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

The Problematic Paradigm of LCL-C, Part 12

Part 12 - The Effects of Diet on LDL-C, As Told By Energy Delivery

Previous - Part 11 - The Effects of Diet on Markers of Cardiovascular and Metabolic Health

In the previous, penultimate section we touched on the ways in which macronutrient distribution affects common markers of cardiometabolic health. One incredibly popular marker still remains, though, and that is of course LDL-C.

There are a couple good reasons to save LDL-C for last. For one, it doesn’t move in a consistent direction with carbohydrate restriction in the way HDL-C, triglycerides, or blood sugar might – how it moves depends on who is restricting carbohydrates. But mostly, we’re discussing it last because this entire series focuses on the shortcomings of the modern cholesterol paradigm, in which LDL-C is the central player.

To be clear, I am not making the claim that nothing in the world aside from energy delivery affects LDL-C levels. For example, plant sterols (essentially the plant version of cholesterol, but not usable in the human body) lower LDL-C to a certain degree. But, as has been explained at length in this series, I am making the claim that energy delivery is the primary driver of LDL cholesterol levels. And furthermore, that this energy system is driven primarily by what you eat.

So…what happens to your LDL-C when you eat more carbs, or, perhaps, what happens when you eat less?

 

Personal Anecdote

Early last month I consumed a fairly prodigious amount of cheese (and more – the reasons why are here, but aren’t important) over the course of a weekend before having my blood drawn the next day. My LDL-C on that morning? 108mg/dl. This was on the heels of some significant fat consumption – a three day average of 192g of saturated fat, some 8 or 9 times more than the USDA recommend the average person eat in a day.

Just 13 days later, another blood draw returned an LDL-C of 180 mg/dl. In the intervening days, I consumed a maximum of 152g of saturated fat and averaged only 83g per day. Clearly, saturated fat consumption didn’t drive the extreme increase in LDL-C, as it is traditionally thought to do. So, what happened?

The important missing information is that the second blood draw came on day 3 of an extended fast, meaning I had literally consumed nothing – zero grams of fat – the two days prior. My LDL-C was elevated for the exact reasons that have been outlined at length in these writings – increasing LDL-C is an unavoidable consequence of utilizing fat for energy.

 

Low-Carb Trials and LDL-C

We don’t need to rely on my stories for evidence though – studies indeed demonstrate that healthy individuals will see a rise in LDL-C during extended fasting.^1,2 Healthy individuals moving to a very low-carbohydrate diet experience the same, just as we would expect.^3–7 Note the use of the word “healthy” here – these are individuals without significant metabolic dysfunction. They neatly fit the profile we’ve described of a metabolically healthy individual with excellent health markers that experience an increase in LDL-C as a consequence of trafficking triglycerides for energy.

But what if they weren’t healthy? Imagine instead a study that enrolled only those with metabolic dysfunction, obesity, and insulin resistance. These individuals might very well already have elevated LDL-C alongside poor markers of metabolic health, a consequence of poor triglyceride utilization, increased return of triglycerides to the liver, and compensatory VLDL production. The traditional cholesterol paradigm would likely be aghast at the suggestion that these individuals consume more fat, with their LDL-C already considered a risk to their health and the increased fat, surely, likely to elevate it even further.

But of course, this is not what happens. As many studies that demonstrated, the common finding in these individuals is indeed lower LDL-C following the transition to a low-carb, high-fat diet.^8–21 Of course, an energy delivery model of lipid metabolism explains clearly why this is the case – reduced blood sugar and insulin levels allow for improved fatty acid utilization, increased triglyceride clearance, reduced triglyceride return to the liver, and the gradual reduction of excess VLDL production. Much like my fasting example above, a traditional paradigm that suggests fat consumption as the prime driver of elevated LDL-C levels simply cannot explain these observations.

