Tag Archives: CHD

Proving that black is white

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Last week I was going through some old files, and presentations, in a vague effort to clean up my computer. Whilst looking a one of many thousands of studies I had filed away I came across this paper: ‘Clarifying the direct relation between total cholesterol levels and death from coronary heart disease in older persons1.’

I read it, and immediately recalled why I kept it. For it came to the following, final, conclusion:

 ‘Elevated total cholesterol level is a risk factor for death from coronary heart disease in older adults.’

I remember when I first read this paper a few years ago. My initial thought was to doubt that it could be true. Most of the evidence I had seen strongly suggested that, in the elderly, a high cholesterol level was actually protective against Coronary Heart Disease (CHD).

However, when a bunch of investigators state unequivocally that elevated cholesterol is a risk factor for heart disease, I try to give them the benefit of the doubt. So I read the damned thing. Always a potentially dangerous waste of precious brainpower.

Now, I am not going to dissect all the data in detail here, but one sentence that jumped out of the paper was the following:

‘Persons (Over 65) with the lowest total cholesterol levels ≤4.15 mmol/L had the highest rate of death from coronary heart disease, whereas those with elevated total cholesterol levels ≥ or = 6.20 mmol/L seemed to have a lower risk for death from coronary heart disease. ‘

Now, I can hardly blame you if you struggled to fit those two quotes together. On one hand, the conclusion of the paper was that .. ‘Elevated total cholesterol level is a risk factor for death from coronary heart disease in older adults.’ On the other hand, the authors reported that those with the lowest total cholesterol levels had the highest rate of CHD; whilst those with the highest cholesterol levels had the lowest rate of CHD.

Taken at face value, this paper seems to be contradicting itself…. utterly. However, the key word here, as you may have already noted, is seemed. As in… those with elevated total cholesterol levels ≥ or = 6.20 mmol/L seemed to have a lower risk for death from coronary heart disease. ‘

Now you may think that this is a strange word to use in a scientific paper. Surely those with elevated total cholesterol levels either did, or did not, have a lower risk of death from CHD? Dying is not really something you can fake, and once a cause of death has been recorded it cannot be changed at a later date. So how can someone seem to die of something – yet not die of it?

The answer is that you take the bare statistics, then you stretch them and bend them until you get the answer you want. Firstly, you adjust your figures for established risk factors for coronary heart disease – which may be justified (or may not be). Then you adjust for markers of poor health – which most certainly is not justified – as you have no idea if you are looking at cause, effect, or association.

Then, when this doesn’t provide the answer you want, you exclude a whole bunch of deaths, for reasons that are complete nonsense. I quote:

‘After adjustment for established risk factors for coronary heart disease and markers of poor health and exclusion of 44 deaths from coronary heart disease that occurred within the first year, (my bold text) elevated total cholesterol levels predicted increased risk for death from coronary heart disease, and the risk for death from coronary heart disease decreased as cholesterol levels decreased.’

Why did they exclude 44 deaths within the first year?  Well, they decided that having a low cholesterol levels was a marker for poor health, and so it was the poor health that killed them within the first year.

The reason why they believed they could do this is that, a number of years ago, a man called Iribarren decreed that the raised mortality always seen in those with low cholesterol levels is because people with low cholesterol have underlying diseases. And it is these underlying diseases that kill them. (What, even dying from CHD. And how, exactly does CHD cause a low cholesterol levels….one might ask).

In truth, there has never been a scrap of evidence to support Iribarren’s made-up ad-hoc hypothesis. [A bottle of champagne for anyone who can find any evidence]. However, it is now so widely believed to be true, that no-one questions it.

Anyway, without chasing down too many completely made-up ad-hoc hypotheses, the bottom line is that this paper stands a perfect example of how you can take a result you don’t like and turn it through one hundred and eighty degrees. At which point you have a conclusion that you do like.

Young researcher: (Bright and innocent)  ‘Look, this is really interesting, elderly people with low cholesterol levels are at greater risk of dying of heart disease.’

Professor: (Smoothly threatening) ‘I think you will find…. if you were to look more carefully, that this is not what you actually found….. Is it? By the way, how is your latest grant application going?’

Young researcher: (Flushing red at realising his blunder) ‘Yes, by golly, how silly of me. I think I really found that elderly people with high cholesterol levels are at a greater risk of dying of heart disease.’

