All people like better products. Teenagers are people. Therefore….

by Carl V Phillips

So today FDA Commissioner Gottlieb is pumping cigarette company stock prices by threatening to ban flavors in vapor products (or something — not entirely clear), unless the manufacturers magically get teenagers to switch back to smoking instead (or something — not entirely clear). I wanted to address one aspect of this rhetorical game that does not get talked about enough. I doubt there is any serious observer of this space who does not get this, but much of what is said seems to overlook it rather than drilling down to it as it should.

The prohibitionist’s simplest rhetorical game here is to confuse “this product feature is appealing to teenagers” with “this product feature is particularly or uniquely appealing to teenagers.” But there is a deeper game, trying to cement the premise that intentionally lowering product quality is a good thing. This applies not just to interesting flavors of e-liquid, but also everything from attractive packaging to convenient unit quantities. The standard response to the “teenagers like flavors” rhetoric is to counter that adults like them too, and thus they seem to be critical for smoking cessation. Both systematic data and a deluge of testimonials make this point. It is a great point, and those making it are doing a great job.

However, the prohibitionists at FDA and elsewhere are obviously not unaware that adults also like and buy interesting flavors. Similarly, adults and teenagers both like it that e-cigarettes are less than five kilograms and come in colors other than day-glo orange. They like it that they are affordable, that cartridges last for a while, and that the devices do not burn your lips. They like it that there is no regulation that says tobacco products must be smeared with feces before they are packaged. All of these are aspects of product quality. The same features that make a product appealing to people (and thus, the banning of which would make them less appealing to people) make it appealing to teenagers. It turns out that teenagers are very similar to people, and many would argue that they are people. Lower the quality of the product, and fewer teenagers will choose to consume it. Fewer adults too. This works for food, movies, and pens also. There is no magic here.

The magic exists entirely in the rhetoric, in which the prohibitionists trick people into endorsing (or at least not actively pushing back against) their underlying premise: Intentionally lowering product quality is a good thing because it discourages teenage use. Never mind that intentionally lowering people’s welfare is a phenomenally radical action for a government to take, one that ought to be based on a lot of open and honest analysis, not sneaky rhetoric. I find it is a useful clarifying thought to replace whatever quality-lowering regulation is being debated with “mandatory smearing with feces” (assume the feces are sterilized so they are not a health hazard): If it is okay to intentionally lower the product quality by doing X (flavor bans, “plain packs”, punitive taxes, etc.), then it must be okay to mandate feces smears.

Consider the usual scientific response to flavor ban proposals, that there is no evidence that particular flavors or categories are particularly appealing to teenagers. This is accurate; there is no such evidence and no reason to believe it is true. If someone wanted to lower vapor product quality in a way that particularly affected teenagers, perhaps the orange coloration or increased mass options would be the better bet. After all, isn’t the usual claim that teenagers are taking advantage of the products being so subtle that they can hide them from parents and teachers? Adults would not like ugly heavy products, but they could deal with them.

The thing is that FDA et al. are not actually claiming that the flavors are particularly appealing to teenagers, just that they are appealing. This is obviously true (see above observation that teenagers are very much like people). A casual reader might conclude they are claiming that this is a targeted lowering of quality that affects teenagers but not adults. In fact, the serious actors in the space seldom actually claim that, and when they do it seems usually to be a matter of sloppy word choice. They do not actually consider it a problem that a regulation lowers the appeal of a product for everyone (and thus hurts all consumers). To them, this is a feature, not a bug. They want to ruin the products for everyone.

In getting opponents to go along with their fiction that this is not their motive, they win their greatest victory. One of the important skills of a conman like Scott Gottlieb is to get people to adopt his hidden premises without him ever stating them, let alone defending them. When the arguments hinge on “but adults like flavors just as much as teenagers do”, they effectively concede a key prohibitionist premise: If there were a way to intentionally lower product quality, such that it hurt teenage consumers more than adult consumers, then doing it would be fine. Not just fine, but good or even clearly the right thing to do. No doubt there are some vape advocates who accept that, but presumably most are not ready to agree that their e-cigarettes should have to look like traffic cones. But by just fighting the empirical claim (which is not actually even being claimed), they are often implicitly endorsing the normative premise.

