mean:

I think that’s actually worse than women’s clothes, because at least we all sort of know “Size 8” has no real definition. “36 inches” does leave one with the strong impression that you’re actually getting a specific measurement.

Anyway, I don’t really care what the fashion industry does or doesn’t get credit for, or what the sizes actually are. The broader point I’m trying to make is that we do give numbers a bit of a magical power and that we heavily gravitate towards numbers that make us feel good rather than numbers that tell us the truth.

Keep this in mind the next time someone says “the numbers are clear”.