Why a Couple Pieces of Fruit Sent My Triglycerides Through the Roof, and How it Relates to Chronic Health

A Demonstration of the "Energy Delivery" Nature of Lipid Mechanics

Last Monday, I had my blood drawn and triglycerides measured at 103 mg/dl. On a Tuesday test they spiked to 241 mg/dl and by Thursday had once again returned to a baseline of 106 mg/dl.

I didn’t “cheat” on any of these blood draws. They were all standard, appropriately fasted tests that no clinician would ever take issue with. So what happened to cause these dramatic changes?

The answer, in short, is that I ate a bit of fruit. Two bananas and an apple to be exact. But a little fruit obviously doesn’t usually send a person’s triglycerides skyrocketing, so it’s the context that make this demonstration so interesting and illustrative.

 

What I Did

 

To be clear, this is hardly the world’s most rigorous experiment. It really wasn’t an experiment at all, just a decision to measure an effect I knew would occur during a planned real-life event. I had been eating only meat for the last couple weeks and was now planning to reintroduce a bit of fruit to my diet. As such, my reliance on stored body fat was going to decrease and create a prime opportunity to illustrate the energy delivery nature of lipid mechanics. The conventional wisdom that chronic fat consumption drives gradual changes in lipid levels is broadly incorrect and insufficient to explain lipid behavior, and the expected rapid changes during this dietary transition would serve as a demonstration of this reality.

So anyway….I ate nothing but meat for a while before reintroducing a small amount of fruit last Monday with my dinner (2 bananas, an apple, some ground beef). I had my blood drawn for three lipid panels during the transition – Monday (before introducing fruit), Tuesday, and Thursday. The total fat and carbohydrate consumption in the days leading into and during the transition are given in the graph below. 

The Results 

Full lipid panels are given in the following chart. As can be seen, dramatic changes in triglycerides were observed, with values spiking significantly on the second day before returning to baseline shortly thereafter. LDL-C changes are also fairly dramatic, but LDL-C + VLDL-C levels decrease gradually across the 3 tests. While the triglyceride changes were the main point of the demonstration, the LDL/VLDL changes also occur in a manner that can be much better explained by an energy delivery model of lipid behavior rather than the standard “fat consumption” paradigm. The second graph shows how dramatic an outlier this triglyceride result was compared to my typical values. 

Date	4/8/24	4/9/24	4/11/24
LDL-C	137	109	120
HDL-C	56	43	49
Triglycerides	103	241	106
VLDL-C	18	42	19
LDL+VLDL	155	151	139

What This Shows

What this essentially demonstrates is the degree of reliance on fatty acids for energy in the complete absence of carbohydrates. In a low glycemic, low insulin environment stored triglycerides are being broken down rapidly and returned to the liver to be packaged and distributed to the body within VLDL particles. The extreme lack of insulin and high reliance on fatty acids for energy means this is happening at an increased rate – It shows up on the lipid panel as a moderate increase in LDL-C.

**Quick refresher/explainer on terminology and physiology - fat entering the liver is converted to triglycerides and packaged into lipoproteins called VLDL. VLDL carry cholesterol and triglycerides away from the liver to the muscle and fat cells of the body. VLDL are typically short-lived and are converted to LDL particles after they offload triglycerides either to the cells of the body or back at the liver. LDL particles have a longer lifespan (days instead of hours) and carry primarily cholesterol around the bloodstream. VLDL-C and LDL-C refer to the amount of cholesterol contained within each particle class. LDL-C, but not VLDL-C, typically goes up when larger amount of triglycerides need to be trafficked for energy because the higher number of VLDL particles offload triglycerides quickly and convert to LDL. More background info can be found here**

Why not elevated triglycerides though? Because despite my body producing more triglyceride containing VLDL particles than the average person would, blood levels of triglycerides remain unelevated due to their rapid utilization. In essence, the total fatty acid throughput – first from body fat to liver, then in VLDL from liver to muscle (and, for some, back to body fat) – is high, but the levels in the blood at any given time are not.

The introduction of even a small amount of carbohydrates demonstrates the rate at which triglycerides were moving around. Upon consumption, they elevate the blood sugar and their removal from the bloodstream prioritizes them as an energy source over the significant flow of triglycerides. Because it takes some amount of time for newly liberated fat stores to travel to the liver and be repackaged in VLDL particles (and perhaps because insulin does not spike high enough or fast enough after limited carb consumption to immediately “shut off” fat breakdown), there will for some time be a build-up of triglycerides leaving the liver waiting to be taken up by the body.

The carbs delay these triglycerides and, combined with the triglycerides being provided by the rest of my dinner, cause the high throughput to come to an abrupt halt. The next morning, a full 13 hours fasted, the backlog still fails to fully clear, resulting in high measured triglyceride (and VLDL-C) levels. Given a bit more time, however, this backlog does indeed clear as fewer VLDL particles are produced.

Just two days after the spike, triglycerides levels return to Monday’s baseline level. Carbohydrate consumption remains but, overall, things have now changed. The small carbohydrate contribution to energy is no longer additional to the heavy reliance on stored body fat, but instead replaces a portion of it as the breakdown of stored body fat is throttled back a degree. Fewer triglycerides are mobilized from the body’s stores and so the brief excess of energy supply no longer exists.

This same effect can be observed in my LDL-C and VLDL-C levels as well. Remember, reliance on these lipoproteins for energy transport is a prime driver of LDL/VLDL cholesterol. As such, those combined values are highest during my first blood draw but decrease gradually over the next two as less fat is mobilized from my body’s stored reserves. With less stored fat being liberated, less fat is necessarily trafficked to the liver to be packaged and distributed in VLDL particles. The “build-up” effect can be clearly seen on the second blood draw, where VLDL-C spikes as the VLDL particles fail to offload triglycerides and convert to LDL particles. The failure of these VLDL particles to appropriately (ie. quickly) convert to LDL causes the sharp decrease in LDL-C as old LDL particles are removed from circulation without being replaced. LDL-C rebounds to a degree on the final draw despite lower VLDL production because these previously long-lived VLDL particles have now finally converted to LDL.

