For background, Snowdon exposes many of these, and his article in 2009 is a damn good guide as to how they are universally designed to mislead.
It is not a question of having a closed mind or being unduly suspicious. Smoking bans cannot bring about huge reductions in the heart attack rate of 10, 20 or 30 per cent because it is a mathematical impossibility.
And so it is like watching David Copperfield doing his flying trick. It might look impressive but you know it's just a trick. With magic, the fun is in trying to work out how it's done. And just as the flying trick is always going to involve some form of industrial strength wire, the explanation to a heart attack miracle is always going to involve some form of cherry-picking.
In the UK, we have seen the Scottish example described by the BBC as "the facts in the way of a good story".
There is also a suggestion that the StopIt study compared 10 months before the ban in March 2006, with 10 months after. So the two periods might have spanned different parts of the year.
Indeed this was the case. That aspect was quite important as it was designed to exclude months of the year which were colder, a known contributory factor in heart attacks.
In fact, even that statistical fraud was just a small part of the lie as a whole. Real life hospital admissions showed it up to be demonstrable nonsense, yet politicians still to this day quote the 17% reduction lie.
Stung by The Times calling the Scottish 'miracle' out as one of the top ten junk stats of the year, Anna Gilmore's lies to produce the subsequent English 'miracle' of 2.4% were much more convoluted and nuanced.
As you can see, the decline in admissions in the year after the smoking ban was larger than the year before but smaller than the year before that. In fact, the average in the previous two years was 4.2%—almost exactly what it was in the year after the ban (4.26%).
Desperate to spin gold from straw, Gilmore throws everything she can at the data. She makes adjustments for surface air temperature, flu seasons, population size and Christmas holidays but she does not address more significant factors like smoking status, diet, exercise or stress (that's not her fault—the NHS does not have this data—but let's not pretend she is isolating smoking in public as the sole uncontrolled risk factor).
None of these calculations are shown or can be verified, but these manipulated data are then fed into a series of computer programs to arrive at an adjusted average daily admissions figure. Although Gilmore uses the July-June figures for all pre-ban years, she goes up to September 2008 for her post-ban year, thereby leaving in July and August, which is when the AMI rate is invariably at its lowest. It's baffling and more than a little suspicious. Why not go up to June 2009? Or at least stop at June 2008?
From this almost incomprehensible mass of heavily adjusted data, she arrives at the figure of 2.4% mentioned above. This 2.4% is the supposed decline in AMI admissions that she directly attributes to the smoking ban.
It's all designed to produce a headline via science by press release, of course. And the dolts at the BBC duly oblige every time, like the useful idiots that the health section have consistently proven to be (latest example was just the other day, funnily enough).
But none of those, surely, comes even close to the jaw-dropping mendacity of this from Prince Edward Island (yes, I had to look it up too, it's in Canada apparently).
A study published online in the journal PLoS ONE concludes that a partial smoking ban in Prince Edward Island resulted in a 14%-24% decline in heart attack admissions, while the study data show that the rate of heart attacks actually increased in the five-year period following the smoking ban compared to the five-year period before the ban.
The study conclusion is based entirely on the abnormally low heart attack rates observed during the period 1995-1997. If one compares the trend in heart attacks from 1998-2003 (five years prior to the smoking ban) with the trend from 2003-2008 (five years after the smoking ban), one finds that the smoking ban was actually associated with an increase in the rate of heart attacks.
Here are the approximate trends in the heart attack rates in the five-year periods before and after the smoking ban:
1998-2003 (PRIOR TO BAN): -0.4% per year
2003-2008 (AFTER BAN): +1.1% per year
So, err, they compared historical rates from eight years prior to the ban and compared them with five years after the ban, ignoring an entire five years simply because it didn't fit their pre-determined outcome?
Yes. Yes, they did.
Author of the above couple of paras, Dr Michael Siegel, reckons there might be something whiffy going on here.
Author of the above couple of paras, Dr Michael Siegel, reckons there might be something whiffy going on here.
At this point, it has become clear to me that there exists a strong investigator bias in favor of finding a significant effect of smoking bans on the reduction of heart attacks. So many studies have drawn conclusions that are simply not supported by the data that it is apparent that investigators want to find an effect.Masterful understatement, Mickey-boy.
How on Earth does appalling guff like this get published (as a vandal might say)? They'll probably big up that it's been peer-reviewed too, as if that means anything at all.
Because, while reviewing, if no-one in the public health community can spot some kind of methodological problem with the data set in this 'study' - along with the dozens of others which have been run along exactly the same junk lines - you have to wonder about your safety in other areas when it's clear that irresponsible, self-enriching propagandists are being entrusted to 'scientifically' advise on worldwide government health policy.
Prince Edward Island, you won, OK? I hope that $1 bet was worth the global trashing of method and trust in modern public health advocacy.
