this post was submitted on 29 Aug 2025
92 points (88.3% liked)
Public Health
1032 readers
105 users here now
For issues concerning:
- Public Health
- Global Health
- Health Systems & Policy
- Environmental Health
- Epidemiology
- etc.
🩺 This community has a broader scope so please feel free to discuss. When it may not be clear, leave a comment talking about why something is important.
Related Communities
- Medical Community Hub
- Medicine
- Medicine Canada
- Premed
- Premed Canada
- Public Health (📍)
See the pinned post in the Medical Community Hub for links and descriptions. link (!medicine@lemmy.world)
Rules
Given the inherent intersection that these topics have with politics, we encourage thoughtful discussions while also adhering to the mander.xyz instance guidelines.
Try to focus on the scientific aspects and refrain from making overly partisan or inflammatory content
Our aim is to foster a respectful environment where we can delve into the scientific foundations of these topics. Thank you!
founded 2 years ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
Don't you think calling a proportional hazards model "guessing" is doing a disservice to Lemmy posters here? Not everyone has a background in statistics, and honestly quite a few people here struggle with highschool math. It's not much different than linear regression. Its fancy linear regression, not fancy guessing.
Does their model not fit or something?
At its most essential level - when you have a epidemiology dataset you don't know the relationships until you analyze the data, in order to make controls for some factors in the data you have to assume some relationship for that factor. It's typically assumed to be some linear relationship. If you knew the relationship between factors with certainty, you wouldn't need a epidemiological dataset in the first place, but since we are trying to control for a confounder by definition we don't know the relationship. It is a guess in colloquial terms, a educated guess to be sure, but still a guess.
This is a good overview of cause and effect in inferential statistics, and confounders (start at the 5 minute mark) https://www.youtube.com/watch?v=n4YV7tEtg3I
If you prefer something written with more rigor: https://pmc.ncbi.nlm.nih.gov/articles/PMC4017459/
This is a critical weakness of epidemiology when inferences are made about something not directly measured.
while all true, I'm taking issue with you calling it guessing, not that it's a perfect method.
also, we use epidemiological data because it's kind of hard to do a double blind study where you tell some group of people to eat meat for 20 years, and another group of people to not eat meat for 20 years, and then have them live exactly identical lives for that 20 years.
you're kind of not mentioning that. it's kind of dishonest when the audience (Lemmy) is full of layman who are definitely not reading your linked citations, I certainly don't have time to. I'm not defending this study at all because I haven't read it, I'm just taking issue with how you are presenting these (useful) techniques
These are useful techniques to generate hypothesis to test, absolutely!
The results from epidemiology, especially weak hazard ratios, and poor confounders, really have no business being publicized to lay people to get them to change any aspect of their life.
Sure, but that isn't science. Science is a falsifiable hypothesis that can be tested, if we say we can't test these things then we are not in the realm of empiricism but of theology. That is fine, but we should be clear that the message isn't backed by science.
Good lord there should be a confirmation for the delete button.
Anyway,
This is certainly a problem with science reporting.
I would like to know how you think we've established the link between smoking and cancer. Or air quality, etc. It's just a tool, not something perfect.
This is the key of my issue with your statements here. I am no vegetarian. When you are being hyperbolic like this, it makes everything else you say suspect.
Ah, Good question! I do cover this in my evidence standards post (i know, I know, no time to read, but I'll quote the bits here) https://discuss.online/post/25820268
I'm not being hyperbolic, if the response to feedback about the rigor of something is that the thing is untestable, that is no longer science.
Depending on your lemmy interface there should be a undelete button too.
Yes, fine, this is what I am saying: Take issue with the findings of the model, not epidemiological data (edit: as a technique that is akin to theology). Focus on that.
It was theology before, but now that hazard ratio is fine, because the number is big? There's big numbers in the bible too, friend. This is what I would call hyperbole. Either it's theology or it's not.
I totally agree with you, actually.
However, this is so rare, that it is exceptional.
It does not prove causation, there is no downside to giving up smoking, so why not? Does smoking cause cancer in all circumstances, no. So, give up smoking, sure why not. Does smoking cause cancer? It hasn't been proven.
There is more nuance here, in some contexts smoking is correlated with cancer. I have my own personal theories on the incidence of cancer increasing even though smoking has existed throughout documented history, but that is neither here nor there.
To you there is no downside. People actually do take up smoking for reasons. For example, I have worked shitty jobs where smokers get extra breaks, or get extra time to bullshit with the boss. They also might do it because they feel it looks cool. These are not valid reasons for me (being that it is unhealthy, expensive, and messy). It sure seems like I'm being nit picky here, but this statement just isn't true! It's also pretty hard to quit if you've started, why bother doing it? The money may be less important than the downsides of withdrawals there. It's why it's important to point out that smoking is bad for you, and epistemological studies is one of the tools we have for that.
Similarly, people give up meat for reasons that do not make sense to you: It can be expensive, it can contain pathogens, industrial farming is a blight, etc etc etc. For them, the benefits do not outweigh the negatives. I'm not litigating this. I'm just pointing it out. I eat meat. This isn't part of my identity, it is the force of gravity for me. Eating meat is easy.
Incredible that you're speaking about nuance when you've just called epistemology theology. I mean I totally agree with you, the devil is in the details, but.... damn dude. :')
Ah, I see our disconnect. I don't think of epidemiology as theology at all. I think of the abandonment of science throwing up all enquiry on a subject because its hard to test, but still using weak epidemiology to inform public policy, guidelines, and even lifestyle... that is theology.
Epidemiology is a tool that can be used in science, it is hypothesis generating after all, but by itself it is not science, it is a part of science, not the end of science.
Weak epidemiology can be engineered for any result you want... Paper - Grilling the data: application of specification curve analysis to red meat and all-cause mortality
Yes, there does seem to be a disconnect here.
Using weak epidemiology to inform public policy, etc, is bad.
Calling epidemiology guessing, or saying that it's use is "not in the realm of empiricism but of theology" is hyperbole. If you're going to critique a paper because it's being presented to a layman audience, you should probably avoid that (that being: exaggeration. Don't do that.).
This has, more or less been my point for this entire comment chain. Your exaggeration is harmful to your overall argument. Especially because people take up a sports-team sort of ideological following for eating meat vs not eating meat. I'd be especially avoidant of exaggeration for that reason.
I didn't say epidemiology was guessing
I said the statistical controls for confounding variables are guesses. And that is true
I didn't say epidemiology was theology.
The abandonment of science, falling back onto week epidemiology is theology
I don't know how to express this more clearly