by Carl V Phillips
Tomorrow a new paper about the supposed gateway effect from e-cigarettes will come out of “embargo”. Over the last few days, Clive Bates and Michael Siegel have published pre-rebuttals of it (Clive basically declared as much on Twitter. Mike did not, but the timing seems like more than coincidence.) Sometime I will analyze the paper based on the framework I developed for assessing whether evidence actually supports a gateway claim (which the authors of the paper ignored). For now it is interesting to go meta.
[Note: Please don’t mistake my delay as indicating any respect for the press release and embargo game, which is antithetical to proper science. That game, in turn, is a mere sequela of much more fundamental anti-science problems in health research. In particular that is the notion that it is ever proper science for journals to publish papers that have not been reviewed by the scientific community, and have been read by less than ten people ever. Anyone who complains about the press release and embargo game while accepting the latter just doesn’t understand what the real problems are. Another reason for the delay is that as a student of scientific and quasi-scientific debates themselves, I am curious to see what others are saying so I can analyze that also. That is what I am doing here.]
Clive’s post is entitled “How not to be duped by gateway effect claims”. I find that interesting because I am increasingly inclined to wonder if e-cigarette advocates have been very effectively duped into taking a tact that concedes the most important points, and sets up inevitable success for those attacking e-cigarettes with gateway claims.
For those who may not know, the claim out there is that some empirical evidence suggests that e-cigarette use is causing some people (the focus is on kids) who would not have otherwise smoked to become smokers. My methodology paper explains how to analyze whether that is really the case. All the supposed empirical support for the claim, it turns out, fails to meet some very basic minimal conditions for supporting the claim. Statements that there is evidence of a gateway effect are inevitably followed by pronouncements that, therefore, severe restrictions on e-cigarettes should be enacted. The missing steps in between the empirical claim and the policy demand are what e-cigarette advocates may be conceding when they respond to the empirical claims with some shadow of the analysis of methods that I presented in my paper. (Note that my paper did not address the missing steps either; it was explicitly about empirical methodology.)
Consider the first of the nine points that Clive argues in his post: “Is it clear what is meant by a gateway effect?” This appears to derive from my work, since I have been the one pushing that point and Clive cites me. He picks up on one of the three key points I make about meaning, that the jargon “gateway” clearly refers to the causation I described it in the previous paragraph. Some authors play a game of observing mere association of the behaviors, perhaps with the “right” order, with no analysis to try to sort out whether that is really causal, but then suggest the implications are those of having supported a causal claim. Clive offers a brief summary of the association-vs-causation point in his sixth point and the ordinality point in his third point. You can find greater depth on these points in my paper, but his summaries are just fine.
But one of the points missing from this version of “what is meant”, something I discuss in my paper, is quantification. Those making the gateway claim never (as far as I recall seeing) explain what magnitude of effect they are claiming. This is probably as much a result of the faulty thinking that permeates public health (using methods that are all about measuring quantities, but reporting results as if the dichotomy effect-vs-not is what matters) as it is an intentional tactic in this case. But it is a very effective way to trick readers into thinking that any evidence of any effect is tantamount to evidence of a large effect. Is there any gateway effect? Of course there is. Even though the gateway claim is scientifically extraordinary claim (as I discuss in my paper, and below), millions of nonsmokers have tried e-cigarettes and tens of millions more will. The chance that not even one, among those who would not have otherwise become a smoker, becomes a smoker as a result of e-cigarettes is basically nil.
Those arguing against gateway claims have inadvertently drawn their line of defense at the “this is not happening at all” point. This sets them up for defeat when any evidence is widely interpreted as suggesting there is any gateway effect. This might include those statistical claims that are critically analyzed on their merits as science (as they certainly should be — as I said, that is the point of my paper), but it might also be some ginned-up artificial clinical study or a testimonial from someone who claims the gateway happened to him (as I noted in my paper, there is no such testimonial out there, not even one, but there will be eventually). After all, there are going to be some gateway cases.
