Summer Health Update Part 2 - What 3 Pounds of Meat Every Day Does To Your Blood Work

 

While my neurological health remains a few percentage points short of ideal, I’ve also been increasingly in touch with other aspects of my health as I continue to seek optimal recovery. The amount of “general health” bloodwork I’ve sought, measured, and ordered has increased significantly and, with that in mind, I’ve decided to share the most recent round of (semi-) comprehensive of blood work.

Conventional wisdom suggests that eating a diet high in meat and fat is dangerous for cardiometabolic and chronic health. For over a decade, I’ve progressively ignored that conventional wisdom. For years, this meant eating a lower carb (for an athlete, at least) paleo-type diet. Since my vaccine reaction, it has meant consuming various degrees of low-carb and ketogenic diets. And for more than a year now, it has meant more than 90% of my diet as beef. While I was largely sedentary for the first two years of my illness, the last several months have featured increasing amounts of exercise.

Despite the extended lack of activity and the ostensibly hazardous dietary reliance on meat and fat, you can see below that my chronic health markers are generally quite good. Below are the relevant results from my latest check-in and my commentary on each of the metrics. My recent diet and exercise statistics for reference:

Background statistics - 

Height – 6ft 3in        Weight – 161 lbs.         Age - 32y, 7m

     

8 week exercise averages –

~47 miles/week hiking and jogging, 2-3/week ~20 min strength training

8 week dietary averages –

~3320 calories/day        

70.5% fat/27.1% protein/2.4% carbohydrate (~19g/day)

48% saturated fat/48% monounsaturated fat/4% polyunsaturated fat

3 day dietary averages –

~3430 calories/day

71.2% fat/23.7% protein/5.1% carbohydrate (~43g/day)

48% sfa/48% mufa/4% pufa

 

 

 

 

Triglycerides – 87 mg/dL (Reference range 0-149)

I eat tons of fat, but don’t have tons of fat moving around my blood. What gives? Well, your triglyceride levels don’t reflect fat consumption or triglyceride production by the liver. Trigs reflect fatty acid utilization and fat metabolism. If you efficiently metabolize/utilize fat for energy, you should have low triglycerides. Common recommendations suggest under 150 to be normal, but realistically 150 is pretty sketchy and any values north of 100 suggest room for improvement.

 

HDL – 68 mg/dL (Reference range >39)

HDL levels are primarily responsive to two factors – triglyceride levels, and fat consumption. Elevated triglycerides resulting from metabolic inefficiency subsequently lead to a reduction in HDL-C (you can read about why here!). Meanwhile, fat consumption directly increases the concentration of the structural lipoproteins that eventually form HDL particles. Ergo, low trigs + high fat consumption = high HDL.

 

Triglyceride/HDL Ratio – 1.28

Not a unique measurement, but a reasonably meaningful reflection of metabolic health. Because poor metabolic health increases triglycerides and subsequently decreases HDL, a ratio between the two is a decent proxy for metabolic health. Conventional wisdom would suggest something like 3.5 to still be a fine value, even though cardiometabolic disease rates start exploding once you inch above this level. Personally, I wouldn’t feel great about anything higher than 1.5-2. For fun, I’ll include comparisons to bloodwork taken the day after a brief spring “binge” (3 days of higher carb, higher calorie consumption) as well as the day I ended an 8 day extended fast.

	April “Binge”	April Fast	June
Triglycerides	127	84	87
HDL-C	50	52	68
Trig/HDL Ratio	2.54	1.61	1.28

 

LDL – 113 mg/dL (Reference range 0-99)

Just about the least meaningful standalone marker out there, despite the medical and pharmaceutical indu$try’$ endle$$ obe$$e$$ion with $elling $tatins in order to force it lower in basically everyone. You can read tens of thousands of words I’ve written about the problems with LDL here or here if you’re interested. I’ll say this for now though – LDL is hyper-agile in a metabolically healthy person. My values can effortlessly bounce between roughly 100 and 200 depending on what I eat on any given day. I don’t care to ever see numbers lower than that, as I see no benefit whatsoever (and, for whatever its worth, low LDL is associated with significant increase in death and disease for several plausible reasons). Furthermore, you’ll note that despite consuming tons of fat and saturated fat, this value is actually slightly below the population average, even if its slightly above the recommended level. That’s because saturated fat is absolutely not the prime driver of LDL levels.

