- Credibility, Causality, and Other Word Games
- Publication Bias
- Confounding Variables
- Misclassification Error
- Use of Death Certificates
- Cigarette Equivalents and Exposure: Arguments Against a PEL
- Assessing overall Economic Impacts
- The "Department of Energy Report"
- Assessing the Credibility of the Tobacco Industry: The Historical Record
First, the tobacco industry witnesses limit themselves to detailed (often inconsequential) criticisms of the individual research projects reported in the scientific literature, while steadfastly refusing to consider the evidence as a whole.
Second, they fail to apply the same criticisms or level of scrutiny to work that supports their position as work that supports the conclusion that ETS causes disease.
Third, they establish a standard of proof that is impossible to meet, such as suggesting that the only way to be sure of a conclusion is to conduct an experiment such as a randomized controlled trial. It is simply ethically and practically impossible to randomly assign people to be exposed to controlled levels of ETS for a given length of time, wait for them to die (or kill them), then conduct autopsy to verify the precise cause of death. Animal experiments, in which one could control these variables, are rejected because animals are not people. To meet the objections that the tobacco industry witnesses raised to the evidence OSHA and others have developed that ETS causes disease one would have to do a human study. Even so, many of the same objections raised in the record could be raised: Were the subjects in the sample typical of the American population? The working population? Were the exposure chambers similar to workplaces? Was the controlled diet similar to the diet eaten by all American workers? The list goes on and on.
Fourth, and most important, they deny the obvious. Of the 17 witnesses appearing at the request of the tobacco industry who were asked whether active smoking causes lung cancer or other diseases, not one simply answered "yes " (Holan, p. 4359; Idle, p. 5201; Hubert, p. 5456- 5457; Ashford, p. 5682-5683, 5685; LeVois, p. 5807-5809; R. Witorsch, p. 6089-6091; Springall, p. 6188; Switzer, p. 6335-6340; Starr, p. 6945; Layard, p. 6695; Roth, p. 9192-9195; Gori, p. 9562-9565; Bridges, p. 10088-10093; Holcomb, p. 10776, 10779-10780; P. Witorsch, p. 10643; Newell, p. 10985; Coggins, p. 11633; the actual questions and answers are in Attachment 1). Some did not know, some said it was beyond their professional expertise, some said active smoking was a "risk factor" (the current term the tobacco companies use). Despite persistent questioning, only one witness (Hubert, p. 5456-5457) finally admitted that active smoking causes disease. Indeed, LeVois stated that "you cannot prove causality" even in a controlled experiment (p. 5901).
This situation contrasts with other carcinogens unrelated to tobacco. When asked if anything had been found that causes lung cancer in people, RJ Reynolds' Coggins promptly and unambiguously answered "asbestos," (p. 11641) despite the fact that the precise mechanism by which asbestos causes cancer is not precisely understood. Indeed, there is probably a better understanding of how tobacco causes cancer than how asbestos causes cancer. In any event, despite the fact that the nature and type of evidence available in both cases is similar, Coggins had no trouble concluding that asbestos causes cancer whereas he found the evidence on smoking inadequate.
One can only speculate why the tobacco industry and its lawyers are willing to say "risk factor" but not "cause," but it is clear that the tobacco industry's witnesses avoided the word cause the way a vampire avoids light. This refusal to accept probably the best established fact in biomedical science draws everything else these people have say into question.
The argument that publication bias exists -- particularly when it is defined as broadly as the tobacco industry witnesses defined it -- is a particularly convenient argument to raise because it is an argument about what is not there. The nonexistent studies cannot be critiqued for their methods or related to the other studies.
There are several serious problems with the industry's arguments:
There have been several attempts to address the question of publication bias against negative studies in the ETS literature, all of which have concluded that there is no such bias.
Bero et al  examined the available literature and searched for unpublished data sets on ETS and lung cancer and failed to find any evidence of publication bias. Indeed, if publication bias is defined as failure to publish small studies that do not show a statistically significant effect (in this case, of ETS on lung cancer), they presented evidence that there is a bias in favor of publication of negative or equivocal studies on ETS.
Beaglehole  did a formal search for unpublished data sets and studies on ETS and heart disease and could not locate any.
Wells  noted that the few abstracts on ETS and heart disease that did not ultimately appear as full papers all reported an increase in risk of heart disease associated with ETS exposure.
Finally, Vandenbroucke , originator of the "funnel plot" that several tobacco industry witnesses used to argue that there is a publication bias against negative papers on ETS and heart disease, concluded that no such publication bias existed for ETS and lung cancer in women. It is interesting that none of the tobacco industry witnesses, who discussed funnel plots at such length, pointed out Vandenbroucke's conclusion.
The Vandenbroucke "funnel plot" has never been shown to demonstrate that it actually detects publication bias. In addition, this technique was not consistently applied or interpreted by the tobacco industry's witnesses.
It is important to emphasize that the "funnel plot" is simply an interesting suggestion as a way to think about publication bias. The original Vandenbroucke paper  is only 1_ pages long and contains no empirical evidence that it proves publication bias exists. When asked for such evidence, none of the tobacco industry witnesses could point to any empirical evidence that a funnel plot actually detected publication bias. In addition, Vandenbroucke did not propose any formal analysis of funnel plots to quantify publication bias.
LeVois applied the funnel plot more-or-less as Vandenbroucke originally proposed, with the exception that he added a formal test to see if the data followed the funnel pattern. He did so by applying a Pearson product moment correlation (p. 5884-5885) to the log relative risk versus standard error of the log of the relative risk. When questioned about this procedure, LeVois saw no problems with this approach. There is, however, a fundamental difficulty with what LeVois did. The Pearson product movement correlation coefficient is a parametric statistical test that requires making several assumptions, most notably that the variance in the observations is constant, i.e., the data are not displayed in a "funnel pattern." Virtually any introductory statistics textbook that discusses Pearson correlation in any depth makes this point. Thus, the statistic that LeVois computed is simply not appropriate for analyzing the data he presented.
One could compute the correlation among the points that LeVois presented using a Spearman correlation -- which does not require making the constant variance assumption. Doing so fails to yield a statistically significant P value. Thus, if one accepts the general analytical approach advanced by LeVois (which I do not) and simply uses the correct test statistic, LeVois' data yields the conclusion that there is no publication bias.
In comparison to use of the Pearson correlation in an ad hoc attempt to be quantitative about the analysis of funnel plots as LeVois did, Springall, another tobacco industry witness, specifically eschewed any formal analysis of the plots and chose to rely on subjective judgement (p. 6448-6449, 6453). In fact, the decision that the data are displayed in a "funnel" is an arbitrary and subjective decision. (Vandenbroucke also draws his conclusions by simply looking at the plot.) Indeed, both LeVois (p. 5884-5885) and Springall (p. 6448-6449) simply drew the funnel lines on the plots rather than computing them from the data using any objective procedure.
Later, when asked about LeVois' procedure of computing the Pearson correlation, Springall changed his view and said it was an acceptable procedure (p. 6457-6460). Springall stated that it was reasonable to do such a computation after looking at the data and seeing that it appeared to fall on a straight line. This kind of post hoc analysis was soundly criticized by another tobacco industry witness, Switzer, who said (p. 6251),
Unless researchers state clearly in advance of the data collection, and I emphasize in advance, exactly how they will report the results, there is a real possibility that groupings and other adjustments may be chosen which more clearly exhibit positive findings. I think it's perhaps a natural instinct on the part of people who do studies to try to find positive findings in their research and therefore they may make choices after seeing the data. I would be surprised if they didn't.
Switzer, however, did not see fit to raise the same criticism about LeVois' post hoc analysis of the funnel plot.
