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Article

Heterogeneity in the Relationship between Disinfection By-Products in Drinking Water and Cancer: A Systematic Review

by
Tarik Benmarhnia
1,*,†,
Ianis Delpla
2,†,
Lara Schwarz
1,
Manuel J. Rodriguez
2 and
Patrick Levallois
3,4
1
Department of Family Medicine and Public Health & Scripps Institution of Oceanography, University of California, San Diego, CA 92093, USA
2
École Supérieure D’aménagement du Territoire et de Développement Régional (ESAD), Université Laval, 1624 Pavillon Savard, Québec, QC G1K-7P4, Canada
3
Direction de la Santé Environnementale et de la Toxicologie, Institut National de Santé Publique du Québec, Québec, QC G1V 5B3, Canada
4
Axe Santé des Populations et Pratiques Optimales en Santé, Centre de Recherche du Centre Hospitalier Universitaire (CHU) de Québec, Québec, QC G1V 2M2, Canada
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Int. J. Environ. Res. Public Health 2018, 15(5), 979; https://doi.org/10.3390/ijerph15050979
Submission received: 28 February 2018 / Revised: 7 May 2018 / Accepted: 9 May 2018 / Published: 14 May 2018
(This article belongs to the Special Issue Drinking Water Quality and Human Health)
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Abstract

:
The epidemiological evidence demonstrating the effect of disinfection by-products (DBPs) from drinking water on colon and rectal cancers is well documented. However, no systematic assessment has been conducted to assess the potential effect measure modification (EMM) in the relationship between DBPs and cancer. The objective of this paper is to conduct a systematic literature review to determine the extent to which EMM has been assessed in the relationship between DBPs in drinking water in past epidemiological studies. Selected articles (n = 19) were reviewed, and effect estimates and covariates that could have been used in an EMM assessment were gathered. Approximately half of the studies assess EMM (n = 10), but the majority of studies only estimate it relative to sex subgroups (n = 6 for bladder cancer and n = 2 both for rectal and colon cancers). Although EMM is rarely assessed, several variables that could have a potential modification effect are routinely collected in these studies, such as socioeconomic status or age. The role of environmental exposures through drinking water can play an important role and contribute to cancer disparities. We encourage a systematic use of subgroup analysis to understand which populations or territories are more vulnerable to the health impacts of DBPs.

1. Introduction

Disinfection is widely used for drinking water treatment to inactivate pathogens and to prevent waterborne diseases. This process can produce disinfection by-products (DBPs), which result from a chemical reaction between disinfectants such as chlorine and organic or inorganic matter in the water [1]. Among the various DBPs (>600) [2], trihalomethanes (THMs) are the most studied due to their relatively high prevalence and concentration in drinking water.
Numerous studies assess the association between exposure to chlorinated water and diverse health outcomes. Some of them investigate the influence of chlorinated water or THMs on reproductive health, such as small for gestational age [3,4], stillbirth, and low birth rate [3,5]. However, the majority of epidemiological studies investigate the impact of such water quality exposure on cancer outcomes. Epidemiological studies have shown that DBP exposure through drinking water is associated particularly with some types of cancer, namely, colon, rectal, and bladder [2,6,7,8], though contrasting results for colon and rectal cancers have been found [6]. Reviews revealing a consistent association between long-term exposure to THMs and risk of bladder cancer have been published in recent years [8,9,10]. Additionally, several epidemiological studies found other risk factors for colon, rectal, and bladder cancer, such as tobacco consumption [11,12,13,14,15], and dietary and genetic factors [13,16,17,18,19,20,21]. Other potential risk factors include urban residence [13,22] and alcohol consumption [13,16]. The duration of exposure is also associated with an increasing risk of bladder cancer [7].
In a pooled analysis published in 2004, it was observed that the effect of THMs on bladder cancer risk was more pronounced in men than women [23]. Several explanations were discussed, including residual confounding and biological plausibility such as sex differences in metabolizing DBPs. A proposed mechanism to explain this difference is the role of sex hormones in the modulation of enzymes that metabolize chlorination by-products (for chloroform and brominated THMs) into reactive metabolites. Other possible explanations are anatomic differences or variation in voiding frequency between men and women, which can influence the action of DBPs as hormone disruptors [23].
To our knowledge, besides the study described above, no systematic review has attempted to synthesize the literature that directly evaluates potential effect measure modifiers other than sex in the association between disinfection by-products in drinking water and cancer. Yet, several other potential effect measure modifiers such as socio-economic status could be particularly relevant to shaping policies that target vulnerable populations or territories and aim to reduce inequalities in cancer risks. This could help frame interventions to target specific subgroups and ensure exposure of DBPs, such as THMs and HAAs, are below harmful levels. Such assessments for populations that are unfairly treated in regard to their environmental exposures are relevant to the field of environmental justice, which has drawn recent attention with important concerns about other water contaminants such as with lead exposure in the Flint crisis [24]. In addition, these assessments can identify which populations and territories are more vulnerable to the harmful effects of exposure to THMs and inform interventions to reduce health disparities.
The literature in relation to environmental health inequalities emerged during these last two decades and distinguishes two types of environmental inequalities: (i) inequalities related to the level of exposure and (ii) inequalities related to the level of vulnerability (when the effect of an environmental exposure is modified according to different sub-groups strata of the population) [25,26,27,28].
Findings from studies investigating differential exposure have shown that deprived populations can be more exposed to contaminants in drinking water [5,24,29,30,31,32,33,34,35]. Among the few studies dedicated to the analysis of environmental inequalities associated with DBPs, all focus on inequalities related to the level of exposure, and show contrasting results. Briggs et al. [36] found a positive association between levels of THMs in drinking water and an index of multiple deprivation. Inversely, Delpla et al. [32] showed that municipalities with a lower material deprivation index have a lower risk of elevated THMs levels at their tap. Evans et al. [33] and Vrijheid et al. [35] found no significant relationships between individuals or community deprivation and THM concentrations in drinking water. The absence of an association could be linked to one or more of the following: geographical size of a study that could attenuate the associations when extending the studied area [36], lower participation among people of lower education, type of exposure studied, location of both the early-life and current residence of the person, and/or type of socio-economic indicator chosen [35].
This review focuses on differential vulnerability, which refers to the notion of “effect measure modification” in epidemiology. This concept of vulnerability can be defined as a “greater likelihood of an adverse outcome given a specific exposure, compared with the general population, including both host (individual) and environmental (contextual) factors” [37]. We will focus this review on socioeconomic status (SES) variables, but we will also consider potential vulnerability factors as sex/gender and health behaviors.
Differences in health opportunities and resources related to social class, race, and geographic area can lead to a lower health status for vulnerable groups [38]. For example, it has been shown in the last decade that that neighborhood SES can modify the effect of air pollutants [38,39] on mortality. Such evidence has been used to provide recommendations towards interventions aimed at specific low SES areas to reduce inequalities in mortality [40]. Understanding the effect measure modification (EMM) in the health impacts of DBPs will be useful in shaping policies to reduce cancer inequalities through proportionated interventions aimed at reducing exposure to DBPs. Yet, some drinking water distribution systems may span large geographic areas and serve large and diverse populations, so interventions on the distribution systems may be insufficient. In such a case, targeted local interventions in the infrastructure or through awareness campaigns may be relevant.
The overall objectives of this paper are to synthetize the literature studying the role of EMM in the relationship between DBPs in drinking water and cancer, and understand the extent to which it has been assessed in past epidemiological studies. If this epidemiological information is available in existing publications, this review will allow us to report the epidemiological evidence on the differential vulnerability of DBPs to cancer risk. If epidemiological information is lacking on this topic, the review will serve to highlight the knowledge gap and motivate future studies in this area. Two successive stages are performed: (i) An updated systematic review is conducted on studies measuring the association between DBPs in drinking water and colorectal and bladder cancers and (ii) The presence of EMM is evaluated according to socio-demographic characteristics and individual behaviors considered in the identified studies.

