Over the last few months, I have been following up on the many claims made by the Tobacco Control Lobby regarding the dangerous effects of tobacco smoking. My investigations led me to the conclusion that almost everything being presented as evidence for tobacco’s deleterious effects is junk science. I have also discovered just how many authoritarian followers are out there and just how hate filled and vicious they can be when their core doctrines on the dangers of smoking and secondhand smoke are challenged.

What is junk science?

According to YourDictionary.com junk science is “A cluster of assertions, publications, and experts that have the appearance, but not the actuality, of a scientific specialty.” A more detailed discussion follows here:

The problem … is that defining a “finding” as junk science relies on our having a “clear and unproblematic understanding of what science is, and just as importantly what it is not”. We might think we do. It approximates to that observation-hypothesis-prediction-experiment-new-observation-amendment-(peer review)-theory cycle with which we are all fairly familiar. But, many things we call science, such as experiments that cannot be repeated independently, the LHC [Large Hadron Collider] experiments, large-scale clinical trials, climate modelling etc., do not fit and cannot even be forced to fit this cycle. Moreover, of the many thousands of scientific papers out there that comprise the scientific literature, very few, but for some worthy exceptions, are ever repeated by other scientists.

In reality, observation studies married with statistics, or flawed clinical studies using animals with a predisposition to cancer, are being used to prove whatever the research sponsor wants to prove. It’s junk science. All that is required is to tweak the questionnaire, fiddle with the statistical models, bias the clinical tests and you can have the answer you want. But only so long as that answer is politically correct. Try to use this method to prove something held to be “bad” or “wrong” in the minds of the Public Health Sector, and all hell will break loose.

My approach has been to take an article reporting something about tobacco smoking, read it in detail, look at the research data behind the article, and attempt to read and dissect it in much detail in order to see if it qualifies as science according to the definition of the scientific method.

Epidemiology

Where and how is junk science applied in the study of tobacco smoke? To answer that, let’s start with a quote from “Studies of Cancer in Humans“: “The available knowledge on the relationship between tobacco usage and a variety of human cancers is based primarily on epidemiological evidence.” So, what is epidemiology?

Originally, the word described the study of epidemics to determine the cause, distribution and control of disease in populations. The CDC describes it in lofty terms:

Epidemiology is the study (scientific, systematic, data-driven) of the distribution (frequency, pattern) and determinants (causes, risk factors) of health-related states and events (not just diseases) in specified populations (patient is community, individuals viewed collectively), and the application of (since epidemiology is a discipline within public health) this study to the control of health problems.

The epidemiological studies relating to tobacco smoking and its denormalisation that I have studied are based on observational studies (predominantly questionnaires), to which statistical formulae are then applied. The construction of, and the contents of, these questionnaires, is the area where abuse and fraud are most easily introduced. The methodology applied follows these general guidelines:

  • Define what you want to prove
  • Select a study population
  • Draw up a questionnaire
  • Gather the data
  • Prepare a hypothesis
  • Publish it as scientific fact

All the definitions are quite insistent that epidemiology is a genuine science, but let’s examine that assertion. Back in 1960, at least, the scientific method had four steps:

  1. Observation and description of a phenomenon (visually or with the aid of scientific equipment).
  2. Formulation of a hypothesis to explain the phenomenon in the form of a causal mechanism or a mathematical relation.
  3. Test the hypothesis by analyzing the results of observations or by predicting and observing the existence of new phenomena that follow from the hypothesis. If experiments do not confirm the hypothesis, the hypothesis must be rejected or modified (go back to Step 2).
  4. Establish a theory based on repeated verification of the results.

It was the completion of these four steps that made it science. ‘Scientific’ epidemiology studies today complete steps 1 and 2, then they declare a result and go to press. This is where studies becomes junk science. They’re half-baked; they do not conform to the scientific method.

Epidemiology is the principal tool in the hands of the public health sector, which is responsible for the denormalisation of smoking and what appears to be the persecution of smokers. They also seem to be gearing up to go after obese people, drinkers of soda and alcohol, and consumers of fats and red meat. If their studies on tobacco are anything to go by, these areas of research also are likely to be a rich core to mine for junk science.

Correlation Does Not Prove Causation

Many studies that apparently ‘prove’ the dangers of tobacco smoking do demonstrate some correlation between smoking and disease, but as the maxim goes, “correlation does not prove causation”. For example, if we did a study on the game of basketball, we could come up with an association between playing basketball and being tall. There is a correlation in the data between these two facts. If we concluded our study and issued a press release that said “playing basketball will make you tall”, we would behaving like the Tobacco Control people: presenting a correlation as causation, which is simply wrong. The best we could do with that data is to form a hypothesis for clinical testing. Similarly, with tobacco smoke and lung cancer, a study may note a correlation between the two, but that is a million miles away from proving anything. You still need steps 3 and 4 in order for it to be real science.

“Smoking-Related” Diseases

The phrase “smoking-related diseases” is much abused. Let’s be very clear. There are no truly smoking-related diseases. Think about it for one moment. Can you name one single disease or illness that is only contracted by smokers? The answer is no. Every disease supposedly caused by smoking is also contracted by people who do not smoke. So if we have 100 people with lung cancer, and 50 of them smoke and 50 do not, it cannot be proven that the 50 smokers would not have contracted the disease if they did not smoke. In other words, some smokers may in fact get lung cancer for some other reason not related to their smoking.

Muti-Factor Risks

The reason for this is that all of the diseases so described are diseases which have multiple risk factors. Environmental toxins, diesel fumes, radon, pollution, etc. These can all cause, for example, lung cancer. So any research which looks at a population and then proceeds to draw conclusions based on who smokes and who does not, is not covering the many possibilities that the population being studied has not been affected by any or all of the other risk factors. Those studies are invalid.

In addition, if we look at data on the effects of wood fires, coal burning and air pollution on health, we find all the usual suspects punted for smoking:

Steffen Loft, Ph.D., and colleagues cite the abundant scientific evidence linking inhalation of fine particles of air pollution — so-called “particulate matter” — from motor vehicle exhaust, coal-fired electric power plants, and certain other sources with heart disease, asthma, bronchitis and other health problems.