That brings up the second and even more important layer of the tactical error, ignoring the missing steps in between “there is a gateway effect” and “therefore we should do X.” Tobacco control has achieved enormous success through the tactic of getting others to buy into an explicit claim of “if any bad outcome happens at all, then any policy to stop it is justified.” See, e.g., smoking place bans. I do not have to tell readers of this blog that there are numerous arguments that can be made in that gap. But if they are not made as a matter of habit whenever that gap in instrumental in a discussion, the leap over the gap will win the day by default.
There is one particularly easy gap-challenging argument in this case, which avoids the need to appeal to pesky issues like ethics and policy analysis: If the number of gateway cases is less than the number of people in the same population who quit or avoid smoking as a result of e-cigarettes, then the net population effect is less smoking. This can be argued at the level of a particular subpopulation, such new cohorts that are coming of age, even apart from the cessation effects among established smokers. This challenges the tobacco control’s gap-based claim on its own terms, which measure outcomes merely in terms of caused change in smoking prevalence (though it is still probably a tactical error to concede that those terms are legitimate). This is probably why even the pro-ecig tobacco controllers sort of try to endorse this argument. However, they do a mindbogglingly bad job of it. They walk right up to it and then fail to make the point, claiming something that is patently wrong instead.
For example, Siegel’s thesis is that because smoking is declining in teenage population as e-cigarette use is increasing, there is no gateway effect. Nononono. This junk claim, which he and others have repeatedly made before, is simply false. There are several possible scenarios that are compatible with a gateway effect and the observed pattern. The most obvious is the aforementioned point that e-cigarettes are causing a net decrease in smoking even if they are causing some smoking. This is not, however, what is actually claimed. Rather, the common claim is that the net trend means there is no causation in the other direction, which is obviously false. Even Clive comes very close to saying this in his second point.
Of course, it is not the case that e-cigarettes are causing all of the decline in smoking among teenagers, or even all the dip below the trend, and there is not exactly overwhelming evidence they are causing any of it. The aggressive assertion that this association is causation, by those who have no support for it other than liking the conclusion, is a page straight out of the tobacco control playbook. It is interesting to consider one of the other stories for why there might be even a big gateway effect in spite of these statistics: The gateway claim could be that over the course of five years, a lot of people who became vapers at age 17 become smokers. (This is another element that is missing from the simplest “what is meant by gateway” claims: timing.) Indeed, it is not difficult to imagine the tobacco controllers arranging for the an upcoming official claim about a new increase in teen smoking rates (even just a return to trend from the extremely low — and thus probably downward biased — recent claims). Then they all cry, “see there is the gateway effect starting to appear.” They would not be obviously wrong. Live by unsupported claims of causation based on very crude population statistics, die by….
One additional neglected point within that conceded gap is the question of the evidence that a particular policy would actually have the intended result, and its other effects are ethically acceptable. Again, the problem is that “this phenomenon does not exist” arguments that are presented without the accompanying “even if [or though] there are gateway cases, that does not mean…” are a massive concession. So long as pro-ecig tobacco controllers dominate the responses, it seems safe to assume this will continue to happen. In most of what they do, they depend on no one noticing the missing arguments in the gap, and are not about to risk weakening their primary weapons for this side-battle.
A few other technical points are interesting. In his fifth point, Clive implies that if we do not know how many of the teenage vapers in the study used nicotine — many do not — then that is a problem. I cannot imagine why. If the empirical results actually did support the claim that vaping causes smoking, why would it matter? There are other mechanisms than acquiring a taste for nicotine that could be causing it. After all, isn’t the claim that e-cigarettes are so good a substitute for smoking because they mimic the feel and action of smoking? So why would we assume that if there were a gateway effect, it was not caused by those.
