Environmental Health - Latest Comments

Revision

Koenraad Mariën — 2013-01-08T10:13:40Z

The authors have revised the author contributions to read: TH proposed the collection of toenails to permit the chronological comparison for Hg in toenail and head hair, conducted the toenail-Hg and hair-Hg analyses, and provided the Supplemental Material. AT was a significant contributor to almost all aspects of this project involving the Korean and Japanese populations. AMIBS would not have been as successful without her. AS aided in writing the manuscript. TMB contributed significantly to study design and data interpretation. EM aided in the writing of the manuscript and contributed to the acquisition of the data. All authors contributed substantially to the discussion of the data and their analyses, and provided editorial comments to the draft manuscript.

Errata

Paola Pisani — 2012-10-09T07:40:11Z

The trial of early detection of cervix cancer, reference (8), was conducted in Osmanabad district of Maharashtra state, India, not Kerala as stated in the text on page 3. Apologises to the investigators and participants in the study.

Co-signatories for White Paper

Philippe Grandjean — 2012-10-09T07:38:46Z

Co-signatories who indicate support for the White Paper on Developmental Origins of Non-Communicable Disease: Implications for Research and Public Health:*

Helle Raun Andersen, University of Southern Denmark, Denmark

Anna Bal-Price, Institute for Health and Consumer Protection, European Commission Joint Research Centre, Italy

Scott M. Belcher, University of Cincinnati, United States

David Bellinger, Harvard Medical School, USA

Linda S. Birnbaum, National Institute of Environmental Health Sciences and National Toxicology Program, United States

Bruce Blumberg, University of California, Irvine, United States

Alexandre Bonnin, University of Southern California, United States

Maryse Bouchard, Universite de Montreal, Canada

Nicolas Cabaton, Research Center in Food Toxicology, INRA, France

Ludwine Casteleyn, Center for Human Genetics, University of Leuven, Belgium

Sylvaine Cordier, INSERM, Rennes, France

Carl Cranor, University of California, Riverside, United States

Majorie van Duursen, Utrecht University, The Netherlands

Merete Eggesboe, Norwegian Institute of Public Health, Norway

Ruth A. Etzel, University of Wisconsin, United States

Daniele Evain-Brion, Universite Paris Descartes, France

Pam Factor-Litvak, Columbia University, United States

William E. Funk, Northwestern University, United States

David Gee, European Environment Agency, Denmark

Antonio Gonzalez-Bulnes, Departamento de Reproduccion Animal, INIA, Spain

Veit Grote, University of Munich Medical Centre, Germany

Eunhee Ha, Ewha Womans University, South Korea

Russ Hauser, Harvard School of Public Health, United States

Nicholas E. Heger, Brown University, United States

Carsten Heilmann, National University Hospital, Denmark

Birger Heinzow, Schleswig-Holstein State Social Services Agency, Germany, and Sydney Medical School, Australia

Bernhard Hennig, University of Kentucky, United States

Shuk-mei Ho, University of Cincinnati, United States

John W. Hollingsworth, Duke University Medical Center, United States

Howard Hu, University of Toronto, Canada

Vincent Jaddoe, Erasmus Medical Center, The Netherlands

Tina Kold Jensen, University of Southern Denmark, Denmark

Adeline Jondeau-Cabaton, Research Center in Food Toxicology, INRA, France

Robin Joseph, US Environmental Protection Aagency Office of Children's Health Protection, United States

Claudine Junien, Hopital Necker Enfants Malades, France

Margaret R. Karagas, Dartmouth University, United States

Toshihiro Kawamoto, University of Occupational and Environmental Health, Japan

Byungmi Kim, Ewha Womans University, South Korea

Eunjeong Kim, Ewha Womans University, South Korea

Philip J. Landrigan, Mount Sinai School of Medicine, United States

Paige Lawrence, University of Rochester, United States

Brigitte Le Magueresse-Battistoni, INSERM, Lyon, France

Joelle Le Moal, French Institute for Public Health Surveillance, France

Ilene Lee, Ziv Hospital, Israel

Juliette Legler, University Amsterdam, The Netherlands

Marcel Leist, University of Konstanz, Germany

Karen Lillycrop, University of Southampton, United Kingdom

Molly Losh, Northwestern University, United States

Roberto Lucchini, University of Brescia, Italy

Gwynne Lyons, CHEM Trust, United Kingdom

Paolo Mocarelli, University Milano, Italy

Ulla B. Mogensen, University of Copenhagen, Denmark

Jane Muncke, Food Packaging Forum, Switzerland

Susan K. Murphy, Duke University Medical Center, United States

Angel Nadal, Miguel Hernandez University, Spain

Gilles Nalbone, INSERM, Marseille, France

Maria Neira, Department of Public Health and Environment, World Health Organization, Switzerland