2. Materials and Methods

2.1. Search Strategy

We aim to identify all epidemiological studies investigating the effects of DBPs in drinking water on colorectal and bladder cancers published in English in scientific journals between January 1975 and August 2015. The strategy used to conduct this review, in accordance with the PRISMA guidelines [41], consisted of grouping keywords that represented (i) the exposure (namely DBPs in drinking water) and (ii) the health outcomes (namely, colon and rectal cancer (CRC) and bladder cancer). Keywords, titles, and abstracts were searched in PubMed and Elsevier Embase on the Ovid SP portal and Web of Science. There was no restriction on geographical location.
The keywords used for the literature search are as follows: (Disinfection by-products OR Disinfection-by-products OR water disinfection OR chlorination by-products OR water chlorination OR trichloromethane OR chloroform OR bromoform OR tribromomethane OR dichlorobromomethane OR dibromochloromethane OR THM OR Haloacetic acids) AND (colorectal cancer OR colorectal neoplasm OR colon cancer OR rectal cancer OR bladder cancer OR CRC).
Terms describing EMM were not included at this stage to avoid being too restrictive. Instead, we appraised the EMM assessment during the data extraction process (see below). We did not include keywords related to study design at this stage, but instead assessed this question while selecting studies (see below).

2.2. Selection of Studies

In the first stage, the first two authors of this paper read and screened the abstract of each returned article.
Papers meeting the following criteria were excluded from our review:
  • Commentaries, editorials, review articles, or meta-analysis
  • Studies not performed on human populations
  • Studies not published in English
  • Studies not including DBPs in drinking water or chlorinated water as the exposure
  • Qualitative studies
When reviewers disagreed about whether a study should be excluded, the two met in person to discuss until an agreement was reached.
In a second stage, papers selected in the previous stage were fully screened and then excluded according to the following criteria:
  • Studies not reporting a quantitative estimate between DBPs in drinking water or chlorinated waters and colorectal cancer or bladder cancer
  • Studies not including colorectal cancer and/or bladder cancer as health outcomes
  • Studies using an ecological design or only a spatial analysis
In addition, the reference section of studies identified was searched, and relevant references that were not initially identified were added.

2.3. Data Extraction

Selected articles were reviewed separately by the first two researchers, and each documented the first author, location, date of publication, sample size, study design (case-control, cohort study or case-cohort), exposure measurement, health outcomes assessed, effect size and CI (Confidence Interval), whether they included EMM assessment, and which subgroup was included in this assessment.
Finally, among studies that did not include an assessment of EMM, collected variables (i.e., those presented in the sample description used as confounders) that could potentially be used for an EMM assessment were reported. We included variables for which there is some evidence of EMM in other environmental determinants of population health and with documented mechanisms leading to a differential effect. We thus included the following variables: age [42,43,44,45], socio-economic factors [39,46], urbanization level [47,48], smoking status, and other health behaviors (alcohol consumption, diet, and physical activity) [49,50]. Sex was also included in the review. Socio-economic factors include SES variables such as education and occupation, as well as indexes that were used in the studies selected.

3. Results

3.1. Description of Studies Selected

The abstracts of 226 articles were assessed, and 26 articles were retained for in-depth review after applying the first stage of exclusion criteria. Nine articles were added after screening the references of selected papers. Finally, 19 scientific articles were retained following the second stage exclusion criteria (Figure 1).
Table 1 summarizes the studies that provide a measure of the cancer risk associated with exposure to disinfection by-products through drinking water.
Eleven studies were conducted in North America, six in Europe, and two in Asia (Taiwan). The studies were published between 1981 and 2010. The majority of studies focus on bladder cancer (n = 14), followed by colon cancer (n = 4) and rectal cancer (n = 5). All are case-control studies, with the exception of Wilkins and Comsock, [51] and Koivusalo et al., [52] which are cohort studies. The majority of studies use values of THMs issued from field measurements (n = 10) or modeling (n = 3) to assess the exposure. The remaining ones use presence or absence of chlorinated water (n = 4) or the level of mutagenicity of waters (n = 2) as a marker of exposure to DBPs. THMs cut-offs varied between studies, because the exposure was calculated differently. Studies use long term (>30 years), fixed [53,54], or variable duration of exposure [55,56], although the majority use fixed levels (but different values) of DBPs [57,58,59,60,61,62]. The association between exposure and health issues is almost always assessed using logistic regression, with Odds Ratios (OR) or Risks Ratios (RR) being reported.
Odds Ratios in the studies selected are between 1.20 and 2.99 for bladder cancer, 0.90 and 1.66 for colon cancer, and 1.01 and 1.68 for rectal cancer (for OR calculated on the whole population under study). Fourteen studies found a significant relationship with cancer [52,53,55,57,58,59,60,62,63,64,65,66,67,68]. Five studies did not find a significant relationship between exposure to chlorinated water/DBPs and cancer, four of which studied bladder cancer [51,54,56,61] and one which studied colon cancer [69]. The majority of studies considered the exposure to THMs as a group of compounds without assessing the effects of the different compounds. Only the studies of Bove et al. [59,63] considered different species of THMs (chloroform, bromoform, bromodichloromethane, and chlorodibromomethane) in their analysis.
Approximately half of the studies assess EMM (n = 10), but the majority of them estimate it relative to different sex subgroups (total: n = 8, n = 6 for bladder cancer and n = 2 both for rectal and colon cancers). Generally, higher ORs and relationships that are more significant were noted for men when studying bladder and colon cancers. For example, in the study of Cantor et al. [64], an OR of 1.8 for men compared to an OR of 0.6 for women was found for bladder cancer. For rectal cancer, the results are contradictory, but the number of studies is too limited (n = 2) to draw any conclusion relative to sex. For women, only one study, which is also a cohort study [52], noted positive relationships for bladder and rectal cancer. Moreover, the study of Koivusalo et al. [52] is the only one that found higher risks for women than men (for the three different types of cancer). The duration of exposure was associated with an increase in bladder cancer risk for men only [7,64]. Fewer studies assessed the EMM relative to smoking status (n = 3). Finally, one study assessed EMM considering gene polymorphisms [62]. Generally, in all studies, the EMM assessment was conducted with stratified analyses. In the study of King et al. [57], an interaction term between exposure and sex was calculated.

