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Trihalomethanes in Drinking Water and Bladder Cancer Burden in the
European Union
Iro Evlampidou,
1,2,3
Laia Font-Ribera,
1,2,3,4
David Rojas-Rueda,
1,2,3
Esther Gracia-Lavedan,
1,2,3
Nathalie Costet,
5
Neil Pearce,
6
Paolo Vineis,
7
Jouni J.K. Jaakkola,
8
Francis Delloye,
9
Konstantinos C. Makris,
10
Euripides G. Stephanou,
11,12
Sophia Kargaki,
11
Frantisek Kozisek,
13
Torben Sigsgaard,
14
Birgitte Hansen,
15
Jörg Schullehner,
15,16
Ramon Nahkur,
17
Catherine Galey,
18
Christian Zwiener,
19
Marta Vargha,
20
Elena Righi,
21
Gabriella Aggazzotti,
21
Gunda Kalnina,
22
Regina Grazuleviciene,
23
Kinga Polanska,
24
Dasa Gubkova,
25
Katarina Bitenc,
26
Emma H. Goslan,
27
Manolis Kogevinas,
1,2,3,4
and
Cristina M. Villanueva
1,2,3,4
1
ISGlobal, Barcelona, Spain
2
Universitat Pompeu Fabra (UPF), Barcelona, Spain
3
CIBER Epidemiologia y Salud Pública (CIBERESP), Madrid, Spain
4
Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
5
Université de Rennes, Institut national de la santé et de la recherche médicale (Inserm),
Ecole des hautes études en santé publique (EHESP), Rennes, France
6
London School of Hygiene & Tropical Medicine, London, UK
7
Imperial College of London, London, UK
8
Center for Environmental and Respiratory Health Research (CERH), University of Oulu, Oulu, Finland
9
Service Public de Wallonie, Direction générale de l’Agriculture, des Ressources naturelles et de l’Environnement, Département de l'Environnement et de
l’Eau, Jambes, Belgium
10
Water and Health Laboratory, Cyprus International Institute for Environmental and Public Health, Cyprus University of Technology, Limassol, Cyprus
11
Environmental Chemical Processes Laboratory (ECPL), Department of Chemistry, University of Crete, Heraklion, Greece
12
The Cyprus Institute, Aglantzia-Nicosia, Cyprus
13
National Institute of Public Health, Prague, Czech Republic
14
Department of Public Health, Section for Environment, Occupation & Health, Aarhus University, Aarhus, Denmark
15
Geological Survey of Denmark and Greenland (GEUS), Aarhus, Denmark
16
National Centre for Register-based Research, Aarhus University, Aarhus, Denmark
17
Public Health Department, Estonian Ministry of Social Affairs, Tallinn, Estonia
18
Santé Publique France (French National Public Health Agency), Saint-Maurice, France
19
Environmental Analytical Chemistry, Center for Applied Geosciences (ZAG), Eberhard-Karls-University Tuebingen, Tuebingen, Germany
20
National Public Health Center, Budapest, Hungary
21
Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
22
Public Health Division, Ministry of Health of the Republic Latvia, Health Inspectorate, Riga, Latvia
23
Department of Environmental Sciences, Faculty of Natural Sciences, Vytautas Magnus University, Kaunas, Lithuania
24
Department of Environmental Epidemiology, Nofer Institute of Occupational Medicine, Lodz, Poland
25
Public Health Authority of the Slovak Republic, Bratislava, Slovak Republic
26
National Institute of Public Health, Ljubljana, Slovenia
27
Cranfield Water Science Institute, Cranfield University, Cranfield, Bedford, UK
BACKGROUND:Trihalomethanes (THMs) are widespread disinfection by-products (DBPs) in drinking water, and long-term exposure has been consis-
tently associated with increased bladder cancer risk.
OBJECTIVE:We assessed THM levels in drinking water in the European Union as a marker of DBP exposure and estimated the attributable burden of
bladder cancer.
METHODS:We collected recent annual mean THM levels in municipal drinking water in 28 European countries (EU28) from routine monitoring
records. We estimated a linear exposure–response function for average residential THM levels and bladder cancer by pooling data from studies
included in the largest international pooled analysis published to date in order to estimate odds ratios (ORs) for bladder cancer associated with the
mean THM level in each country (relative to no exposure), population-attributable fraction (PAF), and number of attributable bladder cancer cases in
different scenarios using incidence rates and population from the Global Burden of Disease study of 2016.
RESULTS:We obtained 2005–2018 THM data from EU26, covering 75% of the population. Data coverage and accuracy were heterogeneous among
countries. The estimated population-weighted mean THM level was 11:7lg=L [standard deviation (SD) of 11.2]. The estimated bladder cancer PAF
was 4.9% [95% confidence interval (CI): 2.5, 7.1] overall (range: 0–23%), accounting for 6,561 (95% CI: 3,389, 9,537) bladder cancer cases per year.
Denmark and the Netherlands had the lowest PAF (0.0% each), while Cyprus (23.2%), Malta (17.9%), and Ireland (17.2%) had the highest among
EU26. In the scenario where no country would exceed the current EU mean, 2,868 (95% CI: 1,522, 4,060; 43%) annual attributable bladder cancer
cases could potentially be avoided.
DISCUSSION:Efforts have been made to reduce THM levels in the European Union. However, assuming a causal association, current levels in certain
countries still could lead to a considerable burden of bladder cancer that could potentially be avoided by optimizing water treatment, disinfection, and
distribution practices, among other possible measures. https://doi.org/10.1289/EHP4495
Address correspondence to Cristina M. Villanueva, Barcelona Institute for
Global Health–Campus MAR, Barcelona Biomedical Research Park, Doctor
Aiguader, 88, 08003 Barcelona, Spain. Email: Cristina.villanueva@isglobal.org
Supplemental Material is available online (https://doi.org/10.1289/EHP4495).
The authors declare they have no actual or potential competing financial
interests.
Received 20 September 2018; Revised 26 November 2019; Accepted 26
November 2019; Published 15 January 2020.
Note to readers with disabilities: EHP strives to ensure that all journal
content is accessible to all readers. However, some figures and Supplemental
Material published in EHP articles may not conform to 508 standards due to
the complexity of the information being presented. If you need assistance
accessing journal content, please contact ehponline@niehs.nih.gov. Our staff
will work with you to assess and meet your accessibility needs within 3
working days.
Environmental Health Perspectives 017001-1 128(1) January 2020
A Section 508–conformant HTML version of this article
is available at https://doi.org/10.1289/EHP4495.
Research
Introduction
Drinking water disinfection is essential for public health protec-
tion against waterborne infections. However, disinfection by-
products (DBPs) are formed as an unintended consequence of
water disinfection. DBPs form a complex mixture of hundreds of
chemicals (Hebert et al. 2010;Richardson et al. 2007) to which
virtually the entire population in developed countries is exposed
through ingestion, inhalation, or dermal absorption when drink-
ing or using municipal tap water and swimming in pools.
Chlorine is the most widespread disinfectant used worldwide,
and trihalomethanes (THMs) and haloacetic acids (HAAs) are
the DBP classes formed at the highest concentrations after chlori-
nation. Apart from disinfection methods, the characteristics of
raw water (e.g., the content of natural organic matter) and the
condition of the distribution system also determine the type and
levels of DBPs found in municipal water (Villanueva et al. 2015,
Charisiadis et al. 2015).
Several DBPs have been shown to be genotoxic in in vitro
assays and carcinogenic in animal experiments (Richardson et al.
2007), and the World Health Organization (WHO) International
Agency for Research on Cancer (IARC) classifies chloroform
and other widespread DBPs as possible human carcinogens
(IARC 1991). A series of previous epidemiological studies has
provided estimates of the relationship between DBPs exposure
and the risk of cancer and adverse reproductive outcomes
(Villanueva et al. 2015). Different meta-analyses and pooled
analyses (Costet et al. 2011;King and Marrett 1996;Villanueva
et al. 2003,2004) of studies in Europe and North America pro-
vide consistent evidence that long-term exposure to THMs, used
as a surrogate of DBPs, is associated with an increased bladder
cancer risk. In the most recent international meta-analysis of
case–control studies, men exposed to annual mean THM levels
>25 lg=L had a 35% increased bladder cancer risk [95% confi-
dence interval (CI): 9, 66], and those exposed to >50 lg=L had a
51% increased risk (95% CI: 26, 82) compared to levels <5 lg=L
(Costet et al. 2011). However, there are limited large cohort stud-
ies prospectively evaluating the association with bladder cancer
to unequivocally conclude a causal association, and the epidemi-
ological evidence concerning other cancer sites is inconsistent
(Villanueva et al. 2015).