Moreover, consider what would happen if there really is a gateway effect, and it only occurs among those vaping nicotine. Imagine some hypothetical empirical result that genuinely supported the gateway claim, but it did not differentiate between vapers who used nicotine and not. Then the true gateway effect would be greater the estimated magnitude. The result would be attenuated by counting among in the exposed population some people who did not actually have the relevant exposure. Similarly in his fourth point, Clive suggests that poor measures of vaping and smoking status should cause us to doubt the claim. But if the measure of vaping was “ever tried one puff” and the study showed a gateway effect (again: hypothetically, genuinely), then the result would probably be attenuated for actual vapers (assuming that the effect only manifested after some quantity of vaping rather than one puff). On the other hand, if the measure of taking up smoking were similarly overly expansive, then the quantitative result would be biased upward: more people would be identified as gateway cases of actual smoking (rather than just trying a puff of a cigarette) than actually were. On the other hand, if a study showed an effect based on that expansive definition, they it would almost certainly mean there was some real gateway effect; it is difficult to imagine something that increased the trying of cigarettes that did not increase the probability of some of those trialers becoming smokers.
The point is here is that if you are going to try to analyze what the statistics actually mean, it is more complicated than just saying “they are not the best possible measures and therefore the result is not right.”
A final observation in this disjoint collection: In my analyses, I have emphasized the extraordinary nature of the gateway claim. I explain it more in my paper, but basically the issue is why would someone using a low-risk product, someone who would not have otherwise used the high-risk product, ever want to switch to the high-risk product? It is such an odd and unnatural behavior pattern that it would take extremely compelling evidence to legitimately overcome the doubt we should have about it occurring. (Which is to say, occurring much; as noted, given millions of chances, many very odd things will happen at least once.) However, I may have overstated this logic by not making clear it applies to people who have happily settled in to using the low-risk product. It does not necessarily describe someone who just tries the low-risk tobacco product and is enamoured with it but finds it unsatisfying and so shops around other options.
This scenario is interesting because it could mean that there is substantial gateway from the state “trying e-cigarettes and not adopting them” even when there is no measurable gateway from actually being a vaper. It would also mean that the gateway was caused by the fact that in the absence of e-cigarettes this individual would have remained ignorant of the fact that he really liked smoking — as opposed to being someone who would genuinely not want to smoke, and was made to want to smoke by using another product.
It is an interesting scientific question. Anyone who bristles at the presentation of the interesting question should probably just stay away from analyzing the science, since his interest is issue activism and not science. That is a valid role to adopt, of course, but if that is the chosen role, it might be wiser to focus on core arguments that live in that gap rather than fiddly scientific points. One more of those core arguments follows immediately from this interesting scientific question, by the way: In that story, stumbling upon the gateway and discovering the joy of smoking made this individual better off. Indeed, it is difficult to imagine any gateway case who is not made better off, since they still have the option of sticking with the low-risk product unless they like smoking a lot better. So a question to put in the unexamined missing steps is, “what business does anyone else have declaring that this individual should be denied the chance to make that choice?”
The gateway claim is indeed quantitative. If ecigs cause net public health harm, there must be, in the long run, at least as many gateway cases as there are quits caused by ecigs. This means (unless we assume absurd time lags of ten years or so), that there are millions of gateway victims already out in the population. This makes the complete absence of any real-world cases very powerful. There could be few dozen cases hidden in the population, but it is totally impossible that millions of people experience a profound change in their lives and they leave absolutely no trace. Even if they were sworn to secrecy, someone would talk.
We just have to be careful not to draw the wrong conclusions. The absence of any observation doesn’t mean that no-one could be gatewayed, ever. That would indeed be unwarranted and blown apart by the first testimonial. It does mean, however, that it does not happen in a magnitude that would be meaningful at the population level. This wouldn’t change even if some testimonial or medical case should surface. It would still be a rather exotic phenomenon.
I totally agree that the safe bet is that the phenomenon is and will remain exotic. It is utterly unimaginable that the gateway cases could outnumber the quitters in the population as a whole, at least if we are not counting across decades of future. Someone could argue that a net increase in smoking in some subpopulation (e.g., those born in 2001) is bad, despite the population effects overall. Saying that warrants a police (not a typo) response, however, is a big claim inside that gap. I cannot see a remotely defensible case for anything that is not perfectly targeted at the righ birth cohort based on that, even setting aside the cases against any punitive or anti-freedom restrictions.
