Nightlight,
How do you explain that 85-90% of the cases of lung cancer in this country occur in smokers. Only 10-15% of cases occur in non smokers. Lung cancer =s death or severe disability. If there was some protective effect then this simply would not be. Any positive effects on the nervous system are far outweighed by this simple statistic.
Statistical
correlation between some phenomena A (e.g. smoking) and B (disease) is not synonymous with A
causes B. For example, use of breathing
ventilators is correlated with respiratory problems, strokes, heart attacks... yet use of ventilators reduces breathing problems, risk of stroke, heart attack... Similarly, if your grades increased last semester, that doesn't mean they are now better than those of another student whose grades remained the same or decreased in that semester. The increase/decrease (in grades or in disease rates) is a
derivative of a function, which is a very different quantity, the mass media obfuscation notwithstanding, than a
function value (your grades or disease rate).
Some habit A can be protective or therapeutic against disease B and yet show positive correlation (of any strength) with B in the samples in which the real causes of B are not properly controlled (as it is the case with most cancers, where the fundamental etiology is not known).
In the example of ventilators use, if that is the only parameter under control (in addition to age) you will find that
users of ventilators will have much shorter life expectancy than
non-users, while the
former users (self-selected) will fall somewhere in between. This is no different statistical phenomenon than what is found regarding smoking and the so-called
'smoking related' diseases.
Generally, a statistical correlation between phenomena A and B implies only that one or more of the following
causal relations is the explanation:
1) A causes B
2) B causes A
3) Some other phenomenon C causes A and B
In case of B occurring later than A and without being anticipated (since the anticipation or fear of B could cause A), then possibility (2) is eliminated, leaving a choice (1) and/or (3).
Normal science, takes therefore such statistical correlation of A and B
as a hint for a followup research using the methods of
hard science which can distinguish between the possible
causal models (1) or (3).
Note also that (3) includes not just some gene C making carriers simultaneously more likely to smoke and more likely to develop lung cancer (both phenomena do have a strong genetic component), but also the situations where C is some well established carcinogenic substance which also has other irritating effects when inhaled, such as asbestos or many dusts in metal ores mines. Since the doubling of glutathione (and other antioxidants and detox enzymes) in smokers will help remove such toxins at twice the rate than in nonsmokers, smoking provides
immediate relief against the
acute irritating effects of C. Hence the exposure to C would make it more likely (compared to less exposed general population) that those exposed will smoke. C is thus a common cause, via unrelated pathways, of A and B, yielding an increased statistical correlation of A and B.
Unlike the normal science, the
antismoking "science" (euphemism for the massive extortion racket) is still, half a century later,
stuck in the hint phase. They are merely replicating the same statistical correlation of A and B which they had in 1950s, as if thousand virtual xerox copies of the finding that 'A correlates with B' alone will distinguish between the models (1) and (3). It was
already by 1958, that
Ronald A. Fisher pointed this very problem of the antismoking "science" of that time:
But the time has passed, and although further investigation, in a sense, has taken place, it has consisted largely of the repetition of observations of the same kind as those which Hill and his colleagues called attention several years ago. I read a recent article to the effect that nineteen different investigations in different parts of the world had all concurred in in confirming Dr. Hill's findings. I think they had concurred, but I think they were mere repetitions of evidence of the same kind...
What would Fisher say about it half a century later, with antismoking "science" still stuck in that same loop (well, what can poor folks do but stick with that which works, since going beyond, at the causal relations, always backfired). The reason Fisher was puzzled by the same situation already at that time is because when
normal science encounters some correlation between the exposure to some substance A and cancer B, the
immediate next step is to
use hard science to test whether A
causes B. For example, it is trivial to establish that radiation or inhalation of radioactive particles causes lung cancers -- you expose some mice to such radiation in dose of interest and they develop lung cancers like clockworks. The same goes for various chemical carcinogens for which OSHA and EPA set exposure limits based on easily reproducible animal tests (cancer is a primitive disease, not specific to humans).