Professor: ‘Yes, excellent. Be a good lad, find a good statistician to make sure the figures make sense, and write it up.’

For those who wonder at my almost absolute cynicism with regard to the current state of Evidence Based Medicine, I offer this paper as a further example of the way that facts are beaten into submission until they fit with current medical scientific dogma.

As a final sign off I would advise that any paper that has the word ‘clarifying’ in its title, should be treated with the utmost suspicion. I think George Orwell would know exactly what the word clarifying means in this context. Facts do not need clarification.

 

1: Corti MC et al: Clarifying the direct relation between total cholesterol levels and death from coronary heart disease in older persons. Ann Intern Med. 1997 May 15;126(10):753-60

You are a very black swan indeed

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Here is Wikipedia on the wisdom of Karl Popper:

“The classical view of the philosophy of science is that it is the goal of science to prove hypotheses like “All swans are white” or to induce them from observational data. Popper argued that this would require the inference of a general rule from a number of individual cases, which is inadmissible in deductive logic. However, if one finds one single black swan, deductive logic admits the conclusion that the statement that all swans are white is false. Falsificationism thus strives for questioning, for falsification, of hypotheses instead of proving them.”

Sorry, although I am a great fan of Popper, his language is a bit, well, pedantic.  What he is saying here is that science starts with a hypothesis e.g. ‘all swans are white.’ If you find white swan after white swan, then you will mildly strengthen the hypothesis. However, once you find one black swan, the hypothesis is dead.  (Unless you decree that, as all swans are white, a black swan cannot – by definition – be a swan).

One of the great white swans of cardiology is that Familial Hypercholesterolaemia (FH) causes heart disease. When I give talks to other doctors informing them that the cholesterol hypothesis is bunk, one of the ‘facts’ that is triumphantly used to knock me down is that ‘People with Familial Hypercholesterolaemia die very young from heart disease.’ Case proven, raised cholesterol causes heart disease, now move on.

A little bit of context is needed here. Familial Hypercholesterolaemia (FH) affects about one in five hundred people. It is a genetic condition where those who have it (I refuse to use the words suffer from it) have very high Low Density Lipoprotein (LDL) levels. As everyone knows LDL is known as ‘bad’ cholesterol, which is considered to be the number one risk factor for heart disease. (Of course LDL is not cholesterol at all but, hey, why let scientific accuracy get in the way of…. Well, science).

Goldstein and Brown established that the cause of FH is a lack of LDL receptors on cells. LDL receptors are the things that bind on to LDL molecules and then remove them from the bloodstream. Cells manufacture LDL receptors when they are low on cholesterol and need more.

Once the receptor is made it is pushed out through the cell membrane to attract an LDL molecule. When an LDL molecule has been caught, by binding on to the receptor, the LDL and the attached receptor are pulled back into the cell and broken down. Because they function this way, LDL receptors only work once. If a cell wants more cholesterol, then it needs to manufacture more LDL receptors.

Clearly, if there are not enough LDL receptors being manufactured, the entry of LDL into cells is restricted. This means that blood levels of LDL rise, and you will be diagnosed with Familial Hypercholesterolemia. If, that is, you have a blood test.

Moving sideways for a moment I need to mention that most people with FH are heterozygotic, by which I mean they carry one gene for FH. Their LDL levels are therefore about double that of the surrounding population. However, those with homozygotic FH (carrying both genes) have LDL levels that can be twenty times ‘normal’.  More on this group in a later blog.

Back to FH. If you have a heart attack when young, by which I mean under about 55, and you have FH, doctors will nod sagely and that that ‘it was the FH that did it.’ (If you don’t have FH, they will say it was something else that did it).

Sometimes the relatives of those dying young of CHD with FH, are contacted. It is often found that there is a higher rate of FH and premature CHD in relatives. This type of evidence has been used as proof that FH causes CHD. Maybe. Maybe not. If someone dies young from CHD, and has FH, and other relatives have a higher rate of both FH and CHD, what have we actually proved? We have proved nothing – for certain.

All we have done is to establish that relatives of people with FH and premature CHD also have FH (as they must, as it is a dominant gene) and also have a higher rate of CHD. Now, it could be that the FH is the reason for their CHD. Or it might not. It could be that something else, genetic of behavioural, is causing their high rate of CHD.