One thing to keep in mind, that I did not take the words to go into in the post, is that once the “natural” rate of smoking is low enough, then (for a cohort) the gateway effect could exceed the prevention/quitting effect even if it does not do so now. Again, I am not saying this will be the case, but it could be. Imagine the extreme case where smoking has become so unpopular that no one tries it cold, but vaping is so popular that a few leak from it into smoking.
I agree, but I think you need some additional assumptions to get a net population harm from the latter scenario. What you describe is likely a world in which the prevention effect is so strong that smoking has become obsolete in most people’s preferences. Banning the popular vaping alternative would then lead to a surge of smoking.
You implicitly assume a population in which almost all vapers have preferences vaping>abstinence>smoking, but for some people (the gatewayed) these preferences then flip to s>v>a (caused by vaping). Why the preferences flip is another matter, the popular theory is nicotine addiction, which may or may not be true. Banning vaping in this world would lead to a public health benefit if we only consider health as objective (I agree with you that this is ethically indefensible, but for the sake of modelling let’s stick with it). But this benefit only occurs because there is hardly anyone who has preferences v>s>a to start with. If there are sufficiently many people with such preferences vaping would still be net beneficial even in this scenario.
No, the scenario I described simply had interest in smoking fading. This need not be a result of vaping, and was not in my scenario.
I discussed what the preference reversal claims could mean in more detail in my paper (and in previous posts). I am making no assumptions about the population distribution. I am just noting that in the particular cases of gateway effect for someone who is an established user of a low-risk product must have: v≻a, where v can be either vaping or some other low-risk tobacco product usage (because she has been choosing v); a≻s in the absences of v (or else she would not be a gateway case); and, redundantly, v≻s since smoking was always an option but she was not choosing that. The preference change is more than a flip, it is s climbing past a (plausible) but also on up past v which has most of the benefits and little of the cost (not so plausible).
It is trivial arithmetic to map different prevalences of the various static preference orderings into whether eliminating vaping would serve the goal of the public health pseudo-ethic. It could also be done in terms of prevalences for ultimate preferences after vaping changed some preference orderings. That is what we are doing (one piece of) when we say “it is implausible that the population health effects could…” and such. Choosing vaping is basically always beneficial (measured correctly, not just in terms of the pseudo-ethic) for anyone who chooses it — it was a free choice, after all. It is when very many people have the preference v≻a≻s compared to v≻s≻a that this welfare gain can become a loss for the public health pseudo-ethic.
This was exactly the additional assumption I was referring to — the relative rarity of v>s>a types. Wasn’t clear to me that this is what you meant by “low natural smoking rate”. In a world with a lot of v we would have no way to tell how many of those who choose v are s>a or a>s.
It would indeed be trivial to set up a model defining fractions for each type, quit/prevention rates, relative risks, gateway rates, and see how far one has to tweak the parameters to get net public health harm from THR. But it isn’t done. Quite obviously you would have to assume comically implausible parameters to get even close.
I think we are talking past each other to some extent. The low smoking rate I was referring in the scenario did not necessarily have anything to do with vaping. It was just a low population that was at risk for THR switching, and thus could be exceeded by the rate of gateway switching. I was not claiming that that v≻s≻a is a rare state. Indeed, it apparently describes most of the the current vapers. It is true that it is impossible to tell the ordering below the top choice from revealed preference alone.
As for the scenario with more gateway than THR switching, it is not really all that implausible. Consider the low rates of smoking currently claims for teenagers in the USA (or Australia); those claims may be quite wrong, but people are believing them. With that low baseline, the number engaging in THR switching in the short run is going to be very small, seemingly very likely less than one percentage point of the population by the end of adolescents. Now imagine that a third of teens were trialing ecigs and only a few percent of them gatewayed from that to smoking. That is enough for the gateway effect to exceed THR switching. I am not saying any of these inputs are true, of course, but merely that it is not a heroic set of departures from reality.