3.2. Covariables Collected

Table 2 reports the variables collected that could be used for potential EMM assessment for each of the selected studies.
Although EMM is not assessed in the majority of the selected papers, some studies collect covariables that could be used in the future for an heterogeneity assessment. Information about age is commonly collected in selected studies (n = 16). Moreover, other individual data such as education and/or occupation status are collected in some of the studies (n = 11). Others report an SES index (n = 12). Information about the level of urbanization is also frequently collected (n = 9).

4. Discussion

The majority of studies assessing the relationship between THMs and cancer are case-control studies that focus on bladder cancer. These studies use exposure data issued from direct measurements or modelling. The majority of studies found an association between chronic exposure to THMs and bladder cancer. This review revealed that the majority of studies assessed EMM, but primarily for the effect of sex. Six studies show that the EMM of sex in the association between exposure to DBPs and bladder cancer may exist, with a higher effect for men than for women. However, only a very small number of studies have assessed this effect modification for other cancer sites such as colon and rectal cancer (n = 2 for both cancers), thus preventing any further conclusion about this parameter. Sex has been found as a more consistent EMM in bladder cancer, and several mechanisms have been proposed, as previously mentioned. More precisely, pharmacokinetic models in humans have shown that the activity of CYP2E1, which plays a role in chloroform metabolism, could be higher in men than in women [70,71]. The role of sex hormones in the modulation of enzymes that metabolizes DBPs has also been proposed. Brominated THMs are metabolized through a glutathione conjugation reaction and several studies have shown that glutathione transferases are regulated by thyroid and sex hormones [23].
The duration of exposure is also an important factor, as the outcomes are cancers at different sites with different latencies, and it is associated with an increase in bladder cancer risk for men [7,64]. Despite this, the exposure metrics (duration of exposure and means of exposure assessment) differ between studies selected. This could influence the results obtained in the different studies selected.
Furthermore, many epidemiological studies on DBPs collect other covariables in addition to sex, such as SES, age, urbanization level, and smoking status but without evaluating the EMM. This information could be used to conduct an EMM assessment in future studies and document the existence of vulnerability factors in the association between DBPs and risk of cancer (notably, bladder, colon, and rectal cancers). Of course, EMM assessments should be motivated and rely on a documented hypothesis. These assessments are particularly useful in targeting populations or territories that public policies should prioritize to reduce socio-demographic inequalities in cancer risks from water contaminants exposure. We thus strongly encourage further studies to assess the role of socio-demographic factors such as SES, age, or urbanization level as potential EMMs in the relationship between DBPs and cancer risk. It is also important to mention that various methods exist in the literature that assess EMM, such as the Breslow-Day test, the Wald χ2 test, and the regression-based test of interaction [72,73].
This review is subject to a number of limitations. We included studies that measured THMs exposure in a range of different approaches. THMs exposure measurement methods have drastically evolved in the last decades, but we decided to include older studies, as they can inform one of our aims to reveal possible EMM in the association between THMs exposure and cancer risk. We added 9 studies after the screening of references of existing papers. This may be due to some missing keywords (e.g., “treated drinking water”) despite the fact that we used similar keywords to other systematic reviews on this topic. Finally, some papers that have been recently published are not included in our review. For instance, a case–control study conducted in Spain and Italy by Villanueva et al. [74] assessed the impact of long-term exposure to THMs on colorectal cancer and found no association, considering the total population without including any EMM assessment.
The majority of the studies quantitatively include gender as a subgroup analysis, but very few studies focused on other potentially relevant EMMs such as SES. However, we observed that many studies included in the review collected standard details on covariates that could be, but often are not, used as stratifying variables. By doing so, we aim to highlight that EMM assessments are easily feasible in future studies using data that is already collected. We hope that this assessment will encourage future studies that will assess which populations are more vulnerable to the impacts of THMs exposure.
Studies on EMM are important to improve public health interventions and better estimate the potential benefits of an intervention (or its public health impact). For instance, within a large community/municipality that is supplied by a unique water treatment plant, inequalities in DBP exposure can be associated with the geographical location of deprived population groups within the municipality, living in neighborhoods or sectors with relatively high concentration of DBPs in drinking water (explained by variable residence time of water in the distribution network, pipe material, age and maintenance, or plumbing systems characteristics). In these cases, local interventions can reduce DBP exposure and could include two dimensions: (i) infrastructure: for instance, the renewal of distribution system pipes locally, including plumbing systems, the improving of the local hydraulic management of the system to reduce stagnation of water, or a better management of booster disinfection; and (ii) promoting awareness campaigns directed at deprived population concerning the exposure to DBPs through tap water and other domestic water uses as bath and showering (for example, the adequate use of domestic equipment to reduce DBPs, such as domestic water filtering, boiling, and refrigeration).

5. Conclusions

Inequalities in cancer incidence according to socio-demographic characteristics [75,76,77] or location (ex: rural areas compared to urban areas) have been highlighted in the literature. The role of environmental exposures such as drinking water contaminants can play an important role in such disparities. However, the documentation of EMM evidence is still lacking. We therefore strongly recommend greater use of subgroup analysis when possible, which will provide a greater understanding of which populations or territories are more vulnerable to the impacts of DBPs.