Keiko Nohara, National Institute for Environmental Studies, Japan

Cristina Ovilo, Departamento Mejora Genetica Animal, INIA, Spain

Susan Ozanne, University of Cambridge, United Kingdom

Heather Patisaul, North Carolina State University, United States

Merle G. Paule, National Center for Toxicological Research, Food and Drug Administration, United States

Miquel Porta, Universitat Autonoma de Barcelona and IMIM, Spain

Gail S. Prins, University of Illinois, United States

Alvaro Puga, University of Cincinnati, United States

Cristina Rabadan-Diehl, National Heart, Lung, and Blood Institute, National Institutes of Health, United States

Virginia Rauh, Columbia University, United States

Lars Rylander, University of Lund, Sweden

Greet Schoeters, University of Antwerp, Belgium

Toshi Shioda, Harvard Medical School and Massachusetts General Hospital, United States

Kristin Shrader-Frechette, University of Notre Dame, United States

Maria Skaalum Petersen, Department of Occupational Medicine and Public Health, Faroe Islands

Emily C. Somers, University of Michigan, United States

Ana Soto, Tufts University, United States

Alfred Spira, IReSP/INSERM, France

Jordi Sunyer, Center for Research in Environmental Epidemiology, Spain

Jorma Toppari, University of Turku, Finland

Damaskini Valvi, Center for Research in Environmental Epidemiology, Spain

Anne Vambergue, University of Lille, France

Leo van der Ven, National Institute of Public Health and the Environment, The Netherlands

Francois Veillerette, Generations Futures, France

Nadia Vilahur Chiaraviglio, Center for Research in Environmental Epidemiology, Spain

Martine Vrijheid, Center for Research in Environmental Epidemiology, Spain

Pal Weihe, Department of Occupational Medicine and Public Health, Faroe Islands

Christopher P. Weis, National Institute of Environmental Health Science and National Toxicology Program, United States

Daniel Zalko, Research Center in Food Toxicology, Toulouse, France

Changcheng Zhou, University of Kentucky, United States

* Affiliations are indicated for identification purposes only.

Response

Athena Linos — 2012-06-05T11:56:55Z

Gunther Craun questions the validity of our study ¿Oral ingestion of hexavalent chromium through drinking water and cancer mortality in an industrial area of Greece - An ecological study¿ and subsequently questions the causality of the observed association between oral exposure to hexavalent chromium and cancer. He also suggests that our study should not be used for regulatory purposes. We respond to his concerns on the study below, but also consider the relevance of the precautionary principle in making a regulatory decision on matters such as this. Indeed, we believe that given the strong biological plausibility of this association and because the outcome, cancer, is of serious public health concern, our study offers important information and sufficient evidence to call for immediate application of the precautionary principle.
Gunther Craun bases his argument for delaying making preventative guidelines and public health recommendations on the ¿ecological¿ design of the study and the potential ecological bias due to the role of potential confounders and effect modifiers. Indeed we opted to characterize our report as a report on an ¿ecological¿ study although the design is actually a combination of i) a partially ecologic study- given that the outcome (death from cancer by cancer type) is at individual level and ii) a historical cohort design with regards to exposure. He discusses alcohol consumption, smoking, hepatitis and exposure to air and water pollutants as potential confounders. As we have stated in the study, we have already controlled for some potential confounders such as age, gender, and calendar year in residence.
