Rapid Responses to:
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Rapid Responses: Rapid Responses published:
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Are we getting simple?
- Wiel Maessen (20 October 2005)
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scientific or affective approach to tobacco: a question of ethics?
- Danielle A. PIETTE (2 November 2005)
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A Study of Substance?
- Michael J. McFadden (8 November 2005)
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Re: scientific or affective approach to tobacco: a question of ethics?
- Wiel Maessen (8 November 2005)
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Typographical error?
- Martin Bland (14 November 2005)
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Smoke-free workplaces in bars and restaurants
- Fabio Levi, Paolo Colombo, and Carlo La Vecchia (30 November 2005)
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Not a typographical error
- Alan Kelly, and Shane Allwright, on behalf of the All Ireland Bar Study research team (17 December 2005)
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Wiel Maessen, President Forces Netherlands Holland
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Playing on the naive by waving exposure measurements that show a reduction in cotinine levels -- a byproduct of nicotine -- as evidence that Ireland has started to save lives is indefensible. When one says something believed to be "bad" has been reduced then it surely sounds like an improvement. However, in the scientific world there are two thoughts in this respect: 'The dose makes the poison' and 'exposure does not equal harm'. When you want to lower cotinine levels, you can as well forbid to eat tomatoes as they also generate cotinine in the body. No matter how you slice it, this is an exercise in trying to convince everyone that if the water level we're standing in is reduced from two feet to one, we've been saved from drowning. Competing interests: None declared |
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Danielle A. PIETTE, Professor (health promotion & education) School of Public Health, Free University of Brussels (ULB) Route de Lenik 808 CP596, 1070 Bruxelles
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The article by Shane Allwright and colleagues has sound scientific basis and protocol. On the contrary, the answer by Wiel Maessen, is based on emotion from this President of Forces Netherlands, Holland (http://www.forces-nl.org/), a pro-smoking internet site. Is it the role of the BMJ to publish such type of comments? Or is it an ethical question to accept opinion as well as science? Competing interests: None declared |
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Michael J. McFadden, Writer/Researcher/Activist Philadelphia, PA 19104
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Wiel Maessen's comment was actually a fairly decent appraisal of this study. Basically the investigators discovered two things: 1) When you ban smoking in a place there's not as much smoke in the air so people in that place don't breathe in as much smoke. Somehow, even without a grant to do a study, I think I could conjecture that people standing on a desert island in the middle of the Pacific ocean would generally have less car exhaust to breathe in than people in midtown Manhattan. and 2) If you remove smoke from the air, the kinds of irritations that people complain about in smoky places are reduced, particularly if the people questioned about it may have been more self selected than the average of the whole pool toward favorable ban feelings. The study says nothing about long term health, and says nothing about whether levels of nicotine, cotinine, or other substances were harmful in any way past immediate symptomologies of irritation. Additionally the study pool was quite likely to be biased in favor of bar staff without hostility toward the smoking ban, and indeed in favor of bar staff who were sympathetic to it and far more likely to report symptomatic improvements than the average. There have now been several studies carried out similar to this, all to the best of my knowledge sharing roughly the same defect of self- selection and likely bias in reporting of symptomology and all carried out with the researchers probably knowing fairly well beforehand what results to expect. The value of the studies seems far more political than medical. I realize this sounds like a very harsh assessment and that researchers must take grant money where they can find it, but the continued production of studies like this ilustrates the problem that occurs when special interest groups have disproportionate influence in controlling the funding and thereby the direction and determination of what counts as important in medical research. Michael J. McFadden, Author of "Dissecting Antismokers' Brains", www.Antibrains.com Competing interests: I do not now, nor have I ever, had any financial connections to or interest in the tobacco industry other than as a customer. I am the author of a book titled "Dissecting Antismokers' Brains" and am active in a number of Free-Choice groups although I have no financial connections to any of them other than as an occasional contributor. |
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Wiel Maessen, President Forces Netherlands Netherlands