Some advocates lead with the message that there are already laws about teenage access and these just need to be enforced. This is good in that it does not endorse the premise that it goes without saying that harming adults for the good of the chiiiildren is  justified (though usually this is not explicitly stated). The problem is that Gottlieb has cleverly turned this on its head, and threatens to hurt adults if they do not somehow better enforce the government’s laws, magically figuring out how to do what the government has never been able to do with cigarettes. Today’s rhetoric was mostly threatening the industry (though it is consumers who would suffer, of course), but he has directed that same demand at vapers themselves. Those who have been tricked into endorsing the underlying premises are cornered by this. They have effectively already conceded that destroying product quality is acceptable if minor bans cannot be enforced.

Advocates need to do a better job of backing a few steps up the prohibitionists’ chain of reasoning, rather than being tricked into conceding so much ground. Every argument should begin with the observation, “this policy is about intentionally harming people (vapers, smokers, other product users).” This should always be pointed out, because in itself that is a radical use of government power that should not pass without comment. It should be followed with a demand for an answer to, “by what right do you harm me/adult consumers/your citizens, even if it is true that this harms others more and harming them is a good thing because it changes their behavior?” Only after making those observations, and trying to never let the audience forget them, is it time to add “discouraging teenage vaping probably encourages teenage smoking”, “there the evidence does not support your implicit claim that teenagers like flavors better than adults do”, and other arguments about the scientific facts.

Let’s try to get our criticisms right, shall we? (More on the recent “vaping causes heart attack” study)

by Carl V Phillips

Sigh. We are supposed to be the honest and scientific ones in the tobacco wars. But we won’t be if we are not, well, scientific. Case in point are the criticisms of the recent paper with Glantz’s name on it that has been erroneously said to suggest that vaping doubles the risk of heart attack.

Incidentally, the meaningless statistic in the paper is a RR of 1.8, which is not double. Also, when the paper was originally written as a student class project (not by science students, mind you, but by medical students), that statistic was 1.4. That was when Glantz heard about it, managed to get the kids to put his name on the paper, and taught them how to better cook their numbers. That “contribution” has him being called the lead author.

The paper is junk science. So are most of the criticisms of it. If only someone with expertise in these methods had written a critique of it that people could look to. Oh, wait, here’s one in The Daily Vaper from February. That was based on a poster version of the paper, but as I noted in the article, “It has not yet appeared in a peer-reviewed journal, but it will, and the peer-review process will do nothing to correct the errors noted here.” I wish I could claim this was an impressive prediction, but it is about the same as predicting in February that the sun will rise in August.

You can go read that if you just want a quick criticism of the paper, and also look at the criticism on this page of some hilarious innumeracy Glantz piled on top of it. In the present post I am mostly criticizing the bad criticisms, though at the end I go into more depth about the flaws in the paper.

About half the critiques I have seen say something along the lines of “it was a cross-sectional study, and therefore it is impossible to know whether the heart attacks occurred before or after someone started vaping.” No. No no no no no. This is ludicrous.

Yes, the data was from a cross-sectional survey (the 2014 and 2016 waves of NHIS, mysteriously skipping 2015). And, yes, we do not know the relative timing (as discussed below). But “therefore it is impossible to know” (or other words along those lines)? Come on. A cross-sectional survey is perfectly capable of measuring the order of past events. Almost every single cross-sectional survey gives us a pretty good measure of, for example, whether someone’s political views were formed before or after the end of the Cold War. Wait! what kind of wizardry is this? How can such a thing be known if we do not have a cohort to follow? Oh, yeah, we ask them their age or what year they were born. Easy peasy.

