1. Re: Occupational Asthma guidelines: a systematic quality appraisal using the AGREE II instrument. Authors' response

    We thank Dr. Nicholson and Prof. Cullinan for their interest in our paper,[1] and welcome the opportunity to respond to their comments and provide clarification.

    We did review the most up-to-date version of all guidelines, including the 2010 version of the BOHRF guidelines. In the "Results" section of our paper, the first column of Table 1 cites the most recent guideline versions published in the peer-reviewed literature; for the BOHRF guidelines that was a summary of the 2004 version, published in 2005.[2] Unsurprisingly, our focus was indeed on the 2010 evidence review and recommendations document,[3] which we appropriately cite in the second column of Table 1 and not only in the "Introduction" section, as suggested. It is not clear to us why Nicholson and Cullinan thought that we appraised the older version and not the latest one.

    As explained in the "Methods" section of our paper, for every guideline reviewed "we thoroughly searched for any accompanying technical and supporting documents in order to better inform our assessments". Accordingly, we did of course visit the BOHRF website and were very much aware of the documents that Nicholson and Cullinan make reference to. However, these are short informational brochures based on the BOHRF guidelines, whereas the ERS document is much more comprehensive; it summarizes all key questions and recommendations along with the associated evidence grades, and is suitably titled as "pocket guidelines".[4] Consequently, the statement in our paper that "ERS was the only guideline that provided a pocket version" cannot, in our opinion, be reasonably described as "factually incorrect".

    In the AGREE II, the existence of summary documents represents only one criterion of a single item (out of four) in the "Applicability" domain. In any event though, since all appraisers were indeed aware and took account of the BOHRF brochures, neither the score for "Applicability" nor the overall score of the BOHRF guidelines is "incorrect and unreliable" as suggested.

    Having said that, it should be pointed out that the AGREE II does not claim to be a perfectly objective and repeatable instrument, even though the high number of appraisers in our review ensures improved reliability. The AGREE II does require a measure of personal judgement, and as its authors note, "the criteria and considerations [outlined] are there to guide, not replace, these judgements".[5] It assesses a strictly defined aspect of guideline quality, and does not evaluate, for example, the clinical appropriateness or validity of the recommendations themselves.[6] Therefore, appraisals using the AGREE II should not be perceived as passing judgement on the work of guideline developers, and are best used as tools to identify areas for further improvement.

    We do acknowledge the mistaken URL in reference 9 of our paper, and thank Nicholson and Cullinan for pointing this out. The correct URL is Mar2010.pdf.

    1 Lytras T, Bonovas S, Chronis C, et al. Occupational Asthma guidelines: a systematic quality appraisal using the AGREE II instrument. Occup Environ Med 2014;71:81-6. doi:10.1136/oemed-2013-101656

    2 Nicholson PJ, Cullinan P, Taylor AJN, et al. Evidence based guidelines for the prevention, identification, and management of occupational asthma. Occup Environ Med 2005;62:290-9. doi:10.1136/oem.2004.016287

    3 Nicholson PJ, Cullinan P, Burge PS, et al. Occupational asthma: Prevention, identification & management: Systematic review & recommendations. London: : British Occupational Health Research Foundation 2010. Mar2010.pdf

    4 European Respiratory Society. ERS Pocket Guidelines. Work-related Asthma: Guidelines for the Management of Work-related Asthma. European Respiratory Society 2012. http://www.ers-

    5 AGREE Next Steps Consortium. The AGREE II instrument. 2009.

    6 Brouwers MC, Kho ME, Browman GP, et al. AGREE II: advancing guideline development, reporting and evaluation in health care. CMAJ 2010;182:E839-842. doi:10.1503/cmaj.090449

    Conflict of Interest:

    None declared

  2. Corrections on Asthma Guidelines review

    We write to correct errors in the paper Occupational asthma guidelines: a systematic quality appraisal using the AGREE II instrument 1.