And on this website: lung and bladder cancer.

We see that the diseases designated as “smoking-related” are the same diseases linked to pollution. One must ask whether this was taken into account in the many epidemiological studies conducted into the effects of tobacco smoking. Did the questionnaires ask about levels of pollution or check to see if the people lived near a motorway or in the countryside? Was there a question about the regular passage of diesel trucks or buses? Without considering these questions, how can the data possibly be considered reliable and the results scientific? This just reinforces that the illnesses and diseases designated as “smoking-related” all have multiple risk factors associated with their contraction. A study which considers only one of those risks and then attempts to draw valid conclusions, qualifies as junk science. And that’s what these studies do. If a smoker dies of any of these diseases, their death is classified as caused by smoking.

Questioning Those Questionnaires

A study based on questionnaires is quite different to a study based on actual clinical tests and trials. They have a number of significant limitations, including 1) the propensity of humans to be less than honest in their answers, 2) a lack of ability to remember what they had for breakfast yesterday accurately, and 3) the propensity to spin answers based on personal biases and knowledge of the subject being studied. This last one is called recall bias. For example, a person who has lost a family member to lung cancer, and who is personally convinced the cancer was caused by smoking, is far more likely to exaggerate the results than somebody with no such experience. In addition, the way questions are structured can easily affect the answers given and can request data the person has no knowledge of. An example would be to ask the respondent how many cigarettes a day their parent smoked when they were children, or to estimate how many hours a week they were exposed to secondhand smoke. Inaccurate answers can skew results.

Australian Study

I investigated a large study carried out in Australia which set out to be the gold standard of smoking data for Australia. Bearing in mind the multi-risk factors associated with all “smoking-related” diseases, one would expect to see an attempt in the questionnaire to allow for and capture this type of data in the name of transparency and validity: questions on proximity to motorways, busy roads, levels of pollution in the area, potential for exposure to pollutants through work or leisure. Here is a copy of the questionnaire. What we see are questions on health, diet, physical activity, ethnicity, smoking behaviour, and exposure to passive smoke. That’s it. There is no attempt to gather data on any of the other risk factors. To my mind, without going any further, this study is fundamentally flawed and cannot be an accurate reflection on the effects of smoking on an Australian population.

In the introductory discussion we find this curious statement:

Hazard ratios (described here as relative risks, RRs) for all-cause mortality among current and past smokers compared to never-smokers were estimated, adjusting for age, education, income, region of residence, alcohol, and body mass index.

Already we are into estimates, in this case estimates that adjust for a range of factors. Presumably they are taking into account previously studied statistics on mortality rates associated with those other factors, e.g., people with lower income may have an overall higher mortality rate. If these figures are accurate, they can be useful in parsing out possibly misleading correlations. A simple example: if smokers have a higher mortality rate than non-smokers, but are also poorer than non-smokers, the two influences may cancel out. The higher mortality could be due to income-related factors (access to healthcare and healthy food, for example), not smoking. However, in order to give a true picture, they must also be comprehensive. All possible multiple risk factors must be included. So even if smokers show a higher mortality rate after taking the factors quoted above into account, the correlation may still have some other cause not identified in the study.

This study aims to investigate the relationship of smoking to all-cause mortality in Australia, in the 45 and Up Study cohort. Although cause-specific mortality data have been used in analyses from other countries, these were not available for Australia at the time of writing …

In other words: We do not have information which tells us specifically what people die from but we are going to estimate how many smokers dies from which diseases.

Questionnaire data from study participants were linked probabilistically to data from the NSW Register of Births, Deaths and Marriages up to 30 June 2012 to provide data on fact and date of death. This probabilistic matching is known to be highly accurate (false-positive and false-negative rates <0.4%). Death registrations capture all deaths in NSW. Cause of death information was not available at the time of analysis …

And this one:

It should be noted that although the 45 and Up Study is, like the vast majority of cohort studies, not strictly representative of the general population, the results presented here are based on internal comparisons within the cohort and are likely to be reliable …

And again:

International evidence shows that the vast majority of excess deaths in smokers are caused by smoking and are due to conditions such as cardiovascular disease, cancer, and chronic lung disease. However, it should be borne in mind that a minority of deaths, such as those related to suicide, may be increased in smokers but may not be wholly caused by smoking. Hence, although we are not able to exclude the relatively small number of deaths that are less likely to be causally related to smoking, the large majority of the observed excess mortality in smokers observed here would have been caused by smoking.

Language is Important

In reading research, it is very important you take note of the language being used in the document. Words like “may, could be, appeared to, we believe or suggest” can simply indicate that the researchers are being cautious, but they can also be deceptive, designed to create the association that is desired by the researcher. What is most disturbing is when they draw bold claims without such discretion in their press releases. Here is an example:

Dow Jones Business News, Associated Press, 07/24/2001

CHICAGO — Just half an hour of second-hand smoke can impair normal blood flow to the heart, a Japanese study suggests.

The study examined the effects of spending 30 minutes in a hospital’s smoking room on 15 non-smoking men and 15 smokers. The smokers, whose heart arteries already showed damage, weren’t affected. But in non-smokers, the result was a reduced ability of heart arteries to dilate, which previous research has suggested may be a precursor to hardening of the arteries. “This change may be one reason why passive smoking is a risk factor for cardiac disease” and related deaths in non-smokers, the researchers say in Wednesday’s Journal of the American Medical Association. The study didn’t examine whether the changes from the one-time exposure to smoke were permanent.

Previous research in smokers has found similar changes that may be reversible if smokers quit, said Dr. David Faxon, president of the American Heart Association. If exposure continues, “gradually, as hardening of the arteries sets in, it’s irreversible,” he said. The study “really sort of confirms prior information that we’ve had about the adverse effects of second-hand smoke,” Dr. Faxon said. In the study, Dr. Ryo Otsuka of Osaka City University Medical School and colleagues used blood-pressure tests and an imaging technique called echocardiography to examine the effect on heart arteries’ ability to dilate. Measurements were taken before and after exposure to second-hand smoke. The smoke appeared to impair the functioning of the endothelium, a lining of cells in the arteries that helps regulate dilation. Scientists believe coronary artery disease may begin when the endothelium becomes damaged, leaving the arteries prone to blockages or narrowing.