Given this problem of inherent bias, how could you tell if the FH is causing the CHD or not? Or, better, how could you falsify the hypothesis that FH causes CHD? Can you find a black swan?

Well the best way to find a black swan in this ara is to turn your study inside out. Instead of looking at people with FH and premature CHD, then looking at their relatives to find FH and CHD, you need look for premature CHD first (knowing nothing of FH status), then see if FH is more prevalent in first degree relatives.

How do you do this? Well, firstly you ask hundreds thousands of students if their father had a heart attack, or died of heart attack before the age of 55. Then you measure the LDL level of those students to see if they have FH. At the same time you find age and sex matched control students to see if they have FH.

Now, if FH really were a major cause of premature CHD you would expect to find that FH was far, far, more prevalent amongst those students whose fathers suffered CHD before the age of 55.

Such a study was done once, in the Netherlands. The results were as follows:

In the EARS (European Atherosclerosis Research Society) studies, University students whose fathers had proven CHD before the age of 55 years, were recruited …Age and sex-matched controls were recruited from the same populations for each case.

  • 2 of 1089 students with family history of CHD had FH
  • 4 of 1727 controls had FH

Thus, the prevalence of FH in both groups was not significantly different at approximately 1 in 500, which is the estimated prevalence of the condition in the general population. The evidence that heterozygote FH is, of itself, a cause of atherosclerosis is unsatisfactory.

http://www.bmj.com/content/322/7293/1019/reply

In short, when someone finally did a study on the association between premature CHD and FH, where selection bias was removed, they found that FH was no more common in those with, and without, a strong family history of CHD. This was the blackest of black swans.

However, there is a twist to this tale. Which is that this study was never published anywhere. The only reason that I know about it, is that I was reading the responses section in the British Medical Journal, and the lead investigator of the study wrote the above letter in reply to a discussion on FH. (Something more than easily missed).

I contacted him, and asked why the study had not been published. He did not provide any answer that made any sense to me. The end result of the lack of publication is that the blackest of black swans is not actually black. It is invisible. Until now, of course.

P.S. As for homozygotic FH, I shall deal with this later.

A simple Question – that opens a can of worms

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A day or so ago I received this e-mail from a doctor in London.

Dear Dr Kendrick,

I work as a GP in Wandsworth London and I read that you don’t
believe that much in cholesterol and CHD.

I do agree up to 50% of MI patients have normal cholesterol
but some say what’s normal for UK is actually high. Is this argument valid?

Best wishes

Define ‘normal.’ Does normal mean average? If we took the average height of everyone in the UK we would find (very nearly) that 50% of those dying of CHD (coronary heart disease) were above average height and 50% below. So average is clearly normal, but then again so is being tall, or short.

However, if we decided that average height of everyone living in the UK was above ‘normal’, and we then lowered the definition of ‘normal height’ by three inches, we would find that the vast majority of people dying of CHD were now above average height. At which point we could decree that being taller than normal was a risk factor for CHD.

This would obviously be a completely bonkers thing to do. Yet, you can do it with cholesterol levels and everyone nods in general agreement.

Aha, but the argument goes that our lives are completely different than the lives of our ancestors, which has caused our cholesterol levels to be unnaturally high.

An article in the Journal of the American College of Cardiology best summed up this line of thinking. Under the heading ‘Why average is not normal’, O’Keefe, the lead author, made the claim that: ‘Atherosclerosis is endemic in our population, in part because the average LDL (“bad” cholesterol) level is approximately twice the normal physiologic level.’ In short, according to O’Keefe, our cholesterol level should be about 2.5mmol/l, not 5.2mmol/l.

He based his argument, in part on looking at the cholesterol levels of various animals e.g. elephants, and boars, and suchlike. He also used the argument that very young babies (neonates) have cholesterol level of about 2.5mmol/l. Now, in my opinion, anyone proposing this argument should have their medication increased. We should base our cholesterol levels on those found in other animals species….yes, of course we should. You mean those animal species with an average life expectancy of ten years, for example.

However, this argument is now pretty widely accepted by the medical community. We are all, everyone, living in the West, living in such an ‘unhealthy’ way that our cholesterol levels are unnaturally high. The true normal cholesterol levels is 2.5mmol/l.