Almost every statistic you see about average age of first doing something — a measure of the order in which events occurred (e.g., that currently more Americans become smokers after turning 18 than before, but most extant smokers started before they were 18) — is based on cross-sectional surveys that ask retrospective questions. It is perfectly easy to do a survey that asks heart attack victims the order in which events occurred. Indeed, any competent survey designed to investigate the relationship in question would ask current age, age of smoking initiation and quitting, age of vaping initiation and quitting, and age at the time of heart attack(s), ideally drilling down to whether smoking cessation was just before or just after the heart attack if they occurred the same year. We would then know a lot more than the mere order. But NHIS does not do that because, as I noted in the DV article, it is a mile wide and an inch deep. It is good for a lot of things, but useless for investigating this question. It can be used, as it was here, for a cute classroom exercise to show you learned how to run (not understand, but run) the statistical software from class. But only an idiot would think this paltry data was useful for estimating the effect.

(A variation on these “therefore it is impossible” claims is the assertion that because it is a cross-sectional study, it can only show correlation and not causation. I am so sick of debunking that particular bit of epistemic nonsense that I am not even going to bother with it here.)

So, we do not know the order of events. We can be confident that almost all the smokers or former smokers who had heart attacks smoked before that event. We do not know whether subjects quit smoking and/or started vaping before their heart attacks. Given that vaping was a relatively new thing at the time of the surveys, whereas heart attacks were not, it seems likely that most of the heart attacks among vapers occurred before they started vaping. This creates a lot of noise in the data.

A second, and seemingly more common, erroneous criticism of the analysis is that this noise has a predictable direction: “Smokers had heart attacks and then, desperate to quit smoking following that event, switched to vaping, thereby creating the association.” Again, no no no. Heart attacks do cause some smokers to become former smokers, but there is little reason to believe they are much more likely than other former smokers to have switched to vaping. Some people will have heart attacks and quit smoking unaided or using some other method. Indeed, I am pretty sure (not going to look it up, though because it is not crucial) that most living Americans who have ever had a heart attack experienced that event before vaping became a thing. So if they quit smoking as a result of the event, they did not switch to vaping. Also it seems plausible that the focusing event of a heart attack makes unaided quitting more likely than average, as well as making “getting completely clean” more appealing.

Of course, an analysis of whether behavior X causes event Y should not be based on data that includes many Y that occurred before X started. That much is obviously true. NHIS data is not even a little bit useful here, which is the major problem. There is so much noise from the heart attacks that happened before vaping this that the association in the data is utterly meaningless for assessing causation.

But there is no good reason to assume that this noise biases the result in a particular direction. If asked to guess the direction of the bias it creates, a priori, I probably would go in the other direction (less vaping among those who had heart attacks compared to other former smokers). The main reason we have to believe that the overall bias went in a particular direction is that the result shows an association that is not plausibly causal. We know the direction of the net bias. But this is not the same as saying we had an a priori reason to believe this particular bit of noise would create bias in a particular direction. When we see a tracking poll with results that are substantially out of line with previous results, it is reasonable to guess that random sampling error pushed the result in a particular direction. But we only conclude that based on the result; there was not an a priori reason to predict random sampling error would go in a particular direction.

Moreover, we do not have any reason to believe that the net bias was caused by this particular error, because it has a rather more obvious source (see below).

Sometimes we do have an a priori reason to predict the direction of bias caused by similar flaws in the data, as with the previous Glantz paper with an immortal person-time error (explained here, with a link back to my critique of the paper). If the medical students had engaged in a similar abuse of NHIS data to compare the risks of heart attack for current versus former smoking, then the direction of bias would be obvious: Heart attacks cause people to become former smokers, which would make former smoking look worse than it is compared to current smoking. I suspect that people who are making the error of assuming the direction of bias from the “Y before X” noise are invoking some vague intuition of this observation. They then mistranslate it into thinking that former smokers who had a heart attack are more likely to be vapers than other former smokers.

