Flu vaccination linked to 40% reduced risk of Alzheimer’s disease
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1. The journal article didn't suggest it was causal. But such a correlation with such a large population warrants publication and further research into causation.
2. literally the first thing that any epidemiologist would consider is potential confounders. There is a big list of covariates they included into their model here: https://content.iospress.com/articles/journal-of-alzheimers-...
There are quite a few things that can be done to alleviate potential false correlations: DAGs, prior literature, removing confounders, and including covariates are all things at disposal.
3. Such a large sample size + previously reported findings + an inclusion of enough covariates still doesn't == causation, BUT it's important to publish and shout about so we can then look into the potential biological underpinnings that may cause this. Which by the way, those experiments may still use data science techniques.
4. If you are actually interested, there is a whole topic of this called 'causal inference' with one famous criteria list called the 'Bradford Hill Criteria': https://en.wikipedia.org/wiki/Bradford_Hill_criteria. This list is often argued about.
5. If all of this information was new to you, please stop spouting 'correlation != causation'. You probably don't know as much as you think
Complaining about correlation not being causation is the perfect theme for the midwit meme. It's one of my pet peeves.
As a physicist who had to endure helping biologists with statistics and cooling down their enthusiasm: it make sense to have a deeper thought about the experiment.
As parent wrote, there may be various reasons for the correlations, sometimes you have random stuff, sometimes indirect stuff and in others extraordinary stuff. Many discoveries (especially older ones) fall into the last category.
That hardly seems relevant, since we're talking about causal relationships and chance is the opposite of causation.
Yep, it's in the alt text for https://xkcd.com/552/
"Correlation doesn't imply causation, but it does waggle its eyebrows suggestively and gesture furtively while mouthing 'look over there'."
"We found that flu vaccination in older adults reduces the risk of
developing Alzheimer’s disease for several years. The strength of
this protective effect increased with the number of years that a
person received an annual flu vaccine – in other words, the rate
of developing Alzheimer’s was lowest among those who consistently
received the flu vaccine every year"
(As a footnote, personally, I do believe it is causation; I believe that as with COVID and EB, we've dramatically underestimated the long-term impact of many viral infections. But that's just a personal belief.)
Interesting. I don't read that as claiming causation, I read that as describing the correlation.
You're right though, it's confusing messaging, regardless.
That is distinctly not causal.
They just can't include it in the paper because reviewers will make sure to remove it
The team did indeed find that flu vaccines reduced the risk of Alzheimers. But he specifically doesn't say they know why the flu vaccine lowers the risk. Ie. They can't claim causation if they don't understand the underlying reason for the change. That's not how science works.
In fact in the article in question he says the opposite: That the immune system is vastly complex, and all they can say is the immune system reacts to flu vaccines (all flu, not just a specific one) by diminishing an Alzheimers response. ¯\_(ツ)_/¯ More study needed plz.
> The team did indeed find that flu vaccines reduced the risk of Alzheimers. But he specifically doesn't say they know why the flu vaccine lowers the risk
I don't think that's an accurate statement. They didn't find it reduced risk. They found that there seemed to be a pattern. That's different then saying the flu vaccine reduced risk. Its possible that the vaccine is just a coincidence.
But the pattern looks pretty strong so its interesting news nonetheless.
Sorry but I had to nitpick here. This is exactly how science works. We first observe things that we cannot explain, and we can definitely infer causation without a complete mechanism or even a proper theory for it.
Of course any such explanation is provisional. I might think your comment is just to complain the provisional aspect isn't mentioned in the quote (I think it'd be tiresome to say that in every statement, and the public's understanding of science being provisional is underestimated), but you seem to think it's a problem that causal language is used at all?
While quote may have been offhand, look at what the actual paper says [1]: "[the study] design prevent[s] strong conclusions regarding causation." Note that it doesn't say it prevents any conclusions regarding causation.
By the way, it seems weird that you yourself have come to believe it's causal, while seemingly denying that this paper provides any basis. How did you come to that conclusion then?