(You may notice here that these findings, taken together, suggest that over a long enough time frame an obese individual restricting carbohydrates would experience BOTH an initial decrease in LDL-C and then again increasing LDL-C levels following a return to normal weight and metabolic health. Of course, every other possible marker of health – HDL-C, triglycerides, blood sugar, body fat, blood pressure, etc. – would be much closer to optimal by the end of this journey)

 

Conclusion

If you’ve read the first eleven sections on this topic, nothing written above is surprising or even new. While the traditional paradigm continues to stress carbohydrate consumption in an effort to lower LDL-C, it is overwhelmingly clear that this approach may or may not have the desired effect but will certainly contribute to worsening metabolic health. I’ll end this series with the conclusion from my paper on cholesterol and lipid metabolism:

 

“This paper is absolutely not intended to make the argument that elevated LDL-C via an energy-driven increase in endogenous VLDL production is a metabolic state for which one need necessarily strive. Instead, this particular metabolic presentation is examined at length because it succinctly highlights the failure of the lipid-heart and diet-heart hypotheses that have undermined public health for decades. It is not a metabolic state towards which one needs to strive, but, far more importantly, it is also does not appear to be a metabolic state of which one needs to be afraid. The full body of scientific evidence, massive in both scope and depth, makes this incredibly clear.

What this paper is meant to argue is that the myopic focus on LDL-C and total cholesterol and the demonization of dietary fat must begin receding from medical, nutritional, and public consciousness if chronic health is to improve in western society. It is absolutely meant to highlight the indisputable evidence that every legitimate marker of chronic and cardiometabolic health – HDL-C, triglycerides, modified LDL particles, and others – has been repeatedly and overwhelmingly demonstrated to improve with a decrease in carbohydrate consumption. The understanding that poor triglyceride utilization, driven by insulin resistance and excess carbohydrate consumption, is the primary factor in metabolic dysfunction is crucial to recognizing the failure of conventional guidelines in addressing these risk factors. An energy deliver model of lipid metabolism best explains the available interventional evidence and wide range of lipid observations, existing in stark contrast to the abject catastrophe that is an entrenched paradigm of outdated and anti-scientific dogma pushing unsuspecting persons quickly and aggressively towards dyslipidemia, disease, and death.

The lipid-heart hypothesis has been allowed to survive for so long because the broad relationship between LCL-C and cardiovascular disease will always exist in an insulin resistant population that overconsumes carbohydrates. While the relationship is loosely valid in a diseased population, it should not be considered good enough for the purposes of preventing or especially treating cardiometabolic disease. Instead, the goal in both cases must be to prevent or reverse the underlying insulin resistance and the host of hyperglycemia-induced damages that occur alongside it. Only when this happens, when lipids are fairly viewed as an energy delivery system rather than as a disease state, can cardiovascular, metabolic, and chronic health truly be improved.”

 

 

Key takeaways

• LDL-C is increased when a metabolically healthy person significantly reduces carbohydrate consumption, either through fasting or a low-carb diet
• LDL-C is reduced when a person with poor metabolic health reduces carbohydrates, because previous elevations were driven by metabolic dysfunction rather than fat consumption
• Advocacy for an increase in carbohydrate consumption has variable effects on LDL-C, a marker with little to no independent relationship with cardiovascular disease, while clearly and consistently worsening every other marker of cardiometabolic health

 

1.               Browning JD, Baxter J, Satapati S, Burgess SC. The effect of short-term fasting on liver and skeletal muscle lipid, glucose, and energy metabolism in healthy women and men. Journal of Lipid Research. 2012;53(3):577-586. doi:10.1194/jlr.P020867

2.               Sävendahl L, Underwood LE. Fasting Increases Serum Total Cholesterol, LDL Cholesterol and Apolipoprotein B in Healthy, Nonobese Humans. The Journal of Nutrition. 1999;129(11):2005-2008. doi:10.1093/jn/129.11.2005

3.               Volek JS, Sharman MJ, Gómez AL, Scheett TP, Kraemer WJ. An Isoenergetic Very Low Carbohydrate Diet Improves Serum HDL Cholesterol and Triacylglycerol Concentrations, the Total Cholesterol to HDL Cholesterol Ratio and Postprandial Lipemic Responses Compared with a Low Fat Diet in Normal Weight, Normolipidemic Women. The Journal of Nutrition. 2003;133(9):2756-2761. doi:10.1093/jn/133.9.2756

4.               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

5.               Sharman MJ, Kraemer WJ, Love DM, et al. A Ketogenic Diet Favorably Affects Serum Biomarkers for Cardiovascular Disease in Normal-Weight Men. The Journal of Nutrition. 2002;132(7):1879-1885. doi:10.1093/jn/132.7.1879

6.               Lee HS, Lee J. Influences of Ketogenic Diet on Body Fat Percentage, Respiratory Exchange Rate, and Total Cholesterol in Athletes: A Systematic Review and Meta-Analysis. International Journal of Environmental Research and Public Health. 2021;18(6):2912. doi:10.3390/ijerph18062912