This brings up a serious flaw in the analysis that I did not have space to go into in my DV article: The analysis is not just of former smokers who vape, but includes people who both smoke and vape, as well as the small (though surprisingly large) number of never-smokers who vape. If vaping does cause heart attacks, it would almost certainly do so to a different degree in each of these three groups. For reasons I explored in the previous post, different combinations of behaviors have different effects on the risk of an outcome. Vaping probably is protective against heart attack in current smokers because they smoke less than they would on average. If a smoker vapes in addition to how much she would have smoked anyway, the increased risk from adding vaping to the smoking is almost certainly less than the (hypothesized) increased risk from vaping alone. Whatever it is about vaping that increases the risk (again, hypothetically), the smoking is already doing that. Thus any effect from adding vaping to smoking would be small compared to the effect from vaping compared to not using either product. Most likely the effect on current smokers would be nonexistent or even protective.

Indeed, this is so predictable that if you did a proper study of this topic (using data about heart attacks among vapers, rather than vaping among people who sometime in the past had a heart attack; also with a decent measure of smoking intensity — see below), and your results showed a substantial risk increase from vaping among current smokers, it would be a reason to dismiss whatever result appeared for former smokers. This is especially true if the estimated effect was substantial in comparison to the estimate for former- or never-smokers. If you stopped to think, you would realize that your instrument produced an implausible result, and thus it would be fairly stupid to believe it got everything else right. This is a key part of scientific hypothesis testing. Of course, such real science is not part of the public health research methodology. Nor is stopping to think.

It is a safe bet that the students who did this analysis understand none of that, having never studied how to do science and lacking subject-matter expertise. Glantz and the reviewers and editors of American Journal of Preventive Medicine neither understand nor care about using fatally flawed methods. So the analysis just “controls for” current and former smoking status as a covariate rather than separating out the different smoking groups as it clearly should. This embeds the unstated — and obviously false — assumption that the effect of vaping is the same for current, former, and never smokers. Indeed, because “the same” in this case means the same multiplicative effect, it actually assumes that the effect for current smokers is higher than that for former smokers (because their baseline risk is higher and this larger risk is being multiplied by the same factor).

Though they did not stratify the analysis properly, it is fairly apparent their results fail the hypothesis test. The estimate is driven by the majority of vapers in the sample who are current smokers, so they must have had a substantially greater history of heart attacks.

There is a good a priori reason to expect this upward bias, as I noted in the DV article, but it is not the reason voiced in most of the critiques. It is because historically vapers had smoked longer and more than the average ever-smoker. This is changing as vaping becomes a typical method for quitting smoking, or a normal way to cut down to having just a couple of real cigarettes per day as a treat, rather than a weird desperate attempt to quit smoking after every other method has failed. Eventually the former-smoking vaper population might look just like the average former-smoker population, with lots of people who smoked lightly for a few years and quit at age 25, and so on. But in the data that was used, the vapers undoubtedly smoked more than average and so were more likely to have a heart attack (before or after they started vaping).

Controlling for smoking using only “current, former, never” is never adequate if the exposure of interest is associated with smoking history and smoking causes the outcome, both of which are obviously true here. If there are no such associations then there is no reason to control for smoking, of course. Thus basically any time you see those variables in a model, you can be pretty sure there is some uncontrolled confounding due to unmeasured smoking intensity. In this case, you can be pretty sure that its effect is large and it biases the association upward.

In short, the results are clearly invalid. There are slam-dunk criticisms that make this clear. So let’s try to stick to those rather than offering criticisms that are as bad as the analysis itself. Ok?