[1] In the last paragraph: https://content.iospress.com/download/journal-of-alzheimers-...
Yes the paper says differently. So what? We're used to this from epidemiology by now. The claims they make to the government/media/public about disease frequently don't match their actual data. To discover this you have to not only read the paper but often dig through the most obscure parts of it. The fact that their claims are wrong will only emerge in, like, table 3 of Appendix 2 which is by the way only available on GitHub if at all. Here it emerges in literally the last paragraph. Then someone blogs about this and they get kicked off Twitter for spreading "misinformation".
The public's understanding of science being provisional is actually excellent and far better than the supposedly elite decision making classes. That's why the public increasingly doesn't trust claims made by scientists, and correctly so. Scientists will make bold claims of causation whilst actually having a sketchy P=0.049 regression at best and a fictional model built on circular logic at worst.
We need to hold scientists to higher standards, and especially epidemiologists. The amount of damage their sloppy "offhand" approach has caused is astronomical. Or, quicker, just accept that they aren't going to improve, have learned nothing from COVID and cut them out of society and the public conversation entirely.
You think the scientist quote is dishonest? It seems you too conflate causality with something like proven mathematically or 100% confidence.
Moreover, as a killed comment elsewhere in this thread points out, it's very likely that they made a mistake somewhere. This claim is absurd on its face. A 40% effect size is enormous. Alzheimer's is tracked very closely and there has been no change in incidence over time:
https://ourworldindata.org/grapher/prevalence-of-dementias
Flu vaccines on the other hand have become far more prevalent over the last 20 years especially amongst the age groups most at risk for Alzheimers. So, where's the impact? There isn't any. If flu vaccines really reduced the risk that much then we'd see it in the actual numbers, as a 40% reduction is hard to hide.
I feel like in English, "linked" usually implies some sort of potential causation, not just a general relationship. For example: "boyfriend linked to murder case".
https://www.mcsweeneys.net/articles/an-interactive-guide-to-...
Causation, correlation, coincidence.
And then there's quantum entanglement.
If so, then you might not actually believe linked is simply a synonym for correlation. I know I certainly would think that was a ridiculous way to phrase it.
For those who don't know the reference: http://www.tylervigen.com/spurious-correlations
Loads of people get the flu vaccine. Enough that I'd imagine the sample size is representative of the population at large. A large number of people also don't get the flu vaccine. So this is a surprising result. Especially since we are injecting a liquid into the people so there could reasonably be some effect we never thought of. Which is the whole point. These people aren't correlating things in completely unrelated fields and claiming a link.
This sort of intellectual looseness is not free. People are learning to treat claims by scientists as untrue, and it's partly because of this sort of press release/paper hacking.
Finding a correlation between two random medical data sets does not mean there is a "link" in any English that normal people would use it. It definitely does not mean there's an "effect" or that one thing "reduces" the other. It might mean there's something worth a followup investigation there, though given the prevalence of non-reproducible p-hacked results in science, also maybe not.
Regardless, before doing press releases and going to the public with such a claim there is a large amount of work needing to be done to actually prove causality. Moreover you'd then want to ask why does such a thing happen when there is no prior reason to suspect such an impact.
I don't see it that way. Nick Cage has nothing to do with Alzheimers. We're not finding correlations with Nick Cage movies and then saying "Nick Cage linked to reduction in Alzheimers".
They are suggesting that flu vaccination may have some 2nd order effect beyond protecting you from the flu. Which could be reasonable, science reporting and poor research notwithstanding.
Either way, the refrain "Correlation does not imply causation" is over used in my view. And I'd rather learn the specific ways the research is flawed.
https://www.healio.com/news/primary-care/20200302/flu-vaccin...
I don't think there's a really killer argument here in the abstract: I personally find it unreasonable to imply causation from any medical intervention to any possible outcome based on just a correlation. Yes, it's more reasonable than Nick Cage being associated, but not reasonable enough. That's a judgement call however. I am guided in it by the massive costs and problems created when scientists claim vaccines are miracle cures without sufficiently robust data.