So why then, fifty years later, are we still only handwaving statistical association of smoking and lung cancer, such as "85-90% of the cases..."?
Can't we just make some animals breathe enough tobacco smoke and develop cancers at higher rates, so we can establish it once and for all? We could do that, and it was done, of course, except that the data went the
"wrong way" -- the
smoking mice gets fewer lung cancers than non-smoking mice, with dose-response relation showing that
tobacco smoke is protective against lung cancers:
Inhalation Bioassy of Cigarette Smoke in Rats
A.P. Wehrner, et al. Battelle Pacific Northwest Labs, Richland WA
Journal of Toxiology & Applied Pharmacology, Vol. 61: pp 1-17 (1981)
The results show that the highest number of tumors occurred in the untreated control [non-smoking] rats. The next highest number of tumors occurred in rats subject to sham smoking, i.e. rats which were placed in the smoking machine without smoke exposure, and the lowest number of tumors occurred in the smoke-exposed rats. Among the latter, the largest number of tumors occurred in rats exposed to smoke from cigarettes having the lowest level of nicotine.
No matter how much tobacco smoke they made poor animals inhale, even in equivalents of a carton or more per day (through surgically implanted breathing tubes), the more they smoke the fewer lung cancers they get. It just doesn't work and it even contradicts their "theory" so they just gave it up.
With humans, we can't force them to smoke, or even not to smoke, hence the next best thing, closest to hard science, are
randomized intervention trials -- you take a group of smokers, assign half of them randomly into a 'quit group' (strongly advised not to smoke), and a 'control group' (left alone, to smoke as they wish), then follow them up for some years or decades, observe the smoking rates (which are normally lower in 'quit group') and check for lung cancers or other diseases. That was done, of course, but only a handful of times in the early years of antismoking "science". As with animal experiments, the results of these few randomized intervention trials, whenever they showed anything at all,
also went the "wrong way" -- the 'quit group' ends up with more lung cancers than the 'control group' (and generally higher death rates). You can read about these studies (which most people have never heard of) here:
[1],
[2],
[3],
[4],
[5],
[6].
It should be noted that even the bare statistical correlations often parroted, the "90 percent..." stuff and such, which could mean anything anyway, aren't even on their own nearly as firm as mass media and 'pedagogues' would like you to believe. The diagnostic bias over-diagnoses lung cancers in smokers and under-diagnoses them in non-smokers by about 30 percent each. Further, the 'smokers' variable yielding those large risk ratios,
counts also ex-smokers (usually anyone who smoked for few months or longer in their life), who often have higher rates (depending on sampling criteria, especially age), of lung cancers than current smokers and who are now more numerous than smokers.
Another interesting bit of statistical trivia is that the
absolute numbers of smokers and total number of cigarettes smoked today are in USA lower than in 1950 (also, back then people smoked mostly non-filtered cigarettes which had 2-3 times more "tar" and nicotine per cigarette, plus many more were exposed to SHS since no one knew it is so deadly), yet the absolute number of lung cancer deaths per year is
more than 8 times larger today (from 20k in 1950 to over 160k in 2006).
