Tag Archives: levels

Proving that black is white

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

Association does not mean causation

Of all the things you should bear in mind when looking at health stories, this is probably the single most important. Association does not mean causation. The reason why this is so important is that studies that have only found associations make up the vast bulk of scare stories in the media:

Here is a typical recent headline, which you may have seen:

Eating red meat regularly ‘dramatically increases the risk of death from heart disease’

It is true that this newspaper headline does not actually state that eating red meat causes heart disease. Not quite, but very nearly, and you could be forgiven for thinking that it does. Read it again, and you will not see the word cause anywhere. It is just very implied very strongly

However, as you get into the article itself, any distinction between association and causation fades almost to nothing:

‘Senior author Professor Frank Hu, from Harvard School of Public Health in Boston, US, said: ‘This study provides clear evidence that regular consumption of red meat, especially processed meat, contributes substantially to premature death.

‘On the other hand, choosing more healthful sources of protein in place of red meat can confer significant health benefits by reducing chronic disease morbidity (illness) and mortality.’

The study found that cutting red meat out of the diet led to significant benefits. Replacing one serving of red meat with an equivalent serving of fish reduced mortality risk by 7 per cent.’

At this point we are heading into the territory of Bill Clinton in his impeachment trial where the meaning of words it being stretched to their very limit. ‘But what is, is?’

I defy anyone to read those paragraphs and not conclude the following:

1: These researchers proved that eating red meat causes premature death

2: The researchers further proved that cutting out red meat and replacing with fish reduced mortality risk by 7 per cent.

I don’t think you could be blamed for thinking these two things. Because that appears to be exactly what was said. Or was it? Were you just being fooled by a complex conjuring trick made up of carefully chosen words designed to bewilder.

Here are the actual conclusions of the paper:

Red meat consumption is associated with an increased risk of total, CVD, and cancer mortality.’

Note the word associated. Where is the word cause? It isn’t there, because this study could never, ever, prove causality. Why not? Because it was an observational study (actually it was a review of two other observational studies).

In an observational study you do not do anything active. You just study that things that people do, or eat, and see if any associations emerge. When you find an association the next question you have to ask is the following. Are you looking at yellow fingers, or smoking.

It is certainly true that yellow fingers are associated with a higher rate of heart disease Does it follow that yellow fingers cause heart disease? No, of course not, what it means is that people with yellow fingers are usually people who smoke. And smoking vastly increases the risk of dying of heart disease.

In this case the distinction between the cause and the association is blatantly obvious – or at it has become so after fifty years of research made it clear Indeed, if I were now to try and claim that having yellow fingers causes heart disease, you would look at me as though I were an idiot – and I would be.

Yet, when a study finds that eating red meat is associated with a higher risk of heart disease, we seem to rush headlong into the conclusion that eating red meat consumption almost certainly causes heart disease. But red meat could well just be the equivalent of yellow fingers.

You think not? In that case you are probably thinking that red meat contains saturated fat, and saturated fat raises cholesterol levels, and raised cholesterol levels cause heart disease. If you played this little causal chain in your mind, you would most certainly not be alone in doing so.

It is something that our brains seem hard-wired to do…

‘….our brains and nervous systems constitute a belief-generating machine, an engine that produces beliefs without any particular respect for what is real or true and what is not. This belief engine selects information from the environment, shapes it, combines it with information from memory, and produces beliefs that are generally consistent with beliefs already held. This system is as capable of generating fallacious beliefs as it is of generating beliefs that are in line with truth.http://www.csicop.org/SI/show/belief_engine/

We cannot seem to help ourselves from linking things together to create causal chains, or beliefs, that certain things cause other things to happen. This is emotional, it is exceedingly powerful, and deconstructing such beliefs is the work of Hercules.

In this particular case, though, you would be hard pressed to use this belief as an explanation. How do I know this? I know that because the Harvard team found that those who at the most red meat actually had the lowest cholesterol levels. This table (figures taken from the paper itself) divides people into five groups/quintiles. Those in quintile 1 ate the least red meat, those in quintile 5 the most.

Total Red Meat Intake Quintile, Servings per Day









% with high







Pan A; Sun Qi;, ScD;  Bernstein A; et al: ‘Red Meat Consumption and Mortality:Results From 2 Prospective Cohort Studies.’ Arch Intern. Med.Published online March 12, 2012.doi:10.1001/archinternmed.2011.228

The authors chose not to make any comment at all on this finding. Although you might have thought it worth a quick mention. Had they found rising cholesterol levels with increased meat consumption you can be absolutely certain they would have presented this as a clear cut causal chain. So how did eating read meat cause an increase in the rate of heart disease? Because it just did….through some mechanism unknown to medical science? The evil power of redness.

What is far more relevant is that they also found that those who ate the most red meat also smoked the most, exercised the least, ate far more calories in total, and were more likely to have diabetes. But it was the red meat that killed them from heart disease….you think? Even if red med included pork, and unprocessed red meat included hamburgers.

This study demonstrated, as if any further demonstration were required, that a whole bunch of unhealthy lifestyle factors: smoking, taking no exercise, drinking, eating fast food are all linked together. But I think we knew this already.