As far as the role of potential confounders such as alcohol consumption, smoking and hepatitis exposure we have no indication of different rates in the comparison population in our analysis. To secure that these factors did not play a confounding role, we performed independent comparisons not only with the general population of Greece but also with the Prefecture of Viotia. We found no differences in the results. With regards to the exposure to other pollutants, we present water pollutants measured during the period of follow up along with chromium and arsenic by the municipality in the attached table. No values higher than the allowed levels were observed in any measurement. The very nature of our variable of interest led to the use of group data with regards to exposure but exposure was expressed uniformly as ¿one group exposure¿- the same in the entire municipality. Ecological bias can more often occur in cases where more than one community with different levels of exposure to confounders is included in the analysis. Since we only dealt with exposure as one municipality, this is not a large risk in our study.
Needless to say that in most studies, exposure misclassification leads to underestimation of the effect (a bias towards a null result) and this would be the case, if a proportion of the population used bottled water and therefore was not exposed but classified as exposed.
As far as causality is concerned, biological plausibility and some type of dose response relationship is usually sufficient to provide strong evidence for a causal mechanism in an observational study. Several animal studies have shown that hexavalent chromium is both genotoxic and cytotoxic and has produced several types of cancer in the gastrointestinal track. Hexavalent chromium definitely metabolizes differently than the non toxic trivalent chromium and remains present in the blood after high level oral exposure. Therefore it is not completely metabolized in the acidic environment of the stomach. Furthermore hexavalent chromium is a known carcinogen to humans when exposed through inhalation. Based on the previous arguments, we strongly believe that the association between oral exposure to hexavalent chromium and cancer is biologically plausible.
As far as a dose relationship is concerned, our study could not lead to estimates of exposure dose. We consider, though, that the observed increase of the SMRs in the last year of observation is an indication of a dose response relationship.
As mentioned, Gunther Craun also argues that since there may be questions regarding elements of the study, that regulatory reform should not be based on these findings. Although it is up to the discretion of each regulatory agency to decide whether or not to use the results of an observational study, it is important to note that in most countries, and definitely in the EU and the USA, the precautionary principle prevails.
The World Health Organization (WHO) and governments have repeatedly affirmed that scientific uncertainty should not prevent protection measures. For example, Article 191 of the Treaty on the Functioning of the European Union, and a number of WHO publications including ¿The precautionary principle: protecting public health, the environment and the future of our children¿ (WHO 2004), have underscored this. Principle 15 of the Rio Declaration of the 1992 United Nations Conference on Environment and Development (UNCED) reads: ¿In order to protect the environment, the precautionary approach shall be widely used by States according to their capabilities. When there are threats of serious and irreversible damage, lack of full scientific certainty shall not be used as a reason for postponing cost-effective measures to prevent environmental degradation.¿ Several courts in the USA have also stated that it is better for regulators to err on the side of caution especially when the effect is serious and irreversible. Undoubtedly cancer is both a serious and, in many instances, an irreversible event and therefore despite limitations in our study, the conclusion should not be to ignore these findings, but rather to encourage further analytical epidemiological studies while taking a precautionary approach in the interim.
Ultimately, we agree that further analytical epidemiologic studies on this issue are needed and that it is important to supplement the ecologic with individual-level information. Working in this direction, we continue investigations in the area that would give us the opportunity to have (among other data) estimates on individual exposures. However, until ours and other studies are complete, we strongly believe our published data provide enough evidence to call for immediate application of the precautionary principle.