Together with bromate, total THM concentrations represent-
ing the sum of chloroform, bromodichloromethane, dibromo-
chloromethane, and bromoform are the only DBPs regulated in
the European Union, with a maximum contaminant level of
100 lg=L(EC 1998). Although regulated and monitored, infor-
mation on the levels in drinking water is not easily available in
most European countries, and there is no published report on cur-
rent levels of exposure in the European Union. Epidemiological
studies conducted in different European settings indicate large
variability in the levels within (Villanueva et al. 2017) and
between (Jeong et al. 2012) countries. The European research
project Health impacts of long-term exposure to disinfection by-
products in drinking water (HIWATE) reported that in 2010,
THM levels in drinking water in seven cities from five European
countries ranged from below the limit of detection (Modena,
Italy) to above the current regulatory maximum limit (Barcelona,
Spain) (Jeong et al. 2012). This variability was based primarily
on variations in the characteristics of raw water, drinking water
disinfection methods, and conditions of the water distribution
system (Charisiadis et al. 2015).
Burden of disease measures, such as the number of cases at-
tributable to a given environmental exposure, characterize public
health relevance and can be used in health impact assessment and
economic analysis elaborating the influence of predicted future
changes in DBP levels (due to, for example, lower water quality or
new regulations). Burden of disease estimates for bladder cancer
due to DBP exposure have been previously assessed in France
(Corso et al. 2017) and the United States (Regli et al. 2015;U.S.
EPA 2005),indicating that around 16% of bladder cancer incidence
is currently attributable to exposure to DBPs in drinking water.
In the context of the European Project EXPOsOMICS
(Turner et al. 2018;Vineis et al. 2017), our objective was to cal-
culate Europe-wide estimates of the current concentrations of
THMs in drinking water as a marker of DBP exposure and to
estimate the attributable burden of bladder cancer using different
exposure scenarios.
Methods
Study Area
The study area comprises the 28 countries of the European Union
in 2016 (404,672,106 inhabitants over 20 years of age) (IHME
2016b). These countries are Austria, Belgium, Bulgaria, Croatia,
Cyprus, Czech Republic, Denmark, Estonia, Finland, France,
Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania,
Luxembourg, Malta, the Netherlands, Poland, Portugal, Romania,
Slovakia, Slovenia, Spain, Sweden, and the United Kingdom.
Trihalomethane Data Collection
We designed a questionnaire to collect routine monitoring data
on the concentration of total and individual THMs (chloroform,
bromodichloromethane, dibromochloromethane, and bromoform)
in drinking water (in micrograms per liter) at the tap, distribution
network, or water treatment plant from the latest year(s) avail-
able. We requested information on the annual average concentra-
tion, standard deviation, median, range, and the number of
measurements at national or regional levels. The questionnaire
also ascertained the institution/person providing the information,
reporting year and geographic region, population served, main
disinfectants used, and maximum permissible level for THMs
according to the country’s legislation. In addition, the corre-
sponding raw THM data were requested. We sent this question-
naire between May 2016 and April 2019 to the national contact
people in the organizations maintaining water quality data,
including public health institutes and universities. We explored
other data sources (e.g., open data online, reports, scientific litera-
ture, etc.) in order to complement the information provided by
the questionnaires. Due to the ecological design of the study and
the anonymity of data, ethics approval was not sought.
Table 1 describes the countries that completed the question-
naire and provides drinking water information available from
other sources. For Croatia, Finland, Hungary, Lithuania, and
Malta, we received only the completed questionnaire, while for
11 countries (Belgium, Cyprus, Czech Republic, Estonia, Greece,
Italy, Latvia, Poland, Portugal, Slovenia, and the United
Kingdom), we also received raw monitoring data at different
reporting levels (tap, city/village, water zone, province, and
region). For Germany, Greece, and Luxemburg, we used munici-
pal and water authorities’online data and reports. For Italy, we
obtained partial data provided directly from participating munici-
palities, complemented by online data. For Cyprus, Denmark, the
Netherlands, Slovakia, and Sweden, we directly obtained data af-
ter personal communication with the respective authorities or
researchers. For France, Ireland, and Spain, recent country-level
THM information was published (Water_Team 2014;Corso et al.
2017;Palau and Guevara 2014); hence, reference people were
not contacted. Nine countries reported nonweighted THM meas-
urements or means (Croatia, Denmark, Finland, Germany,
Hungary, Malta, the Netherlands, Slovakia, and Sweden), while
Environmental Health Perspectives 017001-2 128(1) January 2020
Table 1. Water sources and disinfection methods of drinking water, and other information on drinking water specimens for trihalomethanes (THM)
measurements included in the study of 28 European countries (EU28).
Country
Water source
Disinfection method(s) Data source(s) THM data
source
Water tests
collection
point
Level of
THM
reporting
Ground
(%) Surface
(%) Other
(%) Type of other
water
Austria 100 0 0 Bank filtration
in emergencies Chlorine, chlorine
dioxide, UV radiation
(predominately)
Personal
communication,
published report
Imputed NA NA
Belgium 65 35 0 —Chlorine, UV
radiation, ozone
(limited)
Questionnaire,
raw data, perso-
nal communica-
tion, published
report
Monitoring Tap Water zone,
city/village
Bulgaria 35 65 0 —Chlorine, UV radiation
(limited) NA EU mean NA NA
Croatia 70 30 0 —Chlorine Questionnaire Monitoring Distribution
system, tap Country
Cyprus 10 58 31 Seawater Chlorine Questionnaire,
raw data Research Tap Tap
Czech
Republic 50 50 0 —Chlorine, hypochlorite Questionnaire,
raw data Monitoring Tap Water zone
Denmark 100 0 0 —No disinfection, UV
radiation (limited) Personal
communication Monitoring Water works
(outlet),
distribution
system
Country
Estonia 54 36 0 —Chlorine in 2 cities Questionnaire,
raw data Monitoring Water plant,
distribution
system, tap
Water zone
Finland 41 43 16 14% artificial
recharge of
groundwater,
2% bank
filtration
No disinfection, chlo-
rine, hypochlorite,
chlorine dioxide,
chloramine, UV radi-
ation, ozone (limited)
Questionnaire Monitoring Tap Country
France 66 34 0 Four marginal
sea water
catchments
Chlorine, hypochlorite,
chlorine dioxide,
ozone
Published report Monitoring Water plant
(outlet) Country
Germany 68 15 15 8% artificial
recharge of
groundwater,
7% bank
filtration
Chlorine, chlorine
dioxide, hypochlorite,
ozone
Published reports Monitoring Water plant,
distribution
system, tap
Water plant,
distribution
system
Greece 29 71 0 —Chlorine, hypochlorite,
chlorine dioxide,
ozone
Questionnaire,
raw data, pub-
lished reports
Monitoring Tap Tap
Hungary 45 4 51 38% bank
filtration, 13%
other
Chlorine, hypochlorite,
chlorine dioxide Questionnaire Monitoring Distribution
system, tap Country
Ireland 11 82 7 Spring water Chlorine, UV radiation Online database Monitoring Tap Tap
Italy 54 39 7 Bank filtration Chlorine dioxide,
ozone, hypochlorite Questionnaire,
published
reports, raw
data
Monitoring Source,
water plant,
water tank,
well, tap,
public
fountain
Source, water
plant, water
tank, well,
tap, public
fountain
Latvia 59 30 11 Artificial
recharge of
groundwater
Chlorine, hypochlorite,
ozone Questionnaire,
raw data Monitoring Tap Tap
Lithuania 93 0 7 Artificial
recharge of
groundwater
Chlorine in half of one
city Questionnaire Monitoring Distribution
system City
Luxemburg 66 33 0 —Chlorine, hypochlorite,
chlorine dioxide, UV
radiation, ozone,
ultrafiltration
Published reports Monitoring Tap, distri-
bution sys-
tem, water
tank
Municipality,
tap
Malta 27 0 73 Desalination Chlorine Questionnaire Monitoring Tap Country
Netherlands 54 39 7 Bank filtration Ozone, UV radiation Personal
communication Monitoring Water plant Country
Poland 62 24 14 —Chlorine, chlorine
dioxide, hypochlorite,
ozone, UV radiation
Questionnaire,
raw data Monitoring Water
works,
water plant
Province
Portugal 34 66% 0 —Chlorine, chlorine
dioxide Questionnaire,
raw data Monitoring Tap Water zone
Environmental Health Perspectives 017001-3 128(1) January 2020
for the rest, population-weighted THM measurements were
reported or calculated.