    The methodology for this study states that the authors reviewed the most up to date versions of guidelines. While in their Introduction the authors cite (their reference 9) a statement from the 2010 BOHRF systematic review 2; within the Results section it is clear that they appraised their reference 35 which is a short version of the 2004 BOHRF systematic review 3 published in Occup Environ Med in 2005 4.

    The authors state that only the European Respiratory Society guidelines produced pocket sized versions. This is factually incorrect. Both the 2004 and 2010 BORF reviews published a series of concise summaries for: a) employers, workers and their representatives, b) general practitioners (GPs) and practice-based nurses, c) occupational health professionals; and d) an algorithm for GPs. All are freely accessible at Consequently the authors scored the BOHRF guidelines incorrectly low for domain 5 (applicability); as a result the overall quality score is incorrect and unreliable.

    Within the reference section the authors' hyperlink to the 2010 BOHRF occupational asthma review is incorrect; it actually being a link to a review of occupational contact dermatitis.

    1. Lytras T, Bonovas S, Chronis C, et al. Occupational Asthma guidelines: a systematic quality appraisal using the AGREE II instrument. Occup Environ Med. 2014;71:81-6.

    2. Nicholson PJ, Cullinan P, Burge PS, et al. Occupational asthma: Prevention, identification & management: Systematic review & recommendations. London: British Occupational Health Research Foundation, 2010.

    3. Nicholson PJ, Cullinan P, Newman Taylor AJ, et al. Evidence based guidelines for the prevention, identification, and management of occupational asthma. Occup Environ Med 2005;62:290-9.

    4. Newman Taylor AJ, Nicholson PJ, Cullinan P, et al. Occupational asthma: Prevention, identification & management: Systematic review & recommendations. London: British Occupational Health Research Foundation, 2004.

    Conflict of Interest:

    Authors of BOHRF guidelines reviewed in this paper.

  3. Lung cancer risk in coal miners: The need for further investigations

    We thank Dr. Morfeld for his comments on our updated mortality study of the U.S. coal miners study.[1] However, we disagree with his assertion that the excess of lung cancer we observed must be attributed to smoking alone. Firstly, despite the smoking prevalence being higher in our cohort than in the U.S. population in 1970, smokers in our population were significantly less likely to be heavy smokers (> 24 cigarettes daily) than men in the general US population (12.4% vs. 28.0%). Secondly, greater weight should be given to the findings from the internal analysis, which controlled for smoking, than to the SMR analysis. Here, as Dr. Morfeld acknowledges, there was a clear dose-response relationship between coal- mine dust exposure and lung cancer. Of note, there was an inverse relationship between radiographic CWP status and lung cancer mortality, implying that CWP and lung cancer were competing causes of death, and leading to weakening of the relationship between dust exposure and lung cancer for the older miners (i.e., those exposed to the high levels of dust existing prior to the 1969 Federal dust regulations).

    Table 1 shows the mean cumulative coal dust exposures by year, as requested by Dr. Morfeld. These levels were lower in the last eight years of follow-up and were higher among lung cancer cases than among all subjects in that decade. This is probably explained by the fact that subjects with higher cumulative exposures were more likely to die during the earlier years of follow-up due to the effects of exposure and their age.

    Dr. Morfeld correctly stated that we lacked work histories on our miners after enrolment (1969 to 1971), but incorrectly asserted that work histories were absent before enrolment. The lack of work histories in the post-enrolment period may have introduced some misclassification of exposures. However, as we and others have emphasized,[2,3] and as demonstrated by our sensitivity analysis, any such misclassification is likely minimal as most participants accumulated the bulk of their exposure before enrolment.

    We agree with Dr. Morfeld, and stated in our article, that the British study of coal miners [4] had better exposure data than our study. While both studies show an excess of lung cancer in their most recent period of follow-up, [1,4] the British findings suggest that the excess is most strongly associated with silica, rather than with coal dust exposure as seen in our study. However, from both studies it is clear that there is an excess of lung cancer among coal miners which is unlikely explained by smoking alone.