Author Contributions

T.B. and I.D. contributed to the study design, conducted the review, and took the lead in drafting the manuscript. L.S., M.J.R., and P.L. contributed to interpretation of data, provided critical revisions to the manuscript, and approved the final draft.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Rook, J.J. Formation of haloforms during chlorination of natural waters. J. Water Treat. Exam 1974, 23, 234–243. [Google Scholar]
  2. Richardson, S.D.; Plewa, M.J.; Wagner, E.D.; Schoeny, R.; DeMarini, D.M. Occurrence, genotoxicity, and carcinogenicity of regulated and emerging disinfection by-products in drinking water: A review and roadmap for research. Mutat. Res. 2007, 636, 178–242. [Google Scholar] [CrossRef] [PubMed]
  3. Grellier, J.; Bennett, J.; Patelarou, E.; Smith, R.B.; Toledano, M.B.; Rushton, L.; Briggs, D.J.; Nieuwenhuijsen, M.J. Exposure to Disinfection By-Products, Fetal Growth, and Prematurity: A Systematic Review and Meta-analysis. Epidemiology 2010, 21, 300–313. [Google Scholar] [CrossRef] [PubMed]
  4. Levallois, P.; Gingras, S.; Marcoux, S.; Legay, C.; Catto, C.; Rodriguez, M.; Tardif, R. Maternal exposure to drinking-water chlorination by-products and small-for-gestational-age neonates. Epidemiology 2012, 23, 267–276. [Google Scholar] [CrossRef] [PubMed]
  5. Toledano, M.B.; Nieuwenhuijsen, M.J.; Best, N.; Whitaker, H.; Hambly, P.; de Hoogh, C.; Fawell, J.; Jarup, L.; Elliott, P. Relation of trihalomethane concentrations in public water supplies to stillbirth and birth weight in three water regions in England. Environ. Health Perspect. 2005, 113, 225–232. [Google Scholar] [CrossRef] [PubMed]
  6. Rahman, M.B.; Driscoll, T.; Cowie, C.; Armstrong, B.K. Disinfection by-products in drinking water and colorectal cancer: A meta-analysis. Int. J. Epidemiol. 2010, 39, 733–745. [Google Scholar] [CrossRef] [PubMed]
  7. Villanueva, C.M.; Fernandez, F.; Malats, N.; Grimalt, J.O.; Kogevinas, M. Meta-analysis of studies on individual consumption of chlorinated drinking water and bladder cancer. J. Epidemiol. Community Health 2003, 57, 166–173. [Google Scholar] [CrossRef] [PubMed]
  8. Villanueva, C.M.; Cordier, S.; Font-Ribera, L.; Salas, L.A.; Levallois, P. Overview of disinfection by-products and associated health effects. Curr. Environ. Health Rep. 2015, 2, 107–115. [Google Scholar] [CrossRef] [PubMed]
  9. Hrudey, S.E.; Fawell, J. 40 years on: What do we know about drinking water disinfection by-products (DBPs) and human health? Water Sci. Technol. Water Supply 2015, 15, 667. [Google Scholar] [CrossRef]
  10. Parbery, G.; Tivey, D.; McArthur, A. Epidemiological association between chlorinated water and overall risk of cancer: A systematic review. JBI Database Syst. Rev. Implement. Rep. 2012, 10, 1–14. [Google Scholar] [CrossRef]
  11. Chyou, P.-H.; Nomura, A.M.; Stemmermann, G.N. A prospective study of colon and rectal cancer among Hawaii Japanese men. Ann. Epidemiol. 1996, 6, 276–282. [Google Scholar] [CrossRef]
  12. Engel, L.S.; Taioli, E.; Pfeiffer, R.; Garcia-Closas, M.; Marcus, P.M.; Lan, Q.; Boffetta, P.; Vineis, P.; Autrup, H.; Bell, D.A. Pooled analysis and meta-analysis of glutathione S-transferase M1 and bladder cancer: A HuGE review. Am. J. Epidemiol. 2002, 156, 95–109. [Google Scholar] [CrossRef] [PubMed]
  13. Haggar, F.A.; Boushey, R.P. Colorectal cancer epidemiology: Incidence, mortality, survival, and risk factors. Clin. Colon Rectal Surg. 2009, 22, 191–197. [Google Scholar] [CrossRef] [PubMed]
  14. Heineman, E.F.; Zahm, S.H.; McLaughlin, J.K.; Vaught, J.B. Increased risk of colorectal cancer among smokers: Results of a 26-year follow-up of us veterans and a review. Int. J. Cancer 1994, 59, 728–738. [Google Scholar] [CrossRef] [PubMed]
  15. Kälble, T. Etiopathology, risk factors, environmental influences and epidemiology of bladder cancer. Der Urol. Ausg. A 2001, 40, 447–450. [Google Scholar] [CrossRef]
  16. Freudebhiem, J.; Graham, S.; Marshall, J.R.; Haughey, B.P.; Wilkinson, G. A case-control study of diet and rectal cancer in western New York. Am. J. Epidemiol. 1990, 131, 612–624. [Google Scholar] [CrossRef]
  17. Kiemeney, L.A.; Schoenberg, M. Familial transitional cell carcinoma. J. Urol. 1996, 156, 867–872. [Google Scholar] [CrossRef]
  18. Ross, R.K.; Jones, P.A.; Yu, M.C. Bladder cancer epidemiology and pathogenesis. Semin. Oncol. 1996, 23, 536–545. [Google Scholar] [PubMed]
  19. Slattery, M.L.; Sweeney, C.; Murtaugh, M.; Ma, K.N.; Caan, B.J.; Potter, J.D.; Wolff, R. Associations between vitamin D, vitamin D receptor gene and the androgen receptor gene with colon and rectal cancer. Int. J. Cancer 2006, 118, 3140–3146. [Google Scholar] [CrossRef] [PubMed]
  20. Vena, J.E.; Graham, S.; Freudenheim, J.; Marshall, J.; Zielezny, M.; Swanson, M.; Sufrin, G. Drinking water, fluid intake, and bladder cancer in western New York. Arch. Environ. Health Int. J. 1993, 48, 191–198. [Google Scholar] [CrossRef] [PubMed]
  21. Woolcott, C.; King, W.; Marrett, L. Coffee and tea consumption and cancers of the bladder, colon and rectum. Eur. J. Cancer Prev. 2002, 11, 137–145. [Google Scholar] [CrossRef] [PubMed]
  22. Sharp, L.; Donnelly, D.; Hegarty, A.; Carsin, A.-E.; Deady, S.; McCluskey, N.; Gavin, A.; Comber, H. Risk of several cancers is higher in urban areas after adjusting for socioeconomic status. Results from a two-country population-based study of 18 common cancers. J. Urban Health 2014, 91, 510–525. [Google Scholar] [CrossRef] [PubMed]
  23. Villanueva, C.M.; Cantor, K.P.; Cordier, S.; Jaakkola, J.J.K.; King, W.D.; Lynch, C.F.; Porru, S.; Kogevinas, M. Disinfection byproducts and bladder cancer: A pooled analysis. Epidemiology 2004, 15, 357–367. [Google Scholar] [CrossRef] [PubMed]
  24. Hanna-Attisha, M.; LaChance, J.; Sadler, R.C.; Champney Schnepp, A. Elevated blood lead levels in children associated with the Flint drinking water crisis: A spatial analysis of risk and public health response. Am. J. Public Health 2016, 106, 283–290. [Google Scholar] [CrossRef] [PubMed]
  25. Brulle, R.J.; Pellow, D.N. Environmental justice: Human health and environmental inequalities. Annu. Rev. Public Health 2006, 27, 103–124. [Google Scholar] [CrossRef] [PubMed]
  26. Evans, G.W.; Kantrowitz, E. Socioeconomic status and health: The potential role of environmental risk exposure. Ann. Rev. Public Health 2002, 23, 303–331. [Google Scholar] [CrossRef] [PubMed]
