Something that I find amazing is how many headlines talking about risk are simply wrong
Why?
Let's take a quick look at odds ratios #tweetorialpic.twitter.com/XyCldkJiRm
You can add location information to your Tweets, such as your city or precise location, from the web and via third-party applications. You always have the option to delete your Tweet location history. Learn more
The thing is, by definition odds ratios are higher than relative risk ratios - it's mathematically certain When the risks are low, this effect is small, but if the risks are big it's very noticeable
For example, if your two risks are 0.01% and 0.02%, the risk ratio is 2 and the odds ratio is: (0.02/99.98)/(0.01/99.99) = 2.0002 Barely different
But if the two risks are 20% and 40%, the risk ratio is still 2 (40/20) but the odds ratio becomes VERY different: (40/60)/(20/80) = 2.67 That's a lot higher!pic.twitter.com/73Fc7CxeUU
Going back to this headline that I picked up - it looks at a study that used logistic regression, which spits out odds ratiospic.twitter.com/8vHaEBaLIS
The results were reported as odds, with vapers having a 1.83 times higher odds of stroke than non-vapers Given that the prevalence of stroke was 2-4% in the groups, that means that the risk ratio would be a bit lower than 1.83
In other words, the headline rounds UP from 83% to a 100% increase (double), but in actual fact it's more likely that the risk is somewhere around 75% instead!
And this is done almost ubiquitously across the board It's not really the media's fault - scientists do it all the time as well!pic.twitter.com/BjxCDlughU
It's also really hard to tell if the study used risks or odds unless you actually read it, which adds a layer of complexity to the matter
Honestly, I want to end on a nice easy note, but the fact is that odds are confusing, a lot of researchers get them wrong, and it's unlikely we'll have a solution to this any time soon Hurray!
Anyway, a reasonable proportions of the headlines you've seen probably overestimate the actual risk because the studies used odds ratios 
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.