Dual use and the arithmetic of combining relative risks

by Carl V Phillips

It was called to my attention that UCSF anti-scientist, Stanton Glantz, recently misinterpreted the implications of one of his junk science conclusions. Just running with the result from the original junk science (which I already debunked) for purposes of this post, Glantz make the amusing claim that because vaping increases heart attack risk by a RR=2 and smoking by a RR=3 (set aside that both these numbers are bullshit) then dual use must have a RR=5. WTAF?

First off, there is no apparent way to get to 5 except by pulling it out of the air. It is apparent that Glantz thinks he was adding the risks: 2+3=5. Except you cannot add risks that way. Every first-semester student knows the formula for adding risks, which is based on the excess risk. Personally I have always thought that having students memorize that as a formula, rather than making sure they inuit it, is a major pedagogic failure. But that aside, they do memorize the formula, which subtracts out the baseline portion of the RR then adds it back, as should be obvious: (RR1 – 1) + (RR2 – 1) + 1. So, the additive RR = 2-1 + 3-1 + 1 = 4. Think about it: If you “added” Glantz’s way then two risks that had RR=1.01 (a 1% increase in risk) would add to 2.02 (more than double). Or two exposures that reduced the risk by 10% (RR=0.9) would add to an increased risk, RR=1.8. Not exactly difficult to understand why this is wrong.

Additivity of risks is a reasonable assumption if the risk pathways from the exposures are very independent. The excess risk of death caused by both doing BASE jumping and smoking is basically just the excess risk of each added together. (A bit less because if one kills you, you are then not at risk of being killed by the other.) If the risks from the two exposures travel down the same causal pathways (or interact in various other ways), however, adding is clearly wrong. If vaping causes a risk (for heart attack in this example, though that does not matter), then smoking almost certainly causes the same risk via the same pathway. There is basically no aspect of the vaping exposure that is not also present with smoking (usually more so, of course). When this is the case, there are various possible interaction effects. One thing that is clear, however, is that simply adding the risks as if they did not interact is wrong.

The typical assumption built into epidemiology statistical models is that the risk multiply. This is not based on evidence this is true, but merely on the fact that it makes the math easier. The default models that most researchers tell their software to run, having little or no idea what is actually happening in the black box, build in this assumption. It is kind of roughly reasonable for some exposures, based on what we know. In the Glantz case, this would result in a claim of RR = 2 x 3 = 6, which is also not the same as 5.

So, for example, if a certain level of smoking causes lung cancer risk with RR=20, and a certain level of radon exposure causes RR=1.5, then if someone has them both, it is not unreasonable to guess that the combined effect causes RR=30. The impact on the body in terms of triggering a cancer and then preventing its growth from being stopped seems like it would work about like that. On the other hand, there are far more examples where the multiplicative assumption is obviously ridiculous. If BASE jumping once a week creates a weekly RR for death of 20, and rock climbing once a week has RR=2, doing each once a week obviously adds, as above, for RR=21, rather than multiplying to 40. (Aside: most causes of heart attack are probably subadditive, less than even this adding of the excess risks, as evidenced by dose-response curves that flatten out, as with smoking.)

But importantly, notice the “each once a week” caveat. That addresses the key error with the stupid “dual use” myths by specifying that the quantity of each activity was unaffected by doing the other. If, on the other hand, someone is an avid BASE jumper, doing it whenever he can get away, and he takes up rock climbing, the net effect is to reduce his risk. The less hazardous activity crowds out some of the more hazardous activity. This, of course, is what dual use of cigarettes and vapor products (or any other low-risk tobacco product) does. This is not complicated. Every commentator who responds to these dual use tropes — and I am not talking epidemiology methodologists, but every last average vaper with any numeracy whatsoever — points this out. Vaping also does not add to the risk of smoking because it almost always replaces some smoking rather than supplementing it. In this case, using Glantz’s fictitious numbers, it would mean the RR from dual use would fall somewhere between 2 and 3. Not added. Not multiplied. Not whatever the hell bungled arithmetic that Glantz did. Between.