  27. Pearce, J.R.; Richardson, E.A.; Mitchell, R.J.; Shortt, N.K. Environmental justice and health: The implications of the socio-spatial distribution of multiple environmental deprivation for health inequalities in the United Kingdom. Trans. Inst. Br. Geogr. 2010, 35, 522–539. [Google Scholar] [CrossRef]
  28. O’Neill, M.S.; Jerrett, M.; Kawachi, I.; Levy, J.I.; Cohen, A.J.; Gouveia, N.; Wilkinson, P.; Fletcher, T.; Cifuentes, L.; Schwartz, J. Health, wealth, and air pollution: Advancing theory and methods. Environ. Health Perspect. 2003, 111, 1861–1870. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  29. Balazs, C.; Morello-Frosch, R.; Hubbard, A.; Ray, I. Social Disparities in Nitrate Contaminated Drinking Water in California’s San Joaquin Valley. Environ. Health Perspect. 2011, 1272–1278. [Google Scholar] [CrossRef] [PubMed]
  30. Balazs, C.L.; Morello-Frosch, R.; Hubbard, A.E.; Ray, I. Environmental justice implications of arsenic contamination in California’s San Joaquin Valley: A cross-sectional, cluster-design examining exposure and compliance in community drinking water systems. Environ. Health 2012, 11, 84. [Google Scholar] [CrossRef] [PubMed]
  31. Balazs, C.L.; Ray, I. The drinking water disparities framework: On the origins and persistence of inequities in exposure. Am. J. Public Health 2014, 104, 603–611. [Google Scholar] [CrossRef] [PubMed]
  32. Delpla, I.; Benmarhnia, T.; Lebel, A.; Levallois, P.; Rodriguez, M.J. Investigating social inequalities in exposure to drinking water contaminants in rural areas. Environ. Pollut. 2015, 207, 88–96. [Google Scholar] [CrossRef] [PubMed]
  33. Evans, A.M.; Wright, J.M.; Meyer, A.; Rivera-Núñez, Z. Spatial variation of disinfection by-product concentrations: Exposure assessment implications. Water Res. 2013, 47, 6130–6140. [Google Scholar] [CrossRef] [PubMed]
  34. Hales, S.; Black, W.; Skelly, C.; Salmond, C.; Weinstein, P. Social deprivation and the public health risks of community drinking water supplies in New Zealand. J. Epidemiol. Community Health 2003, 57, 581–583. [Google Scholar] [CrossRef] [PubMed]
  35. Vrijheid, M.; Martinez, D.; Aguilera, I.; Ballester, F.; Basterrechea, M.; Esplugues, A.; Guxens, M.; Larrañaga, M.; Lertxundi, A.; Mendez, M.; et al. Socioeconomic status and exposure to multiple environmental pollutants during pregnancy: Evidence for environmental inequity? J. Epidemiol. Community Health 2012, 66, 106–113. [Google Scholar] [CrossRef] [PubMed]
  36. Briggs, D.; Abellan, J.J.; Fecht, D. Environmental inequity in England: Small area associations between socio-economic status and environmental pollution. Soc. Sci. Med. 2008, 67, 1612–1629. [Google Scholar] [CrossRef] [PubMed]
  37. Kuh, D.; Ben-Shlomo, Y.; Lynch, J.; Hallqvist, J.; Power, C. Life course epidemiology. J. Epidemiol. Community Health 2003, 57, 778–783. [Google Scholar] [CrossRef] [PubMed]
  38. Barceló, M.A.; Saez, M.; Saurina, C. Spatial variability in mortality inequalities, socioeconomic deprivation, and air pollution in small areas of the Barcelona Metropolitan Region, Spain. Sci. Total Environ. 2009, 407, 5501–5523. [Google Scholar] [CrossRef] [PubMed]
  39. Hajat, A.; Hsia, C.; O’Neill, M.S. Socioeconomic Disparities and Air Pollution Exposure: A Global Review. Curr. Environ. Health Rep. 2015, 2, 440–450. [Google Scholar] [CrossRef] [PubMed]
  40. Benmarhnia, T.; Rey, L.; Cartier, Y.; Clary, C.M.; Deguen, S.; Brousselle, A. Addressing equity in interventions to reduce air pollution in urban areas: A systematic review. Int. J. Public Health 2014, 59, 933–944. [Google Scholar] [CrossRef] [PubMed]
  41. Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Ann. Intern. Med. 2009, 151, 264–269. [Google Scholar] [CrossRef] [PubMed]
  42. Bell, M.L.; Zanobetti, A.; Dominici, F. Who is more affected by ozone pollution? A systematic review and meta-analysis. Am. J. Epidemiol. 2014, 180, 15–28. [Google Scholar] [CrossRef] [PubMed]
  43. Boffetta, P. Human cancer from environmental pollutants: The epidemiological evidence. Mutat. Res. 2006, 608, 157–162. [Google Scholar] [CrossRef] [PubMed]
  44. Gouveia, N.; Fletcher, T. Time series analysis of air pollution and mortality: Effects by cause, age and socioeconomic status. J. Epidemiol. Community Health 2000, 54, 750–755. [Google Scholar] [CrossRef] [PubMed]
  45. Gundry, S.; Wright, J.; Conroy, R. A systematic review of the health outcomes related to household water quality in developing countries. J. Water Health 2004, 2, 1–13. [Google Scholar] [PubMed]
  46. Hajat, A.; Diez-Roux, A.V.; Adar, S.D.; Auchincloss, A.H.; Lovasi, G.S.; O’Neill, M.S.; Sheppard, L.; Kaufman, J.D. Air pollution and individual and neighborhood socioeconomic status: Evidence from the Multi-Ethnic Study of Atherosclerosis (MESA). Environ. Health Perspect. 2013, 121, 1325. [Google Scholar] [CrossRef] [PubMed]
  47. Bertin, M.; Chevrier, C.; Serrano, T.; Monfort, C.; Rouget, F.; Cordier, S.; Viel, J.-F. Association between prenatal exposure to traffic-related air pollution and preterm birth in the PELAGIE mother–child cohort, Brittany, France. Does the urban–rural context matter? Environ. Res. 2015, 142, 17–24. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  48. Madrigano, J.; Jack, D.; Anderson, G.B.; Bell, M.L.; Kinney, P.L. Temperature, ozone, and mortality in urban and non-urban counties in the northeastern United States. Environ. Health 2015, 14, 3. [Google Scholar] [CrossRef] [PubMed]
  49. Turner, M.C.; Krewski, D.; Pope, C.A., III; Chen, Y.; Gapstur, S.M.; Thun, M.J. Long-term ambient fine particulate matter air pollution and lung cancer in a large cohort of never-smokers. Am. J. Respir. Crit. Care Med. 2011, 184, 1374–1381. [Google Scholar] [CrossRef] [PubMed]
  50. Sobue, T. Association of indoor air pollution and lifestyle with lung cancer in Osaka, Japan. Int. J. Epidemiol. 1990, 19 (Suppl. 1), S62–S66. [Google Scholar] [CrossRef] [PubMed]
  51. Wilkins, J.R.; Comstock, G.W. Source of drinking water at home and site-specific cancer incidence in Washington County, Maryland. Am. J. Epidemiol. 1981, 114, 178–190. [Google Scholar] [CrossRef] [PubMed]
