Don’t get me wrong. It was global warming which caused the snow—what else?—but something had to cause the global warming first. And that, as statistics demonstrate to a very high level of “significance”, was caused by UFOs. Roy Spencer has done the work “correlating” UFO reports and the environment. The statistics say it happened. (Thanks to KA Rodgers for reminding us of this.)
The statistics do prove the association. But nobody not actually preferring tinfoil-lined hats believes UFOs could be a cause of anything. Simultaneous movement in two (or more) time series, such as the increase in UFO reports and (say) ocean temperature, is a necessary condition to prove causality. But it is not a sufficient condition. Correlation does imply causation, but it is nowhere near proving it.
After all, since these two series moved together, it could also be that warming ocean temperatures are releasing more UFOs into the wild (the saucers have been parked down there, some say, for a very long time; hadn’t you seen John Carpenter’s The Thing?).
I apologize for the winding introduction, but it was absolutely necessary to begin with an absurd example of how plotting two or more time series together could lead to insanity. Because here comes another entry, also in the same genre. Not temperatures and ocean levels. But yet another thing the government is most anxious to control. Salt.
The new peer-reviewed article “Salt reduction in England from 2003 to 2011: its relationship to blood pressure, stroke and ischaemic heart disease mortality” by Feng He and others claims that the “reduction in salt intake is likely to be an important contributor to the falls in [blood pressure] from 2003 to 2011 in England. As a result, it would have contributed substantially to the decreases in stroke and [ischemic heart disease] mortality.” (Thanks to reader Rich for alerting us to this study.)
Feng He, like Crichton, plotted the course of several time series, but only over four separate years. The picture above shows some of these series. The data themselves were taken from different sources and measured over different people (and even over slightly different times, but let that pass). The sample sizes of the different data sets were widely different, too.
Emphasis: salt intake was measured on different people in each of the four time periods.
Of the most important series, “Stroke and IHD mortality rates were calculated as the number of stroke or IHD deaths divided by the population.” Of course, the population of England changed over this time, mostly due to immigration of people whose eating habits probably weren’t the same as the native residents’ (I’m guessing, but it’s plausible).
More emphasis: nowhere was salt intake nor heart disease nor stroke occurrence measured on any individual. All we have is four time points for several different disparate heterogeneous series. Nowhere was immigration measured. Obviously, or perhaps not obviously, many other possible causes were not measured.
There thus could be no possibility of claiming causation, nor even really hinting of it. Too many other things might have caused the decrease in deaths by IHD and stroke. And also, over those same four time periods, people in England still died. Each person that died had to die of something. Therefore if there were decreases in the rates of some diseases, such as IHD and stroke, there had to be an increase in the rates of some other disease or diseases. (I’m guessing cancer.) It is very curious we do not also see plotted these other causes. In just the same way, we can say salt was the cause of these increases.
Enter classical statistics: out pops wee p-values which are everywhere taken as proof that whatever the authors claim is therefore true. Sure, people know p-values aren’t proof; or at least that’s what they’ll tell you. But they believe it is, whatever they say.
Since salt was measured on different people than the outcomes, there is no proof that falling salt intake by a few hundred to thousand people means anything. After all, the first people sampled in 2003 may have been eating the same amount of salt through 2011. There is no way to know they hadn’t. This paper is thus not much different than Spencer’s plotting UFOs reports and ocean temperatures, except maybe Spencer’s is better since he used the same ocean throughout.
Anyway, here’s the kicker, the authors’ final word: “Therefore, continuing and much greater efforts are needed to achieve further reductions in salt intake to prevent the maximum number of stroke and IHD deaths.”
That speaks for itself. All uncertainty vanishes. The p-values are the final proof.
They’ll be coming after your salt next.
They’ll be coming after your salt next.
Considering the word salary is linked to the word salt this comes as no surprise especially after Tax Day. They’ve been doing that for years.
OTOH, reducing salt intake may reduce UFO sightings and make the world a safer place.
It must be impossible to measure salt intake except under very controlled conditions (e.g. prisons). Salt shakers still abound, don’t they? Upon further consideration, probably not even in prison since they can not even control illicit drugs there. It is recommended to drink more water and less salt which sounds like a recipe for disaster. Didn’t the Campbell soup company give up on salt reduction when they discovered that sales fell? The body knows what it needs (bacon and whisky anyone?).
It also should be noted that salt intake is not nearly
I guess that I should have read the abstract first “The mean salt intake, as measured by 24 h urinary sodium…”. Although claiming a measurement of intake when you measure output is sloppy. That’s what threw me off. They are no doubt closely related, but it is still sloppy.
I notice that this is thrown in as well “a reduction in smoking prevalence from 19% to 14%” but the salt is still the main focus. Then there is this “It is likely that all of these factors (with the exception of BMI), along with improvements in the treatments of BP, cholesterol and cardiovascular disease, contributed to the falls in stroke and IHD mortality.” They can’t be serious.
Echoing Briggs observation we have “Although salt intake was not measured in these participants, the fact that the average salt intake in a random sample of the population fell by 15% during the same period suggests that the falls in BP would be largely attributable to the reduction in salt intake rather than antihypertensive medications.” This statement in itself should be enough to reject the paper by any competent reviewer.