 

Apolipoprotein B – 84 mg/dL (Reference range <90)

ApoB is the structural protein that forms LDL particles, and is slowly beginning to replace LDL as the en vouge cardiovascular risk measure (It is a better measure than LDL, but is subject to many of the same flaws as well). This value reflects the number of LDL particles in circulation, and you’ll note once again that despite eating tons of fat my values are actually below average and in the “approved” medical range. 

 

LDL/ApoB Ratio – 1.35

My ApoB, which reflects LDL particle count, is in the recommended range, but my LDL cholesterol is still high. How does this work? The answer lies in particle size – fewer ApoB particles carrying a given amount of cholesterol suggests those particles are on the larger size. This matters for a couple reasons – small particles indicate poor metabolic efficiency, while being themselves highly susceptible to the oxidative and glycemic damage that commonly triggers the immune-mediated atherosclerotic process. A ratio of 1.2 or so is a common cut point in the literature, with ratios below that suggesting significant cardiometabolic risk. I’ve previously forced mine as low as 1.15 with just a couple days of higher carb consumption, but would prefer not to see values below about 1.3 in typical conditions. Prior comparisons included here as well.

	April “Binge”	April Fast	June
LDL-C	108	180	113
ApoB	94	139	84
LDL/ApoB Ratio	1.15	1.29	1.35

 

C-Reactive Protein - <1 mg/L (Reference range 0-10)

CRP is a measure of systemic inflammation. You’d like to see this number as close to zero as possible, generally speaking, and the reference range extending to 10 is flat-out crazy. In the absence of some other relevant factor like a recent race, I’d really hate to see even a value of 2. Unfortunately, LabCorp doesn’t report values below 1, meaning you never really want to see an actual value on one of these tests. The one time I managed to have this tested at another lab, it was at 0.2.

 

Hemoglobin A1C – 5.1% (Reference range 4.8 - 5.6)

HbA1C is a measure of long-term blood sugar (specifically a measure of how many red blood cells have been glycated by sugar in the blood). Its commonly used to assess or monitor diabetes status. Values for HbA1C exist across a fairly narrow band – 5 is great, 6 is pretty terrible (though plenty of people hit 8, 9, or even higher). Current guidelines consider 5.7 or higher to be “prediabetes” and you really don’t want to see this above the low 5s.

 

Glucose – 95 mg/dL (Reference range 0-99)

This is on the high side for me, as fasting glucose usually bounces around between about 85 and 95. I don’t think a single number is worth all that much when you can just look at A1C and capture a long-term picture, but it’s a normal enough number regardless

 

Insulin – 1.7 uIU/mL (Reference range 2.6-24.9)

Arguably the single most important measurement on here in my view. Insulin is a storage and growth hormone secreted primarily in response to carbohydrate consumption. Chronically elevated levels of insulin are instrumental in metabolic dysfunction and contribute to the insulin resistance that defines diabetes and so much of cardiometabolic disease. The normal reference range of “less that 25” is absolutely off the rails. A person with fasting insulin levels in the 20s is so metabolically sick. Just ridiculous to label it normal in any sense of the word. This is a number you want in the low to mid single digits, with numbers closer to 10 more than sufficient to disrupt optimal metabolic health and function. As mentioned, carbohydrates are the primary driver of insulin levels. I consume very few, and thus have very low fasting insulin.

 

HOMA-IR - 0.4

The Homeostatic Model Assessment of Insulin Resistance is a simple, non-invasive method of estimating an individual’s resistance to insulin using fasting glucose and insulin values. Insulin resistance is a prime driver of heart disease and other chronic diseases, and quite literally is diabetes. HOMA-IR values under 1 are considered optimal, with values north of 2 indicating moderate or greater insulin resistance. A low HOMA-IR and high insulin sensitivity are generally to be expected when consuming a low-carbohydrate diet. I'll add the binge/fast comparison here as well

	April “Binge”	April Fast	June
Glucose	106	66	95
Insulin	11.4	1.3	1.7
HOMA-IR	3.0	0.2	0.4

 

Uric Acid – 3.5 mg/dL (Reference range 3.8-8.4)

Say it with me – “red meat doesn’t cause gout.” This is bit of nonsense that continues to be propagated throughout nutrition and medical circles, but it doesn’t reflect reality. Uric acid is a nitrogen-containing compound that forms from the breakdown of purines, which are indeed found more abundantly in animal products than in plants. But then a healthy person just pees the uric acid out, while a metabolically dysfunctional individual will not. Which is why elevated uric acid levels are tightly linked to insulin levels, obesity, and metabolic syndrome, while mine is out the bottom of LabCorp’s reference range.