    Finally, we are confused by Dr. Morfeld's reference to the healthy worker survivor effect as a reason for dismissing our findings. As has been shown [3] the study was subject to a strong healthy worker survivor effect, causing a reduction in mortality in the early years of follow-up.

    We remain firm in our conclusion that "Our findings and those from the British coal-miners cohort strongly suggest the need for continued investigation of lung cancer mortality and incidence among coal miners."[1]

    Table I: Coal mine dust by year of death among all cohort members and among those for whom the underlying cause of death was lung cancer

    Mean Cumulative Exposure

    Coal Mine Dust


    All Lung Cancer

    (n= 8,829) (n= 568) Calendar year of death 1970-1989 89.7 86.9 1980-1999 82.0 75.5 2000-2007 42.8 51.5


    1. Graber, J.M., Stayner, L.T., Cohen,R.A., Conroy, L.M., Attfield, M. D., Respiratory disease mortality among US coal miners; results after 37 years of follow-up. Occup Environ Med, 2014. 71: p. 30-39. 2. Kuempel, E.D., et al., Exposure-response analysis of mortality among coal miners in the United States. Am J Ind Med, 1995. 28(2): p. 167-84. 3. Attfield, M.D. and E.D. Kuempel, Mortality among U.S. underground coal miners: a 23-year follow-up. Am J Ind Med, 2008. 51(4): p. 231-45 4. Miller, B.G. and L. MacCalman, Cause-specific mortality in British coal workers and exposure to respirable dust and quartz. Occup Environ Med, 2010. 67(4): p. 270-6

    Conflict of Interest:

    None declared

  4. Lung cancer excess risks after coal mine dust exposure?

    Dear Editor,

    I read with interest about the updated US coalminer mortality study[1]. The lung cancer SMR was slightly elevated (SMR=1.08, 95% CI: 1.00-1.18). This excess is unexceptionable because of a higher proportion of smokers at the start of follow-up in 1969/1971 (current smokers: 54%) in comparison to the US male population in 1970 (44.1%). Internal analyses showed an association of lung cancer mortality with coalmine dust exposure but only during the last follow-up interval from 2000 to 2007. Thus, it is of interest to see the distribution of the cumulative exposures across the different calendar time periods. It remains unclear why this information was not given in Table 2 (why does Table 2 report on 568 lung cancer cases but Table 4 on 583 cases?)

    This US study suffers from an incomplete assessment of occupational histories in coalminers: no start and end date of jobs held before 1969/1971 available, no information on jobs held after 1969/1971, and no end date of working as a coalminer for 16.2% of cohort members. Thus, only a crude assessment of exposure to coalmine dust up to the start of follow- up was possible: no time-dependent exposure analysis or lagging of exposures could be done. Crystalline silica concentration data suffered from additional limitations because measurements were available only after 1981 but had to be allocated to jobs held before 1969/1971.

    The largest study to date with better assessment of exposures in a time-dependent manner was performed in the UK[2]: the overall evidence does not support a lung cancer excess risk due to coalmine dust exposure. The findings of the US study do not seem to change this view despite obvious limitations due to the Healthy Worker Survivor Effect (models that adjust for time since last employment do not solve this problem)[3].


    1 Graber JM, Stayner LT, Cohen RA, et al. Respiratory disease mortality among US coal miners; results after 37 years of follow-up. Occup Environ Med 2014;71:30-39.

    2 Miller BG, MacCalman L. Cause-specific mortality in British coal workers and exposure to respirable dust and quartz. Occup Environ Med 2010; 67:270-276.

    3 Naimi AI, Richardson DB, Cole SR. Causal Inference in Occupational Epidemiology: Accounting for the Healthy Worker Effect by Using Structural Nested Models. Am J Epidemiol. 2013;178:1681-1686.

    Conflict of Interest:

    Yes, I have a competing interest. The author performed epidemiological studies on German coalminers and gives scientific advice to the German coalmining industry.