Stanton Glantz, a professor of medicine at the University of California at San Francisco, said the findings add fuel to the debate over second-hand smoke. “People walking into a smoky restaurant, do they want to be clobbering the ability of the arteries in the heart to get blood to the heart, even if it’s just for a little while?” he said.

Seth Moskowitz, spokesman for R.J. Reynolds Tobacco Co. (RJR), said the study doesn’t change the company’s belief that there is no scientific evidence establishing that second-hand smoke is a risk factor for lung cancer, heart disease or any other disease in adult non-smokers. ”

As you can see, the headline does not reflect the extreme softness of the result of the study. I call this “lies by headline”, where the headline has been engineered to convey different information that that actually contained in the study. As the attention span of the average adult is around 30 seconds these days, a headline is all that the majority will ever bother to read, so it is a very effective mechanism to spread disinformation.

Research Paper Structure

The standard approach with research papers is to provide an abstract at the beginning of the document which summarises what they studied (in many cases what they want to prove), how they went about that study, and a summary of their conclusions – this is the executive summary of the research and it is my firm opinion that the researchers hope this is as deep as you dig into their work. (Of the few people who actually look into the research, I suspect the vast majority do not get past the abstract.) The body of the research data and findings make up the rest of the document. I have found that the most fruitful place to dig for gold is in the ubiquitous Appendices. Here we find the many qualifications of the results, the shortcomings, the questionable details that are never reflected in the summary conclusions and which remain hidden unless you have the fortitude to dig for it and digest the implications.

Clinical Trials

Clinical trials are conducted on a variety of animals, but predominantly rodents and golden hamsters. This quote, discussing how the tobacco is tested, is quite revealing:

As set out in the IARC monographs, the carcinogenicity of cigarette smoke is determined in two ways. The first is through the application of cigarette-smoke condensates to skin. Cigarette-smoke condensates are collected by passing smoke through cold traps and recovering the retained material. The cigarettes are usually machine-smoked and the material is washed from the traps using a volatile substance such as acetone, which is then removed. Many of the procedures for collecting this cigarette-smoke-condensate have not yet been standardized across laboratories, including how the condensate is stored, in what numbers and fashion the cigarettes are smoked, and the type of solvent used. Once the condensate is collected, it is painted onto the skin of the animal test subjects, which are then examined at set intervals to assess the growth of tumors.

This does not simulate smoking in humans; it is not even smoke that is tested.

The second method, as described by the IARC monographs, used to measure the carcinogenicity of cigarette smoke to animals is by exposing them to mainstream cigarette smoke. The IARC monographs define mainstream cigarette smoke as that which is emitted by the mouth end of the cigarette and therefore the smoke that human smokers would be exposed to most. The IARC monographs describe the methods and equipment that scientists have developed to make more effective and standardize the deliverance of mainstream cigarette smoke. These devices vary between whole-body and nose-only exposure, but typically involve machine smoked cigarette smoke being pumped into a small chamber that contains the animal test subjects.

How is whole-body exposure to concentrated smoke in a small box relevant to how people smoke and the effect it has on them?

A variety of factors differentiate the experience of a human smoker from these animal test subjects. Human smokers inhale smoke voluntarily and therefore do so more deeply than do animal test subjects which typically adopt short, shallow breaths when exposed to smoke. The animal test subjects, primarily rodents and dogs, also have significantly morphologically different upper respiratory system from humans. Despite these variables, the doses of smoke administered to these animals can be determined by examining tissue and blood samples. Dogs, which cannot be exposed to cigarette smoke via inhalation chambers as easily as can small rodents, require different methods of cigarette smoke exposure. These methods include thracheostomy, in which smoke is pumped through a tube directly into a hole cut in the dog’s throat, or through a mask fitted to the dog’s face.

The methods described are both cruel and not representative of how a person smokes. These creatures also have quite different upper respiratory tracts than humans, so how relevant are these findings?

    

In many clinical trials, animals are force-fed smoke as they lie in their smoking machine, or being immersed in smoke for hours a day in a very small cage, having concentrated chemicals smeared on them or injected into their lungs and organs.

In a typical study, rats are exposed to the smoke of 7 to 10 cigarettes all day, every day of the week. This is meant to simulate a smoker smoking 10 cigarettes a day. The rat probably weighs less than 1/200th of an average smoker, so that rat is smoking the equivalent of 1400 cigarettes a day. This is not a useful measurement to test the effects of a human smoking. The poison is in the dose, and at this dose there are almost guaranteed to be problems developing in the test animals. Ignoring the fact that researchers acknowledge that these rodents have significantly different respiratory systems or are significantly smaller than humans and that results achieved with animals do not necessarily translate across to humans, these tests are designed to produce the required result, even if that means amplifying the conditions of exposure. These results are then communicated as clear scientific proof that smoking causes X. For X, fill in any disease you so desire. We also note that no allowance is made for the health-destructive power of stress.

The best we can conclude from clinical studies like these is that having chemicals smeared on your skin for the period of your life can induce cancers; that lying in a room of dense smoke for 8 hours a day for all of your life is detrimental to your respiratory system; and that smoking 1400 cigarettes a day is detrimental to your health and possibly cancer-causing.

Additionally, the rodents used in these trials are not wild rats. They are rats that have been specifically bred for the lab. There are a variety of different strains of rats, some of which are bred for their ease of contracting cancer. The selection of a rat type for a trial can have a huge bearing on the trial. This article, discussing the furor over some original research which claimed that GMO products caused cancer in rats, tells us something interesting about the rats used for smoking tests:

Hayes outlined the peer review process, the international criticism the article prompted from the mainstream science community and the subsequent review and reasons behind the decision to retract. The low number of animals had been identified as a cause for concern during the initial review process, but the peer-review decision ultimately weighed that the work still had merit despite this limitation. A more in-depth look at the raw data revealed that no definitive conclusions can be reached with this small sample size regarding the role of either NK603 or glyphosate in regards to overall mortality or tumor incidence. Given the known high incidence of tumors in the Sprague-Dawley rat, normal variability cannot be excluded as the cause of the higher mortality and incidence observed in the treated groups. Ultimately, the results presented (while not incorrect) are inconclusive, and therefore do not reach the threshold of publication for Food and Chemical Toxicology.

