Flu vaccination linked to 40% reduced risk of Alzheimer’s disease

The scientists said it was causation.

    "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"

Yes, that's in an interview for the article. That's the reason (1) the general public misunderstands (2) people scream about it. Scientists get points for "high-impact research," and there is strong incentive to be dishonest.

(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.)

>The scientists said it was causation.

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.

I've always read "protective effect" to be making a predictive statement and not a causal one.

In the interview he seems to be more loose with his words, but that also doesn't say causation. In the paper the conclusion is "This study demonstrates that influenza vaccination is associated with reduced AD risk in a nationwide sample of US adults aged 65 and older."

That is distinctly not causal.

Sitting down and talking it's often hard to be as precise as you would like to be. Especially when you don't have time to reflect on the implications of what you've just said.

This is a mischaracterization of even the words you've quoted.

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.

I disagree that's a mischaracterization.

> 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.

"Reduce" is also an action verb that means causation.

“The team did indeed find that suntan lotion reduced the risk of rain. But he specifically doesn't say they know why the suntan lotion lowers the risk.” - spandrew, probably

<--- Best comment ever.

This comment (and often the "correlation != causation" discussion more generally) seems to equate "causation" with "proof of causation" (in a mathematical sense), which is a flawed criteria for science IMO. The causation part (not the mere association) is the substance, so it's appropriate to use causal language.

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-...

> They can't claim causation if they don't understand the underlying reason for the change. That's not how science works.

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.

It's a little more nuanced. Causation can be inferred in an experimental design. If the researchers can manipulate the independent variable (the vaccine) using an experimental and a placebo group, and then they can measure a statistically (and clinically) significant difference, then we can assume that this is not just correlation.

They were very precise about causation in the interview.

They just can't include it in the paper because reviewers will make sure to remove it

The quote isn't offhand, it's directly and explicitly making claims of causality, e.g. talking about the "effect" and saying the vaccination "reduces the risk".

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 missed my point. I don't actually think the quote was offhand either (another comment suggested that possibility), but the lines from the paper I cited also uses causal language. My point is that using causal language is fine (understanding that it's provisional as all science is), and I think the scientist quote is fine.

You think the scientist quote is dishonest? It seems you too conflate causality with something like proven mathematically or 100% confidence.

If they're going to claim causality for vaccines->less Alzheimers then yes, they need pretty close to 100% confidence for that because this is the sort of thing that gets translated into mandatory government policies. What they have here is literally nothing, it's just a correlation. They don't have any evidence of a causal relation, and they don't have any suggested biological pathway either. It's malpractice to assert causality given such a total absence of evidence.

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.

The presence of protective effects reduces the expectation of future observations of something, and merely describes temporal correlation. I so far just see standard language used in literature.