The tobacco industry's witnesses were inconsistent in their use of the funnel plot; Springall did not apply the funnel plot methodology the same way LeVois did. Rather than plotting the standard error of the logarithm of the relative risk on the horizontal axis (as LeVois and Vandenbroucke did), Springall plotted the square root of the sample size on the horizontal axis. When questioned on why he did not construct the plots as Vandenbroucke originally proposed, he said that he did it because the standard errors were "crazy" (p. 6444). Leaving aside the question of the precise scientific definition of a "crazy" standard error, it is worth noting that simply using the square root of the sample size means that the value along the horizontal axis simply reflects how big the study is, without adjusting for any potential confounding variables. Given the extensive discussion of the importance of confounding variables that the tobacco industry witnesses presented -- including Springall -- it is surprising that Springall chose to ignore any effects of confounding in his analysis of the funnel plot. This point is another example of the inconsistent methods and standards applied by the tobacco industry witnesses.
Most of the papers that have cited Vandenbroucke's paper conclude that ETS causes disease. A search of Science Citation Index located 35 papers, 14 of which dealt with ETS (see Attachment 2). Of these 14 papers, 12 (86%) concluded that ETS harmed health. Both of the papers that stated that there were not enough data to reach such a conclusion were written by scientists with financial connections to the tobacco industry; one of them was by LeVois and Layard  and essentially repeated the testimony presented to OSHA and discussed in this post hearing comment and the other was prepared by Fleiss and Gross  at the suggestion of Myron Weinberg of WASHTEC (a tobacco industry witness at this hearing) with funding from the Tobacco Institute.
Despite the fact that several of the tobacco industry witnesses claimed that there was a bias against publishing -- or even conducting -- negative studies, none of them could point to a specific instance in which they had this problem (Idle, p. 5220; Newell, p. 11052; Coggins, p. 11634). The only specific case that was discussed was an attempt by Ashford to publish a study in the New England Journal of Medicine indicating that children of smoking mothers had better survival rates than children of nonsmokers. The New England Journal rejected this study, but Ashford was able to publish it in the Italian Journal of Obstetrics and Gynecology (p. 5770- 5771). He was unable to locate the reviews of the paper or provide any evidence that the New England Journal had not simply rejected the study on the grounds of poor quality. Moreover, the fact that the paper was ultimately published (albeit in a less prestigious journal) is evidence against the existence of publication bias.
Several tobacco industry witnesses made an issue of the fact that the American Cancer Society had never published an analysis of the CPS-I and CPS-II data sets that examined the question of passive smoking and heart disease and cited this as evidence of publication bias (e.g, Ashford, p. 5654; LeVois, 5768; Gori, P. 9542; Sears, p. 11993; Lee's written submissions, Sirridge's cross examination of Glantz, p. 578- 580). The fact that scientists had not gotten around to doing a specific study is not evidence of publication bias. It is, after all, the American Cancer Society, and heart disease is not a priority for this organization.
In response to these criticisms, I contacted Dr. Michael Thun, Director of Analytical Epidemiology and the American Cancer Society and asked him if there were any results available on ETS and heart disease from these studies (Attachment 3). He informed me that, while they were interested in this question, it had been a low priority for the American Cancer Society. He was kind enough to conduct a preliminary analysis of the data which, in contrast to the analysis presented at the Hearing by LeVois and Layard, showed an elevation in risk of heart disease for nonsmoking men married to women who smoked with a relative risk of 1.21. This value is consistent with the other studies in the literature. (Dr. Thun is now conducting a more complete analysis of this dataset, which will hopefully become available in the near future.)
There are very serious problems with the analysis of the CPS-I and CPS-II data sets put in to the record by LeVois and Layard; their failure to properly account for important confounding variables, particularly age, as well as the likelihood of serious misclassification of nonsmokers as smokers, biases their results towards the null, i.e., missing a real effect of ETS on heart disease.
As Michael Thun noted when I asked him to review LeVois and Layard's written submission:
Although LeVois and Layard reportedly controlled for age in the Poission regression analysis (Table 4), they do not present age-specific data. Active cigarette smoking is known to be a stronger risk factor for CHD death at younger than at older ages. For example, among white male active cigarette smokers in CPS-II, the RR for fatal CHD (compared to never-smokers) decreases from about 6.3 at age 40-44 to 1.4 at ages Æ75. Failure to examine modification of the association by age could easily obscure a true association between passive smoking and CHD mortality.
Perhaps it is this failure to properly account for the confounding variable of age that led LeVois and Layard to fail to detect that effect of ETS that appeared in Thun's preliminary analysis. LeVois was extensively questioned on the relationship between age, smoking, and heart disease risk by Mr. Myers (p. 6008-6011) and failed to recognize the importance of this confounding variable or how to properly correct for it in his analysis.
There is another, more fundamental, problem with the LeVois and Layard analysis of the CPS data sets: the numbers do not add up correctly. As Thun's letter notes, Table 2 of LeVois and Layard's written submission stated that there were 226,067 never-smoking women in CPS-II. This exceeds by over 13,000 the number of women included in a parallel American Cancer Society Study of lung cancer and ETS. Despite extensive questioning on this discrepancy, LeVois could not explain this error of 13,000 women (p. 5861-5867, 6004-6005). During cross examination by Mr. Myers, LeVois admitted that their analysis counted any individual who was married to an ever-smoker as exposed to ETS, even if the ever-smoker quit 10-15 years earlier, perhaps before marrying the person who was the case in the CPS data set (p. 6005-6008). Given the fact that the risk of heart disease in active smokers declines quickly upon smoking cessation, falling by 50% in one year, and essentially back to that of a nonsmoker over a few years . Since the mechanisms by which active and passive smoking cause heart disease are similar, it is likely that ending exposure to ETS will be followed by a similar fall in the risk of heart disease associated with past ETS exposure. As a result, LeVois' practice of including ever smokers as markers of ETS exposure seriously biases his results towards the null, i.e., his analysis will systematically underestimate the risk of current ETS exposure as a cause of heart disease.
It is also worth noting that neither the CPS-I nor CPS-II studies were primarily designed to study the effects of ETS on heart disease. As discussed by Wells in his written submission and testimony (p. 965- 967), the questions used to assess ETS exposure in these studies are limited and raise the possibility of serious biases towards the null in the analysis of the effects of ETS on lung cancer and heart disease. Even given these biases, it is notable that proper analyses of these data sets shows an increase in risk of both lung cancer and heart disease associated with ETS exposure.
Given the extensive critique of the possibility of misclassification of smokers as nonsmokers that several of the tobacco industry witnesses, it is remarkable that none of them raised the issue of misclassification in connection with this study, where it is likely to be a much bigger problem because of the large number of former smokers.
These same criticisms apply to the publication by LeVois and Layard in Regulatory Toxicology and Pharmacology  that essentially repeats the written materials submitted to OSHA. Interestingly, in his oral testimony on November 15, 1994, LeVois said "These data are presented to OSHA in an appendix and are presently being prepared for submission to a journal for publication." In contrast, the published article in the journal states that it was received for publication on June 11, 1994. It is also noteworthy that Gio Gori, another tobacco industry witness, is an associate editor of the journal.
The fact that the analysis of the National Mortality Followback Survey yielded negative results is neither evidence that ETS does not cause heart disease nor that there is a publication bias against publication of negative studies because this analysis has so many problems as to be worthless.
The fundamental problem with this analysis is the definition of a smoker. Someone is identified as a smoker if he or she ever smoked 100 cigarettes in their entire lives. While this is a reasonable definition of never smoker for the cases in the studies, this same definition was used for the spouses that were supposedly exposing (or not exposing) the cases to ETS. Thus, a spouse who was 60 years old but who had smoked only as a teenager would be counted as a smoker and the case would be counted as "exposed." Given the tens of millions of former smokers, this situation created huge misclassification errors in who people are counted as exposed to ETS when, in reality, they are married to a nonsmoker. As of 1987, 40.3% of ever smokers had been nonsmokers for at least one year . This misclassification error strongly biases the results towards the null, i.e., a relative risk of 1. It is remarkable that, at the same time that several tobacco industry witnesses provided extensive discussions of the effects of relatively small misclassification errors (of smokers counted as nonsmokers) in the published studies, not one of them raised this issue in the Layard study of the National Mortality Followback Survey. Despite extensive questioning on this point, Layard showed no evidence of having even considered this problem (p. 6655-6661).