What about a “gateway” effect in which never-smokers take up vaping but remain vaping without ever going into smoking tobacco cigarettes? I don’t believe such a development is outlandish, weird or utterly unrealistic. In fact, I can recount two separate personal experiences involving acquaintances who saw me vaping (one in my home the other in my office terrace). They became curious about it and wanted to try it. One is an ex-smoker who quit smoking 20 years ago, the other is a never-smoker. Both dislike cigarettes but are not anti-smoking fanatics. I have spare mouthpieces at home and at work. I filled the tank with e-juice without nicotine and lowered the voltage so they would not have to deal with huge vapor clouds. I told them to puff gently without inhaling. Both had initial mild coughs and some discomfort, but after a few puffs they were enjoying the vaping experience. They liked the vapor flowing in their mouth and nose, they liked its pleasant fruit-like smell and taste, they felt no irritation. My acquaintances did not become regular vapers, their experience was just for fun, as a one time tasting of an exotic liqueur, but I believe that at least some long time ex-smokers and never-smokers may find vaping pleasant and may become vapers without ever becoming “gateway-ed” to cigarettes. They key issue, I believe, is to eliminate (or greatly reduce) possible harms and discomfort to the lungs by vaping without inhaling. I doubt this form of vaping would represent a health hazard for non-smokers.
Of course, ideological tobacco controllers would not be happy if large numbers of non-smokers became vapers, even if they are almost only adults and that they never moved to actual tobacco consumption. Contollers and regulators would immediately raise the “protect the children” and the “nicotine addiction” issues. Non-smokers becoming vapers would be for the Glantz-like types a nightmare planned in hell that would make their fears come true: a full “re-normalization” of something that looks like smoking but lacks the hazards (at least as far as we can tell). They will launch a crusade and they have a lot of resources for this. However, if vaping leaves the smoking ghetto and a sufficient critical mass of non-smokers starts vaping perhaps not even mighty Tobacco Control may be able to stop it.
A would-be non-user who takes up vaping is indeed reasonably common. But that is not a gateway case, which specifically includes switching to the harmful products. The whole idea was concocted to come up with some rationalization to object to the use of near-harmless drugs.
The anti-tobacco extremists will strongly object to this, of course, because they object to any use regardless of its consequences. Those who follow the public health pesudo-ethic (which is not any more defensible than tobacco control extremism, just different) will object a little bit because of possible small health risk, but it will not be a big deal according to their personal goal.
I agree with some of these points, particularly the magnitude one, which I’ve now added to my point 1 and had intended to include but forgot. I didn’t have the leisure to do flawless and comprehensive work: this was rushed out to help people interpret the inevitable nonsense that would greet the publication of this study and to try to pre-empt the political impact on Congress that it is blatantly aiming for. Vaping advocates had asked for a reaction, and this was the best I could do at providing an accessible guide (yours isn’t an easy or quick read – which is fine by me, but not for everyone) in the time available and in advance.
Bear in mind many of us are trying to do what we can in this area to make up for the damaging and extreme deficiencies in the self-control and correction mechanisms and incentive structure in the ‘professional’ field of public health. By all means, you can “go meta”, but I think it will change one blood-spattered reputation at a time. I hope you will write concise and devastating PubMed Commons critique of the paper and show us how it should be done.
Well, following you to the meta-meta level: Since you note you have limited calendar and/or person time, why reinvent the wheel every time? Why not take advantage of the careful and deep work others have done (and that in this case, you have contributed to)? I understand that you feel the need to write something shorter and simpler, but why not make it a shadow of the best Platonic version we have, rather than an ad hoc piece with de novo analysis?