In Austria, Bulgaria, and Romania, key people were not iden-
tified or did not participate, or recent THM data were not avail-
able. For these three countries, we performed an online literature
review to identify recent scientific and gray literature in English
or in the national language using Google Translate. We used
PubMed, Google Scholar, Mendeley (www.mendeley.com), and
official websites using the following keywords in the Google
search engine: (country name) AND [(drinking water) OR (pota-
ble water)] AND [(trihalomethanes) OR (THMs) OR (disinfec-
tion byproducts) OR (chlorination byproducts)]. The literature
search identified reports of THM levels measured before the year
2000 for Austria (Premazzi et al. 1997), where expected THM
levels are very low, since 99.7%% of drinking water is from
underground sources and ultraviolet (UV) radiation is the pre-
dominant disinfection method (A Indra, personal communica-
tion). Hence, we included Austria in the estimation of the EU
average. We could not find THM data for Bulgaria. In Romania,
we obtained published THM data from 2006–2015 for 8 individ-
ual cities and for small supply areas in 10 counties (Cohl et al.
2015;Dirtu et al. 2016;Kovacs et al. 2007;Thach et al. 2012).
We obtained additional data (mean, minimum, study area,
population coverage, collection points, and disinfection methods)
related to the study of Dirtu et al. 2016 after personal communi-
cation with the researcher (D. Dirtu, personal communication).
We calculated the population-weighted average considering the
population covered by these studies (7.4% of the total population
in Romania) and assigned this weighted THM mean estimate for
Romania as a whole. Because we had limited data for Romania
and no data for Bulgaria, we did not include these countries
when estimating the average annual THM exposure for the
European Union as a whole. When estimating PAFs and num-
bers of THM-attributable bladder cancer cases, we used a
population-weighted average based on published THM values
for Romania and assigned the EU average THM exposure level
and standard deviation (SD) for Bulgaria (Table S1).
Trihalomethane Indices
When available, we used raw data to calculate the country aver-
age, SD, and median THM levels, and we weighted the estima-
tions by the population served in each reporting area using the
function weight = area population in STATA (version 12; Stata
Corp.). For Cyprus, Germany, Greece, Italy, Luxemburg, and
Romania, we built separate databases in Microsoft Excel 2010
using the available THM reports to estimate the population-
weighted average THM for the reported areas, which we then
assigned to the whole country. We obtained the distributions of
country-specific population size and age in 2016 from the Global
Burden of Disease 2016 study (IHME 2016b). The area-specific
population size was either included in the provided database or
report or we obtained it from the latest published country census.
We excluded the outliers and assigned half the value of the
reporting laboratory’s detection limit when measurements were
undetected. For countries that provided information on individual
THMs only (chloroform, bromodichloromethane, dibromochloro-
methane, and bromoform,) we calculated the total THMs by add-
ing the individual THMs. We used the mean values of THMs
instead of the median values, despite the skewedness of some
Table 1. (Continued.)
Country
Water source
Disinfection method(s) Data source(s) THM data
source
Water tests
collection
point
Level of
THM
reporting
Ground
(%) Surface
(%) Other
(%) Type of other
water
Romania 33 64 3 2.2% bank
filtration Chlorine, chlorine
dioxide Published
research
articles,
personal
communication
Research Water plant,
distribution
system, tap
City
Slovakia 85 15 0 —Hypochlorite, chlorine Personal
communication Monitoring Tap Country
Slovenia 67 33 0 —Chlorine, chlorine
dioxide, UV radia-
tion, ozone
Questionnaire,
raw data Monitoring Tap Water zone
Spain 60 38 0.50 Seawater Chlorine, chlorine
dioxide, ozone,
permanganate
Published report Monitoring Water plant,
water
tower, dis-
tribution
system, tap
Country
Sweden 17 61 22 Artificial
recharge of
groundwater
No disinfection, chlo-
rine, hypochlorite,
chloramine, UV
radiation
Personal
communication Monitoring Water plant Country
United
Kingdom 14 64 22 —Chlorine, chloramine Questionnaire,
raw data Monitoring Tap Region
EU28 52 37 10 Seawater, artifi-
cial recharge
of ground-
water, bank fil-
tration water,
spring water
Chlorine, hypochlorite,
chlorine dioxide,
ozone, UV radiation,
aeration,
permanganate
——Tap, water
zone, water
plant, water
tower, dis-
tribution
system,
well, public
fountain
Tap, water
zone, water
plant, distri-
bution sys-
tem,
country
Note: Reporting years and numbers of measurements for countries with monitoring data are indicated in Table 2. Data from European Topic Centre on Inland Coastal and Marine
waters, 2015 (EU and country reports) (ETC ICM 2015), ad hoc questionnaires, personal communication with contributors, and published reports. —, no data; NA, not available;
UV, ultraviolet.
Environmental Health Perspectives 017001-4 128(1) January 2020
data, because many countries provided mean values and pub-
lished literature commonly reports means. For the minimum and
maximum values, we used the nonweighted THM levels to show
the actual range. When only the mean THM of a country was pro-
vided to us, we used it as is.
For the estimation of the EU population-weighted mean of
THMs, we used the information from 26 EU countries that pro-
vided data, thus excluding Bulgaria and Romania, since the data
were nonrepresentative (in Romania, the population coverage
was 7.4%) or not available (Bulgaria). We used both country-
specific weighted and nonweighted mean THMs, depending on
the availability of data, and weighted the EU mean by the popu-
lation of each country using the function weight= country
population in STATA 12. We created country-specificTHM
concentration maps using ArcGIS (version 10.3.1; Esri.).
Bladder Cancer and Trihalomethane Exposure–Response
Function
The exposure–response function was based on data from Costet
et al. (2011), the most recent and complete epidemiological data
set on the relationship between residential THM exposure and
bladder cancer. This is an international pooled analysis and meta-
analysis including six case–control studies: two from the United
States (Cantor et al. 1998;Lynch et al. 1989) and one each from
Canada (King and Marrett 1996), France (Cordier et al. 1993),
Finland (Koivusalo et al. 1998), and Spain (Villanueva et al.
2007). We estimated population-attributable fractions (PAFs) for
each country based on an exposure–response function derived
using pooled data from an analysis of residential THM exposure
and bladder cancer (Costet et al. 2011) that included subjects
from six case–control studies: two from the United States (Cantor
et al. 1998;Lynch et al. 1989) and one each from Canada (King
and Marrett 1996), France (Cordier et al. 1993), Finland
(Koivusalo et al. 1998), and Spain (Villanueva et al. 2007). We
pooled data from 9,458 subjects with estimates of long-term aver-
age residential THM levels, including 3,481 cases (2,776 men,
705 women) and 5,977 controls (4,199 men, 1,778 women) 30–
80 years of age with THM data for ≥70%of the 40-y exposure
window. We derived an odds ratio (OR) of 1.004 (95% CI: 1.002,
1.006) for a 1-lg=LincreaseinTHMinmenandwomencom-
bined, adjusted for study center, age, sex, educational level,
smoking status, high-risk occupation, daily fluid intake, and
coffee consumption, as in Costet et al. (2011). Showering, bath-
ing, or swimming information was not available for all studies
and was not included in the analysis. We used generalized addi-
tive models (GAMs) to confirm the linearity of the exposure–
response association. Thesemodelsshowednosignificant
departure from linearity (p=0:1461) (see Figure S1), and we
used logistic regression to estimate country-specificORsand
95% CIs.
Attributable Bladder Cancer Cases
We followed the burden of disease approach of WHO and the
United Nations Environment Programme (WHO 2015) to esti-
mate the PAF and the annual number of bladder cancer cases at-
tributable to THM exposure. For our primary analysis, we used
the pooled OR = 1:004 for a 1-lg=L increase in THM as the ex-
posure–response function for bladder cancer in men and women
≥20 years of age. In addition, we conducted sensitivity analyses
limited to men and women 30–79 years of age, consistent with
the age range of the population used to derive the pooled OR
(30–80 y). For each country i,wefirst converted the pooled OR
for a 1-lg=L increase to a country-specificOR
ifor bladder
cancer in association with the country-specific mean THM level
(THMi) vs. no exposure (Mueller et al. 2017):
ORi= exp ½ðln1:004Þ× THMi
We estimated the percent PAFifor each country assuming
100% exposure to the mean THM level (ORi) vs. no exposure
(ORref =1:0) (WHO 2014):
PAFi=½ðORi−1:0Þ=ORi× 100
and estimated the number of THM-attributable bladders cancer
cases per year for each country ias
attributable casesi= annual casesi× PAFi
using country-specific bladder cancer incidence rates, numbers of
bladder cancer cases, and population size (men and women age
≥20 y or 30–79 y, as appropriate) data from the 2016 Global
Burden of Disease study (IHME 2016a,2016b).