  52. Koivusalo, M.; Pukkala, E.; Vartiainen, T.; Jaakkola, J.J.; Hakulinen, T. Drinking water chlorination and cancer–a historical cohort study in Finland. Cancer Cause Control 1997, 8, 192–200. [Google Scholar] [CrossRef]
  53. McGeehin, M.A.; Reif, J.S.; Becher, J.C.; Mangione, E.J. Case-control study of bladder cancer and water disinfection methods in Colorado. Am. J. Epidemiol. 1993, 138, 492–501. [Google Scholar] [CrossRef] [PubMed]
  54. Freedman, D.M.; Cantor, K.P.; Lee, N.L.; Chen, L.-S.; Lei, H.-H.; Ruhl, C.E.; Wang, S.S. Bladder cancer and drinking water: A population-based case-control study in Washington County, Maryland (United States). Cancer Cause Control 1997, 8, 738–744. [Google Scholar] [CrossRef]
  55. Zierler, S.; Feingold, L.; Danley, R.A.; Craun, G. Bladder cancer in Massachusetts related to chlorinated and chloraminated drinking water: A case-control study. Arch. Environ. Health Int. J. 1988, 43, 195–200. [Google Scholar] [CrossRef] [PubMed]
  56. Koivusalo, M.; Hakulinen, T.; Vartiainen, T.; Pukkala, E.; Jaakkola, J.J.; Tuomist, J. Drinking water mutagenicity and urinary tract cancers: A population-based case-control study in Finland. Am. J. Epidemiol. 1998, 148, 704–712. [Google Scholar] [CrossRef] [PubMed]
  57. King, W.D.; Marrett, L.D.; Woolcott, C.G. Case-control study of colon and rectal cancers and chlorination by-products in treated water. Cancer Epidemiol. Biomark. Prev. 2000, 9, 813–818. [Google Scholar]
  58. Chevrier, C.; Junod, B.; Cordier, S. Does ozonation of drinking water reduce the risk of bladder cancer? Epidemiology 2004, 15, 605–614. [Google Scholar] [CrossRef] [PubMed]
  59. Bove, G.E.; Rogerson, P.A.; Vena, J.E. Case-control study of the effects of trihalomethanes on urinary bladder cancer risk. Arch. Environ. Occup. Health 2007, 62, 39–47. [Google Scholar] [CrossRef] [PubMed]
  60. Chang, C.-C.; Ho, S.-C.; Wang, L.-Y.; Yang, C.-Y. Bladder cancer in Taiwan: Relationship to trihalomethane concentrations present in drinking-water supplies. J. Toxicol. Environ. Health Part A 2007, 70, 1752–1757. [Google Scholar] [CrossRef] [PubMed]
  61. Michaud, D.S.; Kogevinas, M.; Cantor, K.P.; Villanueva, C.M.; Garcia-Closas, M.; Rothman, N.; Malats, N.; Real, F.X.; Serra, C.; Garcia-Closas, R. Total fluid and water consumption and the joint effect of exposure to disinfection by-products on risk of bladder cancer. Environ. Health Perspect. 2007, 1569–1572. [Google Scholar] [CrossRef] [PubMed]
  62. Cantor, K.P.; Villanueva, C.M.; Silverman, D.T.; Figueroa, J.D.; Real, F.X.; Garcia-Closas, M.; Malats, N.; Chanock, S.; Yeager, M.; Tardon, A. Polymorphisms in GSTT1, GSTZ1, and CYP2E1, disinfection by-products, and risk of bladder cancer in Spain. Environ. Health Perspect. 2010, 118, 1545–1550. [Google Scholar] [CrossRef] [PubMed]
  63. Bove, G.E.; Rogerson, P.A.; Vena, J.E. Case control study of the geographic variability of exposure to disinfectant byproducts and risk for rectal cancer. Int. J. Health Geogr. 2007, 6, 18. [Google Scholar] [CrossRef] [PubMed]
  64. Cantor, K.P.; Lynch, C.F.; Hildesheim, M.; Dosemeci, M.; Lubin, J.; Alavanja, M.; Craun, G. Drinking Water Source and Chlorination Byproducts I. Risk of Bladder Cancer. Epidemiology 1998, 9, 21–28. [Google Scholar] [CrossRef] [PubMed]
  65. Gottlieb, M.S.; Carr, J.K. Case-control cancer mortality study and chlorination of drinking water in Louisiana. Environ. Health Perspect. 1982, 46, 169. [Google Scholar] [CrossRef] [PubMed]
  66. Hildesheim, M.E.; Cantor, K.P.; Lynch, C.F.; Dosemeci, M.; Lubin, J.; Alavanja, M.; Craun, G. Drinking Water Source and Chlorination Byproducts II. Risk of Colon and Rectal Cancers. Epidemiology 1998, 9, 29–35. [Google Scholar] [CrossRef] [PubMed]
  67. King, W.D.; Marrett, L.D. Case-control study of bladder cancer and chlorination by-products in treated water (Ontario, Canada). Cancer Cause Control 1996, 7, 596–604. [Google Scholar] [CrossRef]
  68. Villanueva, C.M.; Cantor, K.P.; Grimalt, J.O.; Malats, N.; Silverman, D.; Tardon, A.; Garcia-Closas, R.; Serra, C.; Carrato, A.; Castaño-Vinyals, G.; et al. Bladder cancer and exposure to water disinfection by-products through ingestion, bathing, showering, and swimming in pools. Am. J. Epidemiol. 2007, 165, 148–156. [Google Scholar] [CrossRef] [PubMed]
  69. Kuo, H.-W.; Tiao, M.-M.; Wu, T.-N.; Yang, C.-Y. Trihalomethanes in drinking water and the risk of death from colon cancer in Taiwan. J. Toxicol. Environ. Health Part A 2009, 72, 1217–1222. [Google Scholar] [CrossRef] [PubMed]
  70. Tanaka, E. Gender-related differences in pharmacokinetics and their clinical significance. J. Clin. Pharmacol. Ther. 1999, 24, 339–346. [Google Scholar] [CrossRef]
  71. Meibohm, B.; Beierle, I.; Derendorf, H. How important are gender differences in pharmacokinetics? Clin. Pharmacokinet. 2002, 41, 329–342. [Google Scholar] [CrossRef] [PubMed]
  72. Kaufman, J.S.; MacLehose, R.F. Which of these things is not like the others? Cancer 2013, 119, 4216–4222. [Google Scholar] [CrossRef] [PubMed]
  73. Altman, D.G.; Bland, J.M. Interaction revisited: The difference between two estimates. Br. Med. J. 2003, 326, 219. [Google Scholar] [CrossRef]
  74. Villanueva, C.M.; Gracia-Lavedan, E.; Bosetti, C.; Righi, E.; Molina, A.J.; Martín, V.; Boldo, E.; Aragonés, N.; Perez-Gomez, B.; Pollan, M.; et al. Colorectal cancer and long-term exposure to trihalomethanes in drinking water: A multicenter case–control study in Spain and Italy. Environ. Health Perspect. 2017, 125, 56–65. [Google Scholar] [CrossRef] [PubMed]
  75. Askari, A.; Aziz, O.; Currie, A.; Athanasiou, T.; Faiz, O. Inequalities in Colorectal Cancer Risk and Educational Level in Developed Countries: A Systematic Review and Meta-Analysis of Observational Studies. Br. J. Surg. 2015, 2015, 187. [Google Scholar]
  76. Choi, K.M. Investigation of cancer mortality inequalities between rural and urban areas in South Korea. Aust. J. Rural Health 2016, 24, 61–66. [Google Scholar] [CrossRef] [PubMed]
  77. Woods, L.; Rachet, B.; Coleman, M. Origins of socio-economic inequalities in cancer survival: A review. Ann. Oncol. 2006, 17, 5–19. [Google Scholar] [CrossRef] [PubMed]
Ijerph 15 00979 g001 550
Figure 1. Flowchart of the selection of studies.
Figure 1. Flowchart of the selection of studies.
Ijerph 15 00979 g001
Table 1. Description of studies included in the review.
Table
(a) Bladder cancer.
(a) Bladder cancer.