You might want to read the paper before saying untrue things like that so confidently:
“Mounting evidence indicates that systemic immune responses can have lasting effects on the brain and can influence AD risk and/or progression. A diverse range of microorganisms and infectious diseases have been associated with an increased risk and/or rate of cognitive decline, particularly among older adults, including influenzal respiratory infections [5, 6], pneumonia [4, 7], herpes infections [7], chronic periodontitis [8], urinary tract infections [4], gastrointestinal infections [9], sepsis [4], and most recently COVID-19 [10]. Prevention or attenuation of microbe-related inflammation may therefore represent a rational strategy to delay or reduce the risk of neurodegenerative disease. Consistent with this hypothesis, studies have found a decreased risk of dementia associated with prior exposure to various adulthood vaccinations, including those for tetanus, diphtheria, pertussis (Tdap) [11–13]; poliomyelitis [11]; tuberculosis [14, 15]; herpes zoster (i.e., shingles) [6, 13, 16, 17]; and influenza [11, 18–21].”
Unlike your Nick Cage theory, this has a clear mechanism and is compatible with the understanding of similar effects.
I said "almost certain". What you did is taken a database of someone who made millions of comparisons, such that coincidences that are very unlikely to occur happen via pure coincidence.
Additionally, I said "enough of a sample size". Given that the analysis you're talking about was over 11 pairs of points, that doesn't even qualify as very unlikely.
Your misplaced trust in your own plausibility filter causes you to make foolish posts on HN.
I find it plausible that the few people who spent hours reviewing this paper didn't think of that, and that the people publishing the paper ignored it since ignoring it could help them gain more funding.
> Your misplaced trust in your own plausibility filter causes you to make foolish posts on HN.
It is foolish to believe that scientists does things properly. As an outsider you only see the outlier results, meaning that most of what reaches HN could be faked or statistical trickery or have simple explanations due to poor science since poor science is more likely to produce headlines, while most scientists could still do the right thing.
But their mistakes are generally subtle, and not what somebody who knows nothing about the subject invents in the first seconds after first hearing about the topic.
The primary COVID model that triggered lockdowns was full of programming errors. It had never been peer reviewed, and its prediction of deaths varied by 80,000 depending on whether you engaged a data loading optimization or not. It gave totally different results depending on available CPU features! There were no tests and the results had never been validated against anything. Outsiders pointed out these problems, and the team didn't care, nor did anyone else in the field of epidemiology.
That's just one example of many. Epidemiology is kinda like the phrenology of our era (one of quite a few). It's not built on a firm scientific foundation.
Hence, while a correlation might be interesting, when presented we need to also understand the methodology and go into the detail a little bit to see how extra factors have narrowed down that finding.
E.g, without looking into any of the data, 'more Flu shots reduces risk of Alzheimer's' might be because people predisposed to Alzheimer's have a poor diet and the flu shot just counters some other terrible health effect. So first bit of detail to look at is whether the selection factors for diet, comorbidities, environment, general health, history, etc.
Not saying anything about this article, but context is always important, hence those claiming 'correlation !== causation' are only correct as far as not looking any deeper. Same for 'well it could be' is useless without knowing how close to 'could be' it is.
More critical imo, is the use of '40% reduction.' If this is relative risk (this study is not, it's absolute), the actual risk could be 0.0037%, where a reduction of 40% is practically nothing. So next check is: is this relative or absolute risk? If relative, relative to what baseline? So many studies are distorted by using relative risks against a meaningless baseline.
And its vileness is far beyond midwittery. It is a lazy & incredibly weasely way to stifle unwelcome lines of inquiry: by pre-emptively accusing anyone who would continue along those lines as a mental defective.
That being said, modern research is mostly a profit/status driven false-positive factory.
Search [0] for "Hypothesized mechanism" or even "BCG" for a concrete example of a vaccine that most likely does not act via prevention of infection (it is a tuberculosis vaccine and most people never get tuberculosis. It still shows a protective effect).
