The first thing people say at this point in the discussion (especially doctors) is, “Sure you can lose weight eating a low carb diet, but you’re clogging up your arteries and killing yourself with all that fat!”
Fair concern. I actually remember thinking this 10 years ago, when people talked about low carbohydrate eating. I was entirely dismissive of this approach but, like most doctors, I didn’t actually look at the data, or even ask the right questions.
What are the “right” questions? Well, there are two: what can I actually measure that predicts my risk of heart disease, and how does diet affect these these things I can measure? I decided to answer these questions. Here’s what I found out.
What can I measure that predicts risk of heart disease?
The (very) short answer is this:
Doctors typically measure the following in a standard cholesterol test:
- LDL-C – the concentration of LDL (“bad”) cholesterol in your blood
- HDL-C – the concentration of HDL (“good”) cholesterol in your blood
- TG – the level of triglycerides (“bad”) in your blood
Combining HDL-C and TG into a ratio (i.e., TG/HDL-C) is probably the single best predictor of cardiac risk you can derive from a standard cholesterol test. The lower the ratio, the lower your chances of having an “adverse cardiac event,” as the medical community describes it (e.g., a heart attack). Despite what doctors tell you, LDL-C is pretty much useless for predicting your risk of heart disease. In fact, it’s not even part of the risk assessment for metabolic syndrome, which everyone agrees is the central link to heart disease (and virtually all other chronic diseases we’re afflicted with).
The real story is that the number, size, and density of cholesterol particles in your blood (LDL-P and HDL-P) are far better predictors of heart disease risk. A quick summary:
- Large, buoyant LDL particles are good
- Small, dense LDL are bad
- Small HDL particles are less protective
- Large HDL particles are more protective
The best way to measure your heart disease risk through LDL cholesterol is to measure the number of LDL particles in your blood, or LDL-P, which you never get checked unless you have a fancy test called a lipid nuclear magnetic resonance test – or NMR test for short. There are two surrogate ways to test this:
- You can look at particle size. As a general rule (this is NOT always the case, however), the larger the LDL particles, for a given LDL-C, the fewer the particles (which is what we want).
- You can look at the concentration of something called apoprotein B, or ApoB for short. Every LDL particle has approximately one ApoB, so knowing how much ApoB you have gives you a very accurate measurement of the number of LDL particles you have.
(For the long-answer to this question, read my post “What is cholesterol?”)
How did changing to a low carb diet impact my measurable risk of heart disease?
Below is graph of my overall change in changes in HDL-C, LDL-C, and TG, along with the ratio of my TG to HDL-C, based on the “standard” cholesterol panel.
As you can see the really significant changes have been, in order, increasing my HDL-C, reducing my TG, and reducing my LDL-C. My ratio of TG to HDL-C is now below 1, which is considered excellent, especially given that I started out at nearly 5. There are, however, problems with this “standard” cholesterol test, especially for understanding LDL risk.
For starters, only total cholesterol (TC) and TG are directly measured. HDL-C is indirectly measured, and LDL-C is actually calculated according to a formula that assumes VLDL is about 20% of TG. It turns out this assumption is not often correct.
The pattern I have observed in myself is actually very typical with respect to HDL-C and TG (virtually everyone who reduces or eliminates carbohydrate see a rise and fall, respectively). On the LDL-C side, I’ve seen (and the literature confirms) that about a third of folks see each of an increase in LDL-C, a decrease in LDL-C, and no significant change in LDL-C. I feel confident saying that LDL-C, in and of itself, is of virtually no value in predicting heart disease. So what should we use?
As I stated above, a better marker of risk with respect to LDL is particle number, LDL-P – the fewer particles, the better; and you can estimate this by measuring particle size, or through concentration of ApoB. It turns out there are a few companies that offer tests for these variables, but you have to ask, specifically, of your doctor to get these tests done. The test I use is called a VAP panel. VAP stands for Vertical Auto Profile, and it is the proprietary version of this test done by a company called Atherotech.
Unfortunately, I only started doing regular VAP testing about a year ago, over one year into my “experiment” of progressive carbohydrate restriction. Hence, I can’t show my progress as longitudinally with VAP as I can with standard cholesterol testing.
Below is figure showing the change in my VAP panel over a seven month period, between January and July 2011.
The first thing you’ll notice is that the LDL and HDL numbers don’t exactly line up with the numbers above, in the standard cholesterol panel. The second thing you’ll notice is that there is a lot more measured than just LDL and HDL. With this test, the things you want to pay attention to are LDL 3 and LDL 4, the small, dense ones, and HDL-2, the larger, potentially more protective ones.
Recall that in January of 2011 I had already eliminated sugar entirely from my diet and shifted the carbohydrates I did eat to those high in fiber and low in glycemic index. My VAP profile at that time was already pretty good. Most lipidologists (cardiologists who specialize in the study of lipids) would say LDL 3+4 of 30 or lower is exceptional, and I was just over 30. Furthermore, my HDL-2 was 17, and most would say that HLD-2 over 10 is good. What’s not shown here is my ApoB, which was 62. Guidelines for ApoB are also not black and white, but generally an ApoB under 109 is considered ideal. Finally, my ratio of ApoB to ApoA1 was 0.41, which is ideal, as most lipidologists like to see that ratio below 0.92.
