Displaying 1-10 letters out of 224 published
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:
Obliterative bronchiolitis in workers laying up fiberglass-reinforced plastics with polyester resin and methylethyl ketone peroxide catalyst.
Cullilinan et al  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:
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:
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' . 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:
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).
Re:Environmental tobacco smoke and severe dementia syndromes
Professor Kawada  commented on our use of Cox regression for the analysis of cross-sectional data.  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). We recently re-visited the relationship between POR and PRR, using the same dataset as the OEM article. 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).  In our recent paper , 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
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:
Environmental tobacco smoke and severe dementia syndromes
Chen et al  reported the positive association between environmental tobacco smoke (ETS) and severe dementia syndromes. They mentioned that Cox regression model was applied to detect statistical significance.
I have two queries on their study. First, they conducted cross- sectional study and Cox regression analysis was applied to detect relative risk by adjusting several confounders. They described the methodological explanation in the 4th paragraph of the discussion, mainly avoiding overestimation of the association. Although they quoted one reference  with their previous two papers to select Cox regression analysis, estimation of odds ratio by logistic regression analysis seems appropriate in their cross-sectional study, because statistical advantage of handling censored cases and duration from baseline to event occurrence was not considered for their analysis.
Second, in their Table 1, 791 current smokers were categorized as no ETS exposure group. There is no difference of ETS exposure from others or from himself/herself, and ETS can be applied to never smokers or former smokers in general. This also related to the content in Table 3, which presents risk assessment of ETS to all participants, including current smokers, with severe dementia syndromes. As Table 3 contains results for 3769 never smokers, their conclusion that highest ETS exposure by cumulative dose is a significant risk factor for severe dementia syndromes is acceptable.
The mean age is over 70 years in their study, and the validation of ETS exposure for long-term period should also be evaluated. As there is a report that heavy smoking in midlife becomes a risk of Alzheimer disease , cause-effect relationship between ETS and severe dementia syndromes by longer follow-up study with adjustment of several confounders should be conducted to validate their results.
1. Chen R, Wilson K, Chen Y, et al. Association between environmental tobacco smoke exposure and dementia syndromes. Occup Environ Med 2013;70:63-9.
2. Zhang J, Yu KF. What's the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. JAMA 1998;280:1690-1.
3. Rusanen M, Kivipelto M, Quesenberry CP Jr, et al. Heavy smoking in midlife and long-term risk of Alzheimer disease and vascular dementia. Arch Intern Med 2011;171:333-9.
Conflict of Interest:
The effect of low cadmium exposure on renal biomarkers
Hambach et al  have published cross-sectional study on the associations between cadmium (Cd) exposure and renal or oxidative stress biomarkers in 36 solderers. They adopted multiple regression analysis to detect statistical significance with adjustment of age and pack-years of smoking. In contrast, there is a significant relationship between low levels of Cd exposure and N-acetyl-beta-D-glucosaminidase (NAG) [2,3], with special emphasis on smoking status [4,5].
I have two queries on their study. First, they used pack-years of smoking as independent variables to know the effect of occupational Cd exposure by excluding the effect of Cd exposure by smoking. In their tables 3 and 4, explanation rate expressed by the square values of multiple regression coefficient (R) were under 0.3, and significant levels were near the borderline. I have some doubt on the validity of non- occupational Cd exposure by pack-years of smoking, especially for populations with low levels of Cd exposure. I want to recommend Hambach et al to add the information on the relationship between Cd exposure and renal or oxidative stress markers without adjustment by pack-years of smoking. In addition, regression coefficients and standard errors of age and pack-years of smoking should also be presented to know the effect of age and smoking on several biomarkers.
Second, Hambach et al described in their Table 3 that urinary NAG was normally distributed and logarithmic transformation was not conducted. In addition, some of the gradients of three renal markers except IAP showed negative values, which is difficult to explain biologically.
I suppose that the separation of occupational and non-occupational Cd exposure is not easy in workers with low level of Cd exposure, and direct relationship between Cd exposure and biological markers with only adjustment of age would be informative to make comparison of their results with past reports.
1. Hambach R, Lison D, D'Haese P, et al. Adverse effects of low occupational cadmium exposure on renal and oxidative stress biomarkers in solderers. Occup Environ Med 2013;70:108-13.
2. Kawada T, Koyama H, Suzuki S. Cadmium, NAG activity, and beta 2- microglobulin in the urine of cadmium pigment workers. Br J Ind Med 1989;46:52-5.
3. Noonan CW, Sarasua SM, Campagna D, et al. Effects of exposure to low levels of environmental cadmium on renal biomarkers. Environ Health Perspect 2002;110:151-5.
4. Akesson A, Lundh T, Vahter M, et al. Tubular and glomerular kidney effects in Swedish women with low environmental cadmium exposure. Environ Health Perspect 2005;113:1627-31.
5. Koyama H, Satoh H, Suzuki S, et al. Increased urinary cadmium excretion and its relationship to urinary N-acetyl-beta-D-glucosaminidase activity in smokers. Arch Toxicol 1992;66:598-601.
