CRP is used like paint to cover just about everything. One of doctors looked at my previous bloodwork that showed elevated CRP and said, "Yeah, you know what can raise CRP? Really bad seasonal allergies. Pain from autoimmune disorders. A broken bone. A bad job that's giving you severe stress."
As Dr Zha said, CRP is sometimes used to determine risk of heart disease. I remember some years ago when this kept cropping up as "People who have had heart attacks have high CRP levels; therefore, CRP tests prove heart disease." And finally someone with a clue said, "Hey, what was their CRP level before the heart attack?" No answers; the tests were only being done post-event. Perfect example of confirmation bias.
As for weight loss vs CVD risk: I think LOOK AHEAD is a great example here. They took two groups of fat diabetics and put one group on weight loss to see if they'd have less CVD & "early deaths" from heart disease. A 20 year study, it was stopped after just 10 years because both groups were dying at the same rate. (Of course, now the results are being data-mined to pieces to "prove" all sorts of weight loss nonsense, in the same way the Framingham study was.)
"The paint to cover just about everything" what a good analogy, it still is even though its 2025. My CRP is high looking at the possible things that elevate CRP lol.
Thank you for mentioning the look AHEAD study which had 16 participating centers and thousands of patients. They stopped early due to "futility." The intervention group had a sharp decline in study measures by year 1 but a "gradual" increase in the following years up to year 10. The graphs didn't look that gradual to me and the convergence between the two groups was apparent if the study were to continue. It still concluded, "overweight or obese adults with type 2 diabetes can lose weight and maintain modest weight loss during a 10-year period" even though this weight loss didn't appear to be meaningful in their study objectives.
Not exactly a study on inflammation and weight but certainly a good example of how even "futile" data can be used to fuel our biases.
I had some trouble understanding the first part of this message, so I recruited a friend who has a graduate degree in theoretical mathematics, and I think there are a couple of typos in your theorem. I'm pointing these out not to discredit your argument but because I think this message is so important and I don't want it to get lost.
Below, I'm assuming "A is associated with B" means "A → B" and "A is correlated with B" means "A & B" because that is my understanding of the words "associated" and "correlated" in this context. If you're using them differently, I'd appreciate the clarification.
First, I believe you intended to use "weight ↓ → inflammation ↓" as the theorem because the theorem you're examining is that weight loss CAUSES a reduction in inflammation, not that weight loss and reduced inflammation are equivalent.
Second, for condition 3, I believe that you meant to write "weight ↓ !→ inflammation ↑".
Third, for condition 4, I believe you meant to write that "inflammation ↑ !& weight ↓". Statements about weight going up are not logically related to any associations with weight going down.
CRP is used like paint to cover just about everything. One of doctors looked at my previous bloodwork that showed elevated CRP and said, "Yeah, you know what can raise CRP? Really bad seasonal allergies. Pain from autoimmune disorders. A broken bone. A bad job that's giving you severe stress."
As Dr Zha said, CRP is sometimes used to determine risk of heart disease. I remember some years ago when this kept cropping up as "People who have had heart attacks have high CRP levels; therefore, CRP tests prove heart disease." And finally someone with a clue said, "Hey, what was their CRP level before the heart attack?" No answers; the tests were only being done post-event. Perfect example of confirmation bias.
As for weight loss vs CVD risk: I think LOOK AHEAD is a great example here. They took two groups of fat diabetics and put one group on weight loss to see if they'd have less CVD & "early deaths" from heart disease. A 20 year study, it was stopped after just 10 years because both groups were dying at the same rate. (Of course, now the results are being data-mined to pieces to "prove" all sorts of weight loss nonsense, in the same way the Framingham study was.)
"The paint to cover just about everything" what a good analogy, it still is even though its 2025. My CRP is high looking at the possible things that elevate CRP lol.
Thank you for mentioning the look AHEAD study which had 16 participating centers and thousands of patients. They stopped early due to "futility." The intervention group had a sharp decline in study measures by year 1 but a "gradual" increase in the following years up to year 10. The graphs didn't look that gradual to me and the convergence between the two groups was apparent if the study were to continue. It still concluded, "overweight or obese adults with type 2 diabetes can lose weight and maintain modest weight loss during a 10-year period" even though this weight loss didn't appear to be meaningful in their study objectives.
Not exactly a study on inflammation and weight but certainly a good example of how even "futile" data can be used to fuel our biases.
I had some trouble understanding the first part of this message, so I recruited a friend who has a graduate degree in theoretical mathematics, and I think there are a couple of typos in your theorem. I'm pointing these out not to discredit your argument but because I think this message is so important and I don't want it to get lost.
Below, I'm assuming "A is associated with B" means "A → B" and "A is correlated with B" means "A & B" because that is my understanding of the words "associated" and "correlated" in this context. If you're using them differently, I'd appreciate the clarification.
First, I believe you intended to use "weight ↓ → inflammation ↓" as the theorem because the theorem you're examining is that weight loss CAUSES a reduction in inflammation, not that weight loss and reduced inflammation are equivalent.
Second, for condition 3, I believe that you meant to write "weight ↓ !→ inflammation ↑".
Third, for condition 4, I believe you meant to write that "inflammation ↑ !& weight ↓". Statements about weight going up are not logically related to any associations with weight going down.
Ah, I see what you are saying now! That's a great point! Thank you.