Exposure Scenarios and Health Impact Assessment
To account for uncertainties in the exposure estimates, we con-
ducted a sensitivity analysis for countries with population coverage
below 50% (Bulgaria, Greece, Italy, Romania, and the United
Kingdom) using the average of 26 European countries (EU26)
instead. In alternative analyses, we conducted a sensitivity analysis
for all countries, where the lowest exposure scenario was simulated
by setting the exposure level at mean THM level −1 SD (and set to
0lg=L if this calculated level was negative), and the highest expo-
sure scenario was simulated by setting the exposure level at mean
THM level + 1 SD for each country. Countries without available
SD data (Austria, Bulgaria, Finland, France, Germany, Malta, the
Netherlands, Slovakia, and Sweden) were assigned the SD of the
EU population-weighted average (11:2lg=L) with the exception
of Austria, which was assigned the SD for Lithuania (5:9lg=L), a
country with a similar water source and THM levels. We also cal-
culated the number of bladder cancer cases that would be avoided
if no country would exceed the EU THM mean.
Statistical analyses were performed with Microsoft Excel
2010, the statistical software STATA 12.0, and RStudio (for
GAM models, the mgcv package) (version 3.4.4; RStudio Team)
(Wood 2006).
Results
Trihalomethane Levels
Drinking water source and disinfection methods used in the study
countries are shown in Table 1. The vast majority of participating
countries use chlorination (chlorine, hypochlorite) as the main
disinfection method alone or in combination with other methods
(ozone, UV radiation, etc.). Chlorine dioxide is additionally used
in Italy, and in Lithuania, chlorine is used only in half of one of
the cities and is supplied with surface water. In Denmark, aera-
tion and filtration are mainly used, and in the Netherlands, ozone
and UV radiation are applied. Some differences between coun-
tries are also present in the various water testing collection points
and the geographical level for reporting THM levels (Table 1).
We obtained recent (2005–2018) information—with the
exception of Austria (1997)—on THM levels in drinking water
through routine monitoring for 26 of the 28 countries in the
European Union (Table 2), covering 75% of the EU26 popula-
tion. Among these countries, the population-weighted mean
THM level was 11:7lg=L [SD: 11.2, median: 10, interquartile
range (IQR): 3.1–24.2]. The actual measurements ranged from
0:0lg=L in multiple countries to 301 lg=L in Portugal, 439 lg=L
Environmental Health Perspectives 017001-5 128(1) January 2020
in Spain, and 771 lg=L in Hungary (corresponding in this last
case to one confirmed and atypical observation). Nine countries
(Croatia, Denmark, Finland, Germany, Hungary, Malta, the
Netherlands, Slovakia, and Sweden) provided mean THM data at
the national level; hence, the population-weighted mean could not
be calculated. The population coverage among the 26 countries,
shown in Table 2, ranged from 22% in Italy to 100% in different
countries (average coverage: 80%). The lowest mean THM val-
ues were observed in Denmark (0:02 lg=L), the Netherlands
(0:2lg=L), Germany (0:5lg=L), Lithuania (1:0lg=L), Austria
(1:1lg=L), Slovenia (2:9lg=L), Italy (3:1lg=L), and Poland
(5:7lg=L). The highest mean THM values were observed in
Cyprus (66:2lg=L), Malta (49:4lg=L), Ireland (47:3lg=L),
Spain (28:8lg=L), and Greece (26:3lg=L) (Figure 1). Maxi-
mum reported concentrations exceeded the EU regulatory limit
(100 lg=L) for 9 of 22 countries with available data (Table 2).
However, the proportion of samples exceeding this limit was
low, and average noncompliance in the nine countries was 0.7%
overall, 0.3% in large water systems, and 1.1% in small water
systems (EIONET).
Based on the literature search, we assigned Austria a mean
(SD) THM level of 1:1lg=L (5.9) and the EU26 mean to
Bulgaria (11:7lg=L) and SD (11.2). For Romania, the estimated
mean (SD) from the published studies was 91:8lg=L (64.2), but
the population coverage was limited (7.4%) (Table S1).
Specific data on individual THMs are shown in Table S2. A
total of 14 countries provided chloroform levels, 13 provided
bromodichloromethane levels, and 12 provided bromoform and
dibromochloromethane levels. The population-weighted average
was 6:8lg=L for chloroform (SD: 6.1; IQR: 1.6–14.2), 2:9lg=L
for bromodichloromethane (SD: 3.2; IQR: 0.3–6.3), 2:3lg=L for
dibromochloromethane (SD: 2.2, IQR: 0.5–4.3), and 1:9lg=L
for bromoform (SD: 2.5; IQR: 1.1–2.5). The average population
coverage among the 14 countries with available data was 72% for
chloroform, 71% for dibromochloromethane, and 70% each for
bromodichloromethane and bromoform.
Attributable Bladder Cancer Cases
The estimated population fraction of bladder cancer attributable
to THM exposure (both sexes, ≥20-y age group) ranged from
0.01% (95% CI: 0.004, 0.013) in Denmark to 23.2% (95% CI:
12.4, 32.7) in Cyprus and 30.7% (95% CI: 16.8, 42.3) in
Romania, which was the country with the highest estimated
THM level based on data reported for 7.4% of the population
(Table 3). The estimated annual bladder cancer cases attributable
to THM exposure ranged from zero in Denmark to 1,482 in
Spain (Table 3). In total, we estimated that 6,561 bladder cancer
cases per year (95% CI: 3,389, 9,537) would be attributable to
THM exposure in the European Union, which represents 4.9%
(95% CI: 2.5, 7.1) of the total annual bladder cancer cases in this
age group. Spain (22.6%), the United Kingdom (20.7%), and
Romania (16.0%) accounted for the largest estimated number of
attributable cases. For men and women 30–79 years of age, we
Table 2. Estimated mean total trihalomethane (THM) levels in drinking water in 26 EU countries.
Country
a
Population
b
MCL
(lg=L) Reporting
year(s) Number of
measurements
Mean
THM
(lg=L) SD
(lg=L) Median
(lg=L) Min
(lg=L) Max
(lg=L) Population
served
c
Population
coverage
(%)
c
Austria
,d,e
8,692,636 —1997 NA 1.1 5.9 ———8,692,636 100
Belgium 11,367,990 100 2011–2014 6,015 13.2 4.0 15.9 0.0 85.1 10,556,971 93
Croatia
d
4,221,725 100 2015 736 10.2 5.9 4.6 0.1 93.4 3,569,000 85
Cyprus 910,587 100 2012–2013 597 66.2 33.2 60.8 0.2 182.0 580,000 64
Czech Republic 10,631,077 100 2015 1,694 12.8 9.6 12.7 0.0 85.5 8,351,792 79
Denmark
d,f
5,724,401 25 2014–2016 5,177 0.02 0.07 0.01 0.01 2.2 5,619,000 98
Estonia 1,317,494 100 2015 215 13.7 12.8 21.5 0.0 127.0 842,589 64
Finland
d
5,507,289 100 2015 204 7.6 NA NA 0.0 93.0 4,400,000 80
France 64,939,098 100 2005–2011 88,350 11.7 NA NA NA NA 64,939,098 100
Germany
d
82,048,579 50 2011–2013 25,382 0.5 NA 0.5 0.0 NA 74,152,913 90
Greece 10,868,170 100 2007–2017 >297 26.3 9.2 29.8 0.0 43.7 4,498,781 41
Hungary
d
9,909,325 50 2015 5,909 10.0 20.0 4.0 0.0 771.0 9,500,000 96
Ireland 4,641,095 100 2014 1,530 47.3 25.4 43.4 0.0 255.0 3,836,798 83
Italy 60,501,702 30 2012–2017 >2,630 3.1 3.6 1.5 0.0 129.5 13,511,378 22
Latvia 1,981,699 100 2015 205 7.2 2.6 5.4 0.2 12.9 1,397,656 71
Lithuania 2,895,874 100 2015 3 1.0 5.9 0.0 NA NA 2,872,298 99
Luxembourg 579,190 50 2011–2018 61 7.5 3.0 6.8 0.4 21.2 341,774 59
Malta
d
420,113 100 2017 40 49.4 —49 0.1 79.0 475,701
g
100
Netherlands
d
17,141,153 25 2015 161 0.2 NA NA 0.0 1.2 17,018,408 99
Poland 38,641,788 100 2016 9,554 5.7 6.7 3.4 0.0 146.0 31,120,597 81
Portugal 10,474,821 100 2015 3,795 23.8 19.3 20.0 0.1 301.0 10,017,800 96
Slovakia
d
5,456,895 100 2015 390 10.0 NA NA 0.0 90.0 4,753,000 87
Slovenia 2,064,986 100 2015 457 2.9 4.5 1.2 0.0 42.1 1,844,236 89
Spain 46,481,496 100 2013 19,003 28.8 28.6 23.5 0.0 439.0 39,473,151 85
Sweden
d
9,887,967 100 2011–2013 4,665 10.0 NA 8.0 0.5 100.0 9,903,122 100
United Kingdom 65,375,433 100 2010–2015 29,914 24.2 7.1 26.5 0.0 100.5 28,700,000 44
Total nonweighted
h
482,682,585 ——>206,984 15.2 16.8 10 0.01 771 360,968,699 75
Total population, weighted —— —11.7 11.2 10 NA NA ——
Note: Mean, SD, and median values are population-weighted (except if otherwise indicated). Min and max are actual measurements (nonweighted). For Greece and Italy, some munic-
ipal reports provided annual means but did not specify the number of measurements. For Sweden, additionally, 3,311 measurements had THM values below 1 lg=L but were not
included in the mean THM value provided for this study. —, no data; max, maximum; MCL, maximum contaminant level; min, minimum; NA, not available; SD, standard deviation.