As I said, everyone with a clue basically gets this, though it is worth going through the arithmetic to clarify that intuition. It is not clear whether Glantz really does not understand or is pretending he does not — as with Trump, either one is plausible for most of of his lies. Undoubtedly many of his minions and useful idiots actually believe it is right. The “dual use” trope gets traction from the fact that interaction effects from some drug combinations are worse than the risk of either drug alone. Many “overdose” deaths are not actually overdoses (the term that should be used for all drug deaths is “poisonings” to avoid that usually incorrect assumption), but rather accidental mixing of drugs that have synergistic depressant effects, often because a street drug was secretly adulterated with the other drug.

But as already noted, that is obviously not the case with different tobacco products, whose risks (if any) are via the same pathways. Even if total volume of consumption was unaffected by doing the other (as with “each once a week”) the risks would not multiply and would probably not even add. Since that is obviously not true — since in reality, consuming more of one tobacco product means consuming less of others — the suggestion is even more clearly wrong. In fact, using the term “dual use” to describe multiple tobacco products makes no more sense than saying that about someone who smokes sticks that came out of two different packs of Marlboros on the same day.

In the context of tobacco products, the phrase “dual use” is inherently a lie. It intentionally invokes the specter of different drugs (or other exposure combinations) that have synergistic negative effects. That is not remotely plausible in this case. It also intentionally implies additivity of the quantity of exposure (“doing all this, and adding in this other”) when it is actually almost all substitution, as with which pack you pull your cigarette from. To the extent that it increases total consumption of all products, this is a minor effect (a smoker who vapes not only as a partial substitute, but also occasionally when he would not have smoked even if he did not vape). This only matters to someone who does not care about risk, let alone people, and only cares about counting puffs.

There is a long list of words and phrases that when used by “public health” people should make you assume they whatever they are saying is a lie: “tobacco” (when used as if it were a meaningful exposure category), “addictive” (meaningless for drugs with little or know functionality impacts), “chemical” (a meaningful word, but invariably used because it sounds scary), and “carcinogen” (when used as a dichotomous characterization, without reference to the relevant dosage and risk). “Dual use” should be added to this list, in the same general space as “chemical”, another word that is inherently just a simple boring technical descriptor, but that is almost exclusively used to falsely imply negative effects.

A balanced view of ad hominem judgments

by Carl V Phillips

Tap tap tap. Is this thing on?

Welcome back to this blog. As many of you know, The Daily Vaper, where I published most of my good material for a year, has ceased publication (the articles, fortunately, are still archived at my author page at dailycaller.com, and they redirect from the original links if you have used those somewhere). I also recently did a “best of” Twitter thread highlighting some of what I wrote there (and here and elsewhere). There is something simultaneously atavistic and postmodern about watching (now nonexistent) the DV website slip slowly down the list of top guesses for where I might want to go when I open a new browser tab.

I am writing most of my subject-matter analysis under contract these days, with a bit of freelancing for commercial websites. Deep-think tangents will start to reappear here. Like this one. (I thought about doing it as a Twitter thread, but I realized that would never work.) Continue reading

The travesties that are Glantz, epidemiology modeling, and PubMed Commons

by Carl V Phillips

I was asked to rescue from the memory hole a criticism of a Glantz junk paper from a year ago. I originally covered it in this post, though I do not necessarily recommend going back to read it (it is definitely one of my less elegant posts).

I analyzed this paper from Dutra and Glantz, which claimed to assess the effect of e-cigarette availability on youth smoking. What they did would be a cute first-semester stats homework exercise, but is beyond stupid to present it as informative. It is simple to summarize: Continue reading

The academic scandal hiding within the Stanton Glantz sexual harassment scandal

by Carl V Phillips

By now you have probably heard about the lawsuit against Glantz by his former postdoc, Eunice Neeley. Buzzfeed broke the story here, which (like other reports) appears to be based entirely on the complaint filed in a California court (available here). There appear to be no public statements, other than the blanket denial that Glantz posted to his university blog, which was picked up in at least one press report.

