The FBI has finally released crime statistics for 2023!
Let's have a short thread.
First thing up is recent violent crime trends:
Now let's focus in on homicides.
The homicide statistics split by race show the same distribution they have for years.
As with every crime, it's still men doing the killing, but it's also largely men doing the dying.
What about Hispanics? Their data is still a mess, but here it is if you're interested.
The age-crime curve last year looked pretty typical. How about this year?
Same as always. Victims and offenders still have highly similar, relatively young ages.
Everything else, from locations to motives to weapons is pretty similar to previous years. What's different is that the OP might show incorrect numbers.
For the past two years, the FBI has silently updated their numbers after about two weeks.
You can use the web archive to see that the data from the OP is the data shown at release last year, and the data from 2023 is the 2022 data with the FBI's suggested reductions (i.e., -11.6% homicides, -2.8% aggravated assaults, -0.3% robberies, etc.).
But you can see on their site now that they've adjusted the numbers up, so the reduction they suggested has brought us down to a figure that's less impressive than my chart shows. The difference isn't huge so I showed the OP without updating to their new data.
For reference, 2022 as reported then had a homicide rate of 6.3/100k, and they silently updated that to 7.48/100k. The 2023 data they provided today actually has a murder rate of 6.61/100k, higher than last year's initially-reported number, but lower than the updated number. To make matters worse, if you use their Expanded Homicides Report, you get a rate of 5.94 for 2022 and 5.24 for 2023.
Methodology matters and we get to see inconsistency in this year's data, not even data that's been updated or anything. It's a mess, so take everything with a grain of salt and, in the interest of caution, only interpret trends. Trends are mostly common between all data sources even if the absolute magnitudes are off, constantly updated, etc.
I've seen a lot of people recently claim that the prevalence of vitiligo is 0.5-2%.
This is just not true. In the U.S. today, it's closer to a sixth of a percent, with some notable age- and race-related differences.
But where did the 0.5-2% claim come from?🧵
The claim of a 0.5-2% prevalence emerged on here because Google's Gemini cited a 2020 review in the journal Dermatology which proclaimed as much in the abstract.
Simple enough, right? They must have a source that supports this estimate in the review somewhere.
They cite four studies for the 0.5-2% claim, so let's look into those studies.
Relationships between class and fertility and IQ and fertility used to routinely be negative in the not-so-distant past.
But across the developed world, they're increasingly positive, albeit only slightly. In this Swedish birth cohort (1951-67), the transition came early:
In this example, there's also some interesting confounding: between families, IQ isn't monotonically associated with fertility, but within families, it is.
Something seems to suppress the IQ-fertility relationship between families!
Sweden's positive IQ-fertility gradient (which, above, is just for males, since it's draftee data), has been around for quite a while (but has varied, too), whereas in countries like France, Japan, and the U.S., the gradient shift towards being slightly positive is more recent.
This is a really strong claim based on really scant evidence.
Add in a control for family history or use Bonferroni instead of Benjamini-Hochberg and 5-aminovaleric acid betaine goes nonsignificant. Add in polygenic risk scores too and Cyclo(Leu-Pro) goes nonsignificant.
Using a small number of the total tests (multiple comparison correction was too lax), the model with both metabolites in it alone led to p-values of 0.3512 for 5-AVAB and 0.0188 for Cyclo(Leu-Pro) and that's from a model without family history or genetic risk.
I don't see any good reason why, but the authors preferred to make inferences from a model missing important controls they had available
But to make matters worse, 5-AVAB wasn't measured super well, and the analyses with cLP were not quantitative at all, as most data was missing