I’m curious about your take on the influence of the healthy user bias on nutrition research. On the one hand, it makes a lot of sense that populations with increased consumption of (insert largely criticized food group/nutrient here) would also have behaviors that negatively impact health. On the other hand, the healthy user bias seems like an easy way to discredit any research that isn’t perfectly aligned with someone’s agenda.
How does the medical/scientific community account for this and avoid potentially expecting a higher than necessary degree of behavior change from people pursuing various health outcomes?
My understanding is that the healthy user bias is when a sample selection creates some level of unintended discrepancy between the two samples that draws skepticism toward the conclusion. One of the more common examples I see is when someone is criticizing a study on vegan/vegetarian vs. omnivorous diets. Since the vegan/veg population is logically more likely to partake in other health promoting behavior (caloric restriction, exercise, non-smoking, etc.), it’s difficult to draw conclusions pertaining to which effects studied are a result of the absence of meat. Is that not a correct use of the term?
From what I’ve seen (very limited - I’m an accountant), researchers will do replacement studies and try to equate calories. Your red meat article touches on this with the replacement of saturated fats with monos, polys, and complex carbs.
Conversely, I’ve seen fitness personalities use healthy user bias to criticize findings. I’ll use red meat as an example here as well - since a population of people who consume large quantities of red meat are probably less likely to partake in health promoting activities, it’s easy to simply throw away the results of a study a red meat advocate finds unfavorable because the participants don’t even lift bro.
I understand in this example the fitness personality is not making an entirely logical argument, but there’s a degree of logic to the general idea since it seems near impossible to control for so many variables.
Observational studies make inferring causal relationships difficult in general, but I do think selection bias can play a role in some skewed findings. In nutrition, we’d like to see multiple lines of converging evidence to feel somewhat confident about making claim.
From what I’ve seen (very limited - I’m an accountant), researchers will do replacement studies and try to equate calories. Your red meat article touches on this with the replacement of saturated fats with monos, polys, and complex carbs.
Yea, those are RCTs, not observational studies- thus not observational or really subject to selection bias (for the most part.
Conversely, I’ve seen fitness personalities use healthy user bias to criticize findings. I’ll use red meat as an example here as well - since a population of people who consume large quantities of red meat are probably less likely to partake in health promoting activities, it’s easy to simply throw away the results of a study a red meat advocate finds unfavorable because the participants don’t even lift bro.
They would be wrong in this particular case based on a number of lines of evidence. When selection bias is identified, it weakens the findings, sure, but fortunately there is additional data showing similar results, e.g. converging lines of evidence.