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It seems to become common practice in the medical society to counter serious arguments against the outcomes or methodologies of studies with ad-hominem attacks. When opposing views do not fit in the 'modern' medical ideology, the man is attacked and not the ball. We saw this happening when Enstrom and Kabat's study was published in BMJ. Dr. Michael Siegel, a respected anti-smoking researcher who started to attack the manipulations of the anti-smoking movement in his blog, never gets answers to the questions he raises but instead gets attacked as a 'front for tobacco companies'. And this time again, Mr. Piette's only defense against the disclosure of a real flaw in this study doesn't consist of any counter argument but an attack on the source of the criticism, of whom he even doesn't know the scientific background. The criticism from the opponent is qualified as an 'opinion' while obviously his own personal interest (considering his own background as a 'health promotion & education' professor) doesn't represent an opinion at all. I know that in Belgium they also call this 'arrogance'. Back to my criticism of this study: it IS 'sound science' until the researchers jump into a conclusion that does not cover the outcome of the study. All scientific studies following the scientific method start with an H0 hypothesis that describes the opposite of what we expect a study to find. In this case this H0 would have read: "removing environmental tobacco smoke ban does not influence the amount of cotinine in a human body". What this study proofs (alternative hypothesis) is that it DOES influence the cotinine level. That's all. The word 'protect' in the conclusion implies a kind of damage though. If we would have compared groups of people that were eating a lot of potatoes, tomatoes, aubergines and other Solanaceae with a group of people who never eat these vegetables we also would have found a lower cotinine level. Is the group of non-Solanaceae eaters then 'protected' against these vegetables? A next question one should raise with this study is whether a cotinine level of 20.4
nmol/l is more dangerous than a level of 5.1 nmol/l. Where is the calibration
line that represents real danger? Nobody knows, but probably it's very much
higher than any of these two figures. Competing interests: None declared |
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Martin Bland, Prof. of Health Statistics University of York, YO10 5DD
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In Table 3, the median change in hours exposed outside work (domestic or social) during past 7 days was given as –1.25 with 95% confidence interval –4 to –1.5. The point estimate is outside the confidence interval. What should it be? Competing interests: None declared |
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Fabio Levi, MD, Prof. Institut universitaire de médecine sociale et préventive, Bugnons 17, 1005 Lausanne, Switzerland, Paolo Colombo, and Carlo La Vecchia
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Editor - The introduction of a comprehensive smoke-free law in all indoor workplaces in Ireland – including bars and restaurants – has led to substantial reduction in exposure to second-hand tobacco and to respiratory symptoms of bar workers.1 Such legislation is also supported by the large majority of the population (i.e., 90.4% in Italy where a similar law was introduced in 2005) and, if anything, favourably affects the business of bars and restaurants (9.6% of the population in Italy reported to go more frequently, and 7.4% less frequently to bars and restaurants after the tobacco ban).2,3 No such ban of smoking in indoor public places has yet been adopted in Switzerland. Thus, we considered data of a survey on smoking conducted in September 2005 by the DOXA, a branch of the Gallup International Association, on a sample of 2000 subjects aged 15 to 74, representative of the Swiss adult population in terms of age, sex, and geographic area. The data were collected by ad hoc trained interviewers using a structured computer–assisted telephone interview. In the adult Swiss population, 22.3% were current smokers (23.6% of men, 21.1% of women), and 19.1% former smokers (22.3% of men, 16.2% of women). Overall, 76.8% of the Swiss population was favourable to a total ban of smoking in all indoor public places, 62.2% in all workplaces (including private ones), and 64.1% in bars and restaurants. Among smokers, corresponding proportions were 61.9%, 49.5% and 34.1%, and among ex-smokers 79.6%, 62.6% and 68.4%. This survey confirms that support for smoke-free policies is widespread in the populations of many European countries, and stresses therefore the urgency for adequate political intervention in this vital public health issue.4 Fabio Levi, MD
Paolo Colombo, DSc
Carlo La Vecchia, MD
References 1.Allwright S, Paul G, Greiner B, Mullally BJ, Pursell L, Kelly A, Bonner B, D’Eath M, McConnell B, McLaughlin JP, O’Donovan D, O’Kane E, Perry IJ. Legislation for smoke-free workplaces and health of bar workers in Ireland: before and after study. BMJ 2005:331:1117-20. 2.La Vecchia C, Garattini S, Colombo P, Scarpino V. Attitudes towards smoking regulations in Italy. Lancet 2001;358:245. 3.Gallus S, Zuccaro P, Colombo P, Apolone G, Pacifici R, Garattini S, La Vecchia C. Effects of new smoking regulations in Italy. Ann Oncol (doi:10.1093/annonc/mdj070) 4.Gray N. National and international nicotine dependence. Ann Oncol 2005;16:681-2. Competing interests: None declared |
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Alan Kelly, senior lecturer in biostatistics University of Dublin, Trinity College, and Shane Allwright, on behalf of the All Ireland Bar Study research team