 

Vitamin D – 39.1 ng/mL (Reference range 30-100)

This is lower than I’d like. The reference range says above 30 is fine but would realistically like to be double that. I already triggered neuro symptoms trying some vitamin D drops so now the strategy will be a bit more eggs, salmon, and mid-day sun before maybe assessing again.

 

Thyroxine (T4) – 1.2 ng/dL, TSH – 1.14 uIU/mL (Reference range 0.82-1.77, 0.45-4.5) 

My thyroid hormones are perfectly normal.

 

Blood pressure – 110/70, 110/64 mmHg (Reference range <120/80)

These are my two latest doctor’s office BP readings, although I somewhat regularly measure my own BP and find these values to be quite typical. Elevated blood pressure is really just another manifestation of chronic insulin resistance, rather than salt consumption or any other acute dietary factor (I literally drink salt in my water for whatever that’s worth). Its only chronic carb/sugar consumption and elevated insulin that will raise blood pressure, so again optimal measures are unsurprising.

 

Testosterone: Total – 183 ng/dL, Free - 4.4 pg/mL (Reference range 264-916, 8.7-25.1)

And here’s the one that was actually a problem. Normal testosterone for a healthy 30-something should be a few hundred points higher than this. This proved to be a big sign that I wasn’t eating enough, as downregulated hormone production is one obvious consequence of underfueling (this is just one reason that “calories” is a quasi-worthless way to approach weight and metabolism). Unsurprisingly, I was more sluggish than I should have been and slowly losing weight as well. But while my testosterone was quite low, the good news is I’ve since rectified the problem pretty much by just eating more. A month later, my total testosterone was up to 543.

There you have yet...meat and fat aren't killing me yet!

Summer Health Update Pt 1 - I'm Still Not Quite Healthy

 

A couple Saturdays ago I ran 22 miles. It was slow, and easy. But it was 22 miles nonetheless – my longest run since Kona almost four years ago. Two days after that I ran a semi-spontaneous mile at a local track. It was slow, and quite hard. But it was fast enough to suggest some fitness was coming along. In only my 9^th week back running, I had clearly managed at least some degree of improvement.  

Unfortunately, that day I also had woken up feeling less than optimal – just a bit agitated, heart rate was high, slight head and neck pains. The kind of extremely low-grade nervous system dysfunction I had largely avoided the prior couple of months. This got worse for a couple of days, until I finally realized the vitamin D drops I had started taking (more on this in the next post) were causing the problem. The drops were suspended in coconut oil, and even just a drop or two a day turned out to be enough to start triggering my ever-lurking neurological symptoms.

My diet had remained quite strict through the spring and summer, but was more inclusive than it had been at one point. I was consistently consuming reasonable amount of organic fruits – specifically berries and avocados – without issue, to go along with copious meat and occasional fish and egg consumption. This had been working fine, and had resulted in weeks of borderline symptom free training – I was running nearly every day, and hitting upwards of 60 miles per week.

However, even after quitting the vitamin D drops, the diet and my health kind of came apart on me a bit. An all-day road trip saw me cave and drink a cup of coffee, in addition to plantain chips and the consumption of packaged meats that served as my reintroduction to pepper and other seasonings. Lasting for several days after, for the first time since spring, an entire constellation of neurological symptoms returned – limbs tingling and going numb when sitting, brain fog, heart palpitations, increased pain and sensitivity in my neck. Just like that, I was no longer running again.

To be clear, it hasn’t been dietary factors alone triggering or exacerbating symptoms, and my health hadn’t been literally perfect. But it had been quite close, and my mistakes in those couple of weeks both temporarily derailed my progress and made clear that my underlying issues still required some reasonable measure of improvement to return to full health. The poor air quality in the decades old building at which I work seems a bit of a trigger, but has been partially remedied by an air purifier. The smoke from the Canadian wildfires may be as well, and significant emotional and/or cognitive strain still seems to exacerbate any symptoms already present.

But mostly it’s the food, or the plants specifically. So now I retrace my steps yet again, and hope for even further improvement. I’ve just ended a nearly 4 day fast as I type this (the previous 8 day fast in April marked a massive step forward and my return to quasi-normal health and exercise), and intend now to redouble my efforts to avoid dietary mistakes that threaten to disrupt my progress. Beef, salmon, eggs, some organic fruit remain the staples and will stay that way for quite some time, ideally without exception. While there is still a fair bit of progress to be made, I feel generally good about my health, both with respect to the gradual neurological/autoimmune progress and (as I’ll write about next) in a comprehensive metabolic sense.