 

 

What This Implies for Chronic Health

 

This particular demonstration is a unique sort of one-off that won’t apply to most people in most situations, but it is nonetheless relevant to chronic metabolic health as well. While my demonstration succeeds in creating an “energy back-up” in the short term, it is that same backlogged delivery of triglycerides that serves as a hallmark of chronic metabolic dysfunction. In short, it is the precisely the same mechanisms – prolonged VLDL residence times and increased triglyceride levels due to delayed or failed triglyceride uptake at the periphery – in each case. The underlying reasons, however, differ.

In my case, as has been covered, the backlog is very brief and is caused by essentially dropping some carbohydrates into a fast-moving river of fatty acid energy. But in chronic cases, the build-up is more gradual and subject to progressive long-term forces. When a person chronically overconsumes carbohydrates, becomes insulin resistant, increases fat stores, and so forth, triglycerides are in certain ways both more prone to enter the bloodstream and more resistant to leaving.

They fail to leave the bloodstream in an appropriately quick manner for largely the same reason as in my experiment – chronically elevated blood sugar forces a prioritized reliance on carbohydrates for energy. This isn’t a major issue in any acute sense, but becomes one when carbohydrates are chronically consumed in excess. Many of these carbohydrates, in the form of fructose, are in fact converted to triglycerides in the liver and join the flow of VLDL particles to the periphery. Additionally, an overweight, insulin resistant individual will become dulled to insulin’s fat-storage effects. While typically the consumption of carbohydrates and corresponding increase in insulin makes it very difficult to liberate body fat, this effect is progressively reduced in cases of insulin resistance. Now, triglycerides in the body’s fat stores are inappropriately broken down and trafficked to the liver for packing in VLDL particles.

When this person chronically consumes carbohydrates, increasing insulin levels and extending VLDL residence time, they contribute to a backlog of these additional sources of VLDL/triglycerides. When the VLDL are unable to offload triglycerides properly, they must be returned to the liver and be offloaded there instead. This is in fact the most critical source of excess triglycerides entering and exiting the liver. When excess triglycerides are returned to the liver, they join the aforementioned additional sources of triglycerides in being packaged again into VLDL particles and leaving the liver to join the triglyceride backlog. For as long as carbohydrate consumption remains high and insulin levels remain elevated, this risks becoming a progressively more serious issue, as triglycerides are increasing unable to be offloaded to the cells of the body and instead returned to the liver to join the ever-growing backlog once more.

The end result, in this case, is chronically elevated triglyceride levels that can’t likely snap back to healthy levels in a day or two. Increasing triglycerides directly lowers HDL-C and increases VLDL production, ultimately leading to the increase in LDL particles and LDL-C commonly assumed to be the cause of chronic cardiovascular disease. In fact, the increased presence of triglyceride-rich lipoproteins is (through the action of CETP) among the actual instrumental drivers of such disease, as the presence of excess triglycerides also generate smaller damage-prone LDL (and HDL) particles. As these effects are secondary to excess carbohydrate consumption, they will necessarily be accompanied by a trend towards increased development of advanced glycation end-products, depressed nitric oxide availability, increased free radical production, and other hyperglycemia-induced facets of compromised vascular health. 

  

Conclusion

In short, I was able to briefly replicate a very unhealthy state that those suffering from metabolic dysfunction experience on a chronic basis. Importantly, the lipid changes observed during this demonstration can only be explained by the demand for energy transport, not by fat consumption. While my failed triglyceride metabolism was effectively a mirage caused only by the unique, acute introduction of carbohydrates, the chronic state is reached by millions and millions who overconsume carbohydrates habitually. This triglyceride backlog and failure of fatty acid metabolism is an instrumental component of cardiovascular disease progression that can be largely moderated or reversed by a shift away from traditional, carbohydrate-based dietary guidelines. 

Further reading on the topics addressed above can be found here - 

• Terminology and Overview of Lipid Classes
• Triglyceride Mechanics - General, Dysfunctional, Efficient/Low-carb Dynamics
• Consequences of Poor Triglyceride Uptake
• Other Factors Influencing Atherosclerosis

The "Intermittent Fasting Will Causes Heart Disease" Articles Are Bullshit, But Let's Talk About Why

My wife doesn't follow nutrition research and writing the way I do. She doesn't, for example, have email alerts set up to tell her about new studies and publications. So when she becomes aware of a new study or article, I can usually be pretty sure the item in question is filtering out in to the mainstream consciousness. 

Today the item in question is a report from the American Heart Association that engaging in intermittent fasting, the practice of limiting your food consumption to a certain time period, is associated with a significant increase in heart disease. This shocking headline is being reported by the Washington Post, and CNN, and NBC News, and so on and so on. Mainstream consciousness, indeed. These articles suggest that the researches found “that people who adhered to the eight-hour eating plan had a 91 percent higher risk of dying from heart disease compared to people who followed a more traditional dietary pattern of eating their food across 12 to 16 hours each day” and includes quotes from the researches advising those who practice intermittent fasting to be “extremely cautious.” ¹

The major problem with these results though, is that the researchers did not in any way study people who engaged in intermittent fasting. Nor did they make any attempt to

 

Intermittent Fasting Research

Let’s take a moment here to pause and consider what you as a researcher might do if you wanted to assess the effects of intermittent fasting.

