Comment by stymaar
10 hours ago
It pains me to see such a low-effort contrarian comment at the top: as stated in TFA taxi drivers are below other profession when controlling for age, and there are multiple professions with lower life expectancy that still have significantly higher Alzheimer rate than taxi drivers.
Fella has read the article, has an argument and some stats. What more do you want from a comment? He isn't running a study.
Besides, the point is a good one. There are a lot of professions. If we glance at the underlying study [0] Figure 1 suggests that we'd probably expect to see an outlier or two in that mess just through chance, we're expecting a few p<0.01. Taxi drivers doing unusually well doesn't seem especially impressive in that light, especially since it is one of the professions that seem to die off rather young and we might expect one of those professions to do rather well on Alzheimers.
[0] https://www.bmj.com/content/387/bmj-2024-082194
> Fella has read the article
Their argument doesn't show that at all though, they make an argument against an age bias when the article explicitly says age is being controlled for.
> Figure 1 suggests that we'd probably expect to see an outlier or two in that mess just through chance, we're expecting a few p<0.01.
That's a valid point, and a much better criticism than the one I'm calling out. That doesn't redeem the original comment though.
The comment insinuates that the study did not control for age. The study controlled for age.
It's not terrible to not make a good point, but it's not a good point. The not good points should not be ranked highly.
But after the study controls for age the starkness of the effect more or less disappears (eyeballing Fig 1, the 2nd graph).
It turns out that there is a profession with a lowest risk of getting Alzheimer's (duh, one had to exist) and it looks like a slight outlier (it's the lowest, we'd expect that one to look like a slight outlier). As outliers go it isn't that impressive, it looks like it is part of a fairly boring distribution. We just plotted 400 data points on the graph, the 1/400 chance weird data point is going to look a little weird. We're actually just reading a lot into the fact that the 2nd data point in ambulance drivers which isn't all that convincing.
Not to knock the study, I'm sure it is a great study. Lots of science done. They do good graphs and all that. But the study appears to be telling me that Alzheimer's is random with respect to occupation and ideally don't spend so much time on the road if you want to live to see old age.
It's getting hard to find any study posted without a kneejerk "correlation does not equal causation" take as if that's not something researchers have to control for in order to even conduct the study in the first place, let alone publish
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A distinction is that Alzheimer's is in an uncommon category of mystery diseases.
If a study found people who swim regularly are are less likely to get heart disease, that wouldn't be very surprising because know a lot about why people get heart disease. Therefore it would be valid to insist on more rigour for accepting (swimming => less heart disease) because the only use of that information is for health advice.
However even weak statistical correlations can be a valid lead for further research into Alzheimer's disease if they suggest where to look. You don't need to prove that signposts are correct in order to use them.
> Fella has read the article
Then not closely enough? The study adjusts for age, which is the core of OP’s criticism.
If we read OP's comment closely, it appears to be technically correct. I can imagine someone not upvoting it because it seems to be generic, but there isn't anything wrong or low effort about with it. And I don't see where the stats came from if he hasn't read the article.
"study adjusts for age"
maybe it would help this thread to have someone explain exactly how they control for age, if everyone in the range they want to study, is already dead.
What is the actual process to control for age? This comes up a lot, and the only response is "oh, well, we controlled for that", well exactly how?
Seriously, I'm curious.
//lot of downvotes, not a lot of anybody actually able to explain it.
From Article, the age question does seem sketchy.
"Although proportional mortality analyses do not provide information about the population at risk, with careful selection of controls and risk adjustment for factors that may affect competing risks (eg, age, sex, and social class), these values can still serve as a useful indicator of variations in disease frequency across different occupations.16 17"
Worth mentioning that controlling for confounders is hard, a reasonable prior is the null effect, and any time a researcher makes a mistake it produces a publication claiming a novel effect. You observe a set of publications concentrated with false positives as a form of selection bias. I wonder how many of the causal studies are reproduced by independent teams using independent datasets.
Plausible scenario. Individuals predisposed to Alzheimer’s experience different mental sharpness from birth and this makes them enjoy driving less, and so they pursue taxi driving as a career at lower rates. Under this scenario, driving has no effect, it just induces a selection bias.
True. But, these are still odd outliers in terms of low life expectancy, and that's something that the actual BMJ article cited (https://www.bmj.com/content/387/bmj-2024-082194) or TFA talks about at all. The LE is low enough for both professions to be awkward.
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).
A better low effort contrarian comment - isn't it that early symptoms appear less often with people with a "reserve"?
Being mentally active (or physically active?) IIRC makes actual plaques both less likely, but also less detectable - a taxi driver can forget 90% of what they know and still not get diagnosed because they don't get lost on the way to the shops. Also they are often masters of small talk.
This would suggest they'd need to control for method by which the alzheimer's was discovered. A quick glance seems to indicate they did not do this. This is not information available I guess..
I would suspect this would eliminate a lot of the experiments participants, as only people who go for regular cognitive check-ups might be eligible?
I cannot imagine there would be many people left who'd be eligible. I can only think of 1 person that does it.. and he obviously does it for the pure satisfaction of acing those cognitive tests, and not because he is showing worrying amounts of decline in his mental faculties.
If the "study" is interesting at all, it's because of the implication that driving a taxi somehow wards off Alzheimers... but at the cost of killing you before you get it.
Just the top one?
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?
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But on some level I understand the immediate low level criticism. Of course, it’s stupid to criticize something without reading about it. However, I’ve seen waaaay more studies which was made with even lower effort.
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.
I do wonder if you can truly control for it in this case, or if doing so doesn't in and of itself introduce a survivar bias that masks a reversal of causality. That is: could the taxi drivers who are already predisposed to have a lower chance of developing Alzheimer for other reasons also be the ones who are more likely to live to be older than the average taxi driver?
First time on HN?
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