This study is also an example of the inconsistent application of scientific standards by the tobacco industry witnesses to studies that support and oppose the industry position that ETS is not dangerous. While the studies in the peer reviewed literature that support a link between ETS and disease were soundly criticized (particularly the Fontham study) for using surrogate responses, the National Death Followback Survey relied entirely on surrogate responses. None of the tobacco industry witnesses included this problem in their discussion of problems with epidemiological studies on ETS and disease.
These same criticisms apply to the publication by Layard in Regulatory Toxocology and Pharmacology  that essentially repeats the written materials submitted to OSHA. Interestingly, in his oral testimony on November 17, 1994, in response to whether the work was published in a peer reviewed journal, Layard said "it's about to be submitted." In contrast, the published article in the journal states that it was received for publication on June 25, 1994. It is also noteworthy that Gio Gori, another tobacco industry witness, is an associate editor of the journal.
Here is how confounding variables can make it appear that something causes a disease when, in fact it does not: If A causes B and A causes C, B and C will tend to change together (in response to A), even if B does not cause C because of the effect of the confounding variable A. This situation, in which B is "unjustly" concluded to cause C has led the tobacco industry witnesses to a long list of possible confounding variables that can be used to explain the observed associations between ETS exposure and heart disease and lung cancer. Some of these potential confounding variables include race, age, diet, socioeconomic status, and pet birds. The tobacco industry's witnesses spoke at great length about these possibilities (e.g., LeVois, p. 5771- 5775, 5778, 5782, 5786, 5797, 5805-9, 5814-5815, 5818, 5835, 5841-46, 5850; Witorshch, 6117-6119, 6141-6144; Springall, p. 6173-6175, 6177, 6180, 6183, 6229-6231; Switzer, p. 6247, 6229-6301, 6306, 6310-6314, 6317-6318; Starr, p. 6495-6496, 6502, 6530, 6540; Layard, p. 6592, 6594, 6595-6597, 6601-6604, 6613-6614; Roth, p. 9091-9095, 9098-9910, 9113- 9115, 9128, 9131, 9133, 9154-9155, 9193, 9202, 9210-9215, 9220, 9224, 9227-9233, 9245-9247, 9251-9252, 9256-9257; Coggins, p. 11450-11451, 11466, 11467-114672, 114679, 114682-114683, 114696, 11563). In addition, confounding was the subject of extensive cross examination of OSHA witnesses by the tobacco industry's lawyers (Glantz, p. 531, 541, 561, 579, 731-732, 739; Samet, p. 1192-1196; Benowitz, p. 1233, 1237, 1239, 1279-1280, 1346-1347, 1361-1362; Steenland, p. 1936-1939, 1944, 1950, 1960-1963, 1988-1984, 1990, 1993-1994, 1996, 2078-2081, 2086- 2092.) Despite this extensive presentation, and specific questions from OSHA during cross examination, none of the tobacco industry witnesses provided any empirical evidence that the potential problem of confounding really existed.
Any good epidemiologist should consider possible confounding variables when interpreting the results of an epidemiological study. The fact that someone can list a variable as a potential confounder, however, does not constitute evidence that it is a confounder. (For example, both the EPA  and Fontham et al  carefully evaluated diet as a potential confounder for ETS and lung cancer and found that the ETS effect on lung cancer persisted even after controlling for diet. Hence, any dietary differences between people exposed to ETS and not exposed do not explain the increased risk of lung cancer death associated with ETS.) Indeed, the tobacco industry's witnesses' presentations simply consisted of lists of potential confounding without any empirical evidence or quantitative analysis to support the assertion that these confounding variables actually explained the observed associations between ETS and disease or that such confounding effects, even if present, were large enough to explain the observed associations between ETS exposure and disease. The two exceptions to this failure to present quantitative evidence that confounding, if present, could explain the association between ETS exposure and disease were Springall (p. 6180) and Roth (p. 9133, 9256-9257). In both cases, the witnesses assumed an effect of confounding and then analyzed the impact of this assumed effect. When pressed for the empirical evidence that the effects were as assumed, none was produced. Nothing in the massive amount of material submitted in writing and as testimony at the Hearing by the tobacco industry and its witnesses, constitutes affirmative empirical evidence that real confounders existed that could explain the observed link between ETS exposure and disease. Indeed, the failure of the tobacco industry to produce evidence that real confounders exist increases the confidence that OSHA can have in concluding that ETS causes disease.
As explained by Samet in his cross examination by tobacco industry lawyers, confounding can also mask a real risk. The only industry witness to recognize that it is possible to "overcorrect" for confounders was Starr (p. 6495-6496), who only recognized this fact during cross examination. Any good textbook on multivariate analysis cautions against this procedure; including redundant variables creates a situation known as "multicollinearity" in which real effects of the independent variables are masked because the uncertainty in the parameter estimates (i.e., estimates of the effects of the variables, such as ETS exposure, on the outcome variable, i.e., death). In contrast, when questioned on whether it is possible to "overcorrect" by including too many independent variables in an analysis to evaluate the effects of ETS, LeVois incorrectly stated that it was a good thing to have overlapping independent variables in the analysis (p. 5925-5927).
Likewise, Springall incorrectly stated that multicollinearity increases the risk estimates (p. 6430-6432). Of all the tobacco industry witnesses, in response to cross examination, only Switzer (p. 6324-6328) correctly described the fact that multicollinearity could mask a real effect. Switzer did not, however, raise this issue in criticizing the long lists of overlapping potential confounding variables suggested by other tobacco industry witnesses.
Lee, another tobacco industry consultant, provided an extensive discussion of confounders in his written submission, but did not appear at the hearing to answer questions about his work. In particular, he suggested 33 confounders for heart disease that he stated should be considered in an analysis of the effects of ETS. As noted in the attached tables (Attachment 4), many of these confounders are multiple measurements of the same thing (e.g., 11 dietary variables plus overweight, underweight, and fatty foods). Including all these confounders would create serious multicollinearity problems which could make it impossible to detect a real ETS effect even if one is present. Ironically, LeVois, who spoke at length about the need to account for confounding variables in the analysis of ETS, failed to account for most of Lee's variables in his analysis of the CPS data sets (p. 5919-5925). LeVois even call Lee's list "odd" (p. 5920) when asked one-by-one about Lee's potential confounders without knowing the source. (Springall also questioned the wisdom of including several variables that measured the same thing; p. 6436-6437.) Later, Mr. Rupp submitted LeVois to extensive friendly cross examination to justify LeVois' failure to control for all of Lee's confounding variables (p. 6031-6033, 6039-6041, 6049-6051, 6267, 6270-6274).
Similar to LeVois, Layard's analysis of the National Death Followback Survey did not take into account 100 potential confounding variables Lee suggested for lung cancer (p. 6651-6655). Later, Mr. Rupp offered Layard friendly cross examination (p. 6701-6702) to justify the fact that Layard did not correct for all these confounders, primarily because Layard only had a small number of cases and, as a practical matter, doing such corrections was impossible. It is interesting that Mr. Rupp and the other tobacco industry representatives appeared unwilling to apply such practical considerations to studies that concluded that ETS caused disease.
The fact that the tobacco industry's witnesses criticize most scientists for not controlling for long lists of confounding variables while failing to do so themselves is another of the inconsistencies in the scientific standards the tobacco industry applies to work that agrees and disagrees with its position that ETS is not dangerous.
Finally, when Layard did include the effects of some potential confounding variables in his analysis of the National Death Followback Survey, he found that it did not affect the risks associated with ETS exposure (p. 6629, 6663-6666). Nevertheless, he declined to interpret this empirical result as evidence that these potential confounders would explain the results of other studies.
In contrast to all this hypothetical discussion of the effects of confounders of the effects of ETS exposure, with the presumption that this confounding would make it appear that ETS causes disease when, in fact, it does not, the evidence from the peer reviewed literature on the subject suggests that confounders are leading to underestimates of the effects of ETS on disease. Wells  stratified studies of ETS and heart disease according to study quality, which primarily was judged by the number of confounding variables that were taken into account, and found higher relative risks for ETS in the better studies. Likewise, Fontham et al  found higher relative risks for lung cancer associated with ETS exposure when they controlled for confounding variables than when they did not. When questioned about this finding, Roth (p. 9149) incorrectly cited this fact as a reason to question the Fontham study, rather than recognizing the fact that confounding could mask a risk. The available empirical evidence supports the view that confounding variables tend to mask the effects of ETS exposure, not make it appear that ETS causes disease when it does not.
