[redka]

Could someone explain to me how could researchers come to these conclusions if there are different factors at play that surely impact the results? The article states that:

> Participants consumed a weekly average of 1.5 servings of processed meat, 3 for unprocessed, 2 for poultry and 1.6 servings of fish. People with higher intake were generally more likely to be smokers, drink more alcohol, have a higher body mass index (BMI) and a lower overall diet quality.

If that's the case then how is it possible for a cohort study to properly control for all of these? Isn't 7% increase in risk basically telling nothing then? The other thing is the methodology. The article says that they used "standard food frequency questionnaire" which I think means Food Frequency Questionnaire. This alone seems like it would have great effects on the efficacy of the research making the results even more questionable.

[superpermutat0r]

They use statistical methods to eliminate the confounding variables. But given that they do not understand the fallibility of doing that on extremely noisy data, the conclusions are telling us nothing.

They cannot control anything and it's all just questionnaires.

It's fine too look at these things but they seem to get blown out of proportion every single time, even when industry funded studies come out saying eggs or bacon is fine.

And yes, 7% increased risk is practically nothing. That's baseline risk multiplied by 1.07. It's noise all the way.

[stefd]

> They use statistical methods to eliminate the confounding variables.

Some of those anyway. You can only account for confounders that you know about a priori.

And given they used Food Frequency Questionnaires, it's mostly wasted efforts imho.