[0] https://content.iospress.com/articles/journal-of-alzheimers-... (Open Access)
Which seems to me to be, unambiguously, you should absolutely be religious about getting your flu shot every year. The vaccine is known to be safe and with few side effects (or at least, safer than the actual flu, which is the bar that needs to be cleared.)
And even if it hasn't been conclusively proven that vaccines can avert Alzheimer's, you're at least putting yourself in the best possible cohort, right? Anyone familiar with Bayes' Theorem should be absolutely on board with this.
> Among developed countries, Japan has the lowest prevalence of both dementia in general and Alzheimer's disease in particular.
> The burden of dementia is increasing exponentially especially in Asia-Pacific region, where more than 60% of the population reside [34]. The prevalence of dementia seems to be higher in developed countries, like Japan and Korea, than in countries with low incomes in Asia. A Japanese study found that the prevalence of dementia equals 11% among those aged more than 65 years [35, 36], whereas a Korean one found the prevalence of 6.3% [17]. Another study conducted in Korea, the Seoul study, showed that the prevalence of dementia, excluding very mild cases, was about 5.3% for overall dementia and 4.3% for AD [37].
> The prevalence of dementia greatly varies between different ethnic groups living in the same country, like in Singapore, that is probably the most multicultural region of Asia. A Singaporean study showed low standardized dementia prevalence among the ethnic Chinese (2.5% among the elderly) when compared to the ethnic Malays (4.0% among the elderly) and this finding was independent of the frequency of vascular risk factors [18]. Whereas these differences are due to different genetics or lifestyle it remains a matter of debate.
The COVID vaccines are also "known" to be safe and with few side effects, by the sort of public health people who like to make such claims. That doesn't mean anything.
Here's the problem with flu vaccines. They do not correlate with any reduction in mortality attributed to flu. Every trial indicates effectiveness, yet despite hugely increased number of flu vaccines over the years, deaths due to flu do not move. A rational person should wonder what this implies about the reliability of vaccine trials.
However: it turns out that some of the usual case for yearly flu shots is little more hand-wavy than I'd realized.
Flu-like illnesses aren't as well-tracked as the stats might make you think - with an awful lot of grouping under "influenza-like illnesses" of non-flu diseases (that aren't helped by flu immunization), or tallying with all pneumonias. I have a strong sense that pre-COVID, normal "flu deaths" stats were already being exagerrated as part of the campaign to remind people to get flu shots.
For example, in late 2018, part of the CDC's push for more vaccinations estimated the previous flu season was the deadliest in memory, with 80k deaths, and that previously, the worst year had been 56k deaths: https://www.statnews.com/2018/09/26/cdc-us-flu-deaths-winter...
But in their current estimates, that same flu season only killed 52k - and not a single season of the last 10 reached 56k: https://www.cdc.gov/flu/about/burden/index.html
(Some have been pointing out such issues for a while, such as in this 2005 BMJ comment, "Are US flu death figures more PR than science?" – https://www.bmj.com/content/331/7529/1412.)
This actually came back to bite public health authorities during COVID when even the harder data on early COVID mortality could be characterized, against inflated flu-severity numbers, as "no more than 10x worse than a recent bad flu season". Truer (smaller) flu numbers likely would've led to instead an "at least 10x and probably 20x" comparison.
At the same time, it's quite hard to track the yearly effectiveness of flu shots against strains that often don't not match those chosen when vax production begins. In normal years, even suspected flu deaths don't necessarily lead to a lab-determined confirmation of any infectious agents involved.
You can see how little researchers trust the consistency of data on flu cases in the very research highlighted here. If you think flu vaxes prevent Alzheimer's, one obvious mechanism to theorize might be: actually getting the flu increases Alzheimer's risk, the shot reduces flu cases. But they don't even run that analysis, because they don't trust the data on actual flu cases suffered in their samples as being unbiased. (They write: "Fourth, we chose not to include influenza infections in our analyses because of concerns surrounding influenza infection misclassification in retrospective studies of administrative data [56]. Similar to the authors of a recent study investigating the flu vaccine’s association with dementia risk in a VA cohort [20], we concluded that the potential bias from frequent misclassification of infection status outweighed the potential benefits of including this factor in the analysis.")