The best strategy would probably be to take a bunch of people, record a lot of health data, have them engage in intermittent fasting for some period of time, and measure those same markers again. Bonus points if you have a second comparison group alongside them to eat the same amount of food spread throughout the day. Then you could see if intermittent fasting had any effects on common markers of metabolic health, inflammation, etc.

You will not be surprised to learn that this has been already been done many, many times. This is good, hands-on research that controls and monitors the subjects’ dietary patterns to be sure the intervention in question is being fairly assessed. And this research, it turns out, consistently returns findings that suggest intermittent fasting can improve common markers of metabolic health, insulin resistance, inflammation, etc.^2–6 Not every trial finds improvements in all the health markers they analyze, but they very often do. And since I’ve yet to find a fasting intervention that demonstrated a worsening of chronic health markers, I feel pretty damn confident in saying that the actual hard science demonstrates a tendency for intermittent fasting to improve chronic health.

 

Intermittent Fasting Surveys

So if we wanted the best results possible, we’d engage in hands-on interventional research. Hard science. But hard science is costly, labor-intensive, and time-consuming. So for those or other reasons, maybe we just want to get a peek at what’s happening to those who engage in intermittent fasting, especially those who have been practicing for a while. What would we do then? We’d ask them! You could ask people how long they’ve been practicing intermittent fasting, how often they engage in the practice, how long their typical eating window is, what foods they typically eat, etc. You’d also want to ask anything else you could imagine related to their health (exercise, alcohol, sleep, lifestyle and socioeconomic factors, etc.) to make sure none of those might influence your results. Then when you have all this data, you could compare the current health of your subjects to a control group or the general population to see if you could identify any differences.

This approach is generally weaker than the interventional trials we described above because they can’t demonstrate any causal effects, but if done properly there can still be reasonable value derived from the findings.

“Intermittent Fasting” Surveys

We’ve covered a couple reasonable approaches for how we might assess the question at hand if we wanted decent to good results. But what if we didn’t give a single flying fuck about good results? What would we do then? What if all we wanted was to attach a soundbite to a trending health topic? What if we just wanted to manufacture a scary headline to make it look like not eating for a little bit could literally cause a heart attack?

Well, we can rule out interventional trials. We know with great certainty that those won’t work, because those have repeatedly demonstrated that intermittent fasting is far more likely to be beneficial than harmful. So we’ll have to go the survey route instead. But, we probably want to be careful about the questions we ask. If we ask a bunch of detailed questions that accurately identify subjects deliberately engaged in the practice of intermittent fasting, we might accidently confirm the hard science if we end up with people who are healthier than the general population.

So I have an idea. We’ll find thousands of people and just ask them what they ate yesterday, and when they ate it. And then later this year we’ll ask them again – what time did you consume food yesterday? Then we’ll take this sample size of two and categorize anyone who ate their food in a single eight hour window as someone engaged in “intermittent fasting,” even if they have no idea what those words even mean. And of course we’ll pretend this sample size of two accurately reflects their long-term dietary patterns while we sit around and wait to see who dies over the next several years.

 

Deliberating Avoiding Actual Intermittent Fasting

Hopefully it’s fairly clear that the sarcastic paragraph above actually just describes the study in question.⁷ It was two 24 hour dietary recalls in the span of a year, and years of tracking deaths. The researchers were not seeking out people engaged in regular intermittent fasting or attempting to understand anybody’s long-term dietary habits, even though every damn news article includes references to “people who practice intermittent fasting for long periods of time.”

But why does this produce terrible results? For the same reasons you can’t draw definitive negative conclusions from survey data, I actually can’t say definitely. Buuuuuuut I have a pretty good guess. Take a look at the chart below, which filters the subjects by their average eating window during those two dietary recalls:

 

A couple things jump out to me right away – those that they characterize as engaged in intermittent fasting (8 hour or less eating window) are quite a bit more likely to smoke than the average person, and are 3 times more likely to be black. This suggests a couple of things to me. One if that a good number of these people are obviously not actively seeking the health benefits of intermittent fasting. And the other is that, unfortunately, this group of subjects is almost certainly at a socioeconomic disadvantage compares to the others. It remains a regrettable reality in this country that black Americans are twice as likely to live in poverty and face food scarcity.^8,9 Meanwhile, smoking is nearly twice as common below the federal poverty line as it is above. ¹⁰ We don’t literally have it from what the researchers presented, but we do actually know it – the “intermittent fasting” group is of far lower socioeconomic status than the others.

I can only think of a couple reasons someone would engage in deliberate intermittent fasting. Weight loss and health benefits are the obvious ones. Or maybe that’s really just one reason. Regardless, people who seek out the deliberate practice fasting are relatively privileged enough to be doing so.

But let’s reframe it – what are some reasons a person might skip a meal? Because to a large extent that’s what is actually happening here. Even just on its face, I would frankly expect there to be more people who skip breakfast because they stayed up too late and tried to maximize every minute of sleep before class or work than there are people engaged in mindful intermittent fasting. That’s obviously not a healthful approach to life, but it’s not being accounted for at all. It’s more than just that though, of course. We know that the “fasting” subjects here are disproportionally likely to be poor, have poor access to food, and so forth.

Some people in this study probably are health-minded individuals engaged in intermittent fasting. But quite a number are poor people who stayed up late working their second job and didn’t eat breakfast in the morning. Or skipped breakfast those two days to save a couple bucks. Or are among the millions of highly food-insecure Americans who can’t find dinner tonight.

Maybe that’s being too dramatic, I really don’t know for sure. But I know with certainty that actual hands-on science tends to show the health benefits of intermittent fasting. And I know with certainty that these researchers made zero effort to find people engaged in intermittent fasting. And I know with certainty that the cohort they found to represent “intermittent fasting” is much more likely to be impoverished and hungry than the general population.

