While I certainly agree with you that some or all of the "blame the victim" body count estimates are high, be careful about this criticism -- it is not legitimate. Diseases and deaths always have multiple component causes, all of which can legitimately be called the cause (which is to say a necessary -- not sufficient -- cause of that death or disease at the particular time).So an individual may well die from smoking AND obesity AND eating junk food, and it is perfectly legitimate to say that had any one of these conditions been eliminated the death would not have occurred so soon. Someone who was killed by a drunk driver because a medical error prevented him from being saved in the hospital is a death due to alcohol use, motorized transport, and medical errors, so the causes add up to 3 for the one death. Thus, there is no reason to expect they would add up to the total. Indeed, they should add up to well more than the total if you have a rich enough list of causes.
I agree that this may not be how the man on the street interprets it, though I suspect if pushed that man would not actually be able to clearly state what he thinks it means. That is one of the problems with reciting raw scientific information to people who do not understand the science. Most people do not understand a relative risk statistic, but are barraged with them. But even descriptive statistics -- which most people probably think they understand at first blush -- are subtle. Nothing causes a fraction of a death -- it either causes it or not (see below). There is no obvious way to assign fractions.
As for bringing a death forward by merely one day, that is a fundamentally different question. And, yes, you could argue that a death that is accelerated by just one day by a particular cause should not be attributed to that cause for purposes of assessing public health statistics.
Wouldn't the word "factor" be more appropriate than "cause"? No. Cause is exactly the right word. It is the right word in the science of epidemiology (which is the source of this information) and is also the right word based on the usual intuitive definition. The latter, which is technically translated in epidemiology and most other sciences, is that in the absence of the particular influence, the particular outcome would not have occurred.
The word "factor" is one of those that often gets used because someone does not want to admit that they are making causal claims, even though that is exactly what they are doing. It doe not really mean anything. E.g., the phrase "risk factor", as used, has at least three or four different very distinct meanings, and therefore is worse than useless.
Following the above, it is easy to see why everything has multiple causes. Every death was caused by not only some disease, but also by birth of the individual in question, the evolution of humanity, the big bang, etc. This is part of why assigning fractions would not make sense, as noted above.Angry Exile said:
And if a smoker goes outside the pub for a fag in winter and as a result of the alcohol passes out and subsequently carks it of hypothermia who gets to put their statistics up by one? ASH, Alcohol Concern or the Met Office?
If the individual would not have gone outside absent his smoking habit, then, yes, smoking caused his death, as did the alcohol that caused him to pass out, the weather that caused those to result in hypothermia, as well as, perhaps, his failure to put on a coat, his companion's failure to look for him after he disappeared, cutbacks on foot patrols by the police, and any number of other things.
The summary point is very simple: Everything has an infinite multitude of causes. For a particular outcome (e.g., death) we typically identify a particular set of them as the causes we are interested in intervening on (e.g., drug use, diet, medical tech), but there is nothing magical about that list. There is no reason to expect that those causes will not overlap in many cases, and once that list is made rich enough, overlap is inevitable.
Dr Phillips has recently started a new blog here.