Finally, and this is the kicker which might knock me off my previous habit of annual flu vaxes, until I'm at a more-frail age, is that there was growing recognition before COVID that regular, mismatched flu vaxes might actually increase susceptibility to some future strains.
You can see a bit of discussion of that in this 2019 guide to the "changing science of flu shots" – https://www.statnews.com/2019/10/14/updated-guide-changing-s... – specifically bottom "Can repeated vaccination actually backfire?" section.)
Two mechanisms that might contribute are imprinting (overspecializing immunity to the 1st strains seen, slowing later) and urgency-fading (training the immune system "we see a batch of these paper-tiger threats every year & they never create actual illness, so we can tamp down our responses to this whole class of agents").
This suggests to me that, even as a big fan of vaccination, I may want to use it somewhat more sparingly: when a specific strain has a higher risk, when a specific formula is well-tuned to an emerging threat. Otherwise, both for me & the community, I might be dissipating the benefits before they're urgent.
Mechanisms hypothesized to be at play:
"These mechanisms—and those underlying the effects of adulthood vaccinations on all-cause dementia risk in general—can be grouped into at least three broad, non-exclusive categories: 1) influenza-specific mechanisms, including mitigation of damage secondary to influenza infection and/or epitopic similarity between influenza proteins and AD pathology; 2) non–influenza-specific training of the innate immune system; and 3) non–influenza-specific changes in adaptive immunity via lymphocyte-mediated cross-reactivity."
It indicts everyone still huddled around the amyloid lamppost.
Related (not exhaustive. The infectious theory is rapidly gaining ground especially in light of anti-beta-amyloid drugs repeatedly failing in clinical trials):
* HSV/Alzheimer's: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8234998/
* HSV/Alzheimer's: https://content.iospress.com/articles/journal-of-alzheimers-...
* HSV/Alzheimer's: https://pubmed.ncbi.nlm.nih.gov/29488144/ (current independent phase 2 trial to reproduce outcomes: https://clinicaltrials.gov/ct2/show/NCT03282916)
* Gingivitis/Alzheimer's: https://pubmed.ncbi.nlm.nih.gov/32280099/
* Immunological role of Beta-Amyloid: https://alz-journals.onlinelibrary.wiley.com/doi/full/10.100...
Tdap vaccination is also apparently protective. So, probably too chicken pox vaccination, shingles vaccination, and periodic valacyclovir dosage. Maybe even HPV.
You don't need very good reasons to keep up on your vaccinations.
If you had chicken pox (even asymptomatic), that puts you at especial risk for shingles; not surprisingly, as it is a retrovirus.
I had chicken pox, and got the shingles vaccine. They did not ask.
Frankly, Alzheimer’s prevention makes it seem a hell of a lot more worthwhile to those that are young and healthy.
It is not known whether spacing them out is better, for this specific purpose, or all at once. It is easy to invent plausible arguments for each. Only the data can choose.
And that's just one, who is even admitting anything, the others can be funded through various shell companies which looks at first unrelated to pharma and claim they have nothing to disclose. You won't bite hand that's feeeding you.
I take any research pushing vaccination (especially something like flu vaccines which are pretty much placebo with 10-60% efficacy if you are lucky [1] [2], if not 0%) with big grain of salt nowadays after our experiences with these "safe and effective" COVID vaccines, which were proven to be not so safe and hardly effective at all.
[1] https://www.science.org/content/article/why-flu-vaccines-so-...
[2] https://www.ecdc.europa.eu/en/seasonal-influenza/prevention-...
Although, Tdap and flu vaccination are pretty strongly correlated.
It was noticed, thus prompting these studies.
They then checked a completely disjoint population, in a different health-care system, and got the same number.
I went out and got an over-the-counter Tdap vaccination at a local pharmacy, because how good does your reason for a vaccine booster need to be?
