33: What Actually Moves Your Cholesterol (And Why It’s Not What You’ve Been Told) Part 2

RECAP AND WELCOME

Last week I told you that the 5 to 6% saturated fat target was created from substitution studies rather than trials that tested that specific threshold in people eating their own food, that the foundational research behind these specific guidelines was conducted almost entirely in men, and that hitting 6% is extremely difficult to sustain in typical free-living conditions, meaning you are living your life, eating your own food, making your own food, even if you only eat the foods the American Heart Association recommends. If you have not listened to Part 1, go back and start there. It sets everything up for what we are about to cover.

Good morning and welcome back to Mornings with Megan. This is Part 2 of our saturated fat series. Today we are getting into the data. What actually moves your lipid numbers, why your response may be completely different from someone else’s, and what I found in my own experiment. Let’s do this.

APO-B AND LDL-C: A QUICK RECAP

I touched on the ApoB and LDL-C distinction in Part 1, and I want to build on that briefly here before we get into the comparison because it reframes what we are about to talk about.

Quick recap: LDL-C measures the total amount of cholesterol cargo across all your LDL particles. ApoB counts the number of particles directly. For roughly 70 to 80% of people, those two numbers move together. And if that is you, all of the LDL research we are about to discuss is directly relevant to your situation.

For the remaining 20 to 30%, they diverge. And when they do, ApoB is the better predictor of cardiovascular disease risk because atherosclerosis is driven by how many particles are getting into your artery walls, not the total cholesterol those particles are carrying.

Here is why this matters for today’s episode specifically. Almost every study we are going to talk about was designed around LDL-C as the primary outcome. ApoB was either not measured, measured secondarily, or added to studies more recently as the field has evolved. So when I say this intervention lowered LDL by X points, I want you to hold that awareness that LDL-C and ApoB do not always tell the same story. Where the ApoB data exists, I will call it out. Where it does not, I will say so.

WHAT ACTUALLY MOVES LDL: THE COMPARISON

So let me put the interventions side by side so you can see what we are actually comparing. I am going to use a baseline LDL-C of 130 milligrams per deciliter, which is moderately elevated but not alarming, and hold it as a constant across all of these examples.

First, cutting saturated fat. A systematic review of 14 randomized controlled trials found that reducing saturated fat lowered LDL-C somewhere between 5 and 17 milligrams per deciliter depending on the study population and how dramatically saturated fat was actually reduced. So if we are starting at 130 milligrams per deciliter, 5 gets us down to 125, and 17 gets us down to 113. So it is moving the needle, but we are not dramatically moving the needle.

The studies showing the larger reductions started from a typical American diet of 13 to 16% saturated fat under controlled feeding conditions with all food provided. Replacing saturated fat specifically with polyunsaturated fat produced the larger end of that range. This is a real signal. It is also a signal that came from large dietary swings in controlled settings, not from modest reductions in free-living conditions.

On the question of LDL particle size and saturated fat, I want to be careful here because this is genuinely debated territory. Some research suggests saturated fat tends to raise larger, more buoyant, think beach balls, LDL particles rather than the small, denser, more like BB particles. But the more important point, and this is where Dr. Peter Attia and Dr. Thomas Dayspring land, is that size matters less than particle number. Once you account for how many particles are in circulation, the size distinction becomes less predictive of cardiovascular risk. This is another reason ApoB, which counts particles directly, is a better clinical target than LDL-C or particle size alone.

THE TWO KEY TRIALS

Now let’s look at the two key trials in a little more detail because the individual story matters here.

RISSCI-1 used a controlled feeding design in men, lowering saturated fat from about 19% to 9% of total energy, keeping the calories and the fat constant. The mean LDL-C fell by about 19 milligrams per deciliter. So if we are starting at 130, that gets us down to 111, which is meaningful movement in the right direction.

But the individual response ranges from that same study go from a drop of 54 milligrams per deciliter, which is huge, all the way up to a rise of 30 milligrams per deciliter. That is right, a rise. About a third of that variation was explained by factors the researchers could measure, like starting LDL levels and how much each person actually reduced their saturated fat. The rest was not accounted for by what they could actually measure and track. And every single participant was male. We have no data from this study on how women’s LDL responds to the same change.

GET-READI is one of the few trials that actually reaches the American Heart Association’s 6% saturated fat target. Participants followed a DASH-type diet that brought saturated fat down to 6% of total calories compared to a typical American diet at 16%. LDL-C dropped by 12 milligrams per deciliter. Starting at 130, that gets us down to 118, and that is a meaningful result.

But Lp(a) also rose significantly in the same participants on the same diet. I want to be precise here on two things.

First, the population: GET-READI enrolled 166 African American adults, a group in whom elevated Lp(a) is more common. This finding is not automatically universal, though similar Lp(a) increases in the opposite direction from LDL have been observed across multiple other dietary intervention studies as well.