If each molecule of tobacco smoke has some probability p of causing the
final cancerous mutation of a lung cell upon interaction with it, and the total
number of such molecule-cell contacts per second has declined by a factor 2-3 over half a century in between (while there was a similar number of cigarettes smoked, they had 2-3 times higher "tar" per cigarette),
how would one simulate via a computer model the
eightfold rise in the number of such mutations? Plain old random number generator striking with probability p some population of cells surely
can't do anything remotely what our current "theory" of lung cancer is proclaiming. To make the simulation work as imagined by our smoking-causes-lung-cancer "theory", one would need some kind of
smart molecules, which
learned over these decades how to aim better into the right section of the lung cell's DNA, maybe something like bacteria evolving antibiotic resistance. Except that molecules don't do that. And what's in it for them even if they knew how? If they're so smart, wouldn't they also be able to figure out that this particular DNA aim will hurt their future numbers? Well, that's how absurd it is. It is interesting that even back in 1950s, when Richard Doll concocted our modern lung cancer from tobacco smoke "theory" , the famous British mathematician Ronald A. Fisher (the father of modern statistics) noted a
similar anomaly (some kind of "smart molecules" would be needed explain it within their "theory") in Doll's data, as recounted
here:
These strong opinions for and against smoking were not supported by much evidence either way until 1950 when Richard Doll and Bradford Hill showed that smokers seemed more likely to develop lung cancer. A campaign was begun to limit smoking. But Sir Ronald Fisher, arguably the greatest statistician of the 20th century, had noticed a bizarre anomaly in their results. Doll and Hill had asked their subjects if they inhaled. Fisher showed that men who inhaled were significantly less likely to develop lung cancer than non-inhalers. As Fisher said, "even equality would be a fair knock-out for the theory that smoke in the lung causes cancer."
Doll and Hill decided to follow their preliminary work with a much larger and protracted study. British doctors were asked to take part as subjects. 40.000 volunteered and 20,000 refused. The relative health of smokers, nonsmokers and particularly ex-smokers would be compared over the course of future years. In this trial smokers would no longer be asked whether they inhaled, in spite of the earlier result.
Fisher commented: "I suppose the subject of inhaling had become distasteful to the research workers, and they just wanted to hear as little about inhaling as possible". And: "Should not these workers have let the world know not only that they had discovered the cause of lung cancer (cigarettes) but also that they had discovered the means of its prevention (inhaling cigarette smoke)? How had the MRC [Medical Research Council] the heart to withhold this information from the thousands who would otherwise die of lung cancer?"
Five year's later, in 1964, Doll and Hill responded to this damning criticism. They did not explain why they had withdrawn the question about inhaling. Instead they complained that Fisher had not examined their more recent results but they agreed their results were mystifying. Fisher had died 2 years earlier and could not reply.
This refusal to consider conflicting evidence is the negation of the scientific method. It has been the hallmark of fifty years of antismoking propaganda and what with good reason may well be described as one of the greatest scandals in 500 years of modern science.
These correlations are also sensitive to the intensity of the antismoking propaganda -- in countries or populations with
high intensity of antismoking propaganda, the correlations are stronger, with lung cancer
"risk factors" 8-15, while in countries with lower propaganda they go as low as 1.3-1.6 (see ref
[3]). For example,
Japanese men smoke more than twice as often as American men, yet they have 2-3 times fewer lung cancers, while living longer, than Americans (Greece vs USA has similar relation; see also
[4]). A more drastic example are Semai people of Malaysia, who
start smoking at age two, as a way of weaning themselves from nursing, and then happily continue smoking, completely worry free, into the ripe old age. They were studied in 1970s for 'smoking related' diseases, which included chest X-rays for all 12000 Semai adults, and
not a single lung cancer was found (cf. Dr. G. Y. Caldwell, British Medical Journal, Feb. 26 1977, V. 1 (6060) p. 580).
Even within the same country, there are populations who are outside of the "matrix", as it were, such as schizophrenics (who live in their own "matrix" distinct from ours). As noted in the
article quoted above, they smoke at huge rates (over 90%, mostly chain smokers), yet they get 30-50 percent fewer lung cancers than general population.
One of the mechanisms behind such damaging effects of antismoking propaganda (in addition to the detection and recall biases discussed in references given above, which are boosted by the propaganda and which in turn skew the statistical sampling) is the
"witch doctor effect" (negative placebo):
J. Hatton, R. Harris Murder a Cigarette: the Smoking Debate
There was a study in Heidelberg, described by Professor Eysenck in Psychological Reports (1989) in which 528 men were asked whether they, as smokers, were convinced that they would be very likely to develop lung cancer, heart disease, or other 'smoking related diseases'.
The 72 who answered 'yes', while admitting that their views were taken from information in the media, had an almost three times higher death rate at the end of 13 years than those who were not so influenced.