Fine, if we re-set normal at 2.5mmol/l we will find that 99% of people dying of heart disease do have a ‘high ‘cholesterol level. Problem sorted, average is no longer normal, and the hypothesis that a high cholesterol level is a risk factor for heart disease is now true.

Hold on, I’ve got an idea…

How Risky Is A Risk?

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[I was contemplating risk the other day, when someone forwarded me an article I wrote a couple of years ago on risk. I think it is still highly relevant to what is happening today with the mangling of medical statistics]

I have only just recovered from the idea that everyone in the whole world over the age of fifty-five should spend the rest of their lives on six different medications, all stuck together in one great big pill. The following was headline from a study in the BMJ.

‘Polypill—A Statin plus 3 Blood Pressure Drugs plus Folic Acid plus Aspirin. Authors claim Polypill would reduce risk of dying from coronary heart disease by 80%. The authors of the polypill article in the BMJ made the claim that taking their polypill would reduce the risk of dying of coronary heart disease (CHD) by 80%.’

You may have seen the non-story about the, yet to be marketed polypill, peddled in the British Medical Journal (BMJ). I was stimulated to look again at the concept of risk.

Whether or not you believe their figures—and I don’t—I sense that this figure of 80% would be taken by most people to mean that eighty out of one hundred people would be saved from death if they took this magic tablet. But this figure, if true, could only possibly be a relative risk reduction. And a relative risk reduction means almost nothing, by itself.

However, because everyone’s eyes glaze over whenever you start talking about statistics, most researchers manage to get away with using relative risk reduction figures when, in reality, they should be shot for doing so. Now, here’s a challenge. The challenge to make a short article about statistics interesting. Okay, that’s not possible. But maybe a little bit interesting?

You must know the time period, and the absolute risk, for the relative risk to have any meaning

When you talk about a risk, you need to know the absolute risk of a thing happening. For example, the risk of getting struck by lightning. I don’t actually know what this risk is, but I would imagine it is about one in five million. But again, that figure means little unless you put a time scale on it. Is this a one in five million risk over a hundred years, or one year, or a day? If you don’t put a time scale in, you can claim pretty much anything you like.

For example an astronomer could attempt to shock you by stating that ‘The Earth will be hit by a big Asteroid. This is one hundred per-cent certain.’ – stunning announcement from A.N. Astronomer. Read all about it.  And of course, this is true. The Earth will be hit by a big Asteroid, sometime in the next three billion years or so. The odds ratio for this event is 1 = 100% certain. I am even willing to take a bet on it. What you probably want to know is however, is, what is the likelihood of this happening in my lifetime. Sorry, no idea.

Anyway, I hope this makes it clear that you must define risk in two ways, the possibility of the nasty thing happening, and the time period during which it is likely that the thing will happen. With lightening strikes, I would guess this is about a one in five million risk, over a five year period. Not high.

However, whilst the time factor is important, people don’t just bend statistics by ignoring the time factor. What also happens is that people inflate the risk by using relative instead of absolute risks.

For example, the chances of dying of lung cancer, for a non-smoker, are about 0.1% (lifetime risk). If, however, you live with a heavy smoker, your chances will increase to about 0.15%. (These figures are for illustration only, and are not completely accurate).

Now, you can report this in two ways. You can state that passive smoking can increase the risk of lung cancer by 0.05% – one in two thousand. Or, you can state that passive smoking increases the risk of lung cancer by fifty per cent (0.15% vs 0.1%). Both figures are correct. One is increase in absolute risk, the second the increase in relative risk.

If you are an anti-smoking zealot, then I would imagine you would prefer to highlight the second figure. The relative risk figure. And when it comes to reducing cardiovascular risk, exactly the same procedure is used (in reverse).

Let’s say that the chance of dying of CHD over the next five years, in a healthy fifty-five year-old, is 1%. By reducing this risk to 0.2%, you can claim to have reduced the relative risk of dying of CHD by 80%. The absolute risk reduction is 0.8%. Mangling statistics is easy when you know how. It’s even fun.

Anyway, now you know the difference between a relative risk and an absolute risk, and I hope this makes it easier for you to hack your way through the misinformation that spews forth from the great medical research machine.

By the way, I believe the Polypill will achieve a 0.00% absolute and relative risk reduction. But we shall see.