  5. Authors' reply to "Three interpretations of an ecological study

    We thank Dr Idrovo for his thoughts on our paper (1) regarding multilevel approaches to ecological studies (2). We agree with Dr Idrovo that incorporating different levels of aggregation to explore the impact of macro-determinants, or "cultural determinants", would be useful and could, in theory, illuminate important factors beyond causal hypothecation at the individual-level. In our study, however, we were unable to fully explore the effects of different levels of aggregation for the following reasons: (1) a priori it is difficult to define levels of aggregation based on (expected) homogeneity of ecological, social, cultural or economical macro -determinants that could be of importance in investigating associations between cancer incidence and population proxies of this exposure, other than solely based on geographical location or on arbitrarily defined cut- offs in indices like the Human Development Index. (2) Our study included only 165 nations, which limits statistical power on aggregation. Hopefully, national data will become available for more countries with time, but even then the total number of countries in the world is insufficient for exhaustive aggregation.

    In fact, we carried out a multilevel analysis during the development of the methodology in (1) using geographical location (defined as "Continent") as the highest level of aggregation. The results were not described in (1), but a comparison between our final logistic model (using 1995 as the base year for the exposure proxy) and a multi-level logistic alternative showed similar results for the fixed-effects parameters (gross national income per capita, human development index, and 1995 mobile cellular subscriptions [per 100 people]). Aggregation did not provide any additional information, other than an indication that the between- continent variance is relatively small and only about 50% of the variance between countries within a continent. The effect size of the association between mobile cellular subscriptions (per 100 people) and brain cancer (national age-adjusted incidence rates) was similar for both methods but with reduced statistical power. Furthermore, the Bayesian Information Criterion (BIC) indicates that the single level logistic model had a better fit.

    Although we broadly agree with Dr Idrovo's approach to analysing ecological studies we believe the concept of "diseases of civilization" as used by Milham (3) should not be used as an illustration of these macro- determinants. In fact, one of us has published a critique of Milham's paper (4), which we think is an example of the "ecological fallacy" (5) to which Dr Idrovo alludes (2).

    References 1. de Vocht F, Hannam K, Buchan I. Environmental risk factors for cancers of the brain and nervous system: the use of ecological data to generate hypotheses. Occup Environ Med 2013; 70(5): 349-56. 2. Idrovo AJ. Three interpretations of an ecological study. Occup Environ Med 2013; in press. 3. Milham S. Historical evidence that electrification caused the 20th century epidemic of "diseases of civilization". Med Hypotheses 2010;74(2):337-45. 4. de Vocht F and Burstyn I. Historical "evidence" that electrification caused the 20th century epidemic of diseases of civilization and the ecological fallacy. Med Hyptheses 2010; 74(5): 957-8. 5. Morgenstern H. Ecological studies in epidemiology: concepts, principles, and methods. Annu Rev Pub Health 1995; 16: 61-81.

    Conflict of Interest:

    None declared

  6. Obliterative bronchiolitis in workers laying up fiberglass-reinforced plastics with polyester resin and methylethyl ketone peroxide catalyst.

    Cullilinan et al [1] reported six obliterative bronchiolitis (OB) cases with plausible correlation with fiberglass-reinforced plastics (FRP) fabrication. Five of them were boat builders and one worked for a cooling- tower manufacturer. Due to the complexity of the FRP-related boat building processes, the exact agent(s) and process causing OB were difficult to determine. The cooling-tower manufacturing had a simpler manufacturing process, and may help narrow down the actual processes leading to OB. Both industries involved gel coating and manual lamination of FRP.

    Recently, we identified additional two patients with OB and exposure to FRP lamination. The first is a 35 year-old man who has worked in a FRP yacht manufacturing factory for 4 years. He develops persistent dyspnea one year after starting FRP lamination. Lung function shows severe airway obstruction with forced vital capacity (FVC) and forced expiratory volume in 1 second (FEV1) 2.72 and 1.28 liters, respectively. Work exposure included various resins, mainly polyester resin with MEKPO (as catalyst) and styrene (as active diluents).