As with confounding, there are two ways in which misclassification errors can introduce artifacts into the estimate of the risks associated with passive smoking, which introduce opposite biases into the risk estimates.
The first way is to incorrectly classify exposed subjects (cases) who are really smokers as nonsmokers. Given that smoking increases the risk of lung cancer dramatically, lung cancer cases caused by active smoking would be incorrectly attributed to passive smoking, yielding an erroneous increase in the estimated risks due to passive smoking. There is evidence that a few percent of smokers misrepresent themselves as nonsmokers . Several of the tobacco industry witnesses argued strenuously that this source of error is a serious problem. It is important to emphasize, however, that such misclassification errors can only be a problem if active smoking causes the disease in question. When asked whether smoking caused lung cancer in smokers, however, all the tobacco industry witnesses carefully avoided saying "yes." (See discussion above and Attachment 1.) This logical inconsistency did not preclude the tobacco industry's witnesses from making strong statements about misclassification errors.
It is also important to emphasize that for the kind of misclassification that the tobacco industry witnesses discussed depends not only on the fact that smoking causes disease in smokers, but also the magnitude of the increase in risk smokers suffer. For lung cancer, this increase in risk is very large (a relative risk of around 20. In contrast, the relative risk for heart disease in smokers is only around 2, depending on the presence of other risk factors (diet, hypertension, etc.). Thus, the effect of misclassification of smoking cases as nonsmoking cases will be much smaller in the case of heart disease. Indeed, one of the tobacco industry's witnesses, Gori (p. 9543) volunteered this fact.
Misclassification can also introduce errors going the other way, if the spouses who are the source of the ETS exposure are misclassified. Suppose that ETS increases the risk of lung cancer in nonsmoking spouses (cases) married to smokers. If the spouse of the case is a smoker, the risk of lung cancer in the case spouse will be elevated. If, however, the spouse is misclassified as a nonsmoker, this case of lung cancer will not be attributed to ETS exposure, thereby erroneously reducing the risk estimate. None of the tobacco industry witnesses identified this form of misclassification as a problem with any of the studies, despite the fact that these two forms of misclassification error tend to balance out.
As discussed above, the failure of LeVois and Layard to address this second form of misclassification error in their analyses of the CPS and National Mortality Followback Survey data sets is a major problem because not only do they suffer from misclassification errors of current smokers because of reporting errors, but their analysis treats ever- smokers the same as current smokers, even if they have been former smokers for decades. Given the fact that 40.3% of ever smokers of all smokers are former smokers , this failure introduces huge misclassification errors into their analysis, which strongly biases their results towards the null (i.e., no effect). Nevertheless, not one of the tobacco industry's witnesses on misclassification errors commented on this problem with LeVois and Layard's work. In fact, Gori's praised this work at the same time he volunteered that misclassification of smoking cases as nonsmokers was not as much of a problem in heart disease as lung cancer studies (p. 9543).
In contrast the exacting criticisms of higher quality studies in the legitimate peer reviewed literature, tobacco industry witnesses repeatedly held up the LeVois and Layard analyses of the CPS and NMFS data sets as strong evidence that ETS does not cause heart disease (Ashford, p. 5654; Gori, p. 9543; Sears, p. 11447). This failure to apply the same standards to research advanced to support the industry's position that ETS is not dangerous as that which supports the view that it is dangerous is further evidence of the disingenuous nature of the criticisms of the Notice of Proposed Rule Making. Had the tobacco industry applied the same standards to these two studies as they did to better work implicating ETS as a cause of disease, these studies would have ranked at the bottom of anyone's list of quality.
OSHA should not include the analyses of the CPA and NMFS data sets submitted to the record by LeVois and Layard in any meta-analysis or other type of quantitative risk assessment of ETS conducted as part of preparing its final rule. These studies do not meet even minimum scientific standards, much less the exacting standards the tobacco industry would have OSHA apply to legitimate independent scientific studies of ETS.
"Death certificate data is [sic] poor data. We all know that. Like you asked me in the beginning of my testimony about asbestos and smoking. The landmark study there was the Selikoff and Hammond studies. They found it important in their analyses in these studies to go back and reconfirm the death certificate data with better autopsy money when they can get it. That was one of the real strengths of that particular study."
In response to cross examination by Ms. Sherman, Ashford recognized that Fontham's study of ETS and lung cancer had histological verification of cases, which mitigated against his earlier criticisms (p. 9232-9233).
LeVois explicitly stated that death certificate data was not valid for studies of ETS and heart disease (p. 5774):
"The outcome in a better heart disease study should be a clinical diagnosis of illness. That is the rare exception in these studies. Almost all of them either use heart disease death as reported on a death certificate which is, unfortunately, notoriously inaccurate, particularly for heart disease and particularly for older people where heart disease is a default cause of death very often, and is rarely, in these studies, supported by a complete medical evaluation, interviews with the treating physicians and so forth, which would serve as at least a place to start if you don't have clinical diagnosis."
LeVois' blanket criticism of the use of death certificate data is interesting, since his colleague and coauthor (in testimony before OSHA, repeated in their paper in Regulatory Toxicology and Pharmacology ) Layard used invalidated death certificate data in his analysis of ETS and heart disease based on the NMFS. Neither LeVois, nor any of the other tobacco industry witnesses who expressed such concerns about the use of death certificate data in the Helsing and Fontham studies, volunteered any comparable criticisms of Layard's analysis of the NMFS.
In response to a question about Layard's use of death certificate data, Roth, the tobacco industry witness who spoke at the greatest lengths about the problems of using death certificate data, backpedaled (p. 9264-9265):
MS. SHERMAN: Would you say that Dr. Layard's reliance on a death certificate analysis represents a fatal flaw in his study?
DR. ROTH: I wouldn't use the term fatal. It's just a lesser... That's a problem.
But on the other hand, that study had weaknesses, and I don't know the details of it, but what you're talking about is a huge number of deaths. That's a strength of that study that would counterbalance this problem.
I'm not here defending... Death certificate data aren't as good as other data.
In making this defense, Roth makes a fundamental error when he states that the large size of Layard's sample compensates for the alleged problems with death certificate data. As any introductory statistics textbook notes, a large inaccurate sample is just as inaccurate as a small inaccurate sample. Had Roth consistently applied his criticisms, he would have had to dismiss Layard's study under the same terms he dismissed Helsing and Fontham's studies.
Not surprisingly, in response to cross examination by Dr. Glantz, only Layard defended use of death certificate data (p. 6669-6672), in part by pointing out, "Let me point out, however, that the Helsing study upon which OSHA is relying very heavily, has the same problems, does it not?" In normal scientific discourse pointing to one flawed study (Helsing, according to the tobacco industry witnesses) does not justify using the use of this methodology in another study.
The criticisms of death certificate data when used by OSHA but not when used by the tobacco industry witnesses is another example of the inconsistent scientific standards the tobacco industry witnesses applied to evidence that did and did not support their client's position on ETS.
The record contains an extensive discussion of meta-analysis, with the bulk of the discussion surrounding the details of how a specific "EPA-style" meta-analysis is constructed, particularly how the studies to be included in the analysis are selected. (It is important to emphasize that the EPA did not develop any new techniques for meta- analysis; it simply applied well-established textbook methods; see Samet, p. 183-188, 294-296; AMA, p. 4549-4552; Bayard, p. 14720, 14808.) In fact, Mr. Grossman went so far as to question OSHA as to why it did not use a meta-analysis in the Notice of Proposed Rulemaking (p. 316- 319).
