‘Most doctors and nurses will have a deep well of patient stories – examples of great fortitude and its converse. It is clear to any clinician that some patients either feel their symptoms (or report them) more than others.

I wonder, however, whether stoicism has been neglected in the epidemiological literature. It seems likely to be related to many exposures and many diseases. Association with exposure and with disease are two of the key features of a confounding variable.

Stoicism is particularly likely to be associated with diseases where diagnosis relies on self-reported symptoms. Many diseases fall into this category.

I feel stoicism is likely to be related to exposures such as cycling to work every day, ambient household temperature, and so on. However, it’s not hard to imagine that many health behaviours might be influenced by how stoical people are.

Confounding is well illustrated using a classic example, coffee and cancer. People who drink coffee are more likely to get cancer. They are also more likely to be smokers. The well-established association between smoking and cancer largely explains the association between coffee and cancer. Smoking, in this example, is a confounder.

Epidemiologists try to control for confounders to avoid misleading results.

A Pubmed search for ‘stoic*’ AND ‘confound*‘reveals 24 papers, only three of which are even vaguely relevant. None are epidemiological and I can access only one. By failing to control for stoicism in epidemiological studies, do we risk throwing up reams of spurious associations – warmer home environment is associated with fatigue, winter cycling is associated with less chronic low back pain, etc? Will this lead us to spend money trialling useless interventions?

In some cases it may be possible to adjust – person by person – for reported symptoms at another time point. However, to control for confounders, you usually need to be able to measure them.

It is entertaining to think how one might measure stoicism. For example: ‘When you last had a sore throat, did you (a) get on with it (b) have a day off work or (c) go to see your GP?’ We might apply more objective tests – time to first complaint when the waiting room is kept at ten degrees, perhaps? We could devise a scale.

Tom Yates qualified as a doctor in London in 2009. He subsequently completed an academic foundation programme in Oxford, where he was involved in research on hepatitis vaccines. He started an MSc in epidemiology at the London School of Hygiene and Tropical Medicine in September 2011. He is interested in infectious disease and population health. He blogs on epidemiology and population health at sickpopulations.wordpress.com