This is clear evidence from the scientific community that various families of rats are predisposed to cancer, in fact are bred for that purpose. It seems to me that selecting rats that are almost guaranteed to develop cancer, in a trial to test if tobacco smoke causes cancer, is disingenuous to the extreme and actually tells us nothing.

Political Correctness

As far as I can see, there is no tobacco research being done with an open mind; everything starts from the premise that tobacco smoking is harmful. Indeed, the focus of scientists today and for at least the last 40 years is research funding. Without funding they do not get paid and they lose their jobs. Anti-smoking research receives ample funding, but research wanting to honestly investigate the possible link between tobacco smoke and a particular disease would never receive funding and would mark that scientist as somebody to watch out for.

A case in point is Professor James Engstrom. He was eventually fired from his position with UCLA after publishing research in 2003 showing no significant harm from secondhand smoke, something he was viciously attacked for by his colleagues and the anti-smoking industry:

The results do not support a causal relationship between environmental tobacco smoke and tobacco related mortality, although they do not rule out a small effect. The association between exposure to environmental tobacco smoke and coronary heart disease and lung cancer may be considerably weaker than generally believed.

The UCLA commented on his dismissal: “his research is not aligned with the academic mission of the department.”

Passive Smoking

But James Engstrom is not the first neutral researcher to cast doubt on the public health sector’s obsession with passive smoking. In February 2000, a team from Warwick University led by Professor John Copas and Dr Jian Qing Shi argued that findings from previous anti-smoking-funded field studies were ‘unreliable’. Copas himself went on the record as a scientist to say that “research which suggests an increased risk is more likely to be published than research which does not …” But the real embarrassment for the public health lobby in general and the World Health Organisation in particular revolved around a study to end all studies on passive smoking.

The World Health Organisation commissioned France’s International Agency for Research on Cancer (IARC) to carry out a huge Europe-wide study of the effects of passive smoking. It was eagerly awaited, said the International Epidemiology Institute, “because of the size of the study, the special attempts to minimise misclassification of cigarette smoking status and the ability to control for various potential confounding factors.” With 1,008 female lung cancer cases to examine, the sample group was twice as large as any study to date and no one was in any doubt about the importance of the report – including the tobacco industry, who made plans to challenge it in the event that it condemned secondhand smoke as a hazard. They considered this to be the likely outcome after finding out that the IARC’s director was a “‘fervent antismoker’ who believes that ‘passive smoking is more dangerous than active smoking.'”

By March 1998 the study had been completed and written up but remained unreleased, creating speculation that the results did not support the WHO’s view of second-hand smoke as a genuine health hazard. This suspicion was heightened when the Sunday Telegraph found a summary of the results buried in an internal WHO report. On March 8 1998 the newspaper published an article revealed that the researchers had found no statistically significant elevation in risk for those exposed to second-hand smoke as adults and found a statistically significant reduction in risk for those exposed in childhood. Entitled “Passive smoking doesn’t cause cancer – official“, the article not only reported the lack of association but, referring to the data on childhood exposure, reported that passive smoking “might even have a protective effect.” This sent anti-smoking groups into a frenzy but what was good for the goose was good for the gander. For years, they had used weak associations to ‘prove’ the passive smoking theory and now they were left in the position of having to dismiss a statistically significant risk reduction of 22% for children while promoting a smaller and statistically insignificant risk elevation of 11% for the wives of smokers.

As this was research commissioned and funded by WHO, one might expect to find the results of the study reflected in the material on their website. What we find instead is WHO literature stating: “more than 600,000 deaths per year are caused by second hand smoke.” This fact alone raises questions about the impartiality of the WHO and whether it is committed to quality scientific research or the achievement of its public health goals, regardless of the available scientific evidence.

This article from the Telegraph newspaper in the UK highlights the gap between EU anti-smoking policy and scientific evidence relating to smoking and lung cancer:

Mr Bloom wanted to know, in the light of the figure and bans: “could the Commission please name three or four people who have died from Environmental Tobacco Smoke (ETS) within the EU in the last two years?”

Here is the answer on the 79,000 deaths every year figure from Androulla Vassiliou, the European Health Commissioner.

“These estimates are based on the international evidence on the level of risk posed by exposure to ETS and the estimated proportion of the population exposed rather than individual cases of deaths due to passive smoking.”

“The nature of the epidemiological evidence on all risk factors, be they chemical or other, is such that it does not allow to identify the victims at individual level but only populations.”

This argument that ETS is a purely theoretical, statistic risk, rather than a real thing that kills real people seems to be borne out by Commission legal during a staff litigation case earlier this year.

Mrs Kay Labate, the widow of a former official Mario Labate, has gone to the European Court of Justice, which has a special tribunal for EU functionaries, to contest the Commission’s refusal to recognise her husband’s lung cancer as an occupational disease.

Mr Labate was an official with the Commission for 29 years, during which time he was exposed to a large amount of second-hand tobacco smoke – before a 2003 (I think) ban on smoking many EC buildings were smoky places.

“He was declared permanently invalid following the discovery of the lung cancer which subsequently led to his death. He submitted a request for recognition of the illness as an occupational disease,” reads an ECJ paper.

Here is the conclusion from the European Commission’s in-house medics:

“While acknowledging Mr Labate’s exposure to second hand tobacco smoke and finding no other cause for his lung cancer, the Medical Committee in its decision nonetheless stated that it could not establish with certainty the connection with his professional activities.”

“The Commission accordingly denied the request, following the finding by the Medical Committee that the connection between the disease and Mr Labate’s professional activities was not sufficiently established.”

And, thus the judgement from the EU court tribunal: “The claims for compensation… by Mrs Labate are dismissed as manifestly unfounded”.