The tobacco industry witnesses expressed varying opinions about meta-analysis. On one hand, several of the tobacco industry witnesses expressed approval of meta-analysis, properly applied, as a reasonable way to combine several risk estimates or to summarize data (Hubert, p. 5439-5440; Switzer, p. 6290; Layard, p. 6593-6594; Roth, p. 9246). Starr expressed opinions on both sides of the issue, both stating that one should consider the studies one at a time (p. 6467), and also stating that results could be pooled (p. 6506, 6557), but refusing to spell out how to operationalize this pooling (p. 6554-6558). At the other extreme, LeVois stated that "I think that meta-analysis has been largely repudiated by most of the methodologists in epidemiology" (p. 5814) and Ashford calls meta-analysis "a devious technique" (p. 5648).
Despite LeVois' strong criticism of meta-analysis computations, LeVois' colleague and coauthor Layard (p. 6615) reported a meta-analysis of workplace studies of ETS (using the same standard computational methods that the EPA used), which met with general approval from the other tobacco industry consultants (e.g., Switzer, p. 6290). Despite their strong criticisms of meta-analysis as an approach when used by the EPA and OSHA, LeVois and Asford had no criticisms of Layard's work, which used essentially the same methods. Indeed, as discussed below, despite the fact that problems of misclassification, confounding, and exposure assessment that the tobacco industry witnesses raised concerning the EPA and OSHA analyses (e.g., Switzer, p. 6318-6380; Roth, p. 9106; Gori, p. 9536-9539 ) are much more serious in Layard's analysis of workplace ETS studies, not one of the tobacco industry witnesses had any problems with Layard's analysis of the workplace studies (Switzer, p. 6358-6360; Roth, p. 9263- 9265; Gori, p. 9535).
LeVois was completely inconsistent in his statements about the appropriateness of meta-analysis (particularly with regard to ETS). At first he said (p. 5814)
MS. SHERMAN: What about meta-analysis? Do you believe that meta- analysis is an appropriate tool in analyzing these studies?
DR. LeVOIS: Absolutely not. I think that meta-analysis has been largely repudiated by most of the methodologists in epidemiology.
Surprisingly, he later used precisely this technique to obtain other results in his testimony (p. 5659-5860):
MS. SHERMAN: You have a relative risk of 1.28 as the summary result?
DR. LaVOIS: That's correct. And that's a weighted average based on taking as the weight the inverse of the error of the studies and the error is determined by looking at the spread of the confidence interval.
MS. SHERMAN: So you didn't use a meta-analysis for this?
DR. LaVOIS: That is a meta-analysis.
MS. SHERMAN: That is?
DR. LaVOIS: That's what a meta-analysis does.
MS. SHERMAN: Well, I thought you said earlier that you didn't think that meta-analysis was appropriate in this case.
DR. LaVOIS: Meta-analysis is not of any help in interpreting a result. Meta-analysis is a perfectly valid way of giving a weighted estimate to collection of data. It's a matter of whether or not it's of any use at all in inferring causation.
MS. SHERMAN: Which formula did you use to calculate the error?
DR. LaVOIS: As I said, it's just the inverse of the log of the -- these are first log standardized and it's the inverse of the error. It's very simple.
The formula LeVois used is the same as that used by the EPA. If meta- analysis is "not of any help in interpreting a result," one wonders why LeVois presented it in his testimony. Moreover, by coming down on both sides of the issue of meta-analysis, it appears impossible for OSHA to conduct an analysis that would satisfy him, no matter what it does.
The tobacco industry witnesses also were inconsistent in their criticisms of the application of meta-analysis as it apples to ETS studies. On one hand, Starr (p. 6499-6500), Roth (p. 9147), and Gori (p. 9533, 9546-9554) stressed the need for the studies which are combined in a meta-analysis to be "homogeneous," and expressed concern that the different studies were not similar enough in terms of control of confounding variables and other biases to permit combining them. In contrast, Springall (p. 6465-6466) said homogeneity of the studies introduces errors and stressed that it was better if the individual studies were heterogenous. Given that the tobacco industry's witnesses have criticized meta-analysis applied to both heterogeneous and homogeneous studies, it would appear impossible for OSHA to construct an analysis that would satisfy all these witnesses.
In contrast to strong criticism of meta-analysis of spousal studies, the tobacco industry did not express any concerns about meta- analysis of workplace studies, perhaps because these analysis as submitted by the industry through its consultants Lee, Layard, and Tweedie, led to results that the industry consultants interpreted as indicating that ETS exposure did not cause disease. (Unfortunately only Layard appeared at the hearing, so Lee and Tweedie could not answer questions about their work.) Tobacco industry lawyers carefully questioned OSHA and OSHA's witnesses as to why they did not use workplace studies in their meta-analyses (Grossman's examination of OSHA, p. 298; Sirridge's examination of Glantz, p. 570-571; Grossman's examination of NIOSH, p. 1913-1914, 1919, 1972-1974; Rupp's examination of NIOSH, p. 2103-2108; Furr's examination of Bayard, p. 14809-14810).
As explained repeatedly by OSHA's witnesses, however, it is much more difficult to conduct workplace-based epidemiological studies of long term effects of ETS than spousal (Steenland, p. 2103-2108; Bayard, p. 14948-14949). In particular, over a long period of time workplace exposures to ETS are more variable because of people changing jobs, there is more confounding with the effects of other toxins in the workplace, and problems of recall errors are more serious in workplaces than in household situations when someone is married to the same individual for many years. These problems are precisely the same problems that the tobacco industry witnesses raised concerning the spousal studies, except that they are much more serious in the workplace studies. In addition, in the workplace studies, these potential errors all bias the results towards the null, i.e., finding no effect.
The tobacco industry witnesses' unrelenting criticism of the spousal studies, while uncritically accepting the more problematic workplace studies is another example of how the industry accepts evidence that supports its position while rejecting evidence that does not, without regard for scientific logic or consistency. Indeed, the positions advocated by the tobacco industry witnesses regarding meta- analysis are so varied and opposed to each other (and often not even consistent within a given witness) that it would be impossible for OSHA to conduct an analysis that would satisfy all of them.
Another unstated assumption that underlying the tobacco industry's attempt to make a distinction between spousal and workplace studies is that ETS exposure at work somehow has a different effect on nonsmokers' lungs and hearts than comparable exposure at home. The tobacco industry, however, did not produce any empirical evidence to support such an assumption. In considering the effects of ETS, OSHA should consider total exposure, of which workplace exposure is simply one element.
All this discussion leaves OSHA with the question of how to conduct its risk assessment. As noted at the beginning of this section, both the original approach followed by OSHA (selecting the "best" study) and a correctly done meta-analysis are acceptable approaches. My recommendation is that OSHA proceed as follows:
1. Review all available studies in detail, including consideration of exposure assessment, treatment of confounding variables, and potential effects of misclassification errors.
2. Select "acceptable studies" for a meta-analysis, as well as the "best" study.
3. Do not use the workplace studies unless studies can be identified that avoid the problems discussed above with workplace studies. Do not use the Layard and LeVois analyses of the CPS and NMFS data sets for the reasons discussed above.
4. Conduct an analysis both ways and use both results in the final rule.
This is the approach that the EPA used.
The Complementary Nature of the Evidence that ETS Causes Heart Disease
As I noted in my original testimony (p.383-388), it is important to consider all the evidence bearing on the question of ETS and heart disease, not simply examine each study or type of study (e.g., epidemiological, experimental, clinical) in isolation. The tobacco industry witnesses concentrated almost exclusively on criticizing the epidemiological evidence and tended to ignore the important animal experimental and human clinical experiments linking ETS exposure and heart disease. It is important to reemphasize that the fact that there is a consistent pattern of evidence from biochemical, animal, clinical, and epidemiological studies linking ETS exposure and heart disease is very strong. While no one study is perfect, the evidence provided by these studies is complementary, consistent, and reinforcing.
While the tobacco industry witnesses raised a few general objections to the animal studies the presented no empirical evidence that these hypothetical problems invalidated the use of these animal studies to complement the human epidemiological and clinical studies on ETS and heart disease. It is also important to emphasize that, while the rats, rabbits, and cockerels who were used in these studies were not exposed in office workplaces, the exposures to ETS that they were subjected to were of the same order of magnitude as human exposures and of relatively short duration (minutes to weeks).
