" A common feature of epidemiological data is that they are almost certain to be biased, of doubtful quality, or incomplete (and sometimes all three),” explained the epidemiologist John Bailar in The New England Journal of Medicine in 1980. “Problems do not disappear even if one has flawless data, since the statistical associations in almost any nontrivial set of observations are subject to many interpretations. This ambiguity exists because of the difficulty of sorting out causes, effects, concomitant variables, and random fluctuations when the causes are multiple or diffuse, the exposure levels low, irregular, or hard to measure, and the relevant biologic mechanisms poorly understood. Even when the data are generally accepted as accurate, there is much room for individual judgment, and the considered conclusions of the investigators on these matters determine what they will label ‘cause’… "

― Gary Taubes , Good Calories, Bad Calories: Challenging the Conventional Wisdom on Diet, Weight Control, and Disease