    The second patient, a 28 year-old man, was a water storage tank repairer for 8 years. His work involved mainly leakage-proof FRP lamination. Dyspnea developed two years after starting job; and progressed badly that he had to quit this year. Chest CT scan revealed air-trapping. Lung function showed severe irreversible obstructive ventilatory defect, with FVC 3.56 liters and FEV1 1.55 liters, respectively.

    Two points are noteworthy in our second patient. He has never been involved in gel coating processes; and he only used polyester resin (with MEKPO and styrene) as glue at work. These imply that the actual process causing OB was likely FRP lamination, not gel coating. Besides, polyester resin containing MEKPO and styrene could be the responsible agent. Nevertheless, these are indirect evidences. The conclusive identification of the actual causal agent(s) warrants further investigation.

    Reference 1. Paul Cullinan, Clive R McGavin, Kathleen Kreiss, et al. Obliterative bronchiolitis in fibreglass workers: a new occupational disease? Occup Environ Med 2013;70:357-9.

    Conflict of Interest:

    None declared

  7. Three interpretations of an ecological study

    The very interesting article by de Vocht et al (1) is a good opportunity to discuss possible interpretations of results obtained in ecological studies. The study included 165 nations as observations and found an association between mobile/cellular telecommunications (per 100 people) and brain cancer (national age-adjusted incidence rates). Although in this case authors were interested in the generation of individual-level causal hypotheses, the same results can be interpreted in two more ways based on multilevel causal approach,(2) promulgated by social epidemiologists.

    One first alternative interpretation can be called "full-population approach". According to the classic article by Rose, determinants of individual cases are not necessarily determinants of incidence rate.(3) In this approach there is not interest in individual or other level inferences, thus results of one ecological study could be valid in the same aggregation level of observations analyzed. Until I know only one study used national data from Nordic countries,(4) and its inconsistent results can be explained per difficulties to explore latency periods. For this, my conclusion is that de Vocht et al study is the most valid study at national aggregation level.

    The second alternative interpretation is interested in an ecological approach but in different aggregation levels. For instance, it occurs when ecological studies based on national data are evidence for national sub- regions inferences. It can be possible but the presence of fallacy is a threat. In this case is needed to explore cross-level fallacies similar to ecological fallacy.(5) A discussion on this same topic is available in two commentaries,(6,7) and inferences on different aggregation-levels can be responsible of heterogeneity observed.

    Explanations of these alternatives approaches should not to be based on biomedical concepts. Macrodeterminants and population-level outcomes act according to ecologic, social, cultural or economical processes. Thus an initial explanation of results can be based on a previous study by Milham, where "civilization" is the main determinant of some diseases with high occurrence in recent years. (8)

    In conclusion, I agree with the authors that in occupational and environmental health ecological studies can be a useful source of evidence. However their results can offer more evidence if they are analyzed according to different aggregation-level approaches.


    1. de Vocht F, Hannam K, Buchan I. Environmental risk factors for cancers of the brain and nervous system: the use of ecological data to generate hypotheses. Occup Environ Med 2013 (in press).

    2. Diez-Roux AV. A glossary for multilevel analysis. J Epidemiol Community Health 2002;56(8):588-94.

    3. Rose G. Sick individuals and sick populations. Int J Epidemiol 1985;14(1):32-8.

    4. Deltour I, Auvinen A, Feychting M, Johansen C, Klaeboe L, Sankila R, Schuz J. Mobile phone use and incidence of glioma in the Nordic countries 1979-2008: consistency check. Epidemiology 2012;23(2):301-7.

    5. Idrovo AJ. Three criteria for ecological fallacy. Environ Health Perspect 2011;119:A332.

    6. Soderqvist F, Carlberg M, Hansson Mild K, Hardell L. Childhood brain tumour risk and its association with wireless phones: a commentary. Environ Health 2011;10:106.

    7. Aydin D, Feychting M, Schuz J, Roosli M; CEFALO study team. Childhood brain tumours and use of mobile phones: comparison of a case- control study with incidence data. Environ Health 2012;11:35.