Table: Pollutants measured by the municipal authority for which values higher than the permissible levels were never detected (period: June 2005-July 2010)
Pollutant No. of measurements
Al (Aluminium) 34
B (Boron) 11
Cd (Cadmium) 30
Cr (Total Chromium) 77
Cu (Copper) 18
Fe (Iron) 73
Hg (Mercury) 9
Mn (Manganese) 22
Ni (Nickel) 71
Pb (Lead) 32
Sb (Antimony) 11
Se (Selenium) 11

Ecological bias?

Gunther Craun — 2012-06-05T11:56:22Z

We find the ecological study of Linos et al. of interest but disagree that the finding ¿supports the hypothesis of hexavalent chromium (Cr⁺6) carcinogenicity via the oral ingestion pathway of exposure.¿ Potential confounding by personal or occupational exposures coupled with poorly defined Cr⁺6 ingestion exposures raise serious concerns about the validity of the hypothesized association. In ecological studies such as this, where the population group is the unit of observation for exposure and outcome, it is also important to consider ecological bias--the failure of the reported association to reflect an association at the individual level.
Whether Cr⁺6 poses a cancer risk from ingestion exposures in humans is an important public health question (Stout et al. 2008). Occupational epidemiological studies have associated inhalation exposures with increased lung cancer. However, an increased risk of other cancers has not been consistently reported from occupational exposures (Gatto et al. 2010). There is scant epidemiological information about cancer risks associated with the ingestion of environmental levels of Cr⁺6. Since the study of Linos et al. does not provide information about a possible casual association, we urge caution in the use of these data as the basis for making regulatory decisions about waterborne levels of Cr⁺6.
Municipalities in the study area were transformed into industrial areas beginning in the early 1970s with little or no restrictions on disposal of liquid industrial wastes into the Asopos River, which runs through Oinofita, the municipality with elevated cancer mortality. In 2009 there were 700 industries operating in the area with 500 generating undisclosed liquid industrial waste. Occupational, airborne, waterborne, or other environmental exposures to a wide range of undisclosed chemicals could account for the reported elevated risks. If liquid wastes were discharged into the surface and/or ground water sources during the period of industrialization, various chemicals would undoubtedly be present in Oinofita municipal water, possibly contributing to confounding or effect modification. Modest concentrations of arsenic were found in the water, and it is possible that other chemicals may have been present but not measured. Linos et al. note that the available water quality measurements for Oinofita water did not reveal high concentrations of other substances but do not provide a list of chemicals that were measured.
The authors also note that the highest concentration (156 ppb) of Cr⁺6 was measured in a well close to the village of Agios Thomas (population 1090) and that three of the six liver cancer deaths were among residents of this village. Agios Thomas is one of the four villages in Oinofita municipality. This information seems to have been presented as evidence of a strong association between waterborne Cr⁺6 and liver cancer mortality, but readers are not informed whether the contaminated well is part of the Oinofita municipal system and used by residents of Agios Thomas. Rather, the authors offer contradictory statements about this specific exposure: ¿...exposure is expressed as residing in the area assuming that all residents consumed water provided by the municipality (Oinofita)¿ and ¿Well water is very rarely used for drinking in Greece and the level of contamination is very similar.¿ Confusion about the use of this contaminated well also raises concerns that the assumed ecological exposures may not necessarily reflect individual exposures.
Exposure misclassification bias is also possible as ¿Initial concerns were raised after Oinofita area citizens complained about the discoloration and turbidity of their drinking water....¿ with regular protests from 1990s onward. Beaumont et al. (2008) noted that waterborne exposure to Cr⁺6 in an ecological study in China may have been self-limiting due to the lack of palatability of drinking water at high concentrations of Cr⁺6. Armienta-Hernandez and Rodriguez-Castillo (1995) also noted that participants in a study in Mexico did not consume water because of the yellowish color associated with Cr⁺6 concentrations above 500 ppb. Oinofita residents may also have limited their consumption of municipal water and used alternative sources of drinking water (e.g., bottled water). Bottled water use would lower actual exposures, and if bottled water use had been more prevalent among Oinofita residents, nondifferential misclassification bias would result in an over estimate of risk in the current analysis.
All death certificates were scrutinized to exclude all metastatic liver cancers, and this reduces the likelihood for the misclassification of liver cancer mortality. While this strengthens the finding of elevated risks of liver cancer in Oinofita, it does not address the possibility that hepatitis B infection or alcohol consumption may be contributing risk factors. We agree with and strongly support the authors¿ recommendation that ¿Further studies are needed to determine whether this association is causal, and to establish preventative guidelines and public health recommendations.¿ However, to better understand possible risks associated with the ingestion of environmental levels of Cr⁺6, additional epidemiological studies should not use an ecological study design.

Response to comment by Dr. Wilson

Maitreyi Mazumdar — 2012-05-25T13:09:54Z

We agree with Dr. Wilson that the small sample size of our study limits the conclusions that can be drawn regarding associations between childhood blood lead concentrations and intellectual function in adulthood. In fact, we decided not to present results of models with multiple covariates because we believed our sample did not have sufficient power to justify the use of multivariate regression. We did, however, want to present data regarding potential confounders in this study that would be relevant to future studies with a larger number of participants. Thus, of the covariates we thought might be important, we sought to determine which ones affected the association between blood lead concentration and Full Scale IQ. We present that analysis in detail in Table 3. Maternal IQ was not left out of the analysis, but instead was highlighted as a potential confounder. To our knowledge, this study reports the longest period of follow-up of participants from the many influential studies of lead and child development initiated in the 1970s and 1980s. From a scientific perspective, it provides evidence that the effects of lead are persistent, albeit with the limitations of small sample size.

Low-level environmental lead exposure in childhood and adult intellectual function: a follow-up study