I think it just proves people with dementia are less likely to remember to get a flu vaccine.
I think you may have misread the fine article.
Symptoms were observed to develop (or not develop) after a flu vaccination shot.
Prior to that the decline can be decades in the making. My gran obviously had dementia for 15 years before her diagnosis, by the time she was given it the only words she could say was "keep on keeping on"
Specifically to your most recent point, however, I'd observe that if treatment diagnosis is delayed as long as possible to avoid the stigma, that would put back treatment diagnosis for both groups, so it's hardly a compelling distinction there.
Anyway, I'd expect people with dementia at the time of their flu shot would have been assessed by the caregiver, and they would probably have been taken to the clinic by a family or friend anyway.
The compelling anecdote of your gran notwithstanding, of course.
Its called selection bias.
The root cause of the measurement issue is that people are less likely to get the flu vaccine if they have dementia. People who had the flu vaccine are already much less likely to suffer cognitive decline even if the flu vaccine was a placebo.
This sort of stuff is why double blind RCTs exist and have millions spent on them.
Also why all the dementia treatments to date failed to work, because these issues are so often ignored.
Also perversely - mental assessments are typically carried out on people who doctors "dont" think have dementia (to rule it out as a cause of symptoms)
Consider this "back of the envelope" calculation. 10% of the population will develop dementia. having early dementia symptoms makes you 50% less likely to get the flu vaccine. 70% of people get the flu vaccine.
If you randomly selected 200 who didnt get the vaccine and 200 who did from this group, you would expect to see only 13 of the 200 develop dementia when vaccinated, but 53/200 in the unvaccinated group.
https://content.iospress.com/articles/journal-of-alzheimers-...
They controlled by excluding patients if:
"they had a diagnosis of mild cognitive impairment (MCI), encephalopathy, or dementia of any cause during the look-back period, or if they filled a prescription for a medication indicated for AD"
Therefore they didnt exclude patients with early signs of cognitive impairment (because it is not possible to do so, because it is not recorded anywhere)
If your position continues to be that their numbers are skewed - and this is a HUGE correlation here - exclusively because people with dementia will forget to get a flu vaccination, then a) I think you are making unsupported claims, and b) you're arguing with the wrong person.
Perhaps throw the authors of the study a line and suggest this alternative hypothesis for the numbers they saw across their sample set of ~ 1 million people.
But I also said, all they "proved" is that people who dont forget to get the flu vaccine are less likely to develop full blown dementia.
Just to bear that in mind if you think it brings us any closer to preventing/treating/curing dementia.
Maybe, early pre-diagnosis aspects of eventual Alzheimer's (such as undiagnosed mild cognitive impairments) makes people less interested in, and diligent in pursuing, flu vaccinations. (In other words: the causality goes the other way.)
But also, people with active family/social lives are both more likely to be reminded to get a flu vaccine, and less likely to develop Alzheimer's.
And further: more conscientious people seek out vaccines. More conscientious people get Alzheimer's at a much lower rate. For example, this study - https://jamanetwork.com/journals/jamapsychiatry/fullarticle/... – suggests those in the 90th percentile of conscientiousness have 89% lower rates of Alzheimer's diagnoses than those in the 10th percentile of conscientiousness.
While a mechanism from vax-induced immunity, and/or fewer actual infections, to less dementia is plausible, these other well-known correlates/confounders seem a likely explanation for these results, until/unless controlled-for.
Cause-and-effect chains form a DAG (Directed Acyclic Graph). For example, A causes B causes C, in theory (or in this case, A causes B prevents C. Cause vs prevent doesn't really matter, its just a negative on the correlation diagrams)
In this case, we want to determine if "Flu Vaccination causes/prevents Alzheimer's Disease".
Now lets consider a bunch of real life factors. Wealth, Age, Sex, Race, Educational Attainment, Insurance. Just the basic stuff anyone would think about. Lets focus on Educational Attainment + Insurance to keep things simple.