a
Bulgaria and Romania are not included because there was no data (Bulgaria) or data based on literature review (Romania).
b
Country population reported by the Global Burden of Disease Study 2016 (all ages, both sexes) (IHME 2016b).
c
Population served and population coverage in the reporting year(s), corresponding to the country population for which THM information is available.
d
Nonweighted mean and SD.
e
Imputed levels (see Table S1 for details).
f
Only chloroform is monitored in Denmark; THM values correspond to chloroform values only.
g
Higher population served vs. total population is due to different data sources (study questionnaire vs. GBD) and reporting years (2017 vs. 2016).
h
The population of these 26 EU countries represents 95% of the total population in the EU28. The average coverage of included countries is 75%.
Environmental Health Perspectives 017001-6 128(1) January 2020
estimated that 4,518 bladder cancer cases per year (95% CI:
2,339, 6,555) would be attributable to THM exposure in the
European Union as a whole, accounting for 4.9% (95% CI: 2.6,
7.1) of all EU bladder cancer cases among men and women in
this age group (Table S3).
Sensitivity Analysis, Exposure Scenarios, and Health Impact
Assessment
In the sensitivity analysis in which countries with population cov-
erage <50%(Bulgaria, Greece, Italy, Romania, and the United
Kingdom) were assigned the EU26 mean (11:7lg=L), the num-
ber of attributable cases in the European Union (both sexes,
≥20-y age group) was estimated to be 5,711 (95% CI: 2,908,
8,414) cases with a PAF of 4.2% (95% CI: 2.2, 6.2) (Table 3).
Replacing country-specific mean THM values with alternative
low-exposure (mean −SD or 0 if negative, resulting EUmean =
0:5lg=L) and high-exposure (mean + SD; EU mean = 22:9lg=L)
scenarios resulted in 1,907 (95% CI: 972, 2,808) and 12,101 (95%
CI: 6,351, 17,346) estimated attributable cases per year, respec-
tively, among men and women ≥20 years of age (Table 4).
Similarly, in the 30- to 79-y age group, the number of attributable
cases ranged from 1,308 (95% CI: 667, 1,925) in the lowest-
exposure scenario to 8,334 (95% CI: 4,387, 11,918) in the highest-
exposure scenario (Table S4).
Reducing estimated mean THM values to the current EU
mean (11:7lg=L) for 13 countries with higher THM exposures
reduced the estimated number of attributable cases by 2,868 per
year (95% CI: 1,522, 4,060), a 43.7% reduction relative to the pri-
mary estimate for men and women ≥20 years of age (Table 5).
The largest absolute reduction would occur in Romania (891
cases), Spain (860 cases), and the United Kingdom (685 cases).
The largest reduction relative to the current number of attribut-
able cases occurred in Romania (85.1%), Cyprus (80.3%), Malta
(74.5%), and Ireland (73.5%). In the 30- to 79-y age group, 2,016
(95% CI: 1,074, 2,843) annual attributable bladder cancer cases
would be avoided (Table S5).
Discussion
We conducted the first Europe-wide assessment of THM levels in
drinking water and estimated the THM-attributable burden of
bladder cancer using monitoring data covering 75% of the popu-
lation in 26 EU countries. We estimated an annual average THM
level of 11:7lg=L (SD: 11.2) and a PAF of 4.9% (95% CI: 2.5,
7.1; country-specific range: 0–23%), corresponding to 6,561
(95% CI: 3,389, 9,537) bladder cancer cases per year among men
and women ≥20 years of age. Reducing estimated mean THM
levels to the EU average for 13 countries with higher exposures
reduced the estimated number of attributable cases by 43.7%
(2,868 fewer cases per year).
Although national averages may hide disparities within coun-
tries, i.e., areas supplied with ground vs. surface water may have
lower THM levels, we prioritized width to depth in the data col-
lection in order to compare the average situation between coun-
tries. We used the population-weighted mean where possible to
harness this possible difference. The annual THM average was
above 25 lg=L in only 5 of 26 countries with monitoring data:
Cyprus, Malta, Ireland, Spain, and Greece. Chlorine is the main
disinfectant used to treat drinking water in Cyprus, Ireland, and
Greece (where surface water is the primary source) and in Spain
(where groundwater is the primary source). In Malta, where
desalination is the primary source of drinking water, THMs con-
sist primarily of bromoform. Interventions should focus on
Figure 1. Map of national average total trihalomethanes (THM) levels in drinking water in European Union countries, 2005–2018. Note: See Table 1 and
Table S1 for details of the estimated THM averages in the different countries. AT, Austria; BE, Belgium; BG, Bulgaria; CY, Cyprus; CZ, Czech Republic; DE,
Germany; DK, Denmark; EE, Estonia; ES, Spain; FI, Finland; FR, France; GB, United Kingdom; GR, Greece; HR, Croatia; HU, Hungary; IE, Ireland; IT,
Italy; LT, Lithuania; LU, Luxembourg; LV, Latvia; MT, Malta; NL, Netherlands; PL, Poland; PT, Portugal; RO, Romania; SE, Sweden; SI, Slovenia; SK,
Slovakia.
Environmental Health Perspectives 017001-7 128(1) January 2020
Table 3. Estimated population-attributable fraction (PAF) and number of bladder cancer (BC) cases attributable to total trihalomethanes (THM) levels in 28 EU countries, men and women, 20 years of age and
above.