Second, this is an important nuance: Lp(a) is considered a largely genetically determined risk factor. Current guidance is actually to measure it once in a lifetime because it is thought to be relatively stable. What we do not yet fully understand is whether a diet-induced change in Lp(a) over a few weeks translates into meaningful long-term cardiovascular risk in the same way that chronically elevated Lp(a) does. The research is clear that the increase happened. What it means clinically over time is still an open question, and that uncertainty cuts both ways. It is not a reason to dismiss the finding, and it is not a reason to catastrophize it either.

What makes GET-READI particularly relevant for this podcast is that 70% of participants were women, making it one of the very few trials in this space with meaningful female representation. The study that included the most women and hit the actual 6% target is also the one that raised a flag about the separate risk marker Lp(a). Not a reason to dismiss the LDL finding. Just a reason to want the full picture.

FIBER, OATS, AND STATINS: THE REST OF THE COMPARISON

Now let’s compare saturated fat restriction to the other tools we have available.

In free-living conditions, meaning people going about their normal lives, adding 10 grams of psyllium fiber per day drops LDL-C by about 13 milligrams per deciliter. Starting at 130, that gets us down to 117, without changing anything else. Both saturated fat restriction and psyllium husk have strong randomized controlled trial and meta-analysis evidence behind them for LDL-C reduction. What psyllium has additionally is cleaner and more recent ApoB-specific data. The ApoB reduction from psyllium is directly measured and rated as high-quality evidence in a recent analysis. That is meaningful given that most of the saturated fat literature was built on LDL-C as a proxy and did not systematically measure ApoB.

Three grams of beta-glucan from oats, roughly one and a half cups of cooked oatmeal, produces LDL-C decreases of about 10 milligrams per deciliter without driving down HDL or meaningfully affecting triglycerides. I want to be clear that oats are personally off the table for me. If you listened to Episode 20 on my CGM trials, you know that steel cut oats send my blood sugar sky high, enough to set off my workout alarm in a you-are-going-to-die-if-you-do-not-bring-up-your-blood-sugar kind of way. So great tool. Definitely not my tool. This is exactly why individual testing and individual dietary patterns matter.

Then there is the comparison that really puts everything in perspective. Moderate intensity statins reduce LDL-C by 30 to 50%, not points, percent. High intensity statins can reduce it by over 50%. So on that 130 milligram per deciliter baseline, we are talking about reductions of 40 to 65 points at moderate intensity and 65 points or higher at high intensity. That is not a recommendation from me. That is a suggestion that you have a conversation with your provider. I am putting the numbers next to each other so you can see the magnitude of what we are comparing.

I want to be clear that directly comparing the cardiovascular risk reduction from diet and from statins requires some caution because the studies are designed differently and statins have decades of larger event trial data behind them than diet trials do. The direction of the comparison holds. The precise math should be held loosely.

THE MECHANISM: HOW SATURATED FAT AFFECTS YOUR LIVER

Dr. Thomas Dayspring and Dr. Peter Attia have both addressed the individual variability question directly. Here is the mechanism in plain language.

When you eat a lot of saturated fat, it signals the liver to make fewer LDL receptors available. Those receptors are what catch and pull LDL out of your bloodstream. Fewer receptors means more LDL stays in circulation and your levels go up. When you reduce saturated fat, the liver brings those receptors back up and they start catching and clearing more LDL again, and then the levels come back down. That mechanism is real and very well characterized.

But Dr. Peter Attia notes that in his clinical experience, roughly a third to a half of people who consume high saturated fat will also see a meaningful rise in ApoB, while others see no significant change or even a decrease. The range in the RISSCI-1 data, from a drop of 54 milligrams per deciliter to a rise of 30 milligrams per deciliter from that same controlled dietary intervention, illustrates exactly what they are describing. This is not a population-level prescription. This is a personal variable that requires personal testing to understand.

MY PERSONAL N OF ONE

Now I want to share something personal because I think it matters for how you hear the rest of this.

When I had a hard time digesting fat a few years ago, I cut out butter, I dramatically cut back on bacon, removed coconut oil and MCT oil, eliminated cocoa butter except for my square of dark chocolate, cut out ribs, pulled pork and brisket, and stopped cooking with butter, bacon fat, and tallow. I know, seriously, I was on board with keto. My digestion did improve, which was great for me. But it did not move the needle on my lipids in the right direction. My LDL went up. More specifically, it increased by over 30 milligrams per deciliter. That is not a small increase.

This mirrors what the RISSCI-1 data shows. Individual LDL responses to the same intervention range enormously, and a meaningful number of people saw LDL rise rather than fall. I am one of those people. I may simply not be one of the people for whom this lever works the way the guidelines predict.