The Commission, of course, is a supporter of mandatory workplace smoking bans (that means pubs, bars and restaurants) across the EU on the basis that ETS kills 79,000 people every year.

Unlike the statistic, which is a theoretical risk, the bans (and the intolerance that often accompanies them) are all too real. This does not seem quite right to me.

I have asked the Commission to explain and the response will follow. Can anyone point me to a case of someone who has died from ETS, as opposed to people who have won compensation for bronchial irritation or asthma?

Presenting Beneficial Data – a Method for Researchers

If a researcher finds data that might prove a benefit from smoking, there does appear to be a way to have this published. The format is as follows. Disparage the benefits you are going to announce in the title of the paper. Start the paper with a loud condemnation of smoking and its hazards. Then present the positive benefits discovered. Finally finish with another clear statement of the harmfulness of tobacco and rubbish some of the findings you just announced. A good example of this format is found in this study by Dr John A. Baron titled “Beneficial effects of nicotine and cigarette smoking: the real, the possible and the spurious“. Once you have laid this foundation, you can present your findings in relative safety. Here are Baron’s findings:

Preliminary data suggest that there may be inverse associations of smoking with uterine fibroids and endometriosis, and protective effects on hypertensive disorders and vomiting of pregnancy are likely. Smoking has consistently been found to be inversely related to the risk of endometrial cancer, but cancers of the breast and colon seem unrelated to smoking.

Inverse associations with venous thrombosis and fatality after myocardial infarction are probably not causal, but indications of benefits with regard to recurrent aphthous ulcers, ulcerative colitis, and control of body weight may well reflect a genuine benefit. Evidence is growing that cigarette smoking and nicotine may prevent or ameliorate Parkinson’s disease, and could do so in Alzheimer’s dementia.

A variety of mechanisms for potentially beneficial effects of smoking have been proposed, but three predominate: the anti-estrogenic effects of smoking; alterations in prostaglandin production; and stimulation of nicotinic cholinergic receptors in the central nervous system.

Research Funding Sources

It is enlightening to locate the source of research funds for tobacco research. Aside from being funded by our tax dollars in the form of large grants, one of the largest funding sources worldwide is the Robert Wood Johnston Foundation:

Endowed by pharmaceutical giant Johnson and Johnson, the foundation is in the business of pushing pharmaceutical nicotine. Its lobbying activities include state-funded smoking cessation programs where nicotine delivery devices are recommended. The foundation is also active in imposing smoking bans designed to compel cigarette smokers to quit smoking tobacco.

When these components are in place the Foundation reaps its financial rewards. Owning about 72,600,000 shares of Johnson and Johnson, the nicotine delivery device manufacturer, RWJF makes money every time anti-tobacco legislation is enacted. Terms of the tobacco settlement will be very kind to the pharmaceutical nicotine industry as this story makes clear. Johnson & Johnson donates some nicotine devices that haven’t sold well, takes a tax deduction, all the while getting its foot into the multibillion $ smoking cessation business in Minnesota. Now that the settlement is national, Johnson & Johnson and its non-profit Foundation are sitting mighty pretty.

All of the major pharmaceutical companies contribute research dollars to anti-smoking research and activities, in the name of promoting health in our communities. Altruism? Everything these companies do is focused on increasing their revenues and profits, and they see huge profits in anti-smoking products.

Hypocrisy

The rampant hypocrisy of the scientific community becomes evident when we note that ANY research funded by the tobacco industry is immediately denigrated as biased and thereby worthless. (The research published by James Engstrom discussed above is in this category as Engstrom had to gain funds from the industry when his original sources dried up). Yet we have virtually all the anti-smoking research being funded by pharmaceutical companies with a vested interest in the sale of nicotine and smoking-cessation products and drugs. A case of the pot calling the kettle black?

Public Health Data on Smoking-Related Deaths

If you accepted at face value the data presented by governments, health institutions and organisations like the CDC and the WHO on tobacco-related mortality, you would be forgiven for thinking that there is indeed an epidemic caused by smoking. And if you assumed these numbers were real, counted from death certificates and from mortality data specifically for your country, so you could have some confidence in their accuracy, you would be sadly mistaken. That is not how the public health bureaucrats calculate tobacco-related death data.

How do the Public Health bureaucrats estimate these death rates? According to this study, there are a number of different methods, so you can take your choice:

One of the most important measures for ascertaining the impact of tobacco is the estimation of the mortality attributable to its use.

So the most important measure of the impact of tobacco is NOT how many people actually die from disease attributable to tobacco; it’s based on an estimation of that mortality.

It seems there are a number of different methods, and they all give different answers. A quote from the same study has this to say:

The variations can be attributed to methodological differences and to different estimates of the main tobacco-related illnesses and tobacco prevalence. All methods show limitations of one type or another, yet there is no consensus as to which furnishes the best information.

This excerpt is from a study entitled “Mortality attributable to tobacco: review of different methods“. It is quite revealing, as the text swerves from stating categorical “facts about smoking mortality”, to a multi-paragraph discussion on the limitations of the different methods used:

Our review shows that mortality from smoking varied greatly among different countries (from 8% in South Africa to 25% in Hong Kong). Smoking Attributable Mortality (SAM) is highly concentrated among men (33% in Hong Kong and 22.2% in Taiwan) . A comparison between the results that Ezzati and Lopez and Ezzati et al. reported for SAM% with those from studies that use a more uniform methodology shows that the general mortality rate (18% – 23%) was higher for the world and for developed countries in the former studies.

Although it is very difficult to generalize about developing countries as there are huge variations in the smoking epidemic determined by diverse demographics and economic and cultural determinants. First, mortality attributable to smoking in these regions is highly concentrated among men (84% of smoking-attributable deaths). Smoking killed three times as many men as women in industrialized countries and almost seven times as many in developing countries. Second, compared with industrialized countries, developing countries have a higher proportion of SAM at age 30 to 69 (62% in less-developed countries, compared with 49% in industrialized nations) . The tobacco related illnesses that most contribute towards the SAM in developing countries were cancer of the trachea/ bronchial/ lungs, ischemic heart disease, COPD and cerebrovascular diseases. Ezzati and Lopez also found cardiovascular disease, COPD and lung cancer to be the three principal causes of smoking related deaths in developed and developing countries in the year 2000.