Fear can kill. This has been known since disease was first studied. We are entitled to wonder how many people have been killed more by the fear of 'smoking related diseases' than by any actual disease itself.
Leslie Kenton Modern-day Death Curses
Almost everybody has heard of death curses: psychological literature is laced with accounts of how Aboriginal witch doctors have quite literally brought about the death of the young and healthy by cursing them. No sooner do these people learn of the fate which has been cast for them than they begin inexplicably to sicken and eventually to die. It appears that through complex biological processes, their simple belief in the curse brings about destruction of their organism.
In civilized society we tend to look upon such phenomena as anthropological curiosities - products of primitive superstition which simply don't touch us in our more enlightened age. What we are not aware of however is that many of us in the civilized world are also under our own brand of `death curses'. They may be subtler than those issued by witch doctors but they can be every bit as potent in bringing about the physical and mental decline which we have come to associate with aging.
Common (and usually unconscious) notions such as `retirement', `middle-age', `It's all down hill after forty', and `At your age you must start taking things more easily', are widely held. They can exert a powerful effect on the process of aging by creating destructive self-fulfilling expectations about age decline. Instead of facing the future full of confidence and excitement about what lies ahead, optimism is replaced by anxiety as we are warned to `Be careful', or `Don't take chances on a new career at your age.'
Another mechanism is that such
antismoking social engineering by itself
reshapes the statistical distribution of various parameters, so that in our present antismoking "matrix" a random sample of 'smokers' is quite different from a random sample of 'non-smokers' in many other ways (mostly negatively affecting the 'smokers' sample), not just smoking.
For an example on how social engineering can do that, consider that since tobacco is an ancient medicinal plant with numerous therapeutic and protective effects, as illustrated in earlier posts here, people who still smoke despite the obscene financial shakedown and vicious social abuse of smokers, are largely
those who truly need it. For example, a
blue collar worker, exposed to toxic vapors and dusts at work, will find that smoking provides easily noticeable,
immediate relief, due to near
doubling of glutathione from smoking (which in turn will double, among others, the excretion rates of toxic metals, hence halve the effective exposure). Similarly, the
upregulation of neutrophiles (the
frontline defense against microbes and other organic antigens) by tobacco smoke strengthens the resistance against infections and neutralizes quickly most allergens (smoking was traditionally used to treat such problems and has spread through Europe based on similar observations; even the medical textbooks until 1950s
advised smoking as a relief for asthma).
While there was always some fraction of people smoking as a form of
spontaneous self-medication, their proportion has become much greater since anyone who doesn't really need to smoke for therapeutic reasons will have all other reasons to quit or not start. Smoking is thus increasingly becoming a
marker of hardship (i.e. of some unfavorable combination of genetic and environmental factors which causes people to smoke as a self-medication).
Therefore, pointing these days at the statistical correlations of smoking with various diseases, or any other kind of misery, is as meaningless as 'discovering' that people using respirators have lower life expectancy or that aspirin users have more headaches than general population.
In the light of that observation, the present antismoking hysteria (which is merely a facade for the plain old
extortion racket by the pharmaceutical industry), with its shakedown, social discrimination and "denormalization" of smokers, is about as noble an undertaking as ripping the breathing and IV tubes out of hospital patients.
Antismoking con has indeed become
increasingly evil in recent years, almost comparable to any genocide in human history since that is what it comes down to -- you
either 'convert' (quit smoking) and get damaged or killed from the resulting biochemical meltdown (as you can note in the MAO B graphs earlier, biochemistry of smokers is dramatically different from that of nonsmokers; nicotine is only a minor signaling mechanism within the larger symbiotic intertwining of the two complex biochemical networks) and pharmaceutical snake oils elbowing in, trying to replace numerous
therapeutic effects of this ancient medicine,
or you keep smoking and die from the
"death curse" or get sick and die from exposure in the rain, snow, car fumes... after being "denormalized" and shoved out into the street by the hysterical mobs.
Edited by nightlight, 16 April 2007 - 12:33 PM.