Healthy User Bias Taints Everything

In the early 1950s, prominent University of Minnesota physiologist Ancel Keys, whose work was funded in part by the massive Sugar Research Foundation, began publicly promoting his hypothesis that dietary fat and cholesterol were the main drivers of cardiovascular disease

In 1955, President Eisenhower suffered arguably the most noteworthy heart attack in history, launching heart disease fully into the public consciousness. Taking on Keys as a personal advisor, Eisenhower adopted and began advocating for a “prudent” low-fat diet.

In 1961 the American Heart Association officially condemned saturated fat as a likely cause of heart disease. The AHA was by this time the world’s largest non-profit, largely thanks to significant funding from Proctor & Gamble, makers of the industrial saturated-fat replacement product Crisco. That same year, Ancel Keys appeared on the cover of Time Magazine, depicted as a scientific crusader against the scourge of saturated fat.

1977 saw the initial release of the US government’s first “Dietary Goals for Americans,” which advised Americans, in the interest of health, to strictly limit their consumption of saturated fat, cholesterol, and the animal products that contain them.

By this time, the recommendations were fairly predictable. Keys, Eisenhower, the AHA, publicized congressional hearings, and more contributed to what was fast becoming common knowledge – that the consumption of fatty foods, red meat, saturated fat, and cholesterol were a danger to health and well-being.

In the 1980s, finally, researchers began looking to see whether any of it was actually true.

Epidemiology

Now, I don’t mean to say nutrition research as a whole literally started in the 1980s, only the type you’re most familiar with.^1,2 Nutrition research more broadly started in earnest a couple decades prior when researchers set about trying to legitimize the guidelines that had already been set forth. Often, it should be noted, these studies promptly proved them wrong. For example, major trials such as the Sydney Diet Heart Study and Keys’ own Minnesota Coronary Experiment sharply reduced saturated fat intake for thousands of subjects…who subsequently died at higher rates than the groups who continued consuming their butter and eggs.^3,4 A landmark trial in the 1970s included smoking cessation alongside the “prudent diet” and had only to show for it a slight decrease in cardiovascular disease and a slight increase in overall death.⁵ That ostensibly counterintuitive results like these did nothing to slow the low-fat train speaks to how rapidly and aggressively such advice was being pushed.

Instead, the type of study that had never yet been carried out, but with which you’re most familiar today, is something called nutritional epidemiology. In essence, it is a field that attempts to examine dietary trends at a population level and seek out associations between these trends and various health outcomes. A common approach, for example, is to survey hundreds or thousands of subjects on their dietary habits for the past year (using something called a Food Frequency Questionnaire) and either assess or track changes in various health markers. Researches will ask about other things as well – smoking, exercise, etc. – and attempt to find connections between certain habits and favorable or unfavorable health outcomes.

Epidemiology is a weak science in that it is only an observation, and cannot control many factors in the way a well-designed interventional trial can. For this reason, it can never “prove” anything, although it is a popular brand of nutritional science nonetheless, owing largely to its simplicity and comparatively cheap cost. If you’ve ever seen a news headline linking some food to a given disease, what they were reporting on were the results of nutritional epidemiology.

But there’s one major problem with epidemiology that in many circles never garners the attention it deserves. Because conventional nutrition guidelines and advice predate nutritional epidemiology by decades, there has never been an epidemiological study untainted by the effects of these guidelines. As epidemiological observations increase in rate and conventional guidelines persist year over year, this problem continues to get worse.

Because here’s the thing – it is, for better or worse, common knowledge that meat and saturated fat are “bad” for you. Most adults have heard this for their entire lives, and the majority of them likely believe it to be true. They also believe smoking to be bad for their health, likewise for alcohol, sugar, and a sedentary lifestyle. It should not be surprising, then, that one who partakes in any of these ostensibly damaging behaviors is more likely to engage in additional harmful acts as well. Consider a study linking red meat consumption to diabetes, for example, that found the group eating the most red meat was 40% less active, drank 60% more alcohol, consumed several hundred additional daily calories worth of sugar and refined grain, and were three times more likely to smoke than those who ate the least.⁶ (You can read more over here about how ignoring over 400 calories per day of sugar and refined grains helps create the catchy headline about meat causing diabetes).