What I don’t know, as someone in a position fortunate enough to engage in deliberate healthful fasting, is how much poverty, food scarcity, and who knows what else affects cardiovascular disease and mortality. Id imagine that the daily stress experienced by the “intermittent fasting” group explains most or all of the measured increased in CVD mortality. In fact, it seems that low socioeconomic status itself is associated with CVD mortality to a far greater degree than this study claims intermittent fasting to be.¹¹ And basically to a greater degree than any dietary habit. Perhaps the AHA might focus on that relationship, if they aspire to a reduction in CVD deaths.

 

Conclusion

So that about sums it up. We know, from legitimate science, that intermittent fasting tends to impart positive health effects. We also know that these researchers took the about the shittiest approach they could to studying “intermittent fasting,” and I really have no problem accusing them of doing it deliberately. And I have no problem noting that this terrible research being spammed all over the internet, which has not yet even been fully published or peer-reviewed, just happens to once again align with the American Heart Association’s persistent opposition to healthful dietary habits. And while we’re at it, I have no problem suggesting that a lot of what I just wrote about should probably be absorbed as social/political commentary, even if it started as a defense of healthy eating habits.

 

But the bottom line is this – intermittent fasting is unequivocally not going to induce heart disease.

1.               The intermittent fasting trend may pose risks to your heart. Accessed March 20, 2024. https://www.msn.com/en-us/health/other/the-intermittent-fasting-trend-may-pose-risks-to-your-heart/ar-BB1k7bsm

2.               Gu L, Fu R, Hong J, Ni H, Yu K, Lou H. Effects of Intermittent Fasting in Human Compared to a Non-intervention Diet and Caloric Restriction: A Meta-Analysis of Randomized Controlled Trials. Front Nutr. 2022;9. doi:10.3389/fnut.2022.871682

3.               Ahmed N, Farooq J, Siddiqi HS, et al. Impact of Intermittent Fasting on Lipid Profile–A Quasi-Randomized Clinical Trial. Front Nutr. 2021;7. doi:10.3389/fnut.2020.596787

4.               Yuan X, Wang J, Yang S, et al. Effect of Intermittent Fasting Diet on Glucose and Lipid Metabolism and Insulin Resistance in Patients with Impaired Glucose and Lipid Metabolism: A Systematic Review and Meta-Analysis. International Journal of Endocrinology. 2022;2022:e6999907. doi:10.1155/2022/6999907

5.               Wang X, Yang Q, Liao Q, et al. Effects of intermittent fasting diets on plasma concentrations of inflammatory biomarkers: A systematic review and meta-analysis of randomized controlled trials. Nutrition. 2020;79-80:110974. doi:10.1016/j.nut.2020.110974

6.               Cho Y, Hong N, Kim K won, et al. The Effectiveness of Intermittent Fasting to Reduce Body Mass Index and Glucose Metabolism: A Systematic Review and Meta-Analysis. Journal of Clinical Medicine. 2019;8(10):1645. doi:10.3390/jcm8101645

7.               Chen M, Xu L, Horn LV, et al. Association of 8-Hour Time-Restricted Eating with All-Cause and Cause-Specific Mortality.

8.               Poverty in the United States: 2022. Accessed March 20, 2024. https://www.census.gov/library/publications/2023/demo/p60-280.html

9.               Nearly Half of Black and Hispanic People in the U.S. Face Food Insecurity, New Study Finds | Johns Hopkins | Bloomberg School of Public Health. Published February 26, 2021. Accessed March 20, 2024. https://publichealth.jhu.edu/2021/nearly-half-of-black-and-hispanic-people-in-the-us-face-food-insecurity-new-study-finds

10.             Garrett BE. Socioeconomic Differences in Cigarette Smoking Among Sociodemographic Groups. Prev Chronic Dis. 2019;16. doi:10.5888/pcd16.180553

11.             Zhang YB, Chen C, Pan XF, et al. Associations of healthy lifestyle and socioeconomic status with mortality and incident cardiovascular disease: two prospective cohort studies. BMJ. 2021;373:n604. doi:10.1136/bmj.n604

 

 

Colorectal Cancer is in the News Again. Don't Blame Red Meat

 

Colorectal Cancer in the News

NBC News and other prominent outlets are currently reporting on a dramatic increase in both rates of colon cancer and colon cancer mortality among young adults.¹ These news reports, based on a recent publication from the American Cancer Society, suggest a substantial uptick in the disease but can only theorize as to what might be driving it.² While the ACS report itself is only a dry statistical report, various news outlets and the public health experts they interview hypothesize a number of potential causes, typically of an environmental or dietary nature. One of these potential causes, is of course, meat consumption. So now seems like as good of time as any to discuss why I believe there is no legitimate evidence whatsoever linking meat (most specifically, red meat) consumption to colon and colorectal cancer (CRC) incidence.

Lets start with the ACS report itself, which reports increasing incidence of 6 of the top 10 cancers. For example, cancers of the breast and pancreas ticked up very slightly (less than 1% over five years), while cancers of the prostate and kidney were among those increasing most rapidly (upwards of 3% over five years). Colorectal cancer, on the other hand…is not increasing. So why all the headlines? I think part of it is that CRC makes for a trendy headline of sorts, as its been a particular mainstream focus in the last decade or so (more on that in a minute). The other reason is that, while CRC rates are not increasing overall, they are indeed increasing (between 1 and 2 percent) among people in their 30s and 40s. Perhaps even more relevantly, rates of CRC morality in that demographic are increasing as well.

