I'm also a little concerned that the BMJ plot of risk adjusted mortality still shows a clear positive correlation with age at death, which I strongly suspect would turn out to be statistically significant. The adjustment does not appear to be correct, therefore, and while that might still preserve these odd findings, it's definitely not ideal.
The much better occupation, from the graph, is the third outlier -- mining and geological engineers. Life expectancy: 80.3, risk-adjusted mortality: 1.1%. Or, alternatively, economists are close too (80.6; 1.19%).
Aircraft pilots, btw, really were the opposite end of the scale (78.1; 2.3%), surprising enough to be noteworthy beyond a control (the BMJ article does discuss this a little, but seriously -- that's very surprising for a highly-educated profession).
For example, the other day I wanted to figure out what’s the current state about whether gender equality causes measurable benefits for companies… and the studies are terrible. All of them. Most of them was about Norway, and almost all of them had a reference point in 2008, one of the largest economic crisis, and somehow most of them was even worse than this. They openly distorted statistics. Depending on what they wanted to achieve to one way or another. Even the most cited ones. It’s disgusting. The best ones could prove only that inequality is not inherent of economics, but social. But the agenda was different for them too, so they tried to lie something bigger, all the time, while this would be more than enough to support it.
Every top-level thread is like a multiple choice armchair takedown.
Here's an interesting counterpoint. "Unthinkable" presented studies of navigation tasks in 2D/3D and testing/training. Hippocampus measurements correlated with skill and training. Interestingly, this skill and training and measurements all correlated with beneficial responses in a disaster (as in, not panicking). Weird right?
So you have people self selecting out of the profession, self selecting for early death within the profession, and on top of that, a general life expectancy discrepancy that is near impossible to adjust for.
(Unless people highly predisposed to dying in car accidents are also highly predisposed to mudering people who will have, but don’t yet have, Alzheimers. But that seems sufficiently unlikely for the purposes of this hypothetical.)
Jokes aside, the serious answer depends on whether the link is causative or merely collerative.
Not that cab drivers only live to 67 - many would still live to 75, 85, 95, but that occasionally a driver dies at 25 or 35 bringing the mean figure way down.
Delay your aging by using your brain a fuck ton, all the time, learning brand new things nowhere near anything you already know.
I'm not saying you shouldn't try using your brain more but this is just like saying Stephen Hawking should have tried exercising more.
/s
Of those, sleep issues are highly correlated with Alzheimer's and also with auto accidents. Controlling for age alone here would select for low incidence of sleep issues.
So no indication they accounted for the expected lifespan of the profession.
It’s a plausible hypothesis but it’s really really hard to tease things out and controlling for age is the obvious thing but that doesn’t get you the conclusive result you think it does.
then don't post
I don't think many realize how huge the replication crisis is. You have 75% of studies in a leading social psychology journal failing to replicate. [1] Another replication effort on preclinical medical studies found only 11% were able to be replicated, a replication effort on cancer studies found the average effect size to be 85% lower than published, and much more. If you assume most science headlines, at least outside of the traditional hard sciences, are false - you're substantially more likely to be right than wrong.
[1] - https://en.wikipedia.org/wiki/Replication_crisis#In_psycholo...
'Why ‟controlling for a variable” doesn't (usually) work' - https://dynomight.net/control/
Other things that don't work, including four other 'controlling for a variable' entries at items 39 through 43: https://dynomight.net/things/
Also, older ones were exposed to a ton of cigarette smoke.
Sure they might be better and per unit of time they drive they must have miniscule amount of accidents.
But if there's a 0.001% chance per hour driven, then over enough hours a few accidents are inevitable.
Pedestrians are a lot more at risk. So that's unsurprising that annually 1/2 taxi driver might be fatally injured in one.
But I would assume the ratio of other drivers to taxi drivers would be high enough that this number should be zero as well.
That's actually crazy if that's as low as you dare guess. I would have easily guessed it was like, a fraction of a percent. 1 in 10 would be fucking nuts.
"For each occupation, we first calculated the percentage of deaths due to Alzheimer’s disease and the mean age at death in years (ie, average life expectancy). We plotted the association between these two variables, with each observation reflecting a single occupation. The purpose of this analysis was to illustrate the need to account for the person’s age at death since the risk of Alzheimer’s disease rises with age and therefore Alzheimer’s mortality would naturally be lower in occupations with a lower life expectancy."
not to mention the other devil in these studies: some professions are statistically going to have the lowest rate of every possible disease. you can't just cherrypick outliers and declare "causal!"
Where? What country/ies?
For from the look of it it doesn't look like an exceptionally hard job (btw a brother of mine did years of "VTC": "Vehicule de Tourisme avec Chauffeur", basically high-end taxis without the "taxi" logo).
2. The original study didn't just study taxi drivers, but also ambulance drivers. I doubt that their life expectancy is that much lower.
Define "hard job". Carrying heavy objects?