Ian Wilson — 2012-05-25T13:09:33Z

The paper by Mazumdar et al. [1] does little for the credibility of prospective health studies. It lacks accuracy and produces questionable conclusions. The report is based on 43 of the 249 individuals who were originally selected from 9489 births at a Boston hospital between 1979 and 1981. The authors indicate that their sample is too small to construct a model to test the significance of the potential confounding factors. As a result the conclusions are based on simple linear regressions between IQ and blood lead levels. Therefore, the statement that 'All analyses included prespecified covariates ¿' is not accurate. This is confirmed by a later statement that their models 'do not control for the effects of confounders.' Other minor errors include a statement that the maximal blood lead level was at age two while Table 1 shows that it occurred at 12 months and inconsistent references to one set of measurements as occurring at either 4 years or 57 months.
Earlier studies of this cohort showed that on adjustment for covariates, the apparent negative correlation coefficients between IQ and blood lead decreased in magnitude and most became non-significant [2]. Mazumdar et al. had access to a vast array of data on potential confounders and conducted linear regressions on these separately. They indicated that inclusion of maternal IQ in the model reduced the regression coefficient from ¿1.89 to ¿1.11 and changed its significance, but they did not indicate whether the relationship still remained significant. They were unable to test for further reduction of the significance of their key relationship by adding other potentially confounding factors such as HOME scores or maternal education to a multiple regression. The omission of confounding factors contributed to the following weaknesses in their findings:
¿ The apparent negative correlation between childhood lead exposure and adult IQ may be reduced in significance or eliminated by confounding factors.
¿ Even if that relationship is significant, their data do not show any significant effect on IQ at blood levels less than 10 ug/dL as they state that only five of the 43 participants had not recorded blood lead levels above this level.
¿ The apparent relationship between adult IQ and school age blood lead levels may not remain significant when corrected for covariates [2], hence there may not be evidence of greater susceptibility to lead exposure during school age years.
Their attempt to explain the relationship between maternal IQ and child IQ as a result of the mothers with higher IQ actively limiting lead exposure of their children or living where there is less likelihood of exposure may well be partially correct. However, that is not a reason to leave maternal IQ out of the analysis. In fact it should be used as a control variable potentially affecting both IQ and blood lead and the analysis should investigate the relationship between the residuals after controlling for maternal IQ. Their conclusion that a larger study should evaluate the effect of maternal IQ is a sensible way forward but it should include potentially confounding factors and control for any interrelationships between the factors.
1. Mazumdar M, Bellinger DC, Gregas M, Abanilla K, Bacic J, Needleman HL: Low-level environmental lead exposure in childhood and adult intellectual function: a follow-up study. Environ Health 2011, 10:24.
2. Bellinger DC, Stiles KM, Needleman HL: Low-Level Lead Exposure, Intelligence and Academic Achievement: A Long-term Follow-up Study. Pediatrics 1992, 96(6):855-861.

Comments on Toxic marine microalgae and shellfish poisoning in the British isles: history, review of epidemiology, and future implications

Stephanie Hinder — 2012-04-13T16:01:43Z

Re: Toxic marine microalgae and shellfish poisoning in the British isles: history, review of epidemiology, and future implications.

We would like to provide the following comments on the above paper, in order to provide additional and more up to date information and to correct some inaccuracies in the original publication.

First, in Table 1, we note that there are no known human cases of poisoning due to PTXs or YTXs, and only limited information exists from experimental animal studies. Further, these toxins should not be classified with the DSP toxin group. Neither have been shown to cause diarrhetic effects (Dominguez et al., 2010, Tubaro et al., 2010). While PTXs are often found in shellfish in combination with DSP toxins and maximum permitted levels for PTXs are set together with the DSP toxin group under the EC Regulation 853/2004, it was demonstrated by Miles et al. (2004) [53] that PTXs do not have a diarrhetic effect and they are no longer considered to be a part of the DSP group of toxins. YTXs do not share the same mode of action as the DSP toxin group and maximum permitted levels for YTXs are set independently under the EC Regulation 853/2004. Also in Table 1, the toxin associated with some species of Pseudo-nitzschia should read as `domoic¿ acid (page 6, paragraph 5, Table 1, and List of Abbreviations page 10).

With regard to UK Monitoring procedures, for clarification (see page 2 paragraph 5) all groups of toxins (PSP, ASP, OA/DTXs, PTXs, AZAs and YTXs) are included in the biotoxin monitoring programmes in all countries of the UK (http://www.food.gov.uk/foodindustry/farmingfood/shellfish/). The Food Standard Agency (FSA) is not itself a National Reference Library (NRL) (page 2 paragraph 5 of the manuscript), but rather it funds the work of a group of various NRL¿s including an NRL on Biotoxins in Live Bivalve Mollusc (LBMs), which is currently undertaken by the Agri-Food and Biosciences Institute in Belfast (http://www.afbini.gov.uk/index/services/services-diagnostic-and-analytical/marine-biotoxins-nrl.htm). In addition, biotoxin monitoring programmes in England and Wales, Scotland and Northern Ireland apply different frequencies of sampling for biotoxin testing (http://www.food.gov.uk/foodindustry/farmingfood/shellfish/algaltoxin/, http://www.food.gov.uk/foodindustry/farmingfood/shellfish/nibiotoxin/,http://www.food.gov.uk/foodindustry/farmingfood/shellfish/ewbiotoxin/). Testing of LBMs for biotoxins monitoring purposes in Northern Ireland has now moved from DARD (page 2, paragraph 7) and is conducted by the Agri-Food and Biosciences Institute.

We also note that European Council Directives 91/492/EEC and 91/493/EEC (described in Table 3) have been replaced, since 2006, by EC 853/2004. This regulation sets down health standards including maximum permitted levels for biotoxins for LBMs, live echinoderms, live tunicates and live marine gastropods. Liquid Chromatography using Mass Spectrometry (LC-MS) is now a reference method for the detection of lipophilic toxins (EU Regulation 15/2011, amending EC 2074/2005).