These first paragraphs contain the “facts” that the researcher has gleaned from the study. Notice how concrete the statements are. No doubts there. But then he goes on the describe 4 serious limitations in the methodology behind these calculations, calculations which provided those so-called concrete facts just presented.

The first limitation affecting comparison of the cited studies stems from the use of a different methodological approach in the various studies. The studies reviewed here are quite heterogeneous in many aspects: the method for calculating the attributable fraction, the inclusion or not of certain tobacco-related diseases in adults or children, the age range considered, the inclusion of death by burning, passive smoking and the application of the current prevalence to calculate the SAM. All these factors influence the results of the attributable mortality.

The second limitation resides in the absence of a universal definition of the categorization of tobacco use. To view smokers as a single entity could lead to a distorted mortality estimate, since failure to take account of the number of cigarettes smoked, age at initiation and years of smoking.

The third limitation, present mainly in the prevalence based methods, centres on their reliance on current smoking prevalence’s to reflect mortality occasioned by tobacco use in previous years. Knowing current smoking prevalence could be a great help when it comes to predicting future mortality, it might fail however with respect to the present mortality. The use of current prevalence may overestimate or underestimate the attributable mortality. In countries where the prevalence is decreasing, the use of current prevalence is conservative in the proportional attribution method. In Israel, where tobacco use has been decreasing for several decades, using a lagged approach – which took into account the fact that smoking rates between 1959 and 2003 contribute to SAM in 2003, due to lag factors – produced a SAM overestimate of 50% on the SAMMEC categories. The opposite in countries where prevalence is increasing. As yet, this problem has no easy solution, due to the absence of historical series of smoking prevalence in most countries.

Peto et al. avoided the problem entailed in prevalence dependent methods of attribution. For the application of their estimation procedure, lacks of knowledge of the tobacco consumption or latency and induction periods are no limitations. Smoking impact ratio method defined synthetic prevalence as an indicator that summarizes a population’s smoking history, and calculate it by assuming CPS II data on lung cancer mortality rates among smokers and non-smokers to be valid. The use of these two sets of data gave rise to numerous criticisms especially representativeness of the CPS population. Most of the population included in this cohort study was middle class, which may result in lung cancer mortality in non-smokers being underestimated, which in turn may lead to an overestimation of lung cancer mortality attributable to tobacco use and, by extension, to an overestimation of the summarized prevalence.

Possibilities of confounding are also not properly taken into account by the fact that smoker/non-smoker relative risks for diseases other than lung cancer are estimated from unadjusted CPS II data and assumed to apply to countries with a very different distribution of risk factor exposure than the CPS II population, a population which is not even representative of the United States. The method implausibly assumes that lung cancer rates in lifelong non-smokers do not vary by country and by year, thus ignoring possible diseases are unlikely to be representative, in terms of effects of other risk factors.

The fourth limitation centres on the absence of world-wide risk indicators that would reflect the degree of association between tobacco and smoking related-causes of mortality. Although drawn from different sources, the RRs used in the various studies mainly came from the CPS II. Applying these risks to populations other than that of the USA aroused criticism. A solution to these problems was sought through a re-analysis of the data, and the RRs were shown robust. The absence of a simulation study involving and comparing all calculations procedures do not allow us to recommend a method over other one. Data availability should be taken into account when choosing a method. These types of methods furnish estimates that constitute valuable information and help forming a more accurate picture of the problem that smoking poses to world health.

How could anybody could place their trust in the mortality figures produced using these methods? Far from having factual numbers available from an actual headcount, we are served up mortality numbers which are as good as grasped from thin air, numbers that even the researchers admit have produced results even they think are a 50% overestimation.

On this McMillan-Org pamphlet, the first sentence tells us, “There are now an estimated 2.5 million people living with cancer in the UK, rising to 4 million by 2030”. And that is the last reference to estimates. From this point on the brochure reels off death numbers and cancer numbers as if they are facts. And they are not. At best they are educated guesses.

On the New Zealand Government Department of Heath website we see: “Make no mistake tobacco is a highly addictive substance that is claiming the lives of approximately 5000 New Zealanders every year.” Approximately? That’s because it is a best guess estimate.

On the CDC website:

Cigarette smoking causes about one of every five deaths in the United States each year. Cigarette smoking is estimated to cause the following:

More than 480,000 deaths annually (including deaths from second-hand smoke)

278,544 deaths annually among men (including deaths from second-hand smoke)

201,773 deaths annually among women (including deaths from second-hand smoke)

No death certificates stating smoking or secondhand smoking as the cause of death; no accurate count of who actually dies from what and no credible attempt to actually validate how many people die from a particular disease – it’s all “lies, damn lies and statistics”.

This is an article from the FORCES Italian website which really puts the mortality data our governments and Health Departments use into perspective.

‘Not 1 Death or Sickness Etiologically Assigned to Tobacco’

Below is English Translation of the Explanation/Statement by Dr. Tulio Simoncini, MD, Head of FORCES Italiana

To understand it fully, one does not have to be a physician. All the diseases attributed to smoking are also present in non smokers. It means, in other words, that they are multi-factorial, that is, the result of the interaction of tens, hundreds, sometimes thousands of factors, either known or suspected contributors – of which smoking can be one.

Now, follow this:

if I have 2 factors, the way they can possibly combine is 22 – 1 = 3; three factors, 23 – 1 = 7; ten factors, 210 – 1 = 1,023. Among the factors are genetic makeup, environment, diet, amount of tobacco in function of the specific health condition of that life period, stress, and so on, and so on.

Cardiovascular disease has over 300 known factors interacting; lung cancer over 40. Never mind calculating 2300 – 1! Now, to sort them out, there is a primitive tool that really works poorly, called multi-factorial epidemiology; its job is to try to isolate the cause, which is impossible.