 

Insufficient Adjustment

Usually (but not always!), researchers adjust for the most obvious lifestyle habits – exercise, smoking, alcohol – in attempt to prevent them from tainting the results. But what about things like sleep? What about hydration and hygiene and seat belts and safe driving? What about preventative health care? Trying to link a dietary pattern to cancer mortality gets sketchy really quick if one group is more diligent about cancer screenings. The unfortunate reality of epidemiology is that, undoubtedly, the vegetable-eating exercisers who don’t smoke are also going to be healthier in almost every little way you can imagine, even if the researchers don’t adjust for it.

If a study says women who eat the most vegetables are 15% less likely to develop cardiovascular disease, how much of that is actually due to the veggies?⁷ And how much of it is due to the unmeasured practices like those above – sleep habits, preventative health care, risk-taking behavior, and so on? And what if that 15% doesn’t even consider other dietary factors, like sugar? You can be quite certain that those eating the most vegetables were, on average, eating the least sugar. But the researchers in this study didn’t measure or adjust for it, so that’s probably some of our 15% right there.

Unfortunately, its not remotely uncommon for studies like this to completely ignore sugar or any other dietary factor.^8–10 Often, this is even acknowledged once you start reading the actual study. Take for example a meta-analysis (a bunch of studies pooled together for more statistically powerful results) that claims to have found “further evidence that a higher consumption of fruit and vegetables is associated with a lower risk of all-cause mortality” – even while acknowledging that fewer than half of the studies assessed other aspects of the subjects diets.¹¹ They included one that didn’t even adjust for alcohol consumption or exercise!¹² So while they claim that their findings “provide further support for the public health message to increase fruit and vegetable intake”…did they really? Or did they just ask people how many vegetables they eat and found the healthy ones consume more than the sedentary drinkers do.

 

Meat Causes Disease…. Right?

If you’re still looking for more indication that healthy user bias taints epidemiology, consider this study that claims to “provide evidence that dietary modification in choice of protein sources may influence health and longevity.”¹³ They tracked nearly 240,000 (!) men and found that each 3% reduction in red meat consumption was associated with a 7% reduction in cancer mortality, a 12% reduction in cardiovascular death….and an 18% reduction in death due to injury or accident. Another found that men who ate the most red meat (compared to those who ate the least) were at a 22% increased risk of dying from cancer, 27% increased risk of dying from cardiovascular disease, and 26% increased risk of dying in an accident.¹⁴ None of this should be surprising! After all, dangerous drivers are more likely to eat animal based or processed food snacks, while seatbelt use seems to predict chronic disease more strongly than meat consumption does.^15,16 But these behaviors are simply never accounted for in nutritional epidemiology.

The numbers we’re talking about in some of these epidemiological pieces are often tiny, and its impossible to adjust for all the factors that go into a person’s risk for disease – if researchers even try! Remember all the headlines a few years back about bacon causing colorectal cancer, to the tune of an 18% increase if you eat some every day?¹⁷ 18% is a tiny number when considering relative risk – its the difference between a .037% annual risk and a .044% annual risk, a roughly 1 in 14,000 chance your daily bacon will cause colorectal cancer this year.¹⁸ And that’s if we accounted for healthy user bias! Which we certainly did not. Sugar and refined grains are habitually ignored in epidemiology, and you may never find such a study that adjusts for one of the major effects of excess refined carb consumption – elevated insulin levels. Consider that high levels of insulin production may be associated with as much as a 200-300% increase in relative risk of colorectal cancer!^19–21 And we’ve ignored it entirely.

When researchers fail to consider the excess sugar and processed grain consumption of bacon-eaters and the excess insulin that results (among other lifestyle habits left unadjusted), they have fundamentally failed in their task to actually access whether any link exits between bacon and cancer risk. Yet the BBC will still claim unequivocally that bacon causes cancer, further exaggerating the effects of healthy user bias in future epidemiological pieces by pushing the health-conscious to consume even less of the apparently dangerous food item.

 

Conclusion

This entire piece probably makes it sound like I have it out for fruits and veggies while trying hard to defend red meat. But remember, healthy user bias only works in one direction – there are no studies in which vegetables appear unfairly demonized, because its generally healthy people who eat them. Only the foods people have been told are bad (meat, saturated fat, etc.) can be made to look worse than they are, while only foods that people have been told are good (veggies, whole grains, etc.) can be made to look better. And in fact, to some degree, this effect is present in literally every piece of epidemiology you ever read. Regardless of how good or bad each really is, meat and fat will always, without exception, look some degree worse while vegetables and whole grains look better than any of them are in reality.