Country Population
a
Annual BC
cases
a
Mean THM
(lg=L) OR (95% CI)
b
PAF
[% (95% CI)] Attributable cases
(95% CI) Contribution
c
Sensitivity analysis for countries with <50%coverage
(assigned EU26 mean)
PAF
[% (95% CI)] Attributable cases
(95% CI) Contribution
b,c
Austria 7,024,117 2,084 1.1
d
1.004 (1.002, 1.007) 0.4 (0.2, 0.7) 9 (5, 14) 0.1% 0.4 (0.2, 0.7) 9 (5, 14) 0.2%
Belgium 8,808,207 3,188 13.2 1.054 (1.027, 1.082) 5.1 (2.6, 7.6) 163 (83, 241) 2.5% 5.1 (2.6, 7.6) 163 (83, 241) 2.9%
Bulgaria 6,028,262 1,468 11.7
d
1.048 (1.024, 1.072) 4.6 (2.3, 6.8) 67 (34, 99) 1.0% 4.6 (2.3, 6.8) 67 (34, 99) 0.2%
Croatia 3,364,105 1,144 10.2 1.042 (1.021, 1.063) 4.0 (2.0, 5.9) 46 (23, 68) 0.7% 4.0 (2.0, 5.9) 46 (23, 68) 0.8%
Cyprus 707,247 162 66.2 1.302 (1.141, 1.486) 23.2 (12.4, 32.7) 38 (20, 53) 0.6% 23.2 (12.4, 32.7) 38 (20, 53) 0.7%
Czech Republic 8,566,358 2,764 12.8 1.052 (1.026, 1.080) 5.0 (2.5, 7.4) 138 (70, 204) 2.1% 5.0 (2.5, 7.4) 138 (70, 204) 24%
Denmark
e
4,417,579 2,017 0.02 1.000 (1.000, 1.000) 0.0 (0.0, 0.0) 0 (0, 0) 0.0% 0.0 (0.0, 0.0) 0 (0, 0) 0.0%
Estonia 1,055,356 247 13.7 1.056 (1.028, 1.086) 5.3 (2.7, 7.9) 13 (7, 19) 0.2% 5.3 (2.7, 7.9) 13 (7, 19) 0.2%
Finland 4,314,703 890 7.6 1.031 (1.015, 1.047) 3.0 (1.5, 4.4) 27 (13, 40) 0.4% 3.0 (1.5, 4.4) 27 (13, 40) 0.5%
France 49,073,604 16,161 11.7 1.048 (1.024, 1.072) 4.6 (2.3, 6.8) 737 (373, 1,092) 11.2% 4.6 (2.3, 6.8) 737 (373, 1,092) 12.9%
Germany 67,512,197 20,093 0.5 1.002 (1.001, 1.003) 0.2 (0.1, 0.3) 40 (20, 60) 0.6% 0.2 (0.1, 0.3) 40 (20, 60) 0.7%
Greece 8,819,379 3,386 26.3 1.111 (1.054, 1.171) 10.0 (5.1, 14.6) 338 (173, 493) 5.1% 4.6 (2.3, 6.8)
f
155 (78, 229)
f
2.7%
Hungary 7,976,719 2,250 10.0 1.041 (1.041, 1.062) 3.9 (2.0, 5.8) 88 (45, 131) 1.3% 3.9 (2.0, 5.8) 88 (45, 131) 1.5%
Ireland 3,338,589 667 47.3 1.208 (1.099, 1.327) 17.2 (9.0, 24.6) 115 (60, 164) 1.7% 17.2 (9.0, 24.6) 115 (60, 164) 2.0%
Italy 49,506,336 27,294 3.1 1.012 (1.006, 1.019) 1.2 (0.6, 1.8) 336 (169, 501) 5.1% 4.6 (2.3, 6.8)
f
1245 (631, 1845)
f
21.8%
Latvia 1,602,227 406 7.2 1.029 (1.014, 1.044) 2.8 (1.4, 4.2) 11 (6, 17) 0.2% 2.8 (1.4, 4.2) 11 (6, 17) 0.2%
Lithuania 2,330,161 447 1.0 1.004 (1.002, 1.006) 0.4 (0.2, 0.6) 2 (1, 3) 0.0% 0.4 (0.2, 0.6) 2 (1, 3) 0.0%
Luxembourg 452,860 128 7.5 1.030 (1.015, 1.046) 2.9 (1.5, 4.4) 4 (2, 6) 0.1% 2.9 (1.5, 4.4) 4 (2, 6) 0.1%
Malta 334,530 97 49.4 1.218 (1.104, 1.344) 17.9 (9.4, 25.6) 17 (9, 25) 0.3% 17.9 (9.4, 25.6) 17 (9, 25) 0.3%
Netherlands 13,334,551 5,163 0.2 1.001 (1.000, 1.001) 0.1 (0.0, 0.1) 4 (2, 6) 0.1% 0.1 (0.0, 0.1) 4 (2, 6) 0.1%
Poland 31,003,748 7,687 5.7 1.023 (1.012, 1.035) 2.3 (1.1, 3.4) 174 (88, 259) 2.6% 2.3 (1.1, 3.4) 174 (88, 259) 3.0%
Portugal 8,469,059 2,021 23.8 1.100 (1.049, 1.153) 9.1 (4.6, 13.3) 183 (94, 268) 2.8% 9.1 (4.6, 13.3) 183 (94, 268) 3.2%
Romania 15,346,980 3,411 91.8
e
1.443 (1.201, 1.732) 30.7 (16.8, 42.3) 1,047 (572, 1,442) 16.0% 4.6 (2.3, 6.8)
f
156 (79, 231)
f
2.7%
Slovakia 4,350,449 957 10.0 1.041 (1.020, 1.062) 3.9 (2.0, 5.8) 37 (19, 56) 0.6% 3.9 (2.0, 5.8) 37 (19, 56) 0.7%
Slovenia 1,667,591 300 2.9 1.012 (1.006, 1.017) 1.1 (0.6, 1.7) 3 (2, 5) 0.1% 1.1 (0.6, 1.7) 3 (2, 5) 0.1%
Spain 37,275,483 13,648 28.8 1.122 (1.059, 1.118) 10.9 (5.6, 15.8) 1,482 (763, 2,160) 22.6% 10.9 (5.6, 15.8) 1,482 (763, 2,160) 26.0%
Sweden 7,677,260 2,195 10.0 1.041 (1.020, 1.062) 3.9 (2.0, 5.8) 86 (43, 127) 1.3% 3.9 (2.0, 5.8) 86 (43, 127) 1.5%
United Kingdom 50,314,449 14,702 24.2 1.102 (1.050, 1.156) 9.2 (4.7, 13.5) 1,356 (695, 1,984) 20.7% 4.6 (2.3, 6.8)
f
671(340, 994)
f
11.8%
Total EU28 404,672,106 134,976 11.7
g
—4.9 (2.5, 7.1) 6,561 (3,389, 9,537) 100.0% 4.2 (2.2, 6.2) 5,711 (2,908, 8414) 100.0%
Note: CI, confidence interval; OR, odds ratio.
a
Country population and bladder cancer cases reported by Global Burden of Disease Study in 2016 (≥20-y age group, men and women) (IHME 2016a,2016b).
b
Country-specific ORs were derived by converting the pooled OR for a 1-lg=L THM increment (OR = 1:004), derived using pooled data for men and women age 30–80 from Costet et al. 2011) to a country-specific ORifor bladder cancer in
association with the country-specific mean exposure vs. no exposure {ORi= exp ½ðln1:004Þ× THMi;%PAFi=½ðORi−1Þ=ORi× 100; attributable casesi= annual casesi× PAFi}.
c
Country contribution: contribution (percent) of each country to the total attributable cases.
d
Imputed levels (see Table S1 for details).
e
Only chloroform is monitored in Denmark; THM values correspond to chloroform values only.
f
Bulgaria, Greece, Italy, Romania, United Kingdom (countries included in the sensitivity analysis for countries with <50%coverage).
g
EU mean corresponds to the population-weighted average based on the 26 countries for which THM data were available (Table 2).
Environmental Health Perspectives 017001-8 128(1) January 2020
further reductions in THM levels in these countries. Previous
studies in European regions found THM levels similar to the
ones in our study in Italy, Lithuania, Spain, and the United
Kingdom, but Greece (the island of Crete) showed lower levels,
and France (Rennes region) showed higher levels than the
national averages reported in the present study (Goslan et al.
2014;Krasner et al. 2016). Outside the European Union, recently
reported THM levels varied from 6:2lg=L in Dharan, Saudi
Arabia (2012) (Chowdhury 2013)to21:1lg=L in Tetovo, North
Macedonia (2011) (Bujar et al. 2013,2017), 35:4lg=LinAnkara,
Turkey (2016) (Babayigit et al. 2016), 43:9lg=L in Quebec,
Canada (2000–2001) (Rodriguez et al. 2004), and 260 lg=Lin
Islamabad, Pakistan (2012) (Amjad et al. 2013).
Over the last 20 y, many EU countries managed to decrease
the THM levels in their public drinking water by changing
treatment methods including disinfection and by improving
the quality of the water resources and the distribution network
infrastructures (Palacios et al. 2000;Premazzi et al. 1997;
Llopis-González et al. 2010;Gómez-Gutiérrez et al. 2012). In
France, for example, water utilities have made efforts to reduce
soluble organic matter in surface water sources, and chlorine dos-
age has been optimized to keep residual chlorine in the distribu-
tion network with minimal DBP formation (Corso et al. 2018;
Courcier et al. 2014). In Italy, chlorine dioxide is widely used,
contributing to lower levels of THMs but also to higher levels of
chlorite and chlorate (Fantuzzi et al. 2007). In other countries,
the use of ozone (e.g., the Netherlands, Germany, and France),
UV radiation (Austria), or chloramines (e.g., Finland, Sweden)
alone or in combination with chlorine result in lower concentra-
tions of THMs.