 

 

The Untainted Mind

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A few weeks ago, a sixth year student at Westminster School sent me an essay she had written on cholesterol, and why it does not cause CHD. She wants to go to medical school. No one made her do any of this. She just looked at the evidence and made her mind up.  She wrote me this e-mail

Dear Dr Kendrick,

I am a final year student at Westminster School who intends to study medicine. I am extremely interested in your research and reading your book enthused my and led me to spend a large portion of my time researching studies which you and other authors on the same topic have referenced.  The Chief Medical officer came to speak to us today and after her talk I quizzed her about what I have read in your book as well as a large wealth of research I have done myself. (Attached, if you care to look, is a copy of an essay I wrote which won the top prize in school essay competition based on this research). She was extremely defensive of the cholesterol causes heart disease hypothesis and claimed that NICE had on a population level declared this to be the case. She said that the evidence did not add up on a small study level, but when studies were put together (I assume by NICE) that the conclusion is in favour of cholesterol causing CHD.

I would love to know your thoughts on this and where I can find this population based evidence.

Kind regards,

Francesca Greenstreet

I wrote back to her, to say that there was no population based evidence. Or, if there was, it very clearly demonstrated no link between cholesterol levels and heart disease. The Chief Medical Officer was just blustering – as most people do when confronted with someone who dares to question medical dogma.

I thought her essay was extremely well written and makes all the points that I have been making for years. It is just gratifying to see that the evidence on cholesterol and heart disease is clear to anyone with a brain.


In Defence of Cholesterol

The  American government, the British government and the NHS, three venerable bodies respected as sources of dietary advice, currently recommend a diet low in saturated fat and cholesterol.[1] The predominant  reason this advice is given is the accepted belief held within the scientific community that high serum cholesterol levels are linked causally with the accumulation and build up of atheromas which lead to atherosclerosis and Coronary Heart Disease (CHD).

The commonly accepted and taught theory which links cholesterol to heart disease, the Lipid Hypothesis, states that cholesterol is carried from the liver to the rest of the body’s cells in Low Density Lipoproteins (LDLs) and carried back from the rest of the body’s cells to the liver in High Density Lipoproteins (HDLs). After being transported back to the liver by HDLs, Cholesterol is broken down by the liver or passes out of the body as a waste product. The Lipid Hypothesis states that eating saturated fat raises LDL levels. The cholesterol from LDLs forms fatty deposits, atheromas, which build up beneath the endothelium of the arteries. The build up of atheromas narrows the arteries and pieces of the atheromas can break off and become lodged in narrower arteries .Clots can form in the narrowed arteries which prevent blood flow and can starve organs of oxygen and nutrients. When clots or blockages form in the coronary arteries, necrosis occurs. This leaves part of the heart muscle not contracting and relaxing and can lead to a myocardial infarction.[2]

Figure 1: Sudan-stained aorta of a rabbit fed 61 egg yolks over a 70-day period, showing lesions in red.

Figure 1: Sudan-stained aorta of a rabbit fed 61 egg yolks over a 70-day period, showing lesions in red.

The Lipid Hypothesis was brought to attention following a series of studies, the first of which was carried out by Anitschkow, a Russian scientist, in 1913. Anitschkow fed rabbits a diet of purified cholesterol dissolved in sunflower oil and examined the cells and the arteries of the rabbits after killing them. [3] Rabbits which were fed the purified cholesterol were found to have vascular lesions which bore a close resemblance to atheromas found in humans (Figure 1). Following Anitschkow’s study, Dr John Gofman led a team to similar findings and hypothesized that serum cholesterol was the cause of the lesions developing.[4] The similarity of the lesions to those found in humans suffering from CHD was catalytic in the formation of theories that a high cholesterol diet might be linked to CHD in humans.

