My academic background is in epidemiology and biostatistics. Briefly, epidemiology is the study of the interaction between potentially causal external factors and human health, usually at a population level. So, when someone tells you that BPA causes cancer, or that wind turbines or wi-fi signals don’t cause illness, they are speaking in terms of epidemiology. Because of the diffuse nature of many cause/effect relationships and the difficulty of measuring historical exposure, epidemiology is often looked at as a ‘soft science’, which is perhaps a fair charge – we do not deal in certainties; only probabilities.
One of the fundamental concepts that it is necessary to understand in epidemiology is the concept of ‘confounding’. Most of you are likely familiar with the maxim “correlation does not necessarily imply causation” or some permutation of that phrase. Many relationships that may seem causal are better explained by the involvement of a third variable. The classic example is coffee and lung cancer – there is a statistical relationship between frequency of coffee drinking and incidence of lung cancer. However, it would be wildly inaccurate to say that coffee causes lung cancer; what is actually happening is that many people have a cigarette with their coffee, and it is the smoking that causes the cancer. The presence of the third variable (smoking) explains the seeming relationship between the other two. [Read more…]