StudiesLocationYear of PublicationSample SizeStudy DesignDisinfection by-Products MeasurementSubgroups Included in the AnalysisEffect Size and CI
Wilkins and Comstock [51]Maryland, USA198181 cases and 30,699 controlsCohortExposure to chlorinated drinking waterSexAll: RR = 2.2 (0.71–9.39); Men: RR = 1.80 (0.80–4.75); Women: RR = 1.60 (0.54–6.32)
Zierler et al. [55]Massachusetts, USA1988614 cases and 1074 controlsCase-controlDuration of exposure to chlorinated drinking watern.d.All: OR = 2.7 (1.7–4.3)
McGeehin et al. [53]Colorado, USA1993327 bladder cancer and 261 other-cancer controlsCase-controlQuestionnaire & data for TTHM from site visit of water utilitiesSmoking StatusNon–Smokers: OR = 2.9 (1.2–7.4); Smokers: OR = 2.1 (1.1–3.8)
King and Marrett [67]Ontario, Canada1996696 cases and 1545 controlsCase-controlQuestionnaire about source of water. Water source and chlorination status were provided directly by treatment plant surveys. TTHMs modellingn.d.All: OR = 1.66 (1.11–2.51)
Freedman et al. [54]Maryland, USA1997294 cases and 2326 controlsCase-controlExposure to chlorinated drinking waterSex, smoking habitsAll: OR = 1.4 (0.7–2.9); Men: OR = 2.2 (0.8–5.1); Women: OR = 0.6 (0.2–2.2)
Koivusalo et al. [52]Finland1997621 431CohortQuestionnaires. Information on water-pipe connections, past drinking water quality, and treatment practices by waterworks was obtained from administrative registers and municipal waterworks. The level of mutagenicity was estimated by modellingSexAll: RR = 1.12 (0.93–1.36); Men: RR = 1.03 (0.82–1.28); Women: RR = 1.48 (1.01–2.18)
Cantor et al. [64]Iowa, USA19981123 cases and 1983 controlsCase-controlTTHMs in tap water (measures + estimations)Sex, smoking habitsAll: OR = 1.3 (0.9–2.0); Men: OR = 1.8 (1.2–2.7); Women: OR = 0.6 (0.3–1.4)
Koivusalo et al. [56]Finland1998732 cases and 914 controlsCase-controlQuestionnaires. Information on water-pipe connections, past drinking water quality, and treatment practices by waterworks was obtained from administrative registers and municipal waterworks. The level of mutagenicity was estimated by modellingSexMen: OR = 1.17 (0.87–1.57); Women: OR = 1.14 (0.71–1.82)
Chevrier et al. [58]France2004281 cases and 272 controlsCase-controlTTHMs modellingSexAll: OR = 2.99 (1.1–8.5); Men: OR = 3.73 (1.2–11); Women: OR = 1.55 (0.1–32)
Bove et al. [59]New York, USA2007182 cases and 385 controlsCase-controlTTHMs in tap water + water consumptionn.d.THM: OR = 2.34 (1.01–3.66); CLF: OR = 2.55 (1.25–4.66); BRF: OR = 3.05 (1.51–5.69); BDCM: OR = 2.49 (1.19–4.48)
Chang et al. [60]Taiwan2007403 cases and 403 controlsCase-controlTTHMs in tap watern.d.All: OR = 2.11 (1.43–3.11)
Michaud et al. [61]Spain2007397 cases and 664 controlsCase-controlQuestionnaire and records searches (including THM measurements)n.d.All: OR = 2.06 (0.83–5.08)
Villanueva et al. [68]Spain20071219 cases and 1271 controlsCase-controlQuestionnaire and records searches (including THM measurements)SexAll: OR = 2.10 (1.09, 4.02); Men: OR = 2.53 (1.23, 5.20); Women: OR = 1.50 (0.26, 8.61)
Cantor et al. [62]Spain2010680 cases and 714 controlsCase-controlTTHMs in tap waterGene polymorphismAll: OR = 1.8 (0.9–3.5)
NB: n.d.: No data; OR: Odds Ratio; RR: Risk Ratio; CLF: Chloroform; BRF: Bromoform; BDCM: Bromodichloromethane; Q1: lowest THM concentrations quartile; Q4: highest THM concentrations quartile.
Table
(b) Colon and rectal cancers.
(b) Colon and rectal cancers.
StudiesLocationYear of PublicationSample SizeStudy DesignExposition MeasurementSite of CancerSubgroups Included in the AnalysisEffect Size and CI
Gottlieb and Carr [65]Louisiana, USA1982546 cases and 534 controlsCase-controlExposure to chlorinated drinking waterRectaln.d.All: OR = 1.68 (1.17–2.42)
Koivusalo et al. [52]Finland1997621 431CohortQuestionnaires. Information on water-pipe connections, past drinking water quality, and treatment practices by waterworks was obtained from administrative registers and municipal waterworks. The level of mutagenicity was estimated by modellingColon and rectalSexColon: All: RR = 0.90 (0.77–1.04); Men: RR = 0.83 (0.66–1.04); Women: RR = 0.95 (0.78–1.85). Rectal: All: RR = 1.04 (0.86–1.26); Men: RR = 0.85 (0.66–1.09); Women: RR = 1.38 (1.03–1.85).
Hildesheim et al. [66]Iowa, USA1998560 colon cases, 537 rectal cases, and 1983 controlsCase-controlTTHMs in tap waterColon and rectaln.d.Colon: OR = 1.06 (0.7–1.6); Rectal: OR = 1.66 (1.1–2.6)
King et al. [57]Ontario, Canada2000767 colon cases, 661 rectal cases, and 1545 controlsCase-controlQuestionnaire about source of water. Water source and chlorination status were provided directly by treatment plant surveys. TTHMs modellingColon and rectalSexColon: OR = 1.87 (1.15–3.05) for Men; OR = 0.92 (0.49–1.71) for Women. Rectal: OR = 0.98 (0.56–1.72) for Men; OR = 0.72 (0.34–1.53) for Women
Bove et al. [63]New York State, USA2007128 cases and 253 controlsCase-controlTTHMs in tap water + water consumptionRectaln.d.THM4: OR = 1.01 (0.98–1.03); CLF: OR = 1.00 (0.93–1.09); BRF: OR = 1.20 (1.05–1.35)
Kuo et al. [69]Taiwan20092195 cases and 2195 controlsCase-controlQuestionnaire & data on TTHM levels in drinking water in study. Municipalities were collected from the Taiwan Environmental Protection AdministrationColonn.d.All: OR = 1.04 (0.89–1.21)
NB: n.d.: No data; OR: Odds Ratio; RR: Risk Ratio; CLF: Chloroform; BRF: Bromoform; BDCM: Bromodichloromethane.
Table
Table 2. Co-variables collected in the selected studies (candidates for a potential effect measure modification assessment).
Table 2. Co-variables collected in the selected studies (candidates for a potential effect measure modification assessment).
StudyAgeSexSocio-Economic Factors *Urbanization LevelSmokingOther Health Behaviors
Wilkins and Comstock 1981 [51]XXXX
Gottlieb and Carr 1982 [65]XX
Zierler et al. 1988 [55]XX
McGeehin et al. 1993 [53]X
King and Marrett 1996 [67]XXXX
Freedman et al. 1997 [54]XXX
Koivusalo et al. 1997 [52]XXXXX
Cantor et al. 1998 [64]XXXX
Hildesheim et al. 1998 [66]XX
Koivusalo et al. 1998 [56]XXXXX
King et al. 2000 [57]XXXX
Chevrier et al. 2004 [58]XXXX
Bove et al. 2007 [63]XXX
Bove et al. 2007 [59]XXX
Chang et al. 2007 [60]XX
Michaud et al. 2007 [61]XXX
Villanueva et al. 2007 [68]XXXXX
Kuo et al. 2009 [69]XXX
Cantor et al. 2010 [62]XXXX
* Include education, occupation status, or SES index.