In Table 3, the limits for PSP and OA-group of toxins should be 800 ¿g/kg and 160 ¿g/kg respectively, measured in whole body or any part edible separately. In addition, on page 2 paragraph 5, the EU procedure following detection of toxins above the maximum regulatory limits is temporary closure of the bed until two consecutive samples taken at least 48hrs apart and testing below the maximum regulatory levels. In practice in the UK, this can effectively result in the closure period of two weeks, as described in the paper, as samples would normally be taken a week apart. We also note that not all species within each genera listed in table 3 are toxic.

Last, we can provide additional information on the 2008 outbreak in the Shetland Islands. 13 areas were affected between April and October (Table 7), however the outbreak was not continuous and concurrent between these areas. Across the region, harvesting areas were closed and re-opened at various points during the 8 month period. Similarly, Loch Tarbert in Argyll and Bute experienced several toxic episodes of DSP (16 positive results) throughout the year (between April 2008 and February 2009), but the area was not continually closed for 11 months, being re-opened for harvesting at several times during this period.

Stephanie Hinder (Institute of Life Science, Swansea University)

March 2012

References:
Dominguez HJ, Paz B, Daranas AH, Norte M, Franco JM, and Fernández JJ. 2010. Dinoflagellate polyether within the yessotoxin, pectenotoxin and okadaic acid toxin groups: characterization, analysis and human health implications. Toxicon 56(2), 191-217.

Tubaro A, Dell'ovo V, Sosa S, and Florio C. 2010. Yessotoxins: a toxicological overview. Toxicon 56(2), 163-172.

Acknowledgements
Thanks to Kasia Kazimierczak at the Food Standards Agency for comments, and help in clarifying several of these issues

Authors' Response by Lisa G. Gallagher, Veronica M. Vieira, David M. Ozonoff, Thomas F. Webster and Ann Aschengrau

Ann Aschengrau — 2011-11-10T14:28:01Z

Dr. Bukowski, writing at the request of the Halogenated Solvents Industry Association (HSIA), calls into question our results on the grounds that they conflict with occupational studies he alleges show no increased risk of breast cancer at much higher PCE exposures. We understand why the HSIA would want to weigh in on this question because it might suggest that their product, PCE, which is in widespread use and causes extensive exposure in the occupational and general community environment, is an unreasonably dangerous product. Given the size of the exposed population, even relatively small risks could result in an unacceptable breast cancer burden on society.

The majority of the occupational studies he cites examined breast cancer mortality, not incidence, as the outcome, and, as such, did not assess associations with the entire spectrum of this, often non-fatal, disease. These studies also had little adjustment for confounding factors and are confounded by socioeconomic status (SES), an important risk factor for breast cancer. This source of confounding would tend to bias the results of the occupational studies towards the null because low SES women tend to be employed in PCE-exposed occupations while high SES women have an increased risk of breast cancer. In contrast, our study considered and controlled for many potential confounding variables, including a woman's educational level. In our general population study subjects we found little evidence of confounding by SES because the irregular pattern of PCE contamination on Cape Cod often resulted in vastly different exposure levels for adjacent residents and neighborhoods. In addition, the different exposure routes in the occupational studies (e.g. mainly inhalation and dermal) may contribute to the alleged divergent findings between our study and this body of literature.

There are also several statements made by Dr. Bukowski that are incorrect. First, the author misinterpreted our exposure measure as an actual mass value in grams. As noted in our paper, our cumulative measure of PCE exposure was not a mass (a ratio measure), but an ordinal measure used to rank our subjects. In addition, the author's statement that our study results are not internally consistent inaccurately represents our data by mixing results for any exposure with those for exposure levels. Our paper noted no increases in the crude odds ratios until 17 and 19 years latency (ORs 1.3-1.4) among ever-exposed women and stated that adjusted odds ratios among ever-exposed women were null for all latent periods.

Each latency analysis also used a latency-specific exposure distribution to determine percentile cut points. Thus, varying results across latent periods may reflect different cut points (paper Table 2). The cut point for current smoothing analysis (RDD>35) is most comparable to the 90th percentile cut point used in the prior analysis. In addition, some odds ratios for the current 90th percentile may be attenuated because of the lower cut points. In general, the reduction of exposure misclassification resulted in assigning subjects who were unexposed in the prior analysis to low exposure in the current analysis. This change resulted in a cleaner referent population and was expected to strengthen the associations. However, the low exposures determined by the automated method were associated with little or no increased risk.

In summary, we maintain that the new exposure assessment method described in this paper is improved from the original method, as evidenced by an improved correlation with sampling data and reflecting a more accurate estimate of water flow in the piping network. An important contribution of this analysis was to demonstrate that the associations between breast cancer and PCE-contaminated drinking water are relatively robust to refinements in exposure modeling.