This is an n of one. It is anecdotal. But it is consistent with the research on individual variability, and it is why I think self-experimentation with proper testing is so much more useful than applying a population-level target to your individual body.

The bigger question when reducing saturated fat is always: what are you replacing it with? I used avocado oil and olive oil for cooking and chose leaner cuts of meat. I added potatoes back into my diet and my triglycerides went up about 8 points. They are still 56, which reflects solid insulin sensitivity. And my HbA1c actually dropped from 5.4 to 5.2. So metabolically I was moving in the right direction. However, the LDL-C story was just not following the expected script for me in my body.

Here is something I do not talk about too often. This whole food landscape has a lot of baggage in it, and that baggage is not always entirely rational. I think it is worth naming. I went to school during the low-carb craze that tied poor metabolic health almost exclusively to carbohydrates. My personal history with Candida reinforced that for years. A low-Candida protocol is no sugar, no alcohol, no vinegar, no starchy vegetables, no grains, and no flour. That framing lived in my body way longer after the evidence of my own life contradicted it.

We all have baggage around food and it is not always rational or aligned with the research. That is not a personal flaw. That is just being human. I share this because I want you to know that your complicated relationship with food has context, and you are not alone in having a lot of that context.

My favorite meatballs have 11 grams of saturated fat for three and I eat six. That is not compatible with 6% of calories from saturated fat. It is just not, and I am not interested in pretending otherwise, because pretending is not useful to either of us.

THE FUEL PILLAR: WHAT ACTUALLY MOVES THE NEEDLE

So what actually moves the needle? Here is where I want to lay it all out, and this is the Fuel pillar of the Perimenopause Matrix.

Fuel is about how your body actually uses energy, how you eat, how your metabolism responds, how the choices you make at every meal compound over time. For a lot of women in perimenopause, the lipid picture is one of the first places the Fuel pillar starts to signal, not because they are doing something wrong, but because the hormonal landscape is shifting under their feet. What worked at 35 may not work the same way at 45. The guidelines that were largely built on research in men may not be the right map for your body in this stage of life.

The biggest lever for most people, outside of medication, is removing processed foods. It is not the strongest direct LDL-lowering tool in isolation, but it tends to improve LDL, triglycerides, blood sugar, inflammation, and metabolic markers simultaneously because it addresses multiple drivers at once rather than one variable in isolation. For me, that lever was mostly pulled. I cook almost all of my meals. An occasional meat stick when I am stuck out somewhere, Hippeas a few times a year, and obviously my dark chocolate almost every single day. And every once in a while Freddie brings me a Nelly’s bar, which I love.

Here is what the research supports in rough order of evidence strength for lipids specifically.

Removing ultra-processed foods tends to improve the full metabolic picture simultaneously because it addresses multiple drivers at once rather than one variable in isolation.

Increasing viscous soluble fiber from sources like legumes, psyllium, oat beta-glucan if you can tolerate oats, pears, apples, and citrus. Not all fiber behaves the same way. It is the gel-forming viscous fiber that physically binds bile acids in your gut and forces your liver to pull LDL out of circulation to make new ones. The wheat bran in your high-fiber cereal is not doing this. The fiber in your lentils and your apple is.

Reducing refined carbohydrates and added sugar, which directly addresses overproduction of atherogenic particles from the liver and improves the lipid pattern most associated with risk in people with insulin resistance. This is particularly relevant for the 20 to 30% of people where LDL-C and ApoB diverge, because that pattern is often driven by insulin resistance rather than saturated fat intake.

Increasing movement. HDL and triglycerides both respond more strongly to exercise than LDL does, but cardiorespiratory fitness is probably the single most powerful predictor of cardiovascular longevity that we have, independent of any lipid number. I cover the sprint and HIIT data in the Move series, Episodes 22 through 24, which will all be linked in the show notes.

Then for people who are saturated fat sensitive, reducing saturated fat may be a meaningful personal lever. The RISSCI-1 data tells us that some people can drop 50 points from the same change that makes someone else go up 30. Knowing which group you are in requires testing, not assumption. The practical approach: get a baseline, change one variable, hold everything else as steady as you can for six to eight weeks, and retest under the same conditions. That is how you find out what your body actually responds to.

WRAP AND CTA

If your doctor has flagged your cholesterol and sent you home with a pamphlet about cutting out saturated fat, I want you to know there is more to the conversation. For some people, medication will be the right tool, and that is fine. That is matching your intervention with the biology. What I am advocating for is not a specific target. It is a process: know your numbers, test one variable at a time, work with someone who can help you interpret what you find.

The Matrix Lab Review is exactly where we start together. Your numbers, your context, your body. The link is in the show notes.

And if this two-part series made you think of a friend who has been stressing over butter and avoiding olive oil, please send it to her. I will see you all next week.