The science of epidemiology is coming to grips with the following facts: a) no "big" risk factors have been discovered in quite awhile and the future looks to consist mainly in attempting to uncover tiny ones; b) even when big risks in a population are identified the knowledge does not translate into making sound predictions about individuals; because c) chance, or luck, plays a huge role in whether or not we’ll get sick, whatever our exposures. That’s my take on an article you need to read if you’re at all interested in epidemiology – it’s "Epidemiology, Epigenetics and the ‘Gloomy Prospect’: Embracing Randomness in Population Health Research and Practice".
Below are a few lines from the exceptionally well written piece to whet your appetite:
"We should embrace the effects of chance, rather than pretend to be able to discipline them."
"The pioneering epigeneticist Robin Holliday points out that it is commonly stated that disease is either genetic or environmental, when in reality stochastic events are equally important."
"Epidemiological inference is to the group, not to the individual"
"… the determinants of the incidence rate experienced by a population may explain little of the variation in risk between individuals within the population."
"Chance (at one level) and near necessity (at another) may be the only certainty in attempting to understand epidemiological – and many other – processes."
"At a group level, the underlying social causes of IHD (ischemic heart disease) could be social and political structure, sequentially mediated through free trade in toxic microenvironments, in health-related behaviours, and in the elevated body mass index, blood pressure, serum cholesterol, glucose and insulin. At an individual level, it is mostly genes and chance."
"… in terms of public health policy, we should target the modifiable causes of disease that heritability and shared environment tell us about. This must be at the group level, however, and we should do so without pretending to understand individual-level risk, or misrepresent population level data (smokers die earlier on average) as individual level events (each smoker shortens her or his life."
Pay special attention to the section on "lay epidemiology". The narratives we create about our lives, cast in terms of fate, or chance, turn out to be a lot closer to the mark than most epidemiologists have been willing to admit.
h/t Garth Brooks