These studies of ETS use exposures that are of the same order of magnitude as real life exposures. This situation contrasts starkly with the situation that is common in most cancer bioassays, when the animal studies involve exposures that can be thousands to hundreds of thousands times higher than ambient human exposures. As a result, the certainty with which one can apply the data from the animal studies on ETS and heart disease to real human exposures is much higher than typically is the situation in most animal bioassays of other toxic substances.
For example, our studies using rabbits and rats [11-14] exposed the animals to ETS levels similar to those found in a bar (the "low dose" groups) and about 2-10 times higher, depending what component of ETS one chose to examine. Penn et al [15, 16] also used realistic doses in his studies of cockerels, compared to normal human exposures. Indeed, after his initial study demonstrated that ETS accelerated formation of atherosclerotic plaques in a dose-dependent manner, his funding agency, the tobacco industry's Center for Indoor Air Research, asked him to repeat the study only exposing the cockerels to one cigarette at a time. When this experiment demonstrated an effect of ETS on atherosclerotic plaque despite the very low dose, the CIAR cut off Penn's funding .
These animal models are well-established in cardiovascular research . For example, the cholesterol-fed rabbit model of atherosclerosis has been in use since 1908 . For example, my colleagues at UCSF have used this model for several studies on the effects of calcium channel blockers and fish oil on atherosclerosis [19- 23]. The rabbit is a good model for human atherosclerosis. Histologically, the lesions observed in this model look like fatty streaks filled with foam cells which are typical of early atherosclerotic lesions. Likewise, Penn and his colleagues have used cockerels on low cholesterol diets for a variety of studies of the mechanisms of atherosclerosis [24, 25].
In addition to the results I presented in my original testimony, the ARIC  study discussed in detail by Ford (p. 12475-12482), which demonstrated that ETS exposure was associated with increases in carotid artery thickness in humans, provides another important piece of evidence in constructing the chain from molecular biology through death and disability from heart disease due to ETS exposure. The fact that the effects of ETS on carotid thickening was 23% of that found in active smokers is important evidence to support the fact that the effects of ETS are much larger than would be predicted based on the dose in terms of "cigarette equivalents" as advocated by the tobacco industry.
These points are treated in technical detail by the recent paper by Glantz and Parmley in JAMA .
Since the hearing, another study of the effects of smoking restrictions on restaurant revenues (from Texas) was published by the CDC in the MMWR , which actually shows an increase in revenues following passage of the ordinance.
The extensive cross examination by Mr. Rupp concerning our study of the effects of smoke free restaurant ordinances on restaurant revenues (p. 512 ff) was based entirely on a preliminary version of the study that included only four cities. The study I put in the record was a 15 city study that was published in the peer reviewed journal, the American Journal of Public Health , which included the original four cities, as well as 11 others, over a longer time period. My work should be judged based on the final publication, not the preliminary version.
In his cross examination regarding the restaurant study, Mr. Rupp concentrated almost exclusively on one city, Bellflower (p. 522), ignoring the other 14 cities. This attack is typical of the approach used by the tobacco industry in taking isolated points out of context rather than considering all the evidence. It is important to emphasize, however, that the ordinance did not adversely affect restaurant revenues in Bellflower, either.
In addition, on p. 523-525 Mr. Rupp presses the fact that the point estimate for the change in restaurant sales in Bellflower is negative, without regard for the fact that this estimate is small compared with the associated standard error. In other words, the change is well within the random fluctuations of the data and uncertainty of the estimate, i.e., not statistically significant. The fact that Mr. Rupp chooses to stress a non-significant finding when it serves his clients' purposes at the same time that the tobacco industry seeks to ignore statistically significant effects of ETS is another example of the inconsistent behavior of the tobacco industry's representatives and witnesses in the hearing.
The primary "evidence" submitted to support the tobacco industry's position that OSHA's proposed rule will have devastating effects on the hospitality industry was a survey conducted by Price-Waterhouse, nominally for the San Francisco Hotel and Restaurant Association. (Price-Waterhouse seems to specialize in preparing reports for the tobacco industry indicating that smoking restrictions will or have had serious adverse economic consequences; similar studies have appeared around the country, including in Los Angeles and New York, following enactment of local smoking restrictions. Like the study before OSHA, none are based on hard data.) In this study, travel agents were asked to estimate the effects of OSHA's proposed rule on foreign travel to and in the United States. No evidence was submitted that travel agents can estimate the smoking prevalence in foreign countries, much less the amount of money actually spent by foreign visitors, or the fraction of trips that are discretionary versus required. These failings make it difficult to take this study seriously, especially in the face of published work by us and others [28-31] based on objective sales tax data.
In response to questioning by Ms. Sherman and Mr. Sandman, Gelfond (of Price Waterhouse) admitted that the question they used to elicit information about the anticipated effects of OSHA's proposed rule overstated the impact of the proposed rule and so would increase the estimated impact by some unspecified amount (p. 10907, 10937- 10939,10966-10968, 10976-10982). Nevertheless, Price-Waterhouse did not even try to even estimate the size of this bias, much less design an unbiased questionnaire. Another bias that Price-Waterhouse acknowledged was failing to include the benefits of the Proposed Rule in their estimates (p. 10971-10975). These errors are exactly the kind of biases that the tobacco industry's other witnesses severely criticized in other studies of ETS and disease, yet not of them raised the analogous criticism of the Price Waterhouse study, even though, by design, it overstated the alleged adverse effects of the proposed OSHA rule.
It is also interesting to note that Price-Waterhouse relied on estimates by travel agents of the behaviors of smoking and nonsmoking customers, without any evidence that these travel agents had any direct first-hand experience with this matter or evidence that travel agents were qualified to estimate these variables (p. 10939). In light of all the criticism of response bias and surrogate sources for information on ETS exposure that emanated from other tobacco industry witnesses, it is surprising that none of these individuals advanced similar criticisms of the Price-Waterhouse study, which exhibits much more serious deficiencies in this area than any of the ETS studies that OSHA relied on in drafting the Proposed Rule. Indeed, the fact that the tobacco industry would advance such a silly study simply because it supports their (objectively unsupportable) claim that smoking restrictions hurt the restaurant businesses belies the hypocrisy of all the industry's criticisms of the legitimate scientific and economic studies upon which OSHA relied.
The reasons for this effect are quite simple. Eighty-two percent of adult smokers have tried to quit at least once and in any given year about one third of smokers try to quit . Creation of a smoke-free environment makes it easier for smokers to be successful in these attempts. Indeed, the effects on cigarette consumption -- not some concern for public welfare -- is almost certainly what is motivating the tobacco industry's activities at this Hearing and in other efforts to discredit the evidence that ETS is dangerous. For example, in California in 1990, the then-existing mix of restrictions on smoking in the workplace had reduced total cigarette consumption by about 148 million packs of cigarettes worth $203 million in sales . Completely smoke free workplaces would probably double this impact. While this represents a significant loss to the tobacco industry, it represents a significant benefit to people who wish to stop smoking, their employers, and taxpayers . OSHA should consider these benefits in its analysis.
OSHA's analysis should also take note of the fact that, while the rule will result in lower revenues for the tobacco industry, this money will still remain in the economy to be spent on other consumer goods. There may even be a net positive impact on the economy and jobs in most of the country .
Interestingly, one of the tobacco industry witnesses, Viscusi (p. 8251 ff) was the only witness to raise this issue. Viscusi's analysis, however, systematically ignores the benefits to individual consumers, businesses, and society as a whole of reduced tobacco consumption. His analysis of psychic satisfaction and consumer surplus (p. 8282) ignores the fact that nicotine is an addictive drug  and that virtually all smokers begin as children. (Viscusi's example of the costs to a hypothetical smoker who simply wants to smoke a couple of cigarettes in the afternoon at work [p. 8362] goes against everything we know about the pharmacology of nicotine addiction.) These omissions make his assumption of rational consumers acting on complete information seem silly. Indeed, one could argue that, far from representing a reduction in welfare for smokers as Viscusi asserts (p. 8251-8252), providing an environment supportive of quitting represents an increase in smokers' welfare.