* Education -> Flu + Education -> Alzheimer's? Or is it the case that "stronger mind -> Education -> Flu Vaccines" and "stronger mind -> Education -> Alzheimer's" ?? Education is almost certainly a conflating situation (Education would probably cause higher flu vaccine uptake, and simultaneously would reduce Alzheimers), so maybe the Flu vaccine isn't causing the effect... but is instead just a cross-correlation to education level.
* Insurance probably causes flu-vaccines (because flu vaccines are free for most insurance plans). Insurance probably doesn't cause/prevent Alzheimer's though. So we have "Insurance -> Flu-vaccine -> Alzheimer", which means we don't have to worry about a cross-correlation in this case.
--------
Etc. etc.
Basically: to truly understand if we have a cause-and-effect situation here, we need to think of all possible conflating factors (such as education), while discounting factors that are "along" the DAG-chain towards the hypothetical result (ex: Insurance).
After that, there's apparently a lot of math and analysis that we can do. If we take the records of the people who participated in this study, and get their educational levels + insurance information, we can then account for these conflating factors.
I probably messed up the language and everything else for that matter. But just a reminder that public health discussions are rather technical. There's both a science and an art to the whole process, and just reading the "results in the raw" could lead to a misunderstanding.
----------
The best example of this is "Ice Cream causes Drowning". (Real life: Hot summer temperatures cause ice-cream consumption. Hot summer temperatures cause people to swim.) We need to account for the Hot-temperature effect if we want to find the truth behind that correlation.
There's also the chance that we've got it all backwards. Alzheimer's causes people to stop taking the flu vaccine. (IE: Alzheimer's might cause people to be more easily swayed by anti-vax propaganda, causing them to take less flu vaccines)
Figuring out all possibilities (as well as possibilities that aren't even listed) is the job of a public health care specialist. They'll get it wrong, but hopefully less wrong than you or I would. There's apparently mathematical techniques to be used to tackle each of these questions I brought up.
The study measured an extensive list of covariates [1]. The data source, "medical claims, pharmacy claims, administrative claims, and laboratory result data for privately insured or Medicare Advantage with Part D enrollees who have both medical and prescription-drug coverage" [2], excludes the uninsured and those without Medicare Part D, so that's not a confounder.
I'm having trouble finding a bias that would create this effect size other than reverse causation, i.e. people developing AD forget to get their flu shots.
[1] https://content.iospress.com/download/journal-of-alzheimers-...
[2] https://content.iospress.com/articles/journal-of-alzheimers-...
Hmmm... figuring out a possible mistake would require quite a bit of creativity. Creativity that's beyond my abilities at least, lol.
Note that having such a list hampers a lot of "creative" attempts to take down the study. For example, Tobacco Use is very clearly related to the Republican/Democrat divide, and is therefore an adequate stand-in for the effects of political views (in case political views have an effect on flu-vaccinations / Alzheimer's).
So anything "correlated" to these other covariates (ex: Red vs Blue states vs Tobacco) is "already factored in". As such, having a very, very big list like this helps dramatically.
That there is 40% less incidence in flu vaccinated patients is established by observation, but is it due to flu vaccine by itself or factors which surrounds itself in people more prone to flu or who are medically more conscious? (edit: think of analysis of variance tests among identifiable medical & socioeconomic variables). If the researchers establish a positive link, wouldn't it be worthwhile to then suppose that amyloid plaques are somehow related to viral influenza replication - which by itself sounds a bit absurd (edit: Ok lot of good reference about infections around AD. I take this back, my bad)
The alternative hypothesis is worth thinking too: Are people more prone to Alzheimer's also more prone to catching flu.
This is a prominent theory for the cause of Alzheimer's disease [1].
From the abstract:
> Propensity-score matching (PSM) was used to create flu-vaccinated and flu-unvaccinated cohorts with similar baseline demographics, medication usage, and comorbidities.
If you want to argue that the authors did a bad job at this, for some reason, that would be a really meaningful contribution and I'd love to hear the details.
