Science is the discipline of measuring observable phenomenon. From these observations certain conclusions can be drawn. The modern definition of science can be extended to the creation of theories based on a composite of the data surrounding these observations. One of the biggest problems with science is that many scientists disregard the observational data when forming their theories and conclusions. And this relates to the time old human flaws of ego, the pursuit of money and acceptance of peer group pressure. One particular topic that appears to be particularly problematic in this regard is the science surrounding cardiovascular disease and dietary cholesterol. The conclusions that dietary cholesterol is a causative factor in cardiovascular disease, and therefore by extension the entire cholesterol theory of cardiovascular disease, is not in any way supported by the observational data in the nutritional literature. In fact the opposite is true, and the data clearly shows that dietary cholesterol is not a causative agent.
Part of the problem is that so called scientists (and I use the term loosely, as having a PhD does not actually make you a scientist, collecting observational data using the scientific method and drawing valid conclusions makes you a scientist, as the profession is defined by it’s actions not by a certificate), still seem to confuse the words ‘cause and effect’ with the word ‘association’. It would seem that it is often the case that the confusion is deliberately used to obfuscate the true picture. For example, in a recent editorial in the American Journal of Clinical nutrition1, one author stated that ‘….consumption of >7 eggs/wk was associated with 69 % more CVD events in men and women with type 2 diabetes’ and ‘….the consumption of ≥7 eggs/wk was associated with incident heart failure in US physicians’. The conclusion drawn from this was that cautions should be taken with regard consumption of eggs by those with type 2 diabetes. This evidence was based therefore on epidemiology studies investigating associations (correlations).
Put it another way. Police cars are associated with road traffic accidents. Every time you see a road traffic accident you will undoubtedly see a police car at some point. The association is observable and real. To urge cautions regarding the use of police cars around other traffic would to most seem illogical, absurd and even devious in its intended outcome. So why should we urge caution about eggs based on an association with cardiovascular disease? People who get cardiovascular disease eat more eggs. They also eat many other things in greater quantities than those without cardiovascular disease, but identifying the cause is not possible by simply looking as correlative data. If eggs are a problem why did the author not quote a clinical study showing eggs cause a rise in cholesterol? Why only an epidemiological paper showing an association? Oh yes, because there are no such papers and the data does not exist. So to pursue his agenda he must rely on correlation. A classic case of good science leading to erroneous conclusions.
RdB