 

Rates of CRC and other select cancers in adults under the age of 50

So rates are increasing among younger adults in which the disease tends to be relatively rare, but are not increasing overall. What might cause this to be the case? I certainly have a suggestion, but it won’t be the same you see in traditional medical and health circles. If you search the internet for CRC prevention advice, you’ll quickly find (along with advice to exercise and refrain from smoking) advice from the American Cancer Society to limit red and processed meat, from the CDC to limit animal fats, and from Harvard to remove as much meat as possible from your diet (“Red and processed meat has been the dietary factor most consistently linked to colon cancer”). ^3–5

None of these claims and none of these recommendations, though, are based on more than weak epidemiology (i.e. survey data). And while potential explanations (curing nitrates in processed meat, for example) have been sought to explain the association between meat consumption and CRC, I believe a much more obvious causal explanation exists both to explain the general association between red meat consumption and CRC AND the recent uptick in young adult incidence of the disease.

 

Increasing Focus on the Meat-CRC Link

 

It’s often presented as an obvious cause and effect, that red meat consumption is tightly linked to and often instrumental in causing CRC to develop. But the evidence does not support these typical claims. Let’s start in 2015, when the International Agency for Research on Cancer (IARC) prepared a study for the World Health Organization on the potential carcinogenic properties of meat. ⁶ Based (ostensibly) on this paper, the WHO issued a report declaring red meat to be a Category 2A carcinogen, describing it as “probably carcinogenic to humans.” This notion, that beef and other red meat may be cancer-causing, has become increasingly prevalent in the years since.

 

However, I would argue that the claims made by the IARC/WHO are deeply flawed for a number of reasons:

1.       The IARC report did not, in fact, find significant evidence that red meat consumption is linked to cancer in humans

2.       The epidemiological studies that do link meat consumption to cancer are very limited, and typically find only a small effect

3.       The studies linking meat consumption to cancer fail to take into account significant confounding variables.

             

When you first saw the alarming report on the nightly news in late 2015, you’d have been mistaken for believing the WHO made their claims on the back of a significant body of evidence. After all, the WHO is quick to point out that more than 800 studies were examined as part of the report. How many of these 800 studies detailed a significant link between red meat consumption and CRC, you might wonder…

Its certainly not 800. In fact it certainly doesn’t even appear to be 8. Included among those 800 studies were 29 that examined CRC specifically, and of those 29 only 14 showed positive associations between red meat consumption and CRC. But read that sentence again…. Its 14 studies that showed a positive association, not 14 studies that showed a statistically significant connection between CRC and red meat consumption. In fact, in their public report the very first study the IARC references among those 14 says this:

 

“Intake of red meat was positively but not statistically significantly associated with colorectal cancer"⁷

 

So, again, to be very clear – there were not 14 studies that found a scientific, statistical link between red meat consumption and CRC. There were instead 14 studies that demonstrated some vague, uncertain positive relationship between the two. However, the IARC and WHO made the choice in their reports to misrepresent these weak relationships as scientifically valid, when in fact they are anything but. And since every piece of epidemiology is going to pick up a vague, uncertain trend in one way or the other, we can be fairly confident the other 15 demonstrate some vague, weak, unscientific trend in the opposite direction. So while the totality of the evidence examined found no scientific link between CRC and red meat consumption, and the weak, non-significant trends were equally split between positive and negative, the WHO still made the decision, based on jaw-droppingly weak evidence, to label red meat a probable human carcinogen.

 

Why The CRC-Red Meat Link Still Sometimes Exists

 

Ok, ok….the IARC report didn’t support its own conclusions or its headlines. But there are, indeed, some epidemiological studies out there that show a genuine, significant scientific link between CRC and red meat consumption. There was even one in the public IARC report!⁸ So now let’s talk about why that link still isn’t what it seems, and what dietary factor I ultimately think is to blame for the uptick in young adult CRC.

**A quick aside – if you aren’t familiar with the concept of healthy user bias, now would be a good time to acquaint yourself. You can do so in detail HERE, but in short – healthy user bias is the concept by which people who want to be healthy do things they believe to be of benefit to their health. The opposite is "unhealthy user bias," in which people who don't care about their health don't mind doing things that are considered unhealthy. Because recommendations to avoid meat predate nutritional epidemiology by more than two decades, there has never been a study unbiased by the widespread belief that meat and fat are unhealthy. Healthy user bias is a massive problem in epidemiology because its effectively impossible to account for all the habitual differences between “healthy” and “unhealthy” individuals. It’s a problem made all the more massive by the fact that so many researches apparently don’t even make an attempt. For example, failure to adjust for a multitude of factors is how you end up with the consistent finding that red meat consumption “causes” as many or more accidents than it does cases of chronic disease^9–11**

 

Ok, now…A case study –

The same year as the IARC report, researches at Loma Linda University released a study claiming that "Vegetarian diets are associated with an overall lower incidence of colorectal cancers."¹² This study, basically, followed nearly 100,000 Seventh-Day Adventists for six years and compared self-reported diet to incidence of colon cancer. Because meat consumption is frowned upon in the religion, only half of the participants were meat-eaters. What they concluded is that vegetarians, compared to those who consume meat, were 22% less likely to develop colorectal cancer. This translates to roughly a 5% chance that a vegetarian, and a 6% chance that a meat-eater, would develop colorectal cancer during adulthood. And yes, this finding was statistically significant. 

 But it still doesn't mean meat causes cancer. Why? Healthy user bias and confounding variables. It is standard scientific practice to attempt to adjust for HUB, but is not possible to do so completely. Lets specifically examine meat-eaters vs. vegans, using the data from this study, to illustrate why. 