Trying to do new analysis under those circumstances is a dicey business, especially if you plan to put it out as the final word to Congress rather than a working sketch. Sticking with the established analysis would avoid the problem of trying to kludge together points like the definitions of use and nicotine claims you made. I am pretty sure you recognized that I was right about those being wrong as soon as you read it. If you stick with things that have been filtered through some peer conversation — I am talking even as little as a single exchange with an expert on the topic — you can avoid a lot of errors that happen when you work in a vacuum. This is true for everyone, including the top experts on something. There is a reasonable chance that your first cut at an idea is not right, but that this becomes obvious to you as soon as someone points it out. You, unlike Siegel who seems to have such a poor understanding of scientific reasoning that nothing gets through to him, pretty much always get something right the second time after it has been discussed. No one gets everything right the first time.
As for “trying to do what we can”, I know that you do not mean that as do the Dunning-Kruger crowd who just attack highfalutin analysis as if it were a distraction from the important work of making more cartoons for social media. But even you seem to be missing the point that perhaps trying to do everything we can might involve trying to get things right and then use that as an anchor, rather than just writing ad hoc. We have good analyses on this point, so why do the “we” in that cling to the utter nonsense that Siegel writes, or the better, but still substantially wrong, comments of McNeill and Hajek. It is pretty clear from their comments that none of them have even read what I have written about this, and perhaps not even your long-form version of the analysis. If this is the “we” you are talking about and their “what we can” does not even include bothering to understand the science when someone has already laid it bare, then I am not really impressed. Apparently it was Really Really Important, and all that, but not important enough to take the time to check it against what I have written or even drop me an email and ask me to look over the draft.
[And, yes, I am saying that I am the first person you would want to ask about it, for this matter and many other social science subtopics in the arena. I know you know that. False modesty is not a useful trait when you are trying to get something done (“no don’t pass the ball to me despite me being the best shooter on the team and wide open”).]
As for PubMed Commons, I am not really convinced that posting there is any more useful than posting elsewhere. It might be, certainly, but I am not convinced. I do know that you can pick only one from “concise” and “devastating” unless there is some utterly glaring error that can be described in a soundbite (which is almost the case here, but not quite).
@ Messrs Phillips, Bates and Siegel.
I read your posts with some astonishment. Each of you is very intelligent and adequately qualified, but you cannot agree the simplest of ‘modi operandii’. (My Latin is rather rusty).
I am an ignoramus, so you will have to allow for that.
Let me get this straight.
In science, the start is at some theory. Is that correct? Erm… No. The start is some observation, which leads to the theory.
Many decades ago, in Germany, pre WW2, the Government of that country decided that smoking was not good for the health fitness of the people. There were connections between that idea in Germany and tobacco prohibition in the USA. We need not go into those connections because they do not matter.
What matters, scientifically, in the first place, is the observation.
The first observation, going right back to King James 1, was that tobacco smoke was obnoxious. We can take that as read. The second observation was that smoking was unhealthy, which we can also take as read. The third observation was that nicotine is addictive.
From the last observation, came the theory/hypothesis: “Smoking tobacco causes addiction to nicotine which is bad” (in addition to to actual physical harm from tar). Where things go wrong scientifically, is when that theory/hypothesise is inverted: “Addiction to nicotine causes smoking which is bad”. There are strange ways in which those sentences can be constructed. It is unclear what is bad. Is it the addiction or the smoking which is bad?
The ‘gateway’ into smoking depends upon the second idea: “Addiction to nicotine causes smoking which is bad”. But that is where things get tricky. As far as I know, there is no evidence that that is true. Certainly, it is said that nicotine gum, patches and inhalers do not cause smoking.
What amazes me is that none of the theories/hypotheses, have been scientifically proven to be true.
Epidemiology is not science. It is mathematics. It is counting. There is no real ’cause and effect’ revealed by such counting. Dr Snow found the ’cause and effect’ regarding Cholera by intuition. The ‘counting’ merely confirmed his intuition.