The ideas behind the Lipid Hypothesis were formalised by Ancel Keys when, in a study in 1953, he used data from six countries to show a direct link between the percentage calories from fat in the average diet and the number of CHD deaths per 1000.[5] Furthermore, he found the incidence of CHD deaths in those six countries was best predicted by the intake of saturated fat.[6]

However, not all scientists and physicians are in agreement with the Lipid Hypothesis. Regarding Anitschkow’s rabbit study, it has been pointed out that cholesterol does not form part of the natural diet of a rabbit and thus it is possible that the rabbits had an allergic reaction to the high cholesterol diet, or that they were otherwise incapable of processing the chemical. It is significant to note that similar experiments carried out on dogs and rats showed that a rise in blood cholesterol did not lead to a rise in atherosclerosis.[7] This is potentially due to the fact that dogs and rats, unlike rabbits, consume cholesterol as part of their natural diet. The lack of cholesterol in a rabbit’s natural diet, combined with the failure to replicate the findings in dogs or rats, whose natural diets are much more similar to our own, is a significant flaw in the reasoning behind Anitschkow and Gofman’s conclusion: that a high cholesterol diet is linked to atherosclerosis in humans.

Figure 2: Keys’ (1953) selection to show relationship of fat intake to heart disease deaths of 55–59 yr. old men in 1951–53 (open circles left)and the 15 other available countries (closed circles). The relation of heart diseases to animal protein intake is on the right (Mann, 1993). (Adapted from WHO Ann. Epid. and Vital Statistics).

Figure 2: Keys’ (1953) selection to show relationship of fat intake to heart disease deaths of 55–59 yr. old men in 1951–53 (open circles left)and the 15 other available countries (closed circles). The relation of heart diseases to animal protein intake is on the right (Mann, 1993). (Adapted from WHO Ann. Epid. and Vital Statistics).

Another flaw in the Lipid Hypothesis is that Ancel Keys selected with purpose the countries for which he presented data in his study in 1953, rather than choosing them at random. “Yerushalmy and Hilleboe (1957) observed that Keys would have had available data from 22 countries, which would have given a much weaker correlation “(Figure 2).[8]

Figure 2 shows a very weak correlation between deaths per 1000 (from CHD) and percentage of calories from fat when all 22 countries are plotted on the same graph. It is interesting to note that the correlation between deaths per 1000 (from CHD) and percentage of calories from animal protein has a similar and even slightly stronger  correlation than between deaths per 1000 (from CHD) and percentage of calories from fat.  All of this data would have been available to Keys, so his focus on the link between percentage of calories from fat and the number of deaths per 1000 (from CHD) is curious.

The data sample presented by Keys gives a correlation of coefficient of +0.84, a strong positive correlation, whereas “in the simulation study by Wood (1981) on the consumption statistics of 21 countries a total of 116280 different samples of six countries were found, and the correlation between consumption of animal fat and CHD mortality varied from -0.9 to +0.9, the average being    -0.04.”[9] Such a difference in correlation coefficients between similar studies indicates some bias in Keys’ selection of the six countries or insufficient data, since Wood’s study uses many more countries and therefore is more likely to be accurate. As it is obvious that Keys had sufficient access to data from the 22 countries, it seems that his selection was biased.

There have also been many studies which investigate serum cholesterol level in relation to atherosclerosis and CHD in Humans rather than in animals. A notable example is the study led by Paterson  entitled: “Serum Cholesterol Levels in Human Atherosclerosis”. 800 patients who were permenantly confined to hospitals and 100 war veterans who were in hospital for dimiciliary care were given 2500-3000 calories a day in their daily diet, of which 25 to 35% was derived from fat. Serum cholesterol was determined annually or semi-annually and when any patients died, the severity of atherosclerosis was determined using six differnet criteria: crude morphological grading, measurement of the thickness of the largest plaque, determinations of the total lipid content, lipid concentration, total calcium content and calcium concentration. Figure 3 shows a graph showing the abscence of a correlation between Serum Cholesterol in mg.% and Total Lipid in Mg. This shows that for the criterium of total lipid content, there is no correlation in the age group of 60-69 years.

Figure 3: Total coronary artery lipid and serum cholesterol levels in patients 60-69 years. The open circles represent cases without complications of coronary atherosclerosis; the closed circles, cases with complications.

Figure 3: Total coronary artery lipid and serum cholesterol levels in patients 60-69 years. The open circles represent cases without complications of coronary atherosclerosis; the closed circles, cases with complications.