Viscusi's estimates of the effects of reduced cigarette consumption on tax revenues (p. 8253) likewise ignore the fact that the money that would have been spent on cigarettes will simply be spent on other goods, with the attendant generation of tax revenues and jobs. His analysis of the costs of smoking is based entirely on lung cancer, despite the fact that the disease that kills most smokers -- active and passive alike -- is heart disease. This fact is particularly important because smoking-induced heart disease tends to strike workers in the prime of their working life . (For additional discussion of problems with Viscusi's analysis, see Attachment 5.)
Viscusi, like the other tobacco industry witnesses, appeared to be applying different standards to OSHA's analysis of the impacts of ETS regulation from other rules. The transcript includes this revealing exchange (p. 8313-8314):
MR. GORDON: A very well known economist once said, "The over-estimation of the cost of compliance should be a signal for potential biases of industry-based compliance cost estimates." So if you believe that particular statement, wouldn't you suspect that maybe our cost estimates were over-estimated?
DR. VISCUSI: I'm not sure of the context in which the cost estimates were provided, when they were provided, where the studies came from.
MR. GORDON: But the economist of course, I'm referring to, is yourself. I think I would like to introduce into evidence, Your Honor, an article that Dr. Viscusi on the OSHA cotton dust standard. I'd like to give him a copy of it as well.
DR. VISCUSI: Which one? Which paper?
MR. GORDON: "Cotton Dust Regulation," and "OSHA Success Story?" By W. Kip Viscusi, Journal of Policy Analysis and Management.
Indeed, in response to later questioning by Mr. Gordon, Viscusi admits that he has conducted "a rather incomplete analysis" (p. 8341-8342). This is an understatement.
MR. ELI: Dr. Switzer, I wanted to ask you about a document that I just handed to the OSHA panel which is a publication of the U.S. Government as best I can tell, which I believe you have a copy of, which is entitled, "Choices in Risk Assessment, the Role of Science Policy in the Environmental Risk Management Process" prepared for Sandia National Laboratories, sponsored by the U.S. Department of Energy, the Office of Environmental Management, and Office of Environmental Safety and Health. It was published in October of this year, and it's publicly available in the published literature. We just became aware of it.
This report was mentioned many times later in the hearing by the tobacco industry witness and representatives. The statement that "we just became aware of it" strains credibility, given the fact that Philip Morris was involved in the preparation of the report.
Given the importance attached to this report by the tobacco industry, several comments are in order:
Choices in Risk Assessment is not an offiicial Department of Energy report. It was prpeared and is copyrighted by the Regulatory Impact Analysis Project, Inc., a private organization.
Of the 53 nongovernmental organizations contacted in the preparation of the report, only 4 are environmental groups (the Environmental Defense Fund, the National Resources Defense Council, Resources for the Future, and Public Citizen). None of these groups has particular expertise in ETS.
The organizations used to provide information for the report are dominated by industry associations which represent polluters (including the American Automobile Manufactures Association, the American Petroleum Institute, the Chemical Manufacturers Association, that Halogenated Solvents Industry Association, the National Agricultural Chemicals Association, and many others).
The organizations used to provide information include conservative think tanks such as the Heritage Foundation and the Competitive Enterprise Institute.
Even though Choices deals extensively with tobacco smoke as a science policy issue, they did not contact recognized governmental or previewed authorities in the preparation of the report (such as the Centers for Disease Control Office on Smoking and Health or various health groups such as the American Cancer Society).
The authors of Choices relied on several sources closely allied with the tobacco industry, including Philip Morris Companies, the Health Policy Institute, and ENVIRON Corporation. The later two organizations provided witnesses at the OSHA hearings at the request of the tobacco industry.
While Choices criticizes OSHA for not relying on the best available scientific data, it ignored major peer-reviewed scientific consensus documents on ETS, including the 1986 Surgeon General's Report The Health Effects of involuntary Smoking , the 1986 NAS/NRC report Environmental Tobacco Smoke , and the 1992 EPA report Respiratory Health Effects of Passive Smoking: Lung Cancer and Other Disorders . All these documents were the subject of extensive peer review and report careful reviews that concluded that ETS causes lung cancer.
Instead of using on these peer reviewed works, Choices relies heavily on a report prepared by Jane Gravelle and Dennis Zimmerman of the Congressional Research Service. In contrast to the three scientific consensus documents described above [9, 37, 38], the CRS study do not undergo any sort of peer review by outside experts. It also makes many assumptions, such as that of a threshold effect for lung cancer, which are not generally accepted in the scientific community.
The authors of the CRS report themselves acknowledge a lack of qualifications to speak to the scientific and medical issues they raise; in Congressional testimony on May 11, 1994, they stated: "Please note that we are trained as economists and our area of expertise relates to economic analysis ... We do not have technical expertise in physiological and biological transmission and mechanisms of disease causing agents." Given their self-described expertise, one wonders why the authors of Choices gave their work so much weight.
The analysis of OSHA's proposed rule is very similar to the positions being advanced by Philip Morris tobacco, its consultants, and others allied with the tobacco industry that the broader body of scientific opinion on ETS. It suffers severely from the kinds of selection and reporting biases that other tobacco industry witnesses so severely criticized OSHA for, yet not one of the tobacco industry witnesses expressed these concerns about this report, including Switzer, who repeatedly expressed concern that work be done to the highest possible standards.
None of the exhibits (numbers 17 through 22) Mr. Rupp said he would provide to me (p. 500-501) for review were provided. As a result, I cannot attest to their accuracy. It is worth noting that none of the material in these exhibits formed the basis for any questions in my cross examination or the rest of the transcript.
LeVois has a PhD from the University of California San Francisco in Health Psychology. In response to a question by Ms. Sherman about why he did not study epidemiology at UCSF, he said there was no Department of Epidemiology (p.5793-5794) at UCSF. This is not correct; there was and is such a department at UCSF, originally called the Department of Epidemiology and International Health and now called the Department of Epidemiology and Biostatistics.
During Mr. Gordon's cross examination of Viscusi regarding why he did not include the effects of ETS on heart disease in his analysis (p. 8322), Viscusi stated, "I figure if the author of the study [Glantz] himself regards his estimates as implausibly large or words to that effect, then I don't think I'm that remiss in taking them with a grain of salt." This is not an accurate representation of my testimony or our research [27, 39]; we have stated that the effect of ETS on the heart is larger than would be expected based on the dose and the effect of active smoking on smokers. We interpret this result as evidence that one cannot think in terms of "cigarette equivalents" or otherwise extrapolate from the effects of active smoking on smokers to evaluate the cardiovascular effects of ETS. The evidence from the ARIC study  discussed by Ford (p. 12475-12482) provides direct evidence in humans to support this conclusion.
On page 10669 there is a discussion of P. Witorsch's criticism of Glantz and Parmley  for "failing to look for refuting data." In all our research, we search for all relevant data and consider it in our analysis.
In his cross examination of Beale (p. 11241), Mr. Rupp asks a question which contains several factual errors:
MR. RUPP: Are you aware that for the past 20 years Dr. Glantz has campaigned almost full time for the banning of tobacco advertising, for the banning of smoking in all public places, in the workplace, for requirements that cigarettes be sold on prescription only, that he has taken part in nearly every political campaign that has come down the pike over the past 20 years relating to smoking?
It is not accurate to say that I have been working "almost full time" on tobacco control; my full time position is as a member of the faculty at the University of California, San Francisco, where I have significant teaching and research responsibilities that have nothing to do with tobacco (see my Curriculum Vitae for a full description). My public service and research activities related to tobacco are only one of many activities I undertake as a member of the faculty. Moreover, while I have offered occasional comments and done some research on issues related to tobacco advertising, I have not played an active role in efforts to regulate tobacco advertising, other than testifying at a Public Utilities Commission hearing in my home town of San Francisco in support of a proposal (made by others) to end tobacco advertising on City busses, which, in San Francisco, double as school busses. I have never advocated that cigarettes be sold by prescription only. Finally, while I have been involved in several political campaigns surrounding public smoking (and helped engineer the tobacco industry's first electoral defeat in the San Francisco Proposition P campaign in 1983), it is a gross overstatement to say that I have taken part in "nearly every political campaign that has come down the pike over the past 20 years." Indeed, I played no role whatsoever in the campaign to enact California's Proposition 99 in 1988, which is probably the single most important piece of tobacco control legislation ever passed. While I recognize that questions are not evidence, this question again illustrates the lack of concern for accuracy that the tobacco industry and its representatives routinely exhibit.
