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Passive Smoke And Disease

An Incredible Story

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PASSIVE SMOKE AND DISEASE:
AN INCREDIBLE STORY

LIST OF ALL STUDIES EVER PERFORMED ON SECOND HAND SMOKE SMOKE AND LUNG CANCER, UPDATED TO JANUARY 1st, 1998

LIST OF ALL STUDIES EVER PERFORMED ON SECOND HAND SMOKE SMOKE AND HEART DISEASE, UPDATED TO JANUARY 1st, 1998

THE LAYPERSON IS STRONGLY ADVISED TO READ THE EXPLANATORY PREFACE IN ITS ENTIRETY BEFORE EXAMINING THE TABLES

TABLE I: EPIDEMIOLOGICAL STUDIES RELATING TO LUNG CANCER AMONG NONSMOKERS MARRIED TO SMOKERS

TABLE II: EPIDEMIOLOGICAL STUDIES RELATING TO LUNG CANCER AMONG NONSMOKERS REPORTEDLY EXPOSED TO ETS IN THE WORKPLACE

TABLE III: EPIDEMIOLOGICAL STUDIES RELATING TO LUNG CANCER AMONG NON-SMOKERS REPORTEDLY EXPOSED TO ETS IN CHILDHOOD

TABLE IV: EPIDEMIOLOGICAL STUDIES RELATING TO LUNG CANCER AMONG NON-SMOKERS REPORTEDLY EXPOSED TO ETS IN NON-HOME/NON-WORKPLACE SETTINGS

TABLE V: EPIDEMIOLOGICAL STUDIES RELATING TO HEART DISEASE AMONG NONSMOKERS MARRIED TO SMOKERS

TABLE VI: EPIDEMIOLOGICAL STUDIES RELATING TO HEART DISEASE AMONG NONSMOKERS REPORTEDLY EXPOSED TO ETS IN THE WORKPLACE


Download preface and all tables in Rich Text Format




"[e]pidemiological observations ... have serious disadvantages... [T] they can seldom be made according to the strict requirements of experimental science and therefore may be open to a variety of interpretations. A particular factor may be associated with some disease merely because of its association with some other factor that causes the disease, or the association may be an artifact due to some systematic bias in the information collection... It is commonly, but mistakenly, supposed the multiple regression, logistic regression, or various forms of standardization can routinely be used to answer the question: 'Is the correlation of exposure (E) with disease (D) due to merely a common correlation of both with the same confounding factor (or factors) (C)" ... Moreover, it is obvious that multiple regression cannot correct for important variables that have not been recorded at all... These disadvantages limit the value of observations in humans, but ... until we know exactly how cancer is caused and how some factors are able to modify the effects of others, the need to observe imaginatively what actually happens in various different categories of people will remain ..."

(Doll R, Peto R, The causes of cancer, JNCI 66:1192-1312, 1981. p. 1281).

EXPLANATORY PREFACE

EPIDEMIOLOGY: THE JOKE IS ON YOU

The alleged links of passive smoke exposure with lung cancer and heart disease are based on surveys of nonsmokers, but contrary to media and popular misconceptions,there is no science involved.

Epidemiologists -- those who run disease surveys in people -- recognize among themselves the lack of science in what they are doing. As an example, Sir Richard Doll of the University of Oxford in England -- perhaps the most prominent of anti-smoking epidemiologists -- acknowledges in a professional publication that epidemiology cannot be science and is open to all sorts of interpretations. However, epidemiologists studiously avoid letting this little secret transpire in their communications to the public, which usually are falsely described as scientific.

Epidemiologists may ask people in a survey whether they are smokers or not, and simply assume that the answers are correct, usually without checking for sure. Or they may ask about exposure to passive smoking without checking whether people are also touched by a variety of other problems that seems to go with lung cancer or heart diseases, such as a family history of disease, hazardous occupations, poor diets, weight problems, unhealthy homes, lack of exercise and the like. In the end, therefore, epidemiologists measure something but cannot tell for sure what they have measured, and besides their measures are sloppy beyond belief.

To be sure, every measure lacks some precision. Even super-accurate atomic clocks register some error, but most things that we use are sufficiently precise and therefore reliable. For all their complexities, airplanes are built to be reliable for millions of miles and tens of thousands of service hours. Even lowly bicycles function correctly most of the time, or washing machines, telephones, and so on. But would you accept hamburgers that 1 time out of 20 make you sick" Or toothbrushes that fall apart after 19 uses" Or cars that 1 time out of 20 turn left when you actually steer right" Yet, this is the kind of sloppy unreliability that passes for scientific certainty in epidemiology, where universal standard of precision admits 1 in 20 rate of failure, and more.

PASSIVE SMOKE AND DISEASES

In the tables that follow you will find columns with the name of the principal author of a survey, the year it was conducted, and the number of persons (cases) considered. The next column to the right gives the average risk estimate, where you should keep in mind that a value of 1 means no risk difference, a value above 1 means an increased risk, and a value below 1 means a reduce risk or that exposure to passive smoking actually protects against the diseases considered.

The average risk value is iffy because the true value could be higher or lower than the average, depending on the uncertainties of measurement. How different the true value could be is estimated in the last column at the right, where you will find two values, one lower and one higher than the average. What that means is that the true value could be at any point between the low and the high values in the last column.

The uncertainty does not end there because the calculations allow for a probability of 1 in 20 that the true value could actually be even higher or lower than the span of values in the last column. (If you are interested in technical lingo, the span in the last column is called the 95% confidence interval, meaning that we are 95% confident that the true risk value is in that interval).

So, here we have two compounded uncertainties, the first is that the true measure could be anywhere in the interval, and the second that the interval itself could be in error with a 1 in 20 probability. On this basis, some epidemiologists and public officials still feel no shame when they affirm that their results have achieved certainty.

And now the last and most important word about reading the tables below. Remember, as we said before, that values of risk below 1 imply the passive smoke exposure actually protects against the disease in question. Therefore, if the low value in a given interval is less than 1 and the high value is more than 1 the results is moot since the true value could be anywhere in the interval and could mean either protection or risk, but there is no telling one way or another. In those cases the result is said to be non-significant, and the last column to the right in the tables shows that this is by far the most frequent situation.

On the other hand, if both ends of an interval are less than 1 the results implies protection and if both values are above 1 the result implies risk, but such instances are the rare exception, as you can see. Desperate to get some mileage out of this baffling confusion, epidemiologists have tried to average all the surveys available, even though they know perfectly well that the procedure is not permissible. It is like they pretended to make good sauce out of rotten apples.

Other ailments have been surveyed against passive smoke, but the results are even more confused and improbable than those reported for lung cancer and heart diseases. And of course, it has been a self-fulfilling prophecy that some people would be annoyed and even terribly annoyed by passive smoke, after 20 years of relentless and unjustified propaganda from presumed public health authorities that have falsely portrayed passive smoke as the worst bugaboo around. The fact remains that even the Surgeon General and the National Academy of Sciences could not find ways to link passive smoke, respiratory ailments, and asthma.

In the end, the only reasonable conclusion from the surveys so far published is that if passive smoke poses a risk it would be small beyond detection, with a nearly equal possibility that exposure to passive smoke could actually protect from the diseases listed.

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