 

 

 

What you might notice at first is that the vegans in the study actually had more cases of colorectal cancer than did the meat-eaters. 7 percent more, to be accurate. But just stopping there would be very bad science indeed, as there are a number of other factors that can influence the results. For example, the meat-eaters are slightly younger and thus less likely, all things considered, to develop cancer of any kind. When the researchers apply the statistical process known as "adjustment" to the age variable, they can eliminate age as a factor and find that, age-adjusted, the vegans actually had 11 percent FEWER cases of colorectal cancer. 

But we can't just adjust for age. You'll also notice that meat-eaters are more overweight, more likely to smoke, more likely to drink, more likely to have diabetes, less likely to exercise, etc. This is (un)healthy user bias in action. Researchers adjust for these as well, with little impact on the final numbers. But what I want to focus on is not what they do adjust for, but what they don’t – namely, sugar and processed carb consumption, blood sugar, and insulin levels. You’ll note in the chart above that I specifically highlighted the diabetes rate of the meat eating group, and with good reason -

 

1. Diabetes is fundamentally a disease of insulin resistance and increased insulin production tightly related to prolonged overconsumption of high-glycemic (sugary) carbohydrates and obesity

        2. Insulin is a potent growth factor

        3. Cancer is a disease of uncontrolled growth, and cancer cells typically overexpress insulin receptors

 

It should not be surprising then, to find that individuals with increased insulin levels are far more likely to develop colorectal cancer. For example..

"An increased concentration of plasma C-peptide was statistically significantly associated with an increased risk of colorectal cancer (relative risk [RR] for the highest versus lowest quintile of plasma C-peptide = 2.7, 95% confidence interval [CI] = 1.2 to 6.2; P-trend = .047)"¹³

"Colorectal cancer risk increased with increasing levels of C-peptide (P-trend = .001), up to an odds ratio (OR) of 2.92 (95% confidence interval [CI] = 1.26–6.75) for the highest versus the lowest quintiles"¹⁴

"Cancer mortality was significantly higher in those with hyperinsulinemia than in those without hyperinsulinemia (adjusted HR 2.04)"¹⁵

*Note that C-Peptide is a measure of insulin production

 

In fact, a long list of studies show that individuals with high levels of insulin production are as much as 200 to 400 percent more likely to develop colorectal cancer.^16–24 But despite insulin's massive role in the development and progression of cancer, it is partially unaccounted for in the study above. We know, with a high level of certainty, that the meat-eating group had higher insulin levels, largely due to the drastically higher rate of diabetes but also the increased obesity (tightly connected to insulin levels) and the great likelihood that the meat eaters are also consuming more sugar and processed carbohydrate (healthy user bias).

Now it is true that obesity and a clinical diagnosis of diabetes are adjusted for, but the vast majority of meat-eaters did not have diabetes. Still, the massively increased rate of diabetes doesn't exist in a vacuum. Diabetes as a clinical diagnosis really just reflects a certain threshold of insulin resistance, not a discrete state. Which is to say that the meat-eating group has more diabetics because the entire group has higher insulin levels, meaning more people will be past the diabetic threshold. The critical point, then, is that this group will also have more "pre-diabetics" and more people with moderately elevated insulin. But without any adjustment made for the consumption of sugar, the consumption of processed grains, actual blood sugar levels, or actual insulin levels, the influence of insulin is allowed to persist. Certainly, then, the meat-eating group is to at least some degree more likely to develop colorectal cancer for reasons that have nothing to do with the consumption of meat. 

In fact, the end result of the study suggests, based on indirect survey data, that meat-eaters are 14% more likely than vegans to develop CRC. Contrast this with the consistent direct findings that individuals with the highest insulin levels are more like 2-300% more likely to develop CRC. These studies together suggest that high insulin is something like 15-20 times more powerful than high meat consumption in predicting the development of future CRC. When insulin is that much more powerful a predictor, it only takes a small degree of negligence in accounting for it to end up with results like the one is this study. Are meat-eaters 14% more likely to develop CRC because meat is driving the disease or because their more sedentary, processed-carb lifestyle results in elevated insulin that isn’t fully being accounted for?

You can see how glaring an oversight it is, then, to ignore the impact of insulin when you attempt to link meat consumption to CRC using only epidemiological survey data. Remember when I pointed out the one study in the IARC report linking red meat to CRC at a statistically significant level? Not only did that study not measure or adjust for sugar consumption, processed carb consumption, blood sugar, or insulin levels, they didn't even adjust for diabetes! If you then further layer in the pile of direct, controlled trials that demonstrate the capacity of a high fat, low-carb diet to improve blood sugar and lower insulin levels, the claims that meat consumption is causing CRC become even more difficult to believe.^25–35  

Conclusion

The following facts are all true:

1.      The link between meat consumption and CRC development is based only on a small number of epidemiological surveys, and the degree to which these studies suggest meat ostensibly increases one’s risk is quite small.  

2.      Elevated insulin levels predict CRC development as much as 20 times more strongly than does high levels of meat consumption.

3.     Epidemiological studies incompletely account for insulin levels to varying degrees, with some ignoring blood sugar, insulin levels, and diabetes entirely.

4.     Replacing sugar and carbohydrates with meat and fat lowers long-term blood sugar, lowers insulin levels, and improves markers of glucose metabolism and diabetes.

 

The following facts are also true:

1.       Diabetes rates are increasing more rapidly than CRC rates

2.       Diabetes rates are increasing in children and young adults³⁶

 

I’m sure its entirely obvious where I’m going with this by now, but I’ll share an image from last year’s post on red meat and diabetes to drive home the point:

 

 

Red meat doesn’t cause diabetes and in fact can be instrumental in reversing it. In reality, this discussion on CRC is basically just “red meat doesn’t cause diabetes” with extra steps. Red meat consumption has never been legitimately linked to the development of CRC - A minority percentage of epidemiolocal papers suggest a weak link between the two only by utilizing survey data that fails to fully account for meaningful confounding factors.