Sears stated that "Concerning ETS and heart disease, as everyone on the panel knows, the body of evidence is so inconclusive that the EPA abandoned its effort to deal with heart disease in its risk assessment" (p. 11462-11463). This is not correct; the EPA limited its original report to lung cancer and respiratory effects to limit the scope of the project to something manageable.
On November 22, 1994, Philip Morris wrote Judge Vittone withdrawing their witnesses from the Hearing, in part because concerns about my role as a consultant for OSHA. In particular, they "accused" me of identifying ETS as a health hazard before many others in the scientific and medical community. Given that in science one seeks to be first -- and correct -- these hardly seems a criticism. The simple fact is that the scientific conclusions I have advanced on ETS have stood the test of time, to say nothing of being published in the leading peer reviewed scientific journals in the world. There is nothing in this letter that warrants an apology on my part. In a strange way, it is remarkable that Philip Morris was so frightened of a couple of scientists who could ask a few probing questions of their witnesses. It would have been interesting to have seen what they said.
When OSHA considers the comments from "concerned members of the public," both written and at the Hearing, it should be aware of the fact that the tobacco industry has developed a major public relations effort to mobilize "concerned smokers" [40-42] and discredit responsible government authorities, such as the EPA and OSHA . The "outpouring" OSHA recieved should be evaluated with the knowledge that it is hardly "spontaneous."
It is of particular interest that the tobacco industry developed "special projects" through which scientists were funded by the Council for Tobacco Research (CTR), not through the normal peer review process, but by lawyers, in order to develop "useful" information . The tobacco industry ties to these researchers was often not publically disclosed. Several participants at these proceedings, including Sterling, Aviado, and the Oak Ridge National Laboratory, feature prominently in this group. After a careful analysis of these "special projects" and related materials, Bero et al  reccommended
"The involvement of tobacco industry lawyers in the selection of scientific projects to be funded is in sharp contrast to the public statements made by the industry about its review process for the externally funded research [citation deleted]. This decision making process is unheard of in research programs funded by non-tobacco industry sources, such as the National Institutes of Health. The documents show that scientific merit played little role in the selection of special projects or consultancies. Instead, tobacco industry lawyers played an important role in selecting grantees on the basis of their potential legal or political usefulness to the tobacco industry. Projects or investigators that had the potential to produce data unfavorable to the industry were unlikely to be funded. This pattern of behavior should be considered by federal, state, and local decision makers when weighing claims by the tobacco industry and its consultants made as part of legislative or administrative procedures." [emphasis added]
Recent research on the tobacco industry's Center for Indoor Air Research (CIAR), which supported many of the witnesses who appeared on behalf of the tobacco industry at the Hearing, reveals patterns similar to the CTR .
Indeed, the Brown and Williamson documents show that at the same time that the tobacco industry was attacking the developing evidence that ETS caused cancer and other diseases, its own internal researchers and consultants were telling it that there was evidence that ETS caused cancer . In particular,"The documents show that, although the tobacco industry was publicly attacking Hirayama's paper, several of its own experts were privately admitting that his conclusions were valid. On July 24, 1981, Ernest Pepples, B&W's Vice President of Law, wrote a memo to J.K. Wells, B&W's Corporate Counsel [citation deleted]. The memo summarized a telephone conversation Pepples had with Tim Finnegan, an attorney with the firm of Jacob, Medinger & Finnegan. Pepples gave the following summary of 'Interesting Developments in the Hirayama Matter:'
Dr. Adlkofer who is the Scientific Director of the German Verbandt [the German equivalent to the CTR] has committed himself to the position that Lee [presumably Peter Lee, a British statistician and tobacco industry consultant] and Hirayama are correct and Mantel and TI [Tobacco Institute] are wrong. Adlkofer called Frank Colby at Reynolds [R.J. Reynolds Tobacco Co.] and said that Germany has received new data from Japan which confirms the Hirayama work. Adlkofer and Lee and another German associate were all asked to review Hirayama's work and did not find the error picked up by Kastenbaum [a statistician at the Tobacco Institute].They believe Hirayama is a good scientist and that his nonsmoking wives publication was correct.
...Adlkofer had previously proposed four research projects to examine the Hirayama work to be done by the research arm of the Verband [sic]. At a meeting of the board of the research arm on July 15 Adlkofer was asked how he could continue to support the projects if Hirayama's work was dead.He replied with a strong statement that Hirayama was correct, that the TI knew it and that TI published its statement about Hirayama knowing that the work was correct...
Subsequently Adlkofer told Colby that unidentified authors would publish in an unnamed publication an article claiming that Hirayama was correct and that TI published its statement while privately acknowledging Hirayama's correctness. Within a few days Adlkofer called again to say that the article was off. [emphasis added] [citation deleted]
"To our knowledge, Adlkofer never published an article discussing his views on Hirayama's work. The tobacco industry and its consultants have maintained a unified public position that Hirayama's study was flawed and that the health hazards of passive smoking have not been proven. Numerous scientific studies showing a link between passive smoking and lung cancer have since been published [citations deleted], and Hirayama's study is widely regarded in the scientific community as a landmark study on ETS.
"The Brown and Williamson documents provide a great deal of insight into the tobacco industry's public and private responses to rising concern over the health effects of passive smoking. Privately, B&W and BAT have conducted internal research on environmental tobacco smoke, at least some of which has supported the conclusion that ETS is harmful to health. The reports from BAT's annual research conferences show that BAT had found harmful substances in sidestream smoke, including glycoproteins and tobacco-specific N-nitrosamines. In addition, the reports indicate that sidestream smoke had been found "biologically active," and therefore potentially carcinogenic, in BAT's laboratory tests. BAT's primary research goal during the mid-1980s was to develop a new cigarette that emitted less irritating, less visible, and less carcinogenic sidestream smoke.
"Publicly, however, B&W, BAT, and the tobacco industry in general have sought to create doubt about the dangerous effects of ETS. BAT's conference reports stated that BAT and B&W were engaged in research to "anticipate and refute" the evidence that passive smoking is dangerous. Based on statements in its conference reports, BAT also appears to have had a policy of "no disclosure" regarding internal research on the health effects of ETS. In addition, U.S. tobacco companies funded "special projects" related to ETS. In at least one case, data from a special project appear to have been falsified. Finally, the tobacco industry has publicly attacked research which, according to internal documents, some of its consultants have privately acknowledged as valid.
"The tobacco industry's strategy regarding passive smoking has been remarkably similar to its strategy regarding active smoking. Although B&W and BAT have privately conducted internal research supporting the conclusion that passive smoking is harmful to health, it has publicly denied that the hazards of ETS have been proven."
The record the tobacco industry has built in response to the OSHA Notice of Proposed Rulemaking is entirely consistent with this past behavior. OSHA should consider this track record when interpreting the current record.
One place in which I agree with the tobacco industry witness is when they urge OSHA to consider all available evidence. In doing so, however it is important that OSHA critically considers all available evidence. In particular the evidence that the tobacco industry put in to the record, such as the analysis of the CPS and NMFS data sets and the Price-Waterhouse economic study do not even pass minimum scrutiny for scientific quality and should be discounted by OSHA. Indeed, had the tobacco industry witnesses applied the same level of scrutiny to these studies (and others, such as Coggins' experiments in which he used mice as controls in rat studies), they would have been soundly criticized as "seriously flawed." The fact that the tobacco industry witnesses failed to apply the same level of scrutiny to the studies the industry put in to the record makes a strong statement about the objectivity and fairness with which these witnesses approached the task of helping OSHA build the highest quality scientific record.
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