Similar findings were observed in the other age groups with a significant number of participants (70-79 and 80-89). The study concludes: “In the 58 cases in the age group 60-69 years, significant relationships between the serum cholesterol and the severity of the disease were found only once in 40 statistical analyses, and the complications of atherosclerosis were just as frequent in cases with low serum cholesterol levels (150-199 mg. %) as in cases with moderately high ones (250-299 mg. %).”[10]Considering the emphasis from the government and the NHS to reduce cholesterol and saturated fat intake because cholesterol causes heart attacks, this seems to be a remarkably weak correlation.

The Paterson study was not alone in its findings: Sigurd Nitter-Hauge and Ivar Enge published a study in The British Heart Journal in 1973 which reported: “No significant correlation was found when total coronary arterial score was correlated to serum cholesterol values or to triglycerides.”[11]

Not only is there strong evidence to show that serum cholesterol levels have no link to atherosclerosis, but there is also strong evidence to suggest that high cholesterol consumption does not raise blood cholesterol levels. The Framingham Heart Study, which set out to prove that eating more cholesterol in your diet increases your blood cholesterol levels, in fact showed that there was minimal difference in the blood cholesterol levels of the subjects despite subjects consuming cholesterol in widely varying amounts. [12] Scientists working on the Framingham Heart Study also studied the intake of saturated fats but eventually concluded: “There is, in short, no suggestion of any relation between diet and the subsequent development of CHD in the study group.”[13] It is difficult to stress the importance of this finding enough: there was no connection found whatsoever between diet and the development of CHD.

Further evidence that eating a diet high in saturated fat does not lead to CHD was published in The American Journal of Clinical Nutrition in 1981. The study compared the diets of two populations of Polynesians living on atolls near the equator. It also assesses the effect the diets have on the serum cholesterol levels in the populations. One of the populations, the Tokelauans, obtained a very high percentage of energy from coconut (high in saturated fat) compared to the Pukapukans, 63% compared with 34%. The Tokelauans had serum cholesterol levels 35-40mg higher than the Pukapukans. However , “vascular disease is uncommon in both populations and there is no evidence of the high saturated fat intake having a harmful effect in these populations.”[14]

Taking all these studies into account, it would appear that not only does having a high serum cholesterol level not have any connection to CHD, but that a diet high in cholesterol does not lead to high blood cholesterol levels and that a diet high in saturated fat does not have any link to CHD.

One final argument used to support the Lipid Hypothesis is the apparent effectiveness of statins in treating CHD. If, so the argument goes, statins reduce levels of serum cholesterol and they also reduce the risk of CHD, then reducing serum cholesterol levels must be the reason for the lower incidence of CHD. However, this reasoning contains two fallacies: firstly it assumes that statins have been shown to reduce the risk of CHD, and secondly it assumes that lowering serum cholesterol levels is the only effect of statins that could lower the incidence of CHD.

Both of these assumptions are false. A study was carried out by the University of British Columbia, part of the not-for-profit Cochrane collaboration, which concluded: “If cardiovascular serious adverse effects are viewd in isolation, 71 primary prevention patients have to be treated with a statin for 3 to 5 years to prevent one myocardial infarction or stroke.”[15] Small mortality benefits from statins have been shown for high-risk middle aged men.[16], [17] However, these trends are not seen in women and the elderly.15, 16 Even an advertisement for LIPITOR (atorvastatin calcium), one of the best-selling statins in America, has a disclaimer which includes: “LIPTOR has not been shown to prevent heart disease or heart attacks.”[18]

For the small minority of people who are protected  by statins, there is another explanation. Statins have been repeatedly shown to act as “potent anti-inflammatory” agents in patients with cardio vascular disease[19]. The reason for their effects in reducing incidence of CHD could be due to those effects rather than the reduction of serum cholesterol levels. This means that it is innappropriate to use the limited protection against CHD by statins as evidence for high serum cholesterol levels being a cause of CHD.

Gathering together the arguments made in this essay, we can conclude that it is very likely that there is absolutely no causal correlation between high cholesterol, either in the serum or in the diet, and CHD. Nor is there any causal correlation between a diet high in saturated fat and CHD. The emphasis placed on the Lipid Hypothesis by the government and other organisations concerned with public health is potentially due to the inital panic after the publication of Keys’ and Anitschkow’s studies. The feeling of urgency to act in order to prevent ever increasing numbers of deaths from CHD led to premature acceptance of the Lipid Hypothesis without sufficient evidence. The long term effect of this view has been the demonisation of diets high in saturated fat and cholesterol without sufficient justification from otherwise reputable organisations for the past thirty years.