    8. Milham S. Historical evidence that electrification caused the 20th century epidemic of "diseases of civilization". Med Hypotheses 2010;74(2):337-45.

    Conflict of Interest:

    None declared

  8. Re:The effect of low cadmium exposure on renal biomarkers

    The authors want to thank Prof. Dr. Kawada for his interest in our manuscript entitled 'Adverse effects of low occupational cadmium exposure on renal and oxidative stress biomarkers in solderers' [1]. Prof. Kawada recommends performing the multiple linear regression analysis without adjusting for pack-years of smoking. It is known that smoking is a major source of cadmium exposure [2, 3]. However, we want to underline that the possibility of confounding through a non-cadmium-dependent effect of smoking on the kidney must also be considered [2-6]. Therefore, we decided also to adjust for pack-years of smoking. The renal markers NAG, micro-Alb and RBP showed indeed negative regression coefficients. However, the regression coefficients are very small and very imprecise. To comply with space considerations, we did not show the regression coefficients and standard errors for the intercept, age and pack-years of smoking in the paper. Pack-years of smoking is statistically significantly associated with the oxidative stress marker 8-isoprostane (model Cd-B: regression coefficient, B = 0.05; 95% confidence interval, C.I. = 0.02 - 0.07; p <0.001 and model Cd-U: B = 0.05; 95% C.I. = 0.02 - 0.07; p < 0.01). The association between NAG and pack-years of smoking was borderline statistically significant (model Cd-B: B = 0.03; 95% C.I. = -0.001 - 0.06; p= 0.06 and model Cd-U: B = 0.03; 95% C.I. = -0.004 - 0.06; p = 0.08). No statistically significant association was found between pack-years of smoking and the other renal markers (i.e., IAP, micro-Alb and RBP) and oxidative stress markers (i.e., d-ROM, GPX, SOD, 8-OHdG and AOPP).


    1. Hambach R, Lison D, D'Haese P, Weyler J, Francois G, De Schryver A, Manuel-Y-Keenoy B, Van Soom U, Caeyers T, van Sprundel M. Adverse effects of low occupational cadmium exposure on renal and oxidative stress biomarkers in solderers. Occup Environ Med 2013; 70: 108-13.

    2. Jarup L, Berglund M, Elinder CG, Nordberg G, Vahter M. Health effects of cadmium exposure - a review of the literature and a risk estimate. Scand J Work Environ Health 1998; 24: 1-51.

    3. Bernhard D, Rossmann A, Wick G. Metals in Cigarette Smoke. IUBMB Life 2005; 57: 805-9.

    4. McNamee R. Confounding and confounders. Occup Environ Med 2003; 60: 227-34. 5. Orth SR, Viedt C, Ritz E. Adverse effects of smoking in the renal patient. Tohoku J Exp Med 2001; 194: 1-15.

    6. Mercado C, Jaimes EA. Cigarette smoking as a risk factor for atherosclerosis and renal disease: novel pathogenic insights. Curr Hypertens Rep 2007; 9: 66-72.

    Conflict of Interest:

    None declared

  9. Low solar ultraviolet-B irradiance and serum 25-hydroxyvitamin D levels likely explain the link between nightshift work and ovarian cancer

    The finding that nightshift work is linked to increased risk of ovarian cancer1 is one of a long series of studies finding that nightshift work is associated with increased risk of cancer [e.g., Ref. 2]. While reduced production of melatonin is a possible explanation, a better explanation is that since those on night shift sleep during daytime, they spend less time in the sun when they could be making vitamin D. Solar ultraviolet-B (UVB) irradiance is the primary source of vitamin D for most people.

    Based on a study of night shift work and the risk of cancer in men,2 it was pointed out that a much better explanation than low melatonin was low solar UVB and vitamin D [Grant, Am J Epi, in press]. Additional support is found in the fact that night shift work is also associated with reduced risk of skin cancer.3 Also, both solar UVB and vitamin D have been found inversely correlated with risk of ovarian cancer.4,5

    Thus, those working night shifts should consider taking vitamin D supplements in amounts sufficient to raise serum 25-hydroxyvitamin D concentrations to at least 75 nmol/l if not 100 nmol/l.4 To reach these concentrations could take 1000 to 4000 IU/d vitamin D3.


