I’m really keen on this topic, because I do have high cholesterol. The initial aim of Keto was to actually to get rid of some visceral fat, then switch to low carb instead of full keto to maintain it.
From my understanding, one of the reasons for persistence of the “good fat/bad fat” myth is because like every good “lie”, there’s some truth to it. Here are some of the truths that I’ve found
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Saturated fat raises cholesterol - but only for 90m to 2h after eating it. Longer term rises in cholesterol are linked to eating carbs and an excess of fat around the liver… Caused by eating too many carbs.
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Saturated fat isn’t “bad” for you, but unsaturated fat is “good” for you. How does that work? Well, it’s not a binary equation. If someone was eating for example 50g of Saturated fat, 50G of unsaturated fat for a total of 100g, then gave up all saturated fat to eat only 50g of total fats, there’s no change in their risk of mortality. On the other hand, if they swapped the 50g of saturated fat for unsaturated fats, for a total of 100g of unsaturated fat, then their risk of early mortality drops by about 16%. Apparently, many people can’t get their head around that concept, so they accept the simplified version of saturated fats are bad for you.
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Saturated fats are often contained in things which are bad for you, such as cakes and donuts, where as unsaturated fats are often in things which are good for you, such as salad dressings. So it correlative, not causative. Large scale experiments are REALLY expensive to fund (Imagine buying 1000+ people all their food for 10 years to control the experiment, and also having to pay for enforcement - so that participants aren’t sneaking in other food). Observational studies are cheaper, but often have difficulties separating correlation with causation.
I always grimace when people without a science background misunderstand what makes a experiment or study good quality or not. There are experiments which only require very small sample sizes, but anyone who doesn’t want to agree with the finding, calls them worthless. I usually say to them. “Just say you want to create an experiment that will determine whether a gun is loaded or not. How many samples will you need before you are satisfied that your result is reliable?”. That usually confuses them, because they don’t see the relevance, yet many findings in health are the basis of experiments, not observational studies.
Anyway, I’m going to stop ranting, but I did want to make the point that anyone who is relying on an academic study, really needs to educate themselves on how that study was performed and the quality of the study.