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Benmarhnia, T.; Delpla, I.; Schwarz, L.; Rodriguez, M.J.; Levallois, P. Heterogeneity in the Relationship between Disinfection By-Products in Drinking Water and Cancer: A Systematic Review. Int. J. Environ. Res. Public Health 2018, 15, 979. https://doi.org/10.3390/ijerph15050979

AMA Style

Benmarhnia T, Delpla I, Schwarz L, Rodriguez MJ, Levallois P. Heterogeneity in the Relationship between Disinfection By-Products in Drinking Water and Cancer: A Systematic Review. International Journal of Environmental Research and Public Health. 2018; 15(5):979. https://doi.org/10.3390/ijerph15050979

Chicago/Turabian Style

Benmarhnia, Tarik, Ianis Delpla, Lara Schwarz, Manuel J. Rodriguez, and Patrick Levallois. 2018. "Heterogeneity in the Relationship between Disinfection By-Products in Drinking Water and Cancer: A Systematic Review" International Journal of Environmental Research and Public Health 15, no. 5: 979. https://doi.org/10.3390/ijerph15050979

APA Style

Benmarhnia, T., Delpla, I., Schwarz, L., Rodriguez, M. J., & Levallois, P. (2018). Heterogeneity in the Relationship between Disinfection By-Products in Drinking Water and Cancer: A Systematic Review. International Journal of Environmental Research and Public Health, 15(5), 979. https://doi.org/10.3390/ijerph15050979

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