On the contrary, insulin levels are directly, strongly, and significantly linked to the development of CRC. As reflected by ever-increasing rates of diabetes and ever-earlier onset of the disease, population levels of blood sugar and insulin continue to increase. If one begins with the (scientifically-valid) premise that impaired glucose metabolism, elevated insulin, and other diabetic complications are directly influential in the onset of CRC, it is effectively inescapable that the increasing rates of diabetes (and young adult diabetes) must portend an increase in young adult CRC as well.

To the degree than any dietary factor is influencing the increase in CRC incidence and mortality, it is these – excess consumption of sugar and processed carbohydrate, chronically elevated blood sugar, and long-term elevated insulin are directly involved in the development of CRC. Red meat, for decades now lumped with smoking, drinking, sugar, and a sedentary lifestyle as the vices of chronic disease, is occasionally caught in the crossfire of weak epidemiological science.

News articles and “expert” advice will likely continue to focus on the minor, weak, indirect link and urge you to prudently fight CRC by eliminating meat despite the lack of evidence to support this position. I’ll do the opposite – if you want to reduce your risk of colorectal cancer, focus on the direct link more than an order of magnitude stronger. Reduce your insulin levels by reducing or eliminating sugar, grains, and other processed carbohydrates, and make a real, meaningful difference in your risk of developing cancer, diabetes, and a host of other chronic diseases. Don’t blame the meat.

1.               Colon cancer is killing more younger men and women than ever, new report finds. NBC News. Published January 17, 2024. Accessed January 18, 2024. https://www.nbcnews.com/health/health-news/colon-cancer-deaths-younger-men-women-report-rcna134084

2.               Siegel RL, Giaquinto AN, Jemal A. Cancer statistics, 2024. CA: A Cancer Journal for Clinicians. n/a(n/a). doi:10.3322/caac.21820

3.               Colorectal Cancer Prevention | How to Prevent Colorectal Cancer. Accessed January 18, 2024. https://www.cancer.org/cancer/types/colon-rectal-cancer/causes-risks-prevention/prevention.html

4.               What Can I Do to Reduce My Risk of Colorectal Cancer? | CDC. Published February 23, 2023. Accessed January 18, 2024. https://www.cdc.gov/cancer/colorectal/basic_info/prevention.htm

5.               How to prevent colorectal cancer. Harvard Health. Published February 1, 2014. Accessed January 18, 2024. https://www.health.harvard.edu/cancer/how-to-prevent-colorectal-cancer

6.               Bouvard V, Loomis D, Guyton KZ, et al. Carcinogenicity of consumption of red and processed meat. The Lancet Oncology. 2015;16(16):1599-1600. doi:10.1016/S1470-2045(15)00444-1

7.               Norat T, Bingham S, Ferrari P, et al. Meat, Fish, and Colorectal Cancer Risk: The European Prospective Investigation into Cancer and Nutrition. JNCI: Journal of the National Cancer Institute. 2005;97(12):906-916. doi:10.1093/jnci/dji164

8.               Larsson SC, Rafter J, Holmberg L, Bergkvist L, Wolk A. Red meat consumption and risk of cancers of the proximal colon, distal colon and rectum: The Swedish Mammography Cohort. International Journal of Cancer. 2005;113(5):829-834. doi:10.1002/ijc.20658

9.               Huang J, Liao LM, Weinstein SJ, Sinha R, Graubard BI, Albanes D. Association Between Plant and Animal Protein Intake and Overall and Cause-Specific Mortality. JAMA Internal Medicine. 2020;180(9):1173-1184. doi:10.1001/jamainternmed.2020.2790

10.             Sinha R, Cross AJ, Graubard BI, Leitzmann MF, Schatzkin A. Meat intake and mortality: a prospective study of over half a million people. Arch Intern Med. 2009;169(6):562-571. doi:10.1001/archinternmed.2009.6

11.             Cohen_cornellgrad_0058F_10285.pdf. Accessed June 25, 2023. https://ecommons.cornell.edu/bitstream/handle/1813/51613/Cohen_cornellgrad_0058F_10285.pdf?sequence=1#page=111

12.             Orlich MJ, Singh PN, Sabaté J, et al. Vegetarian dietary patterns and the risk of colorectal cancers. JAMA Intern Med. 2015;175(5):767-776. doi:10.1001/jamainternmed.2015.59

13.             Ma J, Giovannucci E, Pollak M, et al. A Prospective Study of Plasma C-Peptide and Colorectal Cancer Risk in Men. JNCI Journal of the National Cancer Institute. 2004;96(7):546-553. doi:10.1093/jnci/djh082

14.             Kaaks R, Toniolo P, Akhmedkhanov A, et al. Serum C-peptide, insulin-like growth factor (IGF)-I, IGF-binding proteins, and colorectal cancer risk in women. J Natl Cancer Inst. 2000;92(19):1592-1600. doi:10.1093/jnci/92.19.1592

15.             Tsujimoto T, Kajio H, Sugiyama T. Association between hyperinsulinemia and increased risk of cancer death in nonobese and obese people: A population-based observational study. International Journal of Cancer. 2017;141(1):102-111. doi:10.1002/ijc.30729

16.             Fung TT, Hu FB, Schulze M, et al. A dietary pattern that is associated with C-peptide and risk of colorectal cancer in women. Cancer Causes Control. 2012;23(6):959-965. doi:10.1007/s10552-012-9969-y

17.             Chen L, Li L, Wang Y, et al. Circulating C-peptide level is a predictive factor for colorectal neoplasia: evidence from the meta-analysis of prospective studies. Cancer Causes Control. 2013;24(10):1837-1847. doi:10.1007/s10552-013-0261-6