Otherwise, can we assume that the scientists writing and reviewing papers did a semi-competent job and are at least as good at analyzing quantitative claims as someone commenting on HN because they are bored at work?
Sometimes HN can do this or turn simple topics into some crazy meta stuff… I’m telling you so many times some comments look like what I will find in a parody of HN and/or bring no real value to the discussion but are so articulated and counter arguing and expanding and what not. Heck half of the times those comments start a new paragraph mid comment with « Heck… ». And they all look the same. /renting
- http://www.tylervigen.com/spurious-correlations
- (honorable mention: https://xkcd.com/552/ - gets cited less often but is relevant nonetheless)
What is your contribution by this rant exactly, except making yourself look absurd?
No, but correlation isn't meaningless either. This study [1] appears to be as robust as one can get without doing a double-blind trial. Given the effect size, I suspect that is in the works.
[1] https://content.iospress.com/articles/journal-of-alzheimers-...
And with a proper survey, you can actually account for a lot of these effects. (Ex: after accounting for outdoor temperatures, the Ice Cream Sales / Drowning correlation can be largely factored out).
Imagine thinking this study and those datasets are remotely the same.
And no, checking whether they had it beforehand doesn't help, it starts to develop many years before its symptoms are so strong that you identify them as Alzheimer's, forgetting rare and optional appointments certainly wouldn't be enough to say it is Alzheimer's yet. That is why scoring well on an IQ test also "protects against Alzheimer", it isn't that the IQ test protects you, it is that the IQ test can detect effects of Alzheimer's before a diagnosis can see it.
* You posted it during a time of day when the site receives less traffic, and it scrolled too far down or off the New page for people to see it and vote it up. (Looks like you posted during lunch time on the US west coast, so maybe this isn't likely.)
* When you posted, there was other big news or something going on that people were absorbed in, and didn't notice your post.
* Some don't visit HN multiple times a day, and perhaps you just got unlucky that many of the people who would have found this interesting didn't see it 2 days ago, but did happen to be around today.
* Your account was created three days ago, and I wouldn't be surprised if HN doesn't weight upvotes on new-account submissions as highly as for older accounts. Also consider that your first submission (the day before) was flagged and killed; that might put you in a time-limited penalty box. (I don't know any of this for a fact, as I have no idea how HN's software works, but it seems plausible.)
* Just dumb luck. I've made a bunch of submissions that I thought were interesting (and though would appeal to a wide variety of HN readers/commenters), but it just turned out that it wasn't the case. Maybe it was just timing or something else.
I believe the mods have stated that HN allows duplicate links within a shorter-than-normal time period if the previous posting didn't get much attention, so it's perhaps not surprising that the software allowed the repost.
Looks like it's UTC, so early Saturday morning vs after lunch Monday.
> * When you posted, there was other big news or something going on that people were absorbed in, and didn't notice your post.
Roe v Wade
HN disallows reposts within 8 hours or if a story has had significant attention in the last year, but neither of those were the case with this repost, so our software allowed it to go through.
I know it's frustrating when your submission 'loses' and someone else's 'wins', but since it's random, it at least evens out in the long run if you submit lots of good stories. Eventually we'll implement some sort of karma sharing to take care of this.
Without a proposed method of action, I suspect this is just noise.
[1] https://content.iospress.com/articles/journal-of-alzheimers-...
A study of this size would not be conducted by idiots. HN has no such filter, though.
> 1) influenza-specific mechanisms, including mitigation of damage secondary to influenza infection and/or epitopic similarity between influenza proteins and AD pathology; 2) non–influenza-specific training of the innate immune system; and 3) non–influenza-specific changes in adaptive immunity via lymphocyte-mediated cross-reactivity.
I don't think the paper or the journal article suggested it was causal either. But such a correlation with such a large population warrants publication and further research into causation.
You unfortunately chose literally the first thing that any epidemiologist would consider, which is considering potential confounders. Maybe read up a bit before commenting.
https://content.iospress.com/articles/journal-of-alzheimers-...
You played yourself.