However, each chemical or disinfection process contributes to
the formation of other disinfectant-specific by-products, e.g.,
aldehydes, ketones, keto aldehydes, carboxylic acids, keto acids
(after ozonation), bromate (after ozonation in presence of bro-
mide), nitrosamines (after chlorination and chloramination), or
chlorite/chlorate (after chlorine dioxide) (Kristiana et al. 2013;
Richardson et al. 2000;Sorlini et al. 2014;von Gunten 2003).
Disinfectants are highly reactive by definition, and any one of
them will lead to the formation of DBPs (Hua and Reckhow
2007). Most of them are not regulated, and many are considered
carcinogenic and/or genotoxic and have been associated with
bladder cancer (e.g., nitrosamines) (Richardson et al. 2007), but
their effect on human health has not been sufficiently studied.
DBPs constitute a complex mixture of hundreds of chemicals
(Richardson et al. 2007), and THMs have been used in epidemio-
logical studies as surrogates of total DBP content. THMs have
limitations as markers of total DBPs since they are not the most
toxic (Plewa et al. 2008), are present in mixtures with other
DBPs and their effects cannot be fully separated (Rice et al.
2009), and correlations with specific DBPs are variable
(Villanueva et al. 2012). However, the exposure–response rela-
tionship is only available for total THMs.
Table 4. Estimated number of bladder cancer (BC) cases in Europe attributable to total trihalomethane (THM) levels in the lowest and highest exposure scenar-
ios, men and women, age 20 years and above, in 28 European countries (EU28).
Country Population
a
BC incidence
(no. per
100,000)
a
Annual BC
cases
a
Mean THM (lg=L) Attributable cases
Current mean ± SD
Lowest
scenario mean
(mean −1 SD)
b
Highest
scenario mean
(mean + 1 SD)
b
Lowest scenario
[n(95% CI)] Highest scenario
[n(95% CI)]
Austria 7,024,117 30 2,084 1:1±5:9
c
0.0 7.0 0 (0, 0) 57 (29, 85)
Belgium 8,808,207 36 3,188 13:2±4:0 9.2 17.1 115 (58, 170) 211 (107, 311)
Bulgaria 6,028,262 24 1,468 11:7±11:2
c
0.5 22.9 3 (1, 4) 128 (66, 188)
Croatia 3,364,105 34 1,144 10:2±5:9 4.3 16.1 19 (10, 29) 71 (36, 105)
Cyprus 707,247 23 162 66:2±33:2 33.0 99.4 20 (10, 29) 53 (29, 72)
Czech Republic 8,566,358 32 2,764 12:8±9:6 3.2 22.4 35 (18, 53) 236 (121, 346)
Denmark
d
4,417,579 46 2,017 0:0±0:1 0.0 0.1 0 (0, 0) 1 (0, 1)
Estonia 1,055,356 23 247 13:7±12:8 1.0 26.5 1 (0, 1) 25 (13, 36)
Finland 4,314,703 21 890 7:6±11:2 0.0 18.8 0 (0, 0) 64 (33, 95)
France 49,073,604 33 16,161 11:7±11:2 0.5 22.9 32 (16, 48) 1,412 (723, 2069)
Germany 67,512,197 30 20,093 0:5±11:2 0.0 11.7 0 (0, 0) 917 (464, 1,358)
Greece 8,819,379 38 3,386 26:3±9:2 17.1 35.6 223 (114, 329) 448 (232, 649)
Hungary 7,976,719 28 2,250 10:0±20:0 0.0 30.0 0 (0, 0) 254 (131, 370)
Ireland 3,338,589 20 667 47:3±25:4 21.9 72.7 56 (29, 82) 168 (90, 235)
Italy 49,506,336 55 27,294 3:1±3:6 0.0 6.7 0 (0, 0) 716 (361, 1,066)
Latvia 1,602,227 25 406 7:2±2:6 4.6 9.7 7 (4, 11) 16 (8, 23)
Lithuania 2,330,161 19 447 1:0±5:9 0.0 6.9 0 (0, 0) 12 (6, 18)
Luxembourg 452,860 28 128 7:5±3:0 4.5 10.5 2 (1, 3) 5 (3, 8)
Malta 334,530 29 97 49:4±11:2 38.2 60.6 14 (7, 20) 21 (11, 29)
Netherlands 13,334,551 39 5,163 0:2±11:2 0.0 11.4 0 (0, 0) 230 (116, 340)
Poland 31,003,748 25 7,687 5:7±6:7 0.0 12.4 0 (0, 0) 371 (188, 549)
Portugal 8,469,059 24 2,021 23:8±19:3 4.5 43.1 36 (18, 53) 319 (167, 459)
Romania 15,346,980 22 3,411 91:8±64:2
c
27.7 156.0 357 (183, 520) 1,581 (913, 2,070)
Slovakia 4,350,449 22 957 10:0±11:2 0.0 21.2 0 (0, 0) 78 (40, 114)
Slovenia 1,667,591 18 300 2:9±4:5 0.0 7.4 0 (0, 0) 9 (4, 13)
Spain 37,275,483 37 13,648 28:8±28:6 0.2 57.4 13 (7, 20) 2,793 (1478, 3,964)
Sweden 7,677,260 29 2,195 10:0±11:2 0.0 21.2 0 (0, 0) 178 (91, 261)
United Kingdom 50,314,449 29 14,702 24:2±7:1 17.2 31.3 974 (496, 1,435) 1,727 (892, 2,511)
Total EU28 404,672,106 33 134,976 11:7±11:2 0.5 22.9 1,907 (972, 2,808) 12,101 (6,351, 17,346)
Note: BC incidence, annual, per 100,000 population. CI, confidence interval; SD, standard deviation.
a
Country population and BC incidence and cases reported by the Global Burden of Disease Study in 2016 (≥20-y age group, men and women (IHME 2016a,2016b).
b
Lowest THM level scenario: mean THM −1 SD, with negative values forced to 0. Highest THM level scenario: mean + 1 SD. When the SD was not available for a given country, the
average SD (11:2lg=L) for Europe was assigned. This was the case for Bulgaria, Finland, France, Germany, Malta, the Netherlands, Slovakia, and Sweden. Austria was assigned the
SD for Lithuania (5:9lg=L).
c
Imputed levels (see Table S1 for details).
d
Only chloroform is monitored in Denmark; THM values correspond to chloroform values only.
Environmental Health Perspectives 017001-9 128(1) January 2020
In 2016, a total of 135,011 bladder cancer cases occurred in
the European Union, of which 134,976 (99.97%) were in the
≥20-y age group (IHME 2016a). Current THM levels would lead
to an estimated considerable attributable proportion of cases,
4.9% (95% CI: 2.5, 7.1), or 6,561 cases (95% CI: 3,389; 9,537).
Spain was the country with the greatest estimated contribution
(23% of attributable EU cases) followed by the United Kingdom
(21%) and Romania (16%), explained largely by high incidence
rates (Spain, Romania), large population size (the United
Kingdom ranks the second EU country in inhabitants), or high
average THM levels (Romania). However, the quality of THM
data for Romania was low (few published studies with very low
population coverage) and may not accurately reflect the current
country average. Romania accounted for 16% of all attributable
bladder cancer cases; therefore, if THM levels were overesti-
mated for Romania, attributable bladder cancer cases would have
been overestimated for the country and for the European Union
as a whole. We estimated a PAF of 4.6% for France (737 attribut-
able cases/year), which is lower than estimates reported by Corso
et al. (2017) (PAF = 16%; 1,485 attributable cases/year) based on
a nationwide study that used 2011 estimates of bladder cancer
incidence in men from the French network of cancer registries
[FRANCIM (INCa and InVS 2011) vs. the 2016 Global Burden
of Disease study used in our analysis], THM levels at the outlet
of all French water treatment plants from the national database
SISE-Eaux (http://www.data.eaufrance.fr/concept/sise-eaux) (vs.
the national mean estimates in the present analysis), and categori-
cal ORs from the pooled analysis of data for men reported by
Costet et al. (2011) vs. the continuous exposure–response func-
tion that we derived using pooled data for both men and women
from Costet et al. (2011). In addition, for Bulgaria, we could not
find any published data at all, and we assigned the EU mean, but
it is a small country (1.5% of the EU population) and therefore
has little influence in the overall European estimates.