Comment on the paper by Gallagher et al.: Risk of breast cancer following exposure to tetrachloroethylene-contaminated drinking water in Cape Cod, Massachusetts: reanalysis of a case-control study using a modified exposure assessment.

John Bukowski — 2011-10-19T16:31:32Z

In this most recent iteration of the Cape Cod perchloroethylene (PCE) study, Gallagher et al. [1] have attempted to improve the exposure assessment used in the previous breast cancer articles [2,3]. However, these authors are still left with the same problem, trying to tease out relatively weak effects from residential exposure, when much higher occupational and laboratory exposures have failed to demonstrate them.

The results reported by Gallagher et al. are in conflict with those of occupational studies in which women were exposed to much higher levels. Assuming that the relative delivered dose (RDD) from the current paper is in grams, women on Cape Cod experienced median cumulative (ie, total) exposures of approximately 2 grams PCE [1]. Using calculations from my recent review on the epidemiology surrounding residential PCE, average occupational exposure from dry cleaning in the 1970s (which is germane to the occupational studies published in the literature) is estimated at 100-700 mg per day [4]. Assuming a 200-day work-year, dry cleaning had exposed working women to 20-140 grams PCE per year, or 400-2800 grams during a 20-year working life. Yet, Gallaher et al. acknowledge that ¿in general, null effects have been found for breast cancer¿ in this literature. In their discussion, these authors cite several isolated studies as support for an epidemiologic link between PCE and breast cancer [1]. Yet, neither authoritative reviews [5-9] nor large cohort studies [10,11] have concluded that there is any relationship, despite the aforementioned several orders of magnitude greater exposure for dry cleaners compared with women in Cape Cod. Gallagher et al. also acknowledge that laboratory studies fail to show a relationship between high-level PCE exposure and mammary cancer [1].

The results of the current study are also internally inconsistent. Gallagher et al. state that there was ¿no increase in the odds ratio until 17 and 19 years of latency.¿ But, their adjusted ORs of 1.3-1.4 for the lower latency categories are essentially the same as for those with 11 or more latent years (OR 1.3-1.5), especially given the statistical variability suggested by the confidence intervals [1]. Such findings are inconsistent with the known latency for breast cancer, in which a median latency as long as 22 years has been proposed [12]. Furthermore, none of the ORs reported by Gallagher et al. are statistically significant [1].

Gallagher et al. similarly provide no evidence of any monotonic exposure-response trend that would support a causal relationship. There is no increased risk for ever vs. never exposure, and the risks for those above either the median or 75th percentile are essentially the same as for those below the median (0.9-1.2), especially when statistical variability is considered [1]. This lack of trend would be even more pronounced if exposure groups were appropriately defined as discrete categories of increasing exposure such as quartiles or deciles. Instead, Gallagher et al. provide exposure categories nested within those below them. That is to say, those above 50% include those above 75%, which in turn include those above 90%. This sliding scale hides irregularities in exposure-response that would further detract from causal confidence. For example, adjusted ORs for those in the highest decile are 1.3-1.5, compared with 0.9-1.1 for those above the 50th or 75th percentiles. The high-risk women above the 90th percentile are included within these lower categories, so the risks from lower exposure would be greatly reduced if those with highest exposure were removed. For this reason, more appropriate categories such as 50%-75% and 75%-90% would most likely have shown OR below 1.0 (ie, protective), which is highly inconsistent with any positive trend from increasing exposure.

Gallagher et al. suggest that they have enhanced the previous Cape Cod breast cancer methodology by refining the exposure metric to reduce misclassification [1]. Although the original misclassification purportedly had a greater impact on those with lower exposure, it was still ostensibly nondifferential, meaning similarly distributed among cases and controls. Such misclassification should bias toward the null, so that improved estimates tend to elevate risks. Yet, in the current situation, most revised OR have been driven downward, including those among the highest exposure decile who were least impacted by the misclassification. Most noteworthy are risks among those with exposure below the median, for whom OR of 1.2-2.1 (from the earlier study iterations) have been completely eliminated by ostensibly decreasing nondifferential exposure misclassification (see table 5, ref. [1]). Given that such findings go against expectation, one cannot help but wonder if some degree of ¿data shopping¿ has been carried out in order to explain away these previous contrary findings.

Gallagher et al. acknowledge that there may have been residual confounding, but discount that as an explanation for results given that ¿the irregular pattern of the ACVL pipe locations¿ would make a differential association with exposure unlikely [1]. Yet, the core confounders must have been differentially distributed by exposure, because adjustment for them decreased OR by as much as 50% (see table 4, ref. [1]). Although not yet proven risk factors, other potential confounders such as bone density, use of estrogen replacement therapy, alcohol intake, diet, and obesity have relative risks similar to those associated with some of the core confounders adjusted for in the current study [13-15]. A model-building process with adjustment for a suite of these other factors (rather than one at a time) may have lowered ORs even further. Also, given that confounding covariates (like exposures) are measured imprecisely, residual confounding from risk-factor misclassification is possible even after adjustment [16, 17]. Therefore, residual confounding should be considered as at least a partial explanation for the reported results.