18.             Xu J, Ye Y, Wu H, et al. Association between markers of glucose metabolism and risk of colorectal cancer. BMJ Open. 2016;6(6):e011430. doi:10.1136/bmjopen-2016-011430

19.             Tsai CJ, Giovannucci EL. Hyperinsulinemia, Insulin Resistance, Vitamin D, and Colorectal Cancer Among Whites and African Americans. Dig Dis Sci. 2012;57(10):2497-2503. doi:10.1007/s10620-012-2198-0

20.             Jenab M, Riboli E, Cleveland RJ, et al. Serum C-peptide, IGFBP-1 and IGFBP-2 and risk of colon and rectal cancers in the European Prospective Investigation into Cancer and Nutrition. International Journal of Cancer. 2007;121(2):368-376. doi:10.1002/ijc.22697

21.             Wei EK, Ma J, Pollak MN, et al. A prospective study of C-peptide, insulin-like growth factor-I, insulin-like growth factor binding protein-1, and the risk of colorectal cancer in women. Cancer Epidemiol Biomarkers Prev. 2005;14(4):850-855. doi:10.1158/1055-9965.EPI-04-0661

22.             Djiogue S, Nwabo Kamdje AH, Vecchio L, et al. Insulin resistance and cancer: the role of insulin and IGFs. Endocr Relat Cancer. 2013;20(1):R1-R17. doi:10.1530/ERC-12-0324

23.             Leroith D, Scheinman EJ, Bitton-Worms K. The Role of Insulin and Insulin-like Growth Factors in the Increased Risk of Cancer in Diabetes. Rambam Maimonides Med J. 2011;2(2):e0043. doi:10.5041/RMMJ.10043

24.             Yoon YS, Keum N, Zhang X, Cho E, Giovannucci EL. Hyperinsulinemia, insulin resistance and colorectal adenomas: A meta-analysis. Metabolism. 2015;64(10):1324-1333. doi:10.1016/j.metabol.2015.06.013

25.             McKenzie AL, Hallberg SJ, Creighton BC, et al. A Novel Intervention Including Individualized Nutritional Recommendations Reduces Hemoglobin A1c Level, Medication Use, and Weight in Type 2 Diabetes. JMIR Diabetes. 2017;2(1):e6981. doi:10.2196/diabetes.6981

26.             Westman EC, Yancy WS, Olsen MK, Dudley T, Guyton JR. Effect of a low-carbohydrate, ketogenic diet program compared to a low-fat diet on fasting lipoprotein subclasses. International Journal of Cardiology. 2006;110(2):212-216. doi:10.1016/j.ijcard.2005.08.034

27.             Yancy WS, Olsen MK, Guyton JR, Bakst RP, Westman EC. A Low-Carbohydrate, Ketogenic Diet versus a Low-Fat Diet To Treat Obesity and Hyperlipidemia. Ann Intern Med. 2004;140(10):769-777. doi:10.7326/0003-4819-140-10-200405180-00006

28.             Garg A, Grundy SM, Unger RH. Comparison of Effects of High and Low Carbohydrate Diets on Plasma Lipoproteins and Insulin Sensitivity in Patients With Mild NIDDM. Diabetes. 1992;41(10):1278-1285. doi:10.2337/diab.41.10.1278

29.             Gower BA, Chandler-Laney PC, Ovalle F, et al. Favourable metabolic effects of a eucaloric lower-carbohydrate diet in women with PCOS. Clinical Endocrinology. 2013;79(4):550-557. doi:10.1111/cen.12175

30.             Yuan X, Wang J, Yang S, et al. Effect of the ketogenic diet on glycemic control, insulin resistance, and lipid metabolism in patients with T2DM: a systematic review and meta-analysis. Nutr Diabetes. 2020;10(1):1-8. doi:10.1038/s41387-020-00142-z

31.             Gu Y, Yu H, Li Y, et al. Beneficial Effects of an 8-Week, Very Low Carbohydrate Diet Intervention on Obese Subjects. Evidence-Based Complementary and Alternative Medicine. 2013;2013:e760804. doi:10.1155/2013/760804

32.             Meng Y, Bai H, Wang S, Li Z, Wang Q, Chen L. Efficacy of low carbohydrate diet for type 2 diabetes mellitus management: A systematic review and meta-analysis of randomized controlled trials. Diabetes Research and Clinical Practice. 2017;131:124-131. doi:10.1016/j.diabres.2017.07.006

33.             Huntriss R, Campbell M, Bedwell C. The interpretation and effect of a low-carbohydrate diet in the management of type 2 diabetes: a systematic review and meta-analysis of randomised controlled trials. Eur J Clin Nutr. 2018;72(3):311-325. doi:10.1038/s41430-017-0019-4

34.             Nielsen JV, Joensson EA. Low-carbohydrate diet in type 2 diabetes: stable improvement of bodyweight and glycemic control during 44 months follow-up. Nutrition & Metabolism. 2008;5(1):14. doi:10.1186/1743-7075-5-14

35.             Unwin DJ, Tobin SD, Murray SW, Delon C, Brady AJ. Substantial and Sustained Improvements in Blood Pressure, Weight and Lipid Profiles from a Carbohydrate Restricted Diet: An Observational Study of Insulin Resistant Patients in Primary Care. International Journal of Environmental Research and Public Health. 2019;16(15):2680. doi:10.3390/ijerph16152680

36.             CDC. By the Numbers: Diabetes in America. Centers for Disease Control and Prevention. Published October 25, 2022. Accessed January 20, 2024. https://www.cdc.gov/diabetes/health-equity/diabetes-by-the-numbers.html