https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD...
https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD...
There was little or no effect of reducing saturated fats on non‐fatal myocardial infarction (RR 0.97, 95% CI 0.87 to 1.07) or CHD mortality (RR 0.97, 95% CI 0.82 to 1.16, both low‐quality evidence), but effects on total (fatal or non‐fatal) myocardial infarction, stroke and CHD events (fatal or non‐fatal) were all unclear as the evidence was of very low quality. There was little or no effect on cancer mortality, cancer diagnoses, diabetes diagnosis, HDL cholesterol, serum triglycerides or blood pressure, and small reductions in weight, serum total cholesterol, LDL cholesterol and BMI."
This is your citation for saturated fat is evil?
And yes, that is my citation in support of that claim. Quote: “There was a 17% reduction in cardiovascular events in people who had reduced SFA compared with those on higher SFA”
and
“When we subgrouped according to replacement for SFA, the PUFA replacement group suggested a 21% reduction in cardiovascular events”
I explain why the null findings on insensitive endpoints aren’t the gotcha some people think they are here: https://news.ycombinator.com/item?id=41960046
they have table with breakdown of events by type, and in both rows with significant reduction it says that quality of evidence is "very low".
One of the main purposes of meta-analyses is to summate multiple studies that may have insufficient statistical power in isolation to find a significant effect, but when summated they do.
I _think_ you're trying to suggest that the insignificant individual event types aren't contributing to the significant findings on the combined event endpoint, so we should ignore the GRADE quality of those (correct me if I'm wrong). But that's not how meta analysis functions - those events are also contributing to the significant finding on that endpoint (which is also why the GRADE quality of the combined endpoint is moderate). They just aren't significant _in isolation_.
to me, it looks like several rows clearly don't add up in key findings table(they derive "moderate quality" conclusions from "very low quality" observations), which makes whole publication as data astrology quality.
I salute your self confidence, I must say I’m somewhat envious of it.
It’s just that you’re blaming the studies, rather than your comprehension.
Please be specific: name the event subtypes you’re looking at, give specific references to the table numbers etc. If I’m wrong about this, I want to know.
If the conclusion that comes out of the other end of the pipeline is that we should avoid eating the things we’ve eaten for millions of years, it’s fair to say what went in might have been based on false premises.
Heck, water treatment plants are novel compared to the pathogen-laced water we’ve been ancestrally consuming, but I doubt you eschew tap water for puddle water.