In conclusion, Gallagher et al. have shown different results using the EPA automated model, but have not proven that this is a superior method to the previous manual method. There was a slightly better correlation between measured and modeled values using the automated method (r=0.65) compared with the manual one (r=0.54). But as the authors point out, the measured values ¿are not a standard at all but just another view of the data¿ [1]. Therefore, given the lack of any gold standard by which to judge that the different results produced by Gallagher et al. are superior (ie, closer to the truth) to those produced previously, the current paper appears to be an academic exercise that adds little useful information to the literature on breast cancer causation. Furthermore, the information that it does provide fails at least four of Hill¿s criteria for causation. Namely, the association is weak, inconsistent with the existing human and experimental evidence, and lacking an exposure-response trend [18]. Given these limitations, the results warrant cautious interpretation and do not support a causal relationship between breast cancer and PCE exposure.

References
1. Gallagher LG, Vieiria VM, Ozonoff D, Webster TF, Aschengrau A: Risk of breast cancer following exposure to tetrachloroethylene-contaminated drinking water in Cape Cod, Massachusetts: reanalysis of a case-control study using a modified exposure assessment. Environ Health 2011, 10:47 Available from: http://www.ehjournal.net/content/10/1/47.

2. Aschengrau A, Paulu C, Ozonoff D: Tetrachloroethylenecontaminated drinking water and the risk of breast cancer. Environ Health Perspect 1998, 106 (Suppl 4):947¿953.

3. Aschengrau A, Rogers S, Ozonoff D: Perchloroethylenecontaminated drinking water and the risk of breast cancer: additional results from Cape Cod, Massachusetts, USA. Environ Health Perspect 2003, 111:167¿173.

4. Bukowsk JA: Review of the epidemiologic literature on residential exposure
to perchloroethylene. Crit Rev Toxicol 2011: 1¿12. Available early online from: http://informahealthcare.com/doi/abs/10.3109/10408444.2011.581649.

5. Weiss NS: Cancer in relation to occupational exposure to perchloroethylene. Cancer Causes Control 1995, 6:257-266

6. Lynge E, Anttila A, Hemminki K: Organic solvents and cancer. Cancer Causes Control 1997, 8:406-419

7. Institutes of Medicine: Gulf war and health. Vol. 2: Insecticides and solvents. Washington, DC: National Academies Press; 2002.

8. Mundt KA, Birk T, Burch MT: Critical review of the epidemiological literature on occupational exposure to perchloroethylene and cancer. Int Arch Occup Environ Health 2003, 76:473-491.

9. Ruder AM: Potential health effects of occupational chlorinated solvent exposure. Ann NY Acad Sci 2006, 1076: 207¿227.

10. Boice JD, Marano DE, Fryzek JP, Sadler CJ, McGlaughlin JK: Mortality among aircraft manufacturing workers. Occup Environ Med 1999, 56:581-597.

11. Blair A, Petralia SA, Stewart PA: Extended mortality follow-up of a cohort of dry cleaners. Ann Epidemiol 2003, 13:50-56.

12. Olsson H, Baldetorp B, Ferno M, Perfekt R: Relation between the rate of tumour cell proliferation and latency time in radiation associated breast cancer. BMC Cancer 2003, 3:11. Available from: http://www.biomedcentral.com/1471-2407/3/11.

13. McPherson K, Steel CM, Dixon JM: Breast cancer-epidemiology, risk factors, and genetics. BMJ 2000, 321:624-628.

14. McTiernan A: Behavioral risk factors in breast cancer: Can risk be modified? Oncologist 2003, 8:326-334.

15. Santen RJ, Boyd NF, Chlebowski RT, Cummings S, Cuzick J, Dowsett M, Easton D, Forbes JF, Key T, Hankinson SE, Howell A, Ingle J: Critical assessment of new risk factors for breast cancer: considerations for development of an improved risk prediction model. Endocrine-Related Cancer 2007, 14:169-187.

16. Greenland S: The effect of misclassification in the presence of covariates. Am J Epidemiol 1980, 112:564-569.

17. Marshall JR, Hastrup JL: Mismeasurement and the resonance of strong confounders: Uncorrelated errors. Am J Epidemiol 1996, 143:1069-1078.

18. Hill AB: The environment and disease: association or causation? Proc R Soc Med 1965, 58:295-300.