I am fascinated by several details that were too subtle for the newspaper reporters. Continue reading

Gateway effect denial claims are a target-rich environment

by Carl V Phillips

I have repeatedly tried to explain what gateway claims mean — that engaging in one behavior causes another behavior (in the present context, that vaping causes smoking), what they do not mean, and what constitutes valid evidence for or against their existence. Why bother? As I noted in a recent piece on the topic, for The Daily Vaper (which links back to some of my more in-depth pieces), “most of the claims by vaping proponents that there is no gateway effect are also nonsense.” Indeed, they create such a target-rich environment for criticism that even Simon Chapman can find the flaws. Continue reading

Index of my Daily Vaper articles (2)

by Carl V Phillips

In my last post, I noted that most of my writing is currently at The Daily Vaper. I also promised that I would keep an index of those publications here for those who following this and not those, highlighting the ones that fans of this blog might be particularly interested in. This also provides an option for commenting on them, which DV does not have, and a chance for me to add a bit more about some of them.

[Update: Indexing is hard and unrewarding. I stopped after this one. Maybe someday I will circle back.]

Here is my belated second entry in the series. I will try to do this more frequently so the list is not so long (sorry — maybe keep this tab open and take a few days to get to all of them you want to see).

In rough descending order of what I think regular readers of this blog would find most interesting (I expect you will want to read at least the first seven):

1. I wrote a science lesson about anchoring bias and why it means that we should really stop describing the risks from low-risk tobacco products in relation to smoking (e.g., “99% less harmful”). I have hinted at some of this here, but I have never really nailed it before. This is new analysis. Anyone interested in my evolving thinking about accurate messaging — based on more years of experience and thought than anyone else involved in this realm — should definitely read this.

2. I reported on a court ruling that is fairly obscure, but truly delightful: The usual gang of anti-tobacco groups petitioned to be co-defendants, alongside FDA, in a suit against FDA by cigar manufacturers over aspects of the deeming regulation. The judge denied it. Why should we care? Because the ruling basically said that they are not stakeholders. For those of us constantly frustrated by the bullshit suggestion that they are (let alone that the primary stakeholders, tobacco product consumers, are not), this is just too good. Unfortunately I suspect I am the only one who will try to make anything of this. I strongly encourage those of you who are involved in advocacy (and especially those involved in lawsuits) to run with it. It really is a huge potential lever.

3. This piece is about the unethical scientific practices of tobacco controllers, specifically their flouting of human subjects protection rules. These are bright-line violations of codified rules, unlike the usual unethical behavior of tobacco control which is evil but not unlawful. I mention a couple of the reports about that which I have written here along with some new material. I suggest that perhaps a blanket boycott campaign would make sense. If I have time, I will write a piece about that specifically for this blog.

4. My personal favorite is this one, where I catch FDA chief Scott Gottlieb, in congressional testimony, offering basically the NIDA definition of “addiction”, a definition that clearly excludes tobacco products (including cigarettes). As my readers know, I have made a study of what people mean when they say “addiction”, and how there is apparently no viable definition that anyone wants to defend that actually includes tobacco/nicotine. In this case, Gottlieb was stuck because he had to talk about opioid addiction, and so was forced effectively undercut all the CTP rhetoric on the subject. Well, undercut it if anyone decides to challenge them based on this, which probably will not happen. The industry is not exactly known for being that clever.

(Foreshadowing note: I actually think I have figured out how to characterize what people mean when they say smoking etc. are addictive. One of these days I hope to write a major piece on this.)

5. In what could basically be an uncharacteristically terse version of a post here, I wrote about a recent “what parents need to know” statement about vaping in JAMA Pediatrics. It was all the terrible you might expect. I shredded it. If your appreciation for shredding exceeds your inclination to be annoyed by the terrible, you should find it a satisfying little read.