So you chaps have to get your thoughts together. What you miss, again and again, are timescales. For example, if smoking takes thirty years of more to have a health effect, how many centuries would have to elapse before a human body, assuming that it is still alive, would have to elapse before such a person would become ill or die from second hand smoke?
All of you avoid that question.
Observation and theory in science are usually interleaved — each advances incrementally alongside the other. A lot of ink has been devoted to that. However in this case the issues are not quite either one of those, but of methodology, which might be seen as being somewhere in between, or perhaps the structure that ties the two together. Methodology is about how to properly do or interpret observations, which will almost always be based on some aspect of theory. The reason methodology debates are so poor in health sciences is because even though it is at the heart of science, most epidemiologists have a terrible understanding of the methods of their field, and medics are far worse still.
Anyway, while Clive and I had a debate about time management and use of resources in the comments here, I doubt we disagree on these fairly simple methodologic points. I speculated that he realized I was right about these as soon as he read what I noted. There are others who are not as good at scientific thinking as Clive or I, of course.
Those questions about what is “bad” are ethical questions, not scientific questions. The “moral” bias against smoking undoubtedly increased the impetus to discover the harms it caused. However, the real observational smoking gun was that medics noticed that they went from rarely seeing a case of lung cancer during the course of their career to seeing quite a few of them. Of course today we would strongly suspect that this exposure would cause a lot of disease even before seeing any outcomes because of what we have learned about other exposures and biology (though much of that we learned due to smoking, so there is a bit of a time travel paradox there).
There is no real theory of why a gateway would happen. It is just hand waving. I note that in my paper. Kandel actually offers a theory of why there might be a gateway from any tobacco product to cocaine use — it is silly, but at least it is an attempt at real science. Public health people do not do real science, and have no idea how to think in scientific terms. In turn, most of their critics who do not come from a real science in the first place learn behavior from them, and so are not very good at it either. Otherwise much more of this “debate” would be focused on pushing someone to explain why it is that this supposed gateway would even happen.
Science contains no proof. I try to explain this all the time. I seem to recall writing this in response to you a couple of times. No observation, including of experimental results, ever proves causation or even “shows” it. Causation cannot be observed, only inferred. Different observations offer varying degree of support for a causal conclusion, but there is no observation that can show it, and no relevant observation that offers no information about it. Snow’s observations were a nice natural experiment that were extremely compelling about the clearly-stated hypothesis (not about a particular buggy, of course, but about the cause of the observed disease).
Timing of what is being claimed is often important, which I mention here and will further mention in the follow-ups. What you seem to be talking about is actually the quantity of risk. While we measure that in events per person-years of exposure, the “years” part of that can be misleading. Though it is common dumbsplaining language, it does not make sense to say “you would have to be exposed for 10,000 years…”. No one is exposed for 10K years. If that were to happen, it would clearly not be the same body the whole time (or the same world around it, which matters), so it would still be wrong. It is reasonably sensible to say “for every 200 people exposed throughout their lives, there will be one case”. It is not sensible to say if 10K people were exposed this year, one of them would get it. This is, in part, because timing matters in defining the exposure. It might be, for example, that 1/200 of people are susceptible and if they have the exposure they will get the outcome. In that case, the guy who is exposed for 10K years will (probably) not have the outcome even still. Meanwhile the 10K people exposed for a year will result in 50 cases, not 1. This is seldom discussed in epidemiology because (a) as noted, people working in that area do not think like scientists, properly trying to specify exactly what question they are asking and what claim they are making, and (b) to the extent that some real scientists in the mix recognize that there are interesting questions about how much the dose of exposure matter and does not just average out as if it were an independent dice roll for each year of exposure, the data are inadequate to figure it out. Any particular estimate of the risk from ETS will be expressed in risk (i.e., with person-years as the denominator), and some cut at the dose question can sometimes be teased out of the data. However, since the methods used are so poor (for reasons I discuss elsewhere) and the results so varied, anyone who makes a precise claim about the risk based on available data is simply lying.
Phew! Not quite shot down in flames!
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