Since the antis are stating with great certainty that primary smoke “causes,” or passive smoke “causes”… The question asks, simply, to find one human being where tobacco can be proven to be the sole cause (etios) of his/her disease (pathos; etiopathology = the cause of the disease), that is, to be sure that tobacco did it. Mono-causality is the only way to be sure. Since the only possible answer is “no,” the question that follows is: “Then, if you cannot even prove your claims for ONE among the millions you claim die (or are sick) from smoking, how can you be sure that tobacco does it?”

The con work of the anti-smokers is on the ignorance of people. Epidemiology has defeated many diseases: small pox, TB (almost) etc, and it has helped to keep track of stuff like Ebola and AIDS. But those diseases are MONOFACTORIAL: one cause, one effect. People do not know that ALL “tobacco-related diseases” are multi-factorial in the extreme, and believe that the same epidemiology that has worked for small pox is at work for smoking. This is not to say that smoking does not cause disease: it probably does; we just cannot say how much. It follows that all the figures we hear are fantasy and wild guess game, right?

True, medicine cannot be an exact science – and no one expects it to be. But, given the size of the claims, one would expect that one case in, say, 10 millions could be certified simply by random chance! But it is not so, and if you really think about the little formula above, you can see why. Imagine a roulette with 300 numbers: what are your chances to hit the zero? (try asthma: thousands of continuously changing co-factors, and they blame passive smoke!) That is why the porno-pictures you see on your packs are real, but the chances that that stroke you see in the picture, for example, is actually caused by smoking are infinitesimal – although, technically, the possibility that it is due to smoking is real.

And this is for DIRECT smoking; in passive smoke, well, the possibility of isolating a mono-factorial etipathology is probably one in more than all the stars in the cosmos, which are more than all the grains of sand on all the beaches of the earth.

I hope I have been exhaustive enough. If there are further questions, do not hesitate to ask; if I don’t have the answer, I will find it; and if there is no answer, differently than the anti-smokers, I’ll say that “I don’t know!”

Research Data Can Mean Different Things to Different Lobbies

When anti-smokers talk about the 4,000 chemicals in tobacco smoke, which are in fact the products of the combustion of plant material, they invariably zero in on a few of their favourite toxins. One of the most popular is formaldehyde, which is a toxin and an irritant. In this particular document, formaldehyde is described as “a substance used in preservation of laboratory specimens”. In reference to tobacco smoking, we are just told that formaldehyde is a toxin and a carcinogen, and one of the reasons tobacco smoke is so deadly. Yet one of the premises of chemical toxicity is that “the dose makes the poison”. So dose really matters. And it is really hard to find data on the calculated dose in tobacco smoke in reference to these 4,000 chemicals.

One study I found suggested (yes, it is that tentative) that the amount of formaldehyde from a 20-pack of cigarettes smoked inside in 30 minutes (these guys are real puffers) ranged from 188 to 2,382 micrograms. Remember, a microgram is one millionth of a gram.

Another document I located tells the following about formaldehyde:

Formaldehyde is a simple but ubiquitous chemical compound made of hydrogen, oxygen and carbon, with the formula CH2O. All organic life forms – bacteria, plants, fish, animals and humans – naturally produce formaldehyde as a consequence of the processes in cell metabolism. Formaldehyde is naturally present in fruits, vegetables, meats, fish, coffee, and alcoholic beverages. Most formaldehyde inhaled by humans is quickly exhaled. The relatively small amounts of formaldehyde that remain in the nose and upper respiratory tract are swiftly metabolized into harmless products. Thus, formaldehyde does not accumulate in animals or people because it is quickly broken down in the nose by the body’s natural metabolic processes. In the environment, formaldehyde is quickly broken down by sunlight in the air or by bacteria present in soil or water.

Hold on a minute! The anti-smokers are telling me this is a toxin and a carcinogen, but this document says it occurs naturally and passes quickly from the body. Then it goes on to say:

Formaldehyde is produced naturally by our bodies, is found in all cells and is a normal component of human blood. In fact, formaldehyde is an essential chemical in the body and serves as a building block for the biosynthesis of more complicated molecules. Formaldehyde is one of the most studied chemicals in use today. Studies in rats, monkeys, and humans show that inhaled formaldehyde does not change the levels of formaldehyde normally present in the blood.

So, here is the thing. If you are an anti-tobacco activist, the smallest amount of formaldehyde in cigarette smoke is a toxin and carcinogenic, a very good reason not to smoke, and the reason why you are killing your neighbours with your secondhand smoke. Yet the above quote says that inhaled formaldehyde does not change the level of formaldehyde in the blood. Who do we believe?

But, if I am pro-vaccine (another mainstream, therefore safe, position to take), then “quantities of formaldehyde at least 600 times more than the amount contained in vaccines (.2mg on average in a vaccine) have been given safely to animals”. So again, it is only large doses we have to worry about.

And if I am an operator of a waste disposal plant in Harlem which has been spewing emissions including formaldehyde for weeks, then:

In low doses, the smelly chemical, which results from incomplete combustion of sewage gas, does not pose a public health risk, officials said.

“A person would need to be consistently exposed to elevated levels for an entire lifetime — 70 years — just to have a one in a million chance of becoming sick,” said city Department of Environmental Protection spokesman Eric Landau.

The same science produces vastly different outcomes, depending what the user is looking to accomplish.

Yet, this cannot be the case. Either formaldehyde in small doses is harmful, as the public health bureaucrats imply or insist, or it is not. It can’t be harmful in cigarettes but not in vaccines and waste plant emissions. Yet both positions are represented as scientifically proven.

Is the Anti-Smoking Lobby a Religion?

A case could be made that the anti-smoking movement is a religion with its own belief system. That belief system is that tobacco smoking is harmful, and that doctrine is held regardless of the evidence. Note this reference from a review called “Tobacco Smoke Carcinogens and Lung Cancer“: “Moreover, exposure to environmental tobacco smoke (ETS) is widely accepted as a cause of lung cancer, although the risk is far lower than that of smoking and can be difficult to demonstrate, even in large studies”.

We cannot prove it but we know it must be true. And this from the same report:

Even in the writings of distinguished scientists with great expertise in cancer causes and mechanisms, one can read statements such as: “The carcinogenic mechanisms of tobacco smoking are not well understood.” And this “While it is true that we may never be able to map each detail of the complex process by which cigarette smoking causes lung cancer and that there is unlikely to be a single mechanism of tobacco carcinogenesis, there are general principles that have emerged from intensive research in the past four to five decades.”