Comparing with my January and July VAP results you can see that my LDL (in total) went down, but more importantly the reduction in LDL was entirely accounted for by the reduction in LDL 3+4 (i.e., the “bad” LDL). Similarly, the increase in HDL was almost entirely driven by the increase in my HDL-2 (i.e., the “good” HDL). My ApoB was reduced slightly to 58 and my ratio of ApoB to ApoA1 was reduced a bit further to 0.36.
Keep in mind how my diet changed between January and July – I reduced carbohydrate intake from approximately 150 grams per day of “good” carbs to less than 50 grams per day. I also increased, dramatically, my intake of fat, including saturated fats.
Insulin and inflammation: the real reasons I reduced my risk of heart disease
Despite the amount of time I’ve expended on explaining all of these nuances of “cholesterol” numbers, I am not entirely convinced that I am healthier today because my cholesterol numbers are better. I wonder if I’m healthier today because of something else, and that whatever else is making me healthier is also correcting my cholesterol problem?
If I had to guess what is really making me healthier today, besides being less fat, I believe it is the combination of how sensitive I’ve become to insulin and how much less inflammation I have in my body, especially in and around my arteries.
If you’ve been reading my blog you’ll no doubt realize the importance of being sensitive to insulin (i.e., not being insulin resistant). Historically, insulin resistance was measured with an invasive test called a euglycemic clamp test. Basically it’s a test to measure how much insulin a person needs to keep their glucose level constant, despite the addition of glucose. The less insulin one requires, the more insulin sensitive one is.
A much simpler way to estimate insulin sensitivity is to use a test called a HOMA-IR (HOMA stands for homeostatic model assessment). The HOMA-IR is a formula that computes a number based on fasting glucose and insulin levels. Ideally, the number it computes should be 1.00. Prior to beginning any dietary intervention, my HOMA-IR was 1.38 – one sign that I was already insulin resistant. An equally obvious sign that I was insulin resistant is noted when looking at the figure below in the left-hand box. The four-square shows the result of a test called the oral glucose tolerance test (OGTT). You show up after an overnight fast and your glucose and insulin levels are measured. (These two numbers are also required to calculate the HOMA-IR.) After your fasting glucose and insulin levels are drawn you drink a (very nasty) orange flavored glucose drink containing 75 grams of glucose. For exactly two hours you do nothing and then repeat the insulin and glucose check.
Here are my test results:
Let’s look at my test from September 2009. My fasting glucose was 93, which is normal, and my fasting insulin was 6, which was also “normal,” except that the HOMA-IR shows the combination of that glucose and insulin level are actually ill-matched. Furthermore, after 2 hours, while my glucose remained barley normal at 108, my insulin was too high, at 36, well above the upper limit of normal of 27. Hence, both by HOMA-IR and OGTT, I was clinically insulin resistant, despite never having elevated glucose levels.
I repeated the OGTT and HOMA-IR test in May 2011, just before beginning the final phase of my nutritional experiment (full-blow nutritional ketosis). By eliminating all sugar, simple carbohydrates, and reducing intake of even “good” carbs my second test was much different, as you can see on the right-hand box. On this test my fasting insulin level was undetectable (this test can’t measure insulin levels below 2, which mine was, so it simply returns a level of “less than 2”). Two hours after drinking the 75 grams of glucose, my glucose went down from 97 to 83 and my insulin “spike” was only to 16. My HOMA-IR was now less than 0.48 (I can’t say how low, because I don’t know how low my fasting insulin was). Hence, by both HOMA-IR and OGTT I had cured my insulin resistance.
Why is this so interesting? Because it actually flies in the face of conventional wisdom and “traditional” medical thinking. Most doctors (erroneously) believe that increase fat intake makes you insulin resistant. This might be true if you consume high amounts of fat in the presence of high amounts of carbohydrates (especially sugar), but when carbohydrate intake is reduced, all the fat in the world does not lead to insulin resistance.
Let me quickly summarize my findings:
- I increased the protective fraction of my HDL cholesterol
- I reduced the harmful circulating triglycerides
- I reduced the harmful fraction of my LDL cholesterol
- I reduced my insulin resistance and became very sensitive to insulin
As I mentioned above, findings #1, 2, and 4 are almost universal in folks who abandon carbohydrates, while finding #3 is somewhat variable.
Which of these is most important? This is an obvious and important question, but one I don’t really know the answer to (nor does anyone else, for that matter). If I had to guess, I believe observation #4 is the most important because insulin resistance is the underpinning of metabolic syndrome.
Look at the figure, below, which represents the ATP III criteria for metabolic syndrome.
At the outset I was not quite at a 40 inch waist, but I was heading there. My fasting triglyceride level was 154, so I failed on that count. My HDL was 31, so I failed on that count. Blood pressure and fasting glucose were still in check.
Two years later, I had reversed all of these symptoms of metabolic syndrome.
People have said things to me like, “Well it’s great that you’ve reduced your risk of all diseases associated with metabolic syndrome, but wouldn’t it be funny if you got hit by a car tomorrow!” All kidding aside, this misses the point. For each of us, the goal should always be to prevent the preventable. While there is no guarantee I won’t succumb to some chronic disease (we all have to die of something at some point), the real question is, will it happen later than it would have had I not changed my eating habits? I believe, without question, that I have done – and continue to do – everything in my power to reduce my risks. And one last point – it’s not just about the number of years you live, it’s also (if not more importantly) about the quality of your life during those years.