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EDITOR-With regard to our recent paper,1 we thank Professor Bland2 for pointing out that the reported point estimate for the median difference between baseline and follow-up (for the Republic of Ireland responders) for the variable “hours exposed outside work (domestic or social) during there last 7 days” (Table 3 long / Table 1 short version) did not lie within the associated confidence interval. The median difference was given as –1.25 hours with a confidence interval of–4 to –1.5 hours. The possibility of a typographical error was implied. In fact, in one sense at least, both sets of figures are correct. The confidence interval for a median may be calculated in several different ways, depending on certain assumptions. Consideration of both sample size and the distribution of the observations should influence the choice of method. The variable in question is highly unusual. The data are not normally distributed although they display a measure of symmetry. The distribution is heavy tailed and there is also a greater than expected concentration of values at zero. The median is –1.25 with an interquartile range of –5.75 to 0.0. The observations are rounded to whole digits (with only 42 distinct values out of the 136 responses) and heavily tied (e.g. 38 ties at zero, 11 ties at – 4 and 11 ties at –5). Given the question posed at baseline and at follow-up, it is perhaps not surprising that many observations would indeed be tied and especially that a value of zero would dominate. To illustrate the practical problems in providing a reasonable confidence interval for the median of these data, a number of recognized methods have been employed. The resulting confidence intervals are shown below. Normal approximation to Binomial: -4 to 0 Binomial (default ‘centile’ command in Stata (v9, 2005, Stata Corp): -3.9 to 0 Bootstrap (based on the 1000 bootstrapped estimates (using BCa) of the median difference): -4 to 0 Walsh averages*: -4 to –1.5 (*This method, which was used in our paper, is recommended by Gardner & Altman.4 It was computed using Mathematica routines accompanying the book by Prof. J. Baglivo5 and also the macro (cid.ado) written by Dr. Patrick Royston6 for Stata. There are (n)(n+1)/2 or 9316 Walsh averages giving the lower bound as –4 and the upper bound as –1.5. The median of the Walsh averages (the Hodges-Lehmann estimator) is –2.5. The ‘centile’ command with the ‘normal’ option in Stata has not been included because it is inappropriate in view of the distribution of these data, in spite of the large sample size.) We used Mathematica to calculate the confidence intervals for differences in medians (Walsh averages) in our paper. There is good agreement between the four methods for the lower bound of –4. However, the estimate of the upper bound of -1.5 derived from the Walsh averages differs from the other upper bound estimates. The point estimate of the population median using the Hodges-Lehmann estimate, -2.5, also differs from the observed median of –1.25 but is within the reported confidence interval and consistent with the p-value (Wilcoxon Signed Rank test). Which of these intervals is the more appropriate in view of the heavily tied nature of this set of observations? Gardner & Altman3 propose the method of Walsh averages. Under these particular circumstances of heavily tied data, Sprent7 also recommends this approach and the Hodges -Lehmann point estimate of the population median. In the case in point, we find this argument to be compelling. The result of the Wilcoxon Signed Rank test comparing the baseline and follow-up data for this variable is highly significant but is not consistent with four of the above confidence intervals which have upper bounds including 0. Because of the large number of tied values at 0 (close to the observed median), it is impossible for a rank-based confidence interval method to find any other upper bound as all ranks between the 71st and the 108th are zero. None of the above methods for confidence intervals explicitly adjust for ties, whereas the standard method for hypothesis testing based on the Wilcoxon Signed Rank test adjusts the estimated variance for general tied values and also for zeros. In this instance, such adjustments have a pronounced effect on the variance estimate and consequently on both the test statistic and the resulting p-value. The unadjusted variance is 211,939; the adjustment for ties reduces this by 111.25 and the adjustment for zeros reduces the variance by a further 4,754.75 to give a final adjusted variance of 207,073. As yet, there appears to be no standard procedure for the adjustment of either rank-based or exact Binomial confidence intervals in the presence of ties. To conclude, the confidence interval method recommended by both Gardner & Altman and Sprent based on the Walsh averages and the Hodges -Lehmann point estimator provide a more suitable set of bounds for the population median and the result happens to be more consistent with the reported hypothesis test. In the published table (Table 3 long / Table 1 short version), it would have been desirable to include the Hodges-Lehmann point estimate for the median in addition to or even in lieu of the observed median. Similar considerations pertain to the variables “Hours exposed at work (pub or bar) during past 7 days” and “Hours worked in past 2 days” (Republic only) in the same table and median number of respiratory symptoms (Republic only) in Table 4 (long version only), as both of these variables contain large numbers of zero ties. The above issues have no implication for the GEE-based modeling on which the paper’s substantive conclusions are based. 1 Allwright SPA, Paul G, Greiner B, Mullally BJ, Pursell L, et al. Legislation for smoke-free workplaces and health of bar workers in Ireland: before and after study. BMJ, Nov 2005; 331:1117 ; doi:10.1136/bmj.38636.499225.55 2 Bland, M. Typographical error? BMJ Rapid responses, 14 November 2005 3 Bland, M. An Introduction to Medical Statistics, 3rd Edition, p.133, OUP, 2000 4 Gardner, M., Altman, DG. Statistics with Confidence, p.76, BMJ, 1989 5 Baglivo, J. Mathematica Laboratories for Mathematical Statistics, SIAM, 2005 6 Royston, P. “cid.ado” a macro for calculating confidence intervals for differences, Statalist, March. 20, 1998 7 Sprent, P. Applied Nonparametric Statistical Methods, 2nd Edition, Chapman & Hall, 1993 Competing interests: None declared |
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