And final quote from that document, to illustrate their mindset: “Nicotine addiction is the reason that people continue to smoke”.

No possibility exists in their minds that people might smoke because they enjoy it and gain significant benefits from so doing. Anti-smokers do not like smoking and they have relentlessly bombarded the population with anti-smoking propaganda that says we need to quit for our health’s sake, so how could anybody else possibly do it for relaxation and pleasure? It must be addiction.

Further evidence for the movement being a religion is that the anti-smoking lobbyists are never swayed by data that contradicts their doctrine. They rubbish it, ignore it or, if they get the chance, suppress it. Or they make up stuff. For example a quote from Forbes magazine in regard to yet another research paper that found no causal link between secondhand smoking and cancer had this to say: “The study doesn’t cover the many other ill effects of breathing somebody else’s cigarette smoke, of course, which include asthma and possibly cardio-pulmonary disease.” All unproven of course, but if you say it often enough, people will believe it.

And the ultimate goal of tobacco control tactics: “The strongest reason to avoid passive cigarette smoke is to change societal behaviour: to not live in a society where smoking is a norm.”

Conclusion

It is unfortunate that so much of the research published today does not conform to the scientific method. It can be justifiably labelled” junk science”, research that cannot be relied upon. And if there was hope that epidemiologists might change their modus operandi, this article from 1997 indicates otherwise:

An estimated 300 attendees a recent meeting of the American College of Epidemiology voted approximately 2 to 1 to keep doing junk science!

Specifically, the attending epidemiologists voted against a motion proposed in an Oxford-style debate that “risk factor” epidemiology is placing the field of epidemiology at risk of losing its credibility.

Risk factor epidemiology focuses on specific cause-and-effect relationships–like heavy coffee drinking increases heart attack risk. A different approach to epidemiology might take a broader perspective–placing heart attack risk in the context of more than just one risk factor, including social factors.

Risk factor epidemiology is nothing more than a perpetual junk science machine.

But as NIEHS epidemiologist Marilyn Tseng said “It’s hard to be an epidemiologist and vote that what most of us are doing is actually harmful to epidemiology.”

But who really cares about what they’re doing to epidemiology. I thought it was public health that mattered!

Finally, this article from 2005 was written by a prominent epidemiologist, Dr. John P. Ioannidis, in which he comments on the state of the science, much to the chagrin of his colleagues. He begins with this comment: “There is increasing concern that most published research findings are false.” The article succinctly addresses the many areas in modern research with which he has difficulty. The following excerpt lists the interesting corollaries he outlines regarding the probability that research finding is (un)true:

Corollary 1: The smaller the studies conducted in a scientific field, the less likely the research findings are to be true. …

Corollary 2: The smaller the effect sizes in a scientific field, the less likely the research findings are to be true. … Modern epidemiology is increasingly obliged to target smaller effect size. Consequently, the proportion of true research findings is expected to decrease. …

Corollary 3: The greater the number and the lesser the selection of tested relationships in a scientific field, the less likely the research findings are to be true. …

Corollary 4: The greater the flexibility in designs, definitions, outcomes, and analytical modes in a scientific field, the less likely the research findings are to be true. … even in the most stringent research designs, bias seems to be a major problem. For example, there is strong evidence that selective outcome reporting, with manipulation of the outcomes and analyses reported, is a common problem even for randomized trails. …

Corollary 5: The greater the financial and other interests and prejudices in a scientific field, the less likely the research findings are to be true. … Conflicts of interest are very common in biomedical research, and typically they are inadequately and sparsely reported. Prejudice may not necessarily have financial roots. Scientists in a given field may be prejudiced purely because of their belief in a scientific theory or commitment to their own findings. Many otherwise seemingly independent, university-based studies may be conducted for no other reason than to give physicians and researchers qualifications for promotion or tenure. Such nonfinancial conflicts may also lead to distorted reported results and interpretations. Prestigious investigators may suppress via the peer review process the appearance and dissemination of findings that refute their findings, thus condemning their field to perpetuate false dogma. Empirical evidence on expert opinion shows that it is extremely unreliable.

Corollary 6: The hotter a scientific field (with more scientific teams involved), the less likely the research findings are to be true. … With many teams working on the same field and with massive experimental data being produced, timing is of the essence in beating competition. Thus, each team may prioritize on pursuing and disseminating its most impressive “positive” results. “Negative” results may become attractive for dissemination only if some other team has found a “positive” association on the same question. In that case, it may be attractive to refute a claim made in some prestigious journal. …

These corollaries consider each factor separately, but these factors often influence each other. For example, investigators working in fields where true effect sizes are perceived to be small may be more likely to perform large studies than investigators working in fields where true effect sizes are perceived to be large. Or prejudice may prevail in a hot scientific field, further undermining the predictive value of its research findings. Highly prejudiced stakeholders may even create a barrier that aborts efforts at obtaining and disseminating opposing results. Conversely, the fact that a field is hot or has strong invested interests may sometimes promote larger studies and improved standards of research, enhancing the predictive value of its research findings. Or massive discovery-oriented testing may result in such a large yield of significant relationships that investigators have enough to report and search further and thus refrain from data dredging and manipulation.

The science behind the anti-smoking movement is not as strong as it is made to appear. The correlations between smoking and disease are just that: correlations. In their more candid moments, researchers will admit that they do not really understand the causal mechanisms involved, if they even exist in the first place. Smoking may be a factor in the development of certain diseases, but at the current level of science involved, we simply don’t know. There could very well be other un-researched that account for the statistics. But that doesn’t stop them and those who stand to gain from trumpeting the results as solid, even to the point of massive social-engineering policies and media campaigns on the “known” risks of smoking. Even with the best of intentions, which are often lacking, this is simply irresponsible science.

About the Author

Gordon Vick is a retired IT Sales Director who lives with his wife in rural New Zealand. In addition to independent research, his favourite activities include eating bacon and pipe smoking.