So, next time a scary headline suggests that steak will literally kill you, remember:

• The study in question did not assess cause and effect, only an association between two items
• The study in question is likely actually measuring an association between red meat + sugar + refined grain consumption and the scary disease, not just red meat and disease
• The researchers did not consider any health behaviors beyond smoking, alcohol, and exercise (hopefully they at least considered those). Sleep, preventative health care, adherence to safety protocol, risk-taking behavior, and other factors were not included in their assessment
• Red meat "causes" more car crashes than it does cases of cancer

 

1.               Mozaffarian D, Rosenberg I, Uauy R. History of modern nutrition science—implications for current research, dietary guidelines, and food policy. BMJ. 2018;361:k2392. doi:10.1136/bmj.k2392

2.               Boeing H. Nutritional epidemiology: New perspectives for understanding the diet-disease relationship? Eur J Clin Nutr. 2013;67(5):424-429. doi:10.1038/ejcn.2013.47

3.               Ramsden CE, Zamora D, Leelarthaepin B, et al. Use of dietary linoleic acid for secondary prevention of coronary heart disease and death: evaluation of recovered data from the Sydney Diet Heart Study and updated meta-analysis. BMJ. 2013;346:e8707. doi:10.1136/bmj.e8707

4.               Ramsden CE, Zamora D, Majchrzak-Hong S, et al. Re-evaluation of the traditional diet-heart hypothesis: analysis of recovered data from Minnesota Coronary Experiment (1968-73). BMJ. 2016;353:i1246. doi:10.1136/bmj.i1246

5.               Multiple Risk Factor Intervention Trial: Risk Factor Changes and Mortality Results. JAMA. 1982;248(12):1465-1477. doi:10.1001/jama.1982.03330120023025

6.               Pan A, Sun Q, Bernstein AM, et al. Red meat consumption and risk of type 2 diabetes: 3 cohorts of US adults and an updated meta-analysis. The American Journal of Clinical Nutrition. 2011;94(4):1088-1096. doi:10.3945/ajcn.111.018978

7.               Liu S, Manson JE, Lee IM, et al. Fruit and vegetable intake and risk of cardiovascular disease: the Women’s Health Study,. The American Journal of Clinical Nutrition. 2000;72(4):922-928. doi:10.1093/ajcn/72.4.922

8.               Bellavia A, Larsson SC, Bottai M, Wolk A, Orsini N. Fruit and vegetable consumption and all-cause mortality: a dose-response analysis1,2,3. The American Journal of Clinical Nutrition. 2013;98(2):454-459. doi:10.3945/ajcn.112.056119

9.               Nakamura K, Nagata C, Oba S, Takatsuka N, Shimizu H. Fruit and Vegetable Intake and Mortality from Cardiovascular Disease Are Inversely Associated in Japanese Women but Not in Men1,2. The Journal of Nutrition. 2008;138(6):1129-1134. doi:10.1093/jn/138.6.1129

10.             Sauvaget C, Nagano J, Hayashi M, Spencer E, Shimizu Y, Allen N. Vegetables and fruit intake and cancer mortality in the Hiroshima/Nagasaki Life Span Study. Br J Cancer. 2003;88(5):689-694. doi:10.1038/sj.bjc.6600775

11.             Wang X, Ouyang Y, Liu J, et al. Fruit and vegetable consumption and mortality from all causes, cardiovascular disease, and cancer: systematic review and dose-response meta-analysis of prospective cohort studies. BMJ. 2014;349(jul29 3):g4490-g4490. doi:10.1136/bmj.g4490

12.             Genkinger JM, Platz EA, Hoffman SC, Comstock GW, Helzlsouer KJ. Fruit, Vegetable, and Antioxidant Intake and All-Cause, Cancer, and Cardiovascular Disease Mortality in a Community-dwelling Population in Washington County, Maryland. American Journal of Epidemiology. 2004;160(12):1223-1233. doi:10.1093/aje/kwh339

13.             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

14.             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

15.             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

16.             Ge Y, He S, Xu Y, Qu W. Effects of dietary patterns on driving behaviours among professional truck drivers: the mediating effect of fatigue. Occup Environ Med. 2021;78(9):669-675. doi:10.1136/oemed-2020-107206

17.             Processed meats do cause cancer - WHO. BBC News. https://www.bbc.com/news/health-34615621. Published October 26, 2015. Accessed June 25, 2023.

18.             USCS Data Visualizations. Accessed June 25, 2023. https://gis.cdc.gov/grasp/USCS/DataViz.html

19.             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

20.             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

21.             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