Word count : 2431 words

(excluding title, name, biliograph and references)

Bibliography

“Trick and Treat” (Barry Grroves,2008)

“The Great Cholesterol Con” (Dr Malcolm Kendrick, 2007)

“The Cholesterol Myths” (Uffe Ravnskov, M.D., Ph.D., 2000)

“Seven Countries: A Multivariate Analysis of Death and Coronary Heart Disease” (Ancel Keys, 1980, Introduction, p. 1-17)

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Figure 1: Daniel Steinberg, 2004. Review series: The Pathogenesis of Atherosclerosis. An interpretive history of the cholesterol controversy: part I, The Journal of Lipid Research, 45, 1583-1593.

Figure 2: Kalle Maijala, Cow milk and human development and well-being, Livestock Production Science 65 (2000) 1–18

Figure 3: J.C. PATERSON, M.D., LUCY DYER, M.Sc. and E.C. ARMSTRONG, M.D., London, Ont., 1960. Serum Cholesterol Levels in Human Atherosclerosis. Canad. M. A. J., 1960, vol. 82

 

[1] http://www.health.gov/dietaryguidelines/dga2000/document/choose.htm

[2] http://www.ncbi.nlm.nih.gov/pubmedhealth/PMH0001224/

[3] Daniel Steinberg, 2004. Review series: The Pathogenesis of Atherosclerosis. An interpretive history of the cholesterol controversy: part I, The Journal of Lipid Research, 45, 1583-1593.

[4] GOFMAN, J.W.;LINDGREN, F.; ELLIOT, H.; MANTZ, W.; HEWITT, J.; STRISOWER,B.; HERRING, V.; LYON, T.P., 1950.The role of lipids and lipoproteins in atherosclerosis,  American Association for the Advancement of Science  Vol. 111pp. 166-171; 186

[5] “Trick and Treat” (Barry Groves, 2008, p.61-62)

[6] “The Cholesterol Myths” (Uffe Ravnskov, M.D., Ph.D., 2000, out of print – available at: http://www.ravnskov.nu/myth4.htm)

[7] “Trick and Treat” (Barry Groves, 2008, p.59)

[8] Kalle Maijala, Cow milk and human development and well-being, Livestock Production Science 65 (2000) 1–18

[9] Kalle Maijala, 2000. Cow milk and human development and well-being. Livestock Production Science 65 1–18

[10] J.C. PATERSON, M.D., LUCY DYER, M.Sc. and E.C. ARMSTRONG, M.D., London, Ont., 1960. Serum Cholesterol Levels in Human Atherosclerosis. Canad. M. A. J., 1960, vol. 82

[11] Sigurd Nitter-Hauge, Ivar Enge, 1973.  Relation between blood lipid levels and angiographically evaluated obstructions in coronary arteries British Heart Journal. 35, 791-795.

[12]“Trick and Treat” (Barry Groves, 2008, p.63)

[13] Kannel WB, Gordon T., 1970.The Framingham Diet Study: diet and the regulations of serum cholesterol (Sect 24). Washington DC, Dept of Health, Education and Welfare.

[14] Ian A. Prior, M.D., F.R.C.P., F.R.A.C.P., Flora Davidson, B.H.Sc., Clare E. Salmond, M.Sc., and Z. Czochanska, DIP.AG., 1981. Cholesterol, coconuts, and diet on Polynesian atolls: a natural experiment: the Pukapuka and Tokelau Island studies. The American Journal of Clinical Nutrition 34, pp. 1552-1561.

[15] “The Great Cholesterol Con” (Dr Malcolm Kendrick, 2007, p.164-165)

[16] “Trick and Treat (Barry Groves, 2008, p.52)

[17] Scandinavian Simvastatin Survival Study Group, 1994. Randomised trial of cholesterol lowering in 4444 patients with CHD: the Scandinavian Simvastatin Survival Study (4S). Lancet; 344: 1383-1389

[18] http://www.westonaprice.org/cardiovascular-disease/dangers-of-statin-drugs

[19] Mukesh K. Jain, Paul M. Ridker, 2005. Anti-Inflammatory Effects of Statins: Clinical Evidence and Basic Mechanisms, Nature Reviews Drug Discovery 4. 977-987