6. I reported how, after Senator Chuck Schumer launched an amazingly stupid attack on vaping in a press conference, Gottlieb practically fellated him on Twitter. (No, I did not put it quite that way.) This suggests that despite all the overly-optimistic talk of regime change at FDA, nothing has really changed in terms of who they consider their political patrons. (*cough* *told you so* *cough*)

5. My most recent piece was about the FDA’s Orwellian-named “Real Cost” campaign. I noted that they are about to aim this anti-scientific propaganda campaign, currently focused on smokeless tobacco and smoking, at vaping. I recount some of the campaign’s content and assess what they will do regarding vaping. I will write more about this shortly.

6. I did some original data analysis in this article, based on a recent CDC report of vaping rates across demographics and occupations. The authors could not see past the raw vaping rates. This is merely an uninteresting echo of the smoking rates; whoever smokes most is going to vape most. I looked at the ratio of vapers to smokers, which is actually useful. I found that across almost every group, the ratio is very close to the overall average. This effectively shows that the rate of switching from smoking to vaping is about the same across the different groups. The one big exception was African-Americans, where the ratio is much lower. That is, few smokers in that population are switching to vaping. I suppose this is worth a journal article, but I do not have time. (Free easy publication for any student or academic who wants to take the lead and write that with me! Seriously, let me know if you are interested.)

7. In this brief piece, I review the results of a recent paper that shows the anti-vaping bias in mainstream media reporting. It just confirms what we all know, but does a nice job of it. Most notably, it observes that anti-vaping statements tend to be attributed to people with supposedly expert credentials (though obviously they are really either clueless or liars), while the truth is attributed to advocates who the average reader will (mistakenly) consider less credible.

8. Here I analyzed a research paper out of FDA which is part of their assessment of how MRTP labeling might affect consumers. Unsurprisingly, it seems designed to make the case that allowing manufactures should not be allowed to tell the truth about their products. The study was bad, and they clearly intend to spin it worse.

9. I reported on FDA’s release of “adverse event” type records that they collect for tobacco products, which are really mostly about vapor products. I noted it is pretty much meaningless, but that it might be used in anti-vaping advocacy. I indicated my suspicion that FDA released it for just that purpose, not because of some belief it should be available because it is genuinely informative (it is not).

10. In this science lesson, I summarized my analysis that shows that the optimal tax rate for low-risk tobacco products is zero if the goal is to promote population health, or any other defensible stated goal. Not “lower than the tax on cigarettes” or “proportional to the risk”, but zero. My readers will already be familiar with these arguments, though if you are looking for a short summary, this is it.

11. I tried to assess the recent FDA “guidance” about the ban on free samples of vapor products (e.g., sampling e-liquid flavors), now that they are deemed as tobacco products, with all the rules that apply to them. I say “tried” because the guidance sort of says that it does not apply to adults-only venues (e.g., most vape shops). But how exactly this will play out — i.e., will flavor sampling be banned? — is not clear.

12. I analyzed a recent survey by BAT about beliefs about the risks from vaping. It is pretty straightforward “latest study” reporting, though I got some additional data from the researchers that allowed me to offer a better assessment than those who were just working from the press release. The main takeaway is that even in the UK, a ridiculously large portion of the population does not understand that vaping is much less harmful than smoking.

13. I introduced readers to the CASAA Testimonials collection that I created in 2013. Long-time readers of this blog will be familiar with it. I plan to publish more little articles that are excerpts from that collection.

14. Finally, I reported on the fight over vapor product taxes in Pennsylvania. The upshot is that tax structure, not just tax rates, matter a lot. A rather more interesting aspect of that story — and of another story that got spiked — does not appear there. I hope to get time to report it here sometime (ooh, more foreshadowing).

(Damn, that is a lot of material. Comments welcome. I suggest using the serial numbers if you are commenting on one in particular.)