In conclusion “The reduction in salt intake is likely to be an important contributor to the falls in BP in England from 2003 to 2011.” When did “likely” become a scientific conclusion worthy of a call to public action? As the authors claim “Therefore, continuing and much greater efforts are needed to achieve further reductions in salt intake to prevent the maximum number of stroke and IHD deaths.” Will anyone be held personally responsible if they are wrong? Solid science is needed, not this junk.
Scotian,
Amen to all. But just you wait and see: this paper will be cited by some advocacy group or other, or even by some government, in their “war against heart disease” (or whatever).
It also should be noted that the salt intake the government tells you is “high” is not nearly as bad as they say it is. Sure, salt can mess with your blood pressure, but that’s usually only if you have some sort of heart condition already. The average salt consumption in Japan is WAY higher than the government’s magic number, but that doesn’t stop them from living well into their 80’s on average.
In fact, these health campaigns against salt may have adverse effects as people start going on salt free diets, convinced of their health benefits. The problem is that you almost have to have lots of salt to get enough sodium in your diet, so this could lead to people dying of nervous system breakdown; so expect government cover-ups! 😉
Oops, misfired the first time up there, might want to go ahead and delete it Briggs.
That does it–I’m stockpiling salt, sugar and anything else “they” might come after. Let ’em try and take my stockpile.
How ’bout this simplistic “analysis” about Florida gun “crime” based in part on a valid complaint about a quirkily presented graph:
http://freethoughtblogs.com/pharyngula/2014/04/15/thats-a-terrible-chart/#comments
It shows gun deaths, with an apparent spike up (but within historical ranges) right after Florida enacted its Stand-Your-Ground law.
Is that increase a direct result, within statistical variability, correlated with other factors (e.g. more unemployment, releases of prisoners, etc.)??
There’s certainly a correlation–which has been philosophically extrapolated to a cause-effect relationship…but is there’s really a cause-effect relationship there?
Yes, Briggs it has started already:
http://www.dailymail.co.uk/health/article-2604761/Salt-intake-falls-15-heart-deaths-fall-40-eat-it.html
Our role model in Britain has his own inimitable take on this:
http://www.numberwatch.co.uk/2014_april.htm
BMJ Open(journal where the salt paper was publisjed) provids the means to write an e-letter in repnse to their publications. Briggs, write one, then more people will know that you have a problem with thier paper. Follow this link to do this
http://bmjopen.bmj.com/letters/submit/bmjopen;4/4/e004549
“Simultaneous movement in two (or more) time series . . . is a necessary condition to prove causality.”
Hmmm, this statement does not seem at all obvious to me. I’ll take a stab at a counter-example.
Let’s say I have three time series. Series 1 is volume of water in a bucket. Series 2 is the total volume of water that has flowed into the bucket from a hose. Series 3 is the total volume of water that has drained from the bucket from a hole.
If series 2 equals series 3 over the observation interval, there is no ‘simultaneous movement’ in series 1. So a causal relationship between series 2 and series 1 can’t be proven, right?
Perhaps there is an assumed qualifier, “Given no context, simultaneous movement in two (or more) time series . . .”? If so, I can accept that, since, as an engineer, I have very little interest in time series with no context.
Or maybe I’m getting hung up on “prove causality”. I.e., causality is not disproved by the lack of simultaneous movement in two time series? I can accept that, too.
Bottom line is that it seems fairly useless to talk about proving or disproving causality based on time series alone. Context is everything.
Here’s another statistical puzzle: After decades of study a harmful cause is NOT having the expected harmful effect, in fact the opposite trend is observed…conclusion: the harmful effect must be ‘masked.’
No way the fundamental hypothesis could be wrong.
Right?
Seems like this study is ripe for an ‘accept/reject the null hypothesis’ sort of statistical test …Briggs can you do one with this study?? It’d be a nice diversion from the p-value theme…
Story at: http://www.sciencedaily.com/releases/2014/04/140415083904.htm
They (the researchers) are saying Finnish moths should be dying off, but the population keeps increasing even despite harmful [what else could it possibly be] global warming…so therefore the harmful effects of global warming must be ‘masked.’ And if the harmful effects are ‘masked’ with Finnish moths, no telling how many other species are even worse off than we can observe.
Observe the “logic” there: Since we can’t see any evidence of a problem, that problem must be even worse than we imagined!
My guess: the “masked” factors are hiding where the “missing heat” is. I’ve got no support backing that hypothesis, so it would appear that, on that point, I’m on as solid a footing as the moth researchers are.
Ken–Sounds like a classic “our hypothesis must be right” so the effects are masked. “Masked” is another word for “we have no clue why this is not behaving properly”, so the logic is most certainly flawed, though you probably would be depressed by how many global warming people take the “masked” conclusion as gospel proof. (It’s also interesting that while global warming scientists will preach evolution, they clearly never believe it happens–nothing adapts to climate change, only dies out. If it’s still alive, then that simply cannot be.)
There’s another interesting study on moths where global warming was “proven” by a moth, only to find a completely different cause when more research was done:
http://landscapesandcycles.net/climate-doom–parmesan-s-butterfly-effect.html
If diabetes is increasing and heart disease is decreasing, does that mean diabetes prevents heart disease?