Well, it would - in the sense that an unbiased study might still find that a meat-eater (i.e. the average person) is less healthy than someone who doesn’t eat meat, and then falsely conclude that meat is the reason, rather than accounting for all the other lifestyle differences. Meanwhile, a study funded by Big Meat would obviously find that meat is good for you - which, let’s not forget, could also be true.
The left/blue side of the graph are outcomes that show meat decreased all cause mortality, the right/red side of the graph are outcomes that show meat increases all cause mortality. If you were a hungry researcher, you could publish unending papers indicating either way from this same observational data pool! - Hence the constant news cycle driven by dietary agendas - not based on hard science RCTs.
The problem with open-ended observational studies, is you can’t prove causation, and you can find tons of associations for or against whatever you like.
when investigators analyze data from observational studies, there are often hundreds of equally justifiable ways of analyzing the data, each of which may produce results that vary in direction, magnitude, and statistical significance
Evidence shows that investigators’ prior beliefs and expectations influence their results [5]. In the presence of strong opinions, investigators’ beliefs and expectations may shape the literature to the detriment of empirical evidence
Then somebody will come along and do a metanalysis of the studies that were just basically association farming. And claim to find some universal truth… at a certain point we have to look at these observational studies as not science, hell it’s not even academics, it’s advertising, propaganda, and agenda pushing. These are hypothesis generating, they should be the beginning of science, they are not the conclusion of science. And they should never be used for policies, or even marketed to lay people.
Well, it would - in the sense that an unbiased study might still find that a meat-eater (i.e. the average person) is less healthy than someone who doesn’t eat meat, and then falsely conclude that meat is the reason, rather than accounting for all the other lifestyle differences. Meanwhile, a study funded by Big Meat would obviously find that meat is good for you - which, let’s not forget, could also be true.
The left/blue side of the graph are outcomes that show meat decreased all cause mortality, the right/red side of the graph are outcomes that show meat increases all cause mortality. If you were a hungry researcher, you could publish unending papers indicating either way from this same observational data pool! - Hence the constant news cycle driven by dietary agendas - not based on hard science RCTs.
The problem with open-ended observational studies, is you can’t prove causation, and you can find tons of associations for or against whatever you like.
Grilling the data: application of specification curve analysis to red meat and all-cause mortality
Then somebody will come along and do a metanalysis of the studies that were just basically association farming. And claim to find some universal truth… at a certain point we have to look at these observational studies as not science, hell it’s not even academics, it’s advertising, propaganda, and agenda pushing. These are hypothesis generating, they should be the beginning of science, they are not the conclusion of science. And they should never be used for policies, or even marketed to lay people.