Conflict of Interest:
Blood lead levels in pregnant women in Nigeria: a cause for great concern
We read the article by Njoku and Orisakwe comparing blood lead levels (BLL) in rural and urban pregnant women in Eastern Nigeria with great interest . The authors found that BLL were substantially higher in rural areas than urban areas (135+/-160 vs 77+/-100 ug/dl). This in itself is an important finding: it may reflect a stronger reliance on locally grown foodstuffs in rural areas, combined with the effect of lead exposure from soil and dust from farming. However, the authors understate the importance of the overall BLL in this area of Eastern Nigeria (99+/-123 ug/dl). This level is substantially higher than has been found during pregnancy in other developing countries (e.g. Mumbai, India (geometric mean 6.4+/-1.69 ug/dl ) or in developed countries where there is a high environmental exposure (e.g. Sweden (smelter) 2.63+/-0.31 ug/dl ), or even in other countries in Africa (e.g. South Africa (median 2.3 ug/dl ). The reported levels are sufficient to cause overt symptoms of lead toxicity. As the authors note, there is free flow of lead though the placenta, with the ratio of fetal:maternal lead being about 0.7-0.9. Thus, the BLL of the newborn infants of these mothers will be about 80 ug/dl, and will rise further with exposure from breast-milk and local foods, and from the environment. These children are at extremely high risk of neurological damage and impaired growth and development, as stated by the authors. It is of note that the Centers for Disease Control and Prevention (CDC) in the USA recommends chelation therapy for BLL of >45 ug/dl in children . The authors provide some data on the lead levels in local staple foods: the high levels in these foods must reflect severe contamination of farmland. The BLL in these pregnant women is of great public health concern, not only for themselves, but also for their children and subsequent generations.
1. Njoku CO, Orisakwe OE. Higher blood lead levels in rural than urban pregnant women in Eastern Nigeria. Occ Environ Med 2012.doi 10.1136/oemed-2012-100947.
2. Raghunath R, Tripathi RM, Sastry VN, Krishnamurthy TM. Heavy metals in maternal and cord blood. Sci Total Environ 2000;250:135-41.
3. Lagerkvist BJ, Ekesrydh S, Englyst V, Nordberg GF, Soderberg HA, Wiklund DE. Increased blood lead and decreased calcium levels during pregnancy: A prospective study of Swedish women living near a smelter. Am J Pub Health 1996;86:1247-52.
4. Rudge CV, Rollin HB, Nogueira CM, Thomassen Y, Rudge MC, Odland JO. The placenta as a barrier for toxic and essential elements in paired maternal and cord blood samples of South African delivering women. J Environ Monitor 2009;11:1322-30.
5. Centres for Disease Control. Lead. Managing elevated blood lead levels among young children: recommendations from the Advisory Committee on Childhood Lead Poisoning Prevention Committee 2002. Available at: http://www.cdc.gov/nceh/lead/CaseManagement/caseManage_chap3.htm (accessed 20 September 2012).
Conflict of Interest:
Cadmium, arsenic and lung cancer: A complete picture?
The Editor Occupational and Environmental Medicine
14th September, 2012
Cadmium, arsenic and lung cancer: A complete picture?
Were the occupational lung cancers among former employees at the cadmium recovery plant located near Denver, CO, USA due to cadmium exposures, arsenic exposures or both? One of us recently suggested that a "simultaneous analysis of lung cancer risks in relation to both recent and distant cadmium and arsenic exposures" was required, and that researchers should "let the data speak and not design an analysis that assumes in advance which of these variables is important". Although the new paper from Robert Park and co-workers  does not appear to respond to these suggestions, we believe their data could assist with authoritative interpretation.
Findings from the only other cohort study to carry out an analysis of occupational lung cancer risks in relation to quantitative estimates of cadmium and arsenic exposures (and exposures to other metals) were consistent with the hypotheses that recent arsenic exposures are more important than distant exposures, and that cadmium exposures are unimportant. In addition indirect evidence that a late stage carcinogen was operating at the Globe plant has already been provided. Analyses of recent exposures in the current study could be illuminating and need to be carried out.
In addition, analyses in which the size of the arsenic effect is not constrained need to be reported. Some of the later stages of processing at the Globe plant would only have had exposures to cadmium because the arsenic had already been removed (e.g. solution, pigment). This contrast provides a cell with cadmium effects only. Therefore, there is the potential for separating the independent effects of arsenic and cadmium, without applying constraints to the modelling.
1. Sorahan T. Cadmium, arsenic and lung cancer: the bigger picture. Occup Med (Lond) 2010;60:236.
2. Park RM, Stayner LT, Petersen MR, et al. Cadmium and lung cancer mortality accounting for simultaneous arsenic exposure. Occup Environ Med 2012;69:303-9.
3. Jones SR, Atkin P, Holroyd C et al. Lung cancer mortality at a UK tin smelter. Occup Med (Lond) 2007;57:238-45.
4. Sorahan T. Lung cancer morality in arsenic-exposed workers from a cadmium recovery plant. Occup Med (Lond) 2009;59:264-6.
1Institute of Occupational and Environmental Medicine, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK;
2Environmental and Occupational Health Sciences, University of Illinois at Chicago, School of Public Health (W) M/C 922, 2121 West Taylor St., Chicago, IL 60612, USA
Conflict of Interest:
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