7.               Burén J, Ericsson M, Damasceno NRT, Sjödin A. A Ketogenic Low-Carbohydrate High-Fat Diet Increases LDL Cholesterol in Healthy, Young, Normal-Weight Women: A Randomized Controlled Feeding Trial. Nutrients. 2021;13(3):814. doi:10.3390/nu13030814

8.               Hussain TA, Mathew TC, Dashti AA, Asfar S, Al-Zaid N, Dashti HM. Effect of low-calorie versus low-carbohydrate ketogenic diet in type 2 diabetes. Nutrition. 2012;28(10):1016-1021. doi:10.1016/j.nut.2012.01.016

9.               Westman EC, Yancy WS, Edman JS, Tomlin KF, Perkins CE. Effect of 6-month adherence to a very low carbohydrate diet program. The American Journal of Medicine. 2002;113(1):30-36. doi:10.1016/S0002-9343(02)01129-4

10.             Foster GD, Wyatt HR, Hill JO, et al. Weight and Metabolic Outcomes After 2 Years on a Low-Carbohydrate Versus Low-Fat Diet. Ann Intern Med. 2010;153(3):147-157. doi:10.7326/0003-4819-153-3-201008030-00005

11.             Lim SS, Noakes M, Keogh JB, Clifton PM. Long-term effects of a low carbohydrate, low fat or high unsaturated fat diet compared to a no-intervention control. Nutrition, Metabolism and Cardiovascular Diseases. 2010;20(8):599-607. doi:10.1016/j.numecd.2009.05.003

12.             Iqbal N, Vetter ML, Moore RH, et al. Effects of a Low-intensity Intervention That Prescribed a Low-carbohydrate vs. a Low-fat Diet in Obese, Diabetic Participants. Obesity. 2010;18(9):1733-1738. doi:10.1038/oby.2009.460

13.             Dansinger ML, Gleason JA, Griffith JL, Selker HP, Schaefer EJ. Comparison of the Atkins, Ornish, Weight Watchers, and Zone Diets for Weight Loss and Heart Disease Risk ReductionA Randomized Trial. JAMA. 2005;293(1):43-53. doi:10.1001/jama.293.1.43

14.             Maki KC, Beiseigel JM, Jonnalagadda SS, et al. Whole-Grain Ready-to-Eat Oat Cereal, as Part of a Dietary Program for Weight Loss, Reduces Low-Density Lipoprotein Cholesterol in Adults with Overweight and Obesity More than a Dietary Program Including Low-Fiber Control Foods. Journal of the American Dietetic Association. 2010;110(2):205-214. doi:10.1016/j.jada.2009.10.037

15.             Harman NL, Leeds AR, Griffin BA. Increased dietary cholesterol does not increase plasma low density lipoprotein when accompanied by an energy-restricted diet and weight loss. Eur J Nutr. 2008;47(6):287. doi:10.1007/s00394-008-0730-y

16.             Lofgren I, Zern T, Herron K, et al. Weight loss associated with reduced intake of carbohydrate reduces the atherogenicity of LDL in premenopausal women. Metabolism. 2005;54(9):1133-1141. doi:10.1016/j.metabol.2005.03.019

17.             Klempel MC, Kroeger CM, Bhutani S, Trepanowski JF, Varady KA. Intermittent fasting combined with calorie restriction is effective for weight loss and cardio-protection in obese women. Nutr J. 2012;11(1):98. doi:10.1186/1475-2891-11-98

18.             Dashti H, Bo-Abbas Y, Asfar S, et al. Ketogenic diet modifies the risk factors of heart disease in obese patients. Nutrition (Burbank, Los Angeles County, Calif). 2003;19:901-902. doi:10.1016/S0899-9007(03)00161-8

19.             Dashti HM, Mathew TC, Khadada M, et al. Beneficial effects of ketogenic diet in obese diabetic subjects. Mol Cell Biochem. 2007;302(1):249-256. doi:10.1007/s11010-007-9448-z

20.             Dashti HM, Mathew TC, Hussein T, et al. Long-term effects of a ketogenic diet in obese patients. Exp Clin Cardiol. 2004;9(3):200-205.

21.             Dashti HM, Al-Zaid NS, Mathew TC, et al. Long Term Effects of Ketogenic Diet in Obese Subjects with High Cholesterol Level. Mol Cell Biochem. 2006;286(1):1. doi:10.1007/s11010-005-9001-x