    1.Bhatti P, Cushing-Haugen KL, Kristine G, et al. Nightshift work and risk of ovarian cancer. Occup Environ Med 2013 70:231-7.

    2. Parent ME, El-Zein M, Rousseau MC, et al. Night work and the risk of cancer among men. Am J Epidemiol. 2012;176:751-9.

    3. Schernhammer ES, Razavi P, Li TY, et al. Rotating night shifts and risk of skin cancer in the nurses' health study. J Natl Cancer Inst. 2011;103:602-6.

    4. Grant WB. Update on evidence that support a role of solar ultraviolet-B irradiance in reducing cancer risk. Anticancer Agents Med Chem. 2013;13:140-6.

    5. Toriola AT, Surcel HM, Calypse A, et al. Independent and joint effects of serum 25-hydroxyvitamin D and calcium on ovarian cancer risk: A prospective nested case-control study. Eur J Cancer. 2010;46:2799-805.

    Conflict of Interest:

    I receive funding from Bio-Tech Pharmacal (Fayetteville, AR), and the Sunlight Research Forum (Veldhoven) and have received funding from the UV Foundation (McLean, VA), the Vitamin D Council (San Luis Obispo, CA), and the Vitamin D Society (Canada).

  10. Re:Environmental tobacco smoke and severe dementia syndromes

    In Reply,

    Professor Kawada [1] commented on our use of Cox regression for the analysis of cross-sectional data. [2] Although logistic regression is often used to compute a prevalence odds ratio (POR) in cross-sectional studies as an estimate of relative risk (RR), when the outcome is not rare this overestimates the RR, sometimes changing the study conclusion. Cox regression has been suggested instead to estimate the prevalence rate ratio (PRR).[3] We recently re-visited the relationship between POR and PRR,[4] using the same dataset as the OEM article.[2] The logistic model showed a POR of 1.22 (95%CI 1.10-1.35) in urban people (60.2% hypertension) versus rural (55.3%), while a Cox model gave a PRR of 1.09 (1.02-1.16). The age-sex adjusted figures were 1.14 (1.03-1.27), and 1.06 (0.99-1.16) for the logistic and Cox models, respectively. In the case of myocardial infarction (5.9% prevalence), however, we found similar RRs between two models (age-sex adjusted POR 2.19, 1.75-2.74, and PRR 2.09, 1.68-2.59). [4] In our recent paper [2], the prevalence of severe dementia syndromes was 10.6%, and if the a logistic model with the same adjustments had been used, the POR would have been 1.43 (1.09-1.88). We believe that the PRR of 1.29 (1.05-1.59) is more appropriate.

    Professor Kawada made good comments on our data that smokers may reduce the risk of severe dementia syndromes if avoiding exposure to environmental tobacco smoke (ETS), although active smoking increased the risk of dementia. The smokers must not smoke together (usually they do as a culture), probably reducing both active and passive smoking in the general population.

    Since the situation of ETS in China remained little changed over the last 3 decades, the ETS level to which the participants were exposed in midlife may be similar to or even higher than that when they were older. We will follow up the cohort to further examine the cause-effect relationship between ETS and severe dementia syndromes.

    Professor Ruoling Chen

    Reference List

    1 Kawada J. Environmental tobacco smoke and severe dementia syndromes (comments). 2013. 2 Chen R, Wilson K, Chen Y, et al. Association between environmental tobacco smoke exposure and dementia syndromes. Occup Environ Med 2013;70 (1):63-9. 3 Lee J. Odds ratio or relative risk for cross-sectional data? Int J Epidemiol 1994;23 (1):201-3. 4 Wang J, Peng WJ, He Q, et al. Relationship between prevalence odds ratio and prevalence rate ratio. Chinese J Health Statistics 2012;29:149-50.

    Conflict of Interest:

    None declared

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