We calculated the burden of bladder cancer based on current
THM levels, assuming no changes in future THM levels, bladder
cancer incidence, and population size and distribution. Thus, our
estimations should be interpreted as future projections rather than
estimates of the actual burden of disease, since recent THM data
do not necessarily reflect past exposures. For future estimates,
sources of error include changes in population structure and inci-
dence rates, since the European population is growing and getting
older (Eurostat), and the bladder cancer incidence is expected to
increase in some European countries and decrease in others over
the next decade (Antoni et al. 2017;Wong et al. 2018). We used
incidence data for bladder cancer from the Global Burden of
Disease 2016 study, which uses multiple sources depending on
the country (e.g., WHO mortality data, national registries, vital
statistics, modeling from neighboring regions, etc.). Accuracy
may differ, since not all keep nationwide cancer registries or there
Table 5. Estimated number of attributable bladder cancer (BC) cases if no country would exceed the current EU total trihalomethanes (THM) mean level
(11:9lg=L), men and women, age 20 years and above, in 28 European countries (EU28).
Country Annual BC
cases
a
Current scenario Reduced exposure scenario
Mean THM
(lg=L) Attributable cases
(95% CI) Mean THM
(lg=L) Attributable cases
(95% CI)
Reduction in
attributable
cases (95% CI)
b
Percent
reduction
Country
contribution
reduction (%)
c
Austria
d
1,908 1.1 9 (5, 14) 1.1 9 (5, 14) 0 (0, 0) 0.0 0.0
Belgium
e
2,909 13.2 163 (83, 241) 11.7 145 (74, 216) 18 (9, 26) 10.8 0.5
Bulgaria
d
1,445 11.7 68 (34, 101) 11.7 67 (34, 99) 0 (0, 0) 0.0 0.0
Croatia 1,102 10.2 46 (23, 68) 10.2 46 (23, 68) 0 (0, 0) 0.0 0.0
Cyprus
e
151 66.2 38 (20, 53) 11.7 7 (4, 11) 30 (16, 42) 80.3 1.1
Czech Republic
e
2,664 12.8 138 (70, 204) 11.7 126 (64, 187) 11 (6, 17) 8.3 0.3
Denmark
f
1,896 0.02 0 (0, 0) 0.02 0 (0, 0) 0 (0, 0) 0.0 0.0
Estonia
e
236 13.7 13 (7, 19) 11.7 11 (6, 17) 2 (1, 3) 14.4 0.1
Finland 816 7.6 27 (13, 40) 7.6 27 (13, 40) 0 (0, 0) 0.0 0.0
France 14,409 11.7 737 (373, 1,092) 11.7 737 (373, 1,092) 0 (0, 0) 0.0 0.0
Germany 18,513 0.5 40 (20, 60) 0.5 40 (20, 60) 0 (0, 0) 0.0 0.0
Greece
e
3,116 26.3 338 (173, 493) 11.7 155 (78, 229) 183 (95, 264) 54.2 6.4
Hungary 2,172 10.0 88 (45, 131) 10.0 88 (45, 131) 0 (0, 0) 0.0 0.0
Ireland
e
621 47.3 115 (60, 164) 11.7 30 (15, 45) 84 (45, 119) 73.5 3.0
Italy 24,693 3.1 336 (169, 501) 3.1 336 (169, 501) 0 (0, 0) 0.0 0.0
Latvia 391 7.2 11 (6, 17) 7.2 11 (6, 17) 0 (0, 0) 0.0 0.0
Lithuania 430 1.0 2 (1, 3) 1.0 2 (1, 3) 0 (0, 0) 0.0 0.0
Luxembourg 120 7.5 4 (2, 6) 7.5 4 (2, 6) 0 (0, 0) 0.0 0.0
Malta
e
91 49.4 17 (9, 25) 11.7 4 (2, 7) 13 (7, 18) 74.5 0.5
Netherlands 4,814 0.2 4 (2, 6) 0.2 4 (2, 6) 0 (0, 0) 0.0 0.0
Poland 7,410 5.7 174 (88, 259) 5.7 174 (88, 259) 0 (0, 0) 0.0 0.0
Portugal
e
1,867 23.8 183 (94, 268) 11.7 92 (47, 137) 91 (47, 131) 49.6 3.1
Romania
d,e
3,349 91.8 1,047 (572, 1,442) 11.7 156 (79, 231) 891 (493, 1,211) 85.1 31.4
Slovakia 922 10.0 37 (19, 56) 10.0 37 (19, 56) 0 (0, 0) 0.0 0.0
Slovenia 276 2.9 3 (2, 5) 2.9 3 (2, 5) 0 (0, 0) 0.0 0.0
Spain
e
12,374 28.8 1,482 (763, 2,160) 11.7 623 (315, 923) 860 (448, 1,237) 58.0 30.0
Sweden 1,969 10.0 86 (43, 127) 10.0 86 (43, 127) 0 (0, 0) 0.0 0.0
United Kingdom
e
13,143 24.2 1,356 (695, 1,984) 11.7 671 (340, 994) 685 (355, 991) 50.5 23.8
Total EU28 123,805 11.7 6,561 (3,389, 9,537) 7.5 3,693 (1,867, 5,478) 2,868 (1,522, 4,060) 43.7 100.0
Note: Reduced scenario: no country exceeds the current EU THM mean (11:7lg=L); the EU mean level was assigned to countries with current THM levels above the EU mean. CI,
confidence interval.
a
Bladder cancer cases reported by Global Burden of Disease Study in 2016 (≥20-y age group, men and women) (IHME 2016a).
b
Reduction-attributable cases: the number of BC cases attributable to THMs were reduced in the reduced exposure scenario.
c
Country contribution: contribution (percentage) of each country to the total attributable cases.
d
Imputed levels (see Table S1 for details).
e
Countries where current THM average level is above the EU mean (11:7lg=L).
f
Only chloroform is monitored in Denmark; THM values correspond to chloroform values only.
Environmental Health Perspectives 017001-10 128(1) January 2020
may be discrepancies with national databases. In the French
study, for example (Corso et al. 2017), bladder cancer cases were
considerably lower in all ages (n= 9,100 in 2011, men only) than
the ones reported in the Global Burden of Disease 2016 study
(n= 13,959 in 2016, men only).
We used pooled data for 3,481 cases and 5,977 controls from
7 case–control studies included in a meta-analysis by Costet et al.
(2011) to derive the continuous exposure–response function that
was the basis of our country-specific ORs for bladder cancer in
association with country-specific mean THM estimates. Although
this is the most comprehensive pooled analysis currently avail-
able, it is limited to case–control studies and does not include a
recent U.S. study of 1,213 bladder cancer cases and 1,418 con-
trols (Beane Freeman et al. 2017).
An underlying assumption of this research study is the causal
relationship between THMs and bladder cancer. Many DBPs
have been classified as mutagenic or genotoxic based on in vitro
assays or experimental studies of animals (Richardson et al.
2007). In addition, a study of 49 adults reported that micronuclei
counts in peripheral lymphocytes and urine mutagenicity were
associated with higher levels of individual brominated THMs in
exhaled breath following 40 min of swimming (Kogevinas et al.
2010), while another study of 43 adults (Espín-Pérez et al. 2018)
reported that changes in exhaled DBPs following a 40-min swim
in a chlorinated pool were associated with microRNA and gene
expression patterns that may indicate an increased risk of bladder
cancer. However, some uncertainties in the association still exist,
e.g., the putative agent(s) is yet to be identified, the biological
pathways are not completely established, and the inconsistent
association in some studies in women is not well understood.
Additionally, the precision of the exposure–response relationship
decreases at higher exposure levels, given the smaller statistical
power at the higher-exposure end, as shown in Figure S1. This
may lead to inaccurate estimates in countries with high THM lev-
els. Polymorphisms in DBP-metabolizing genes have been shown
to modify the exposure–response relationship (Cantor et al.
2010), but these population differences are unlikely to affect our
overall results.
Our analyses are based on men and women combined. While
most of the case–control studies included in the pooled analysis
report a null or inverse association among women, there are also
case–control studies showing higher risks in women than men
(Beane Freeman et al. 2017). Future studies may want to consider
comparing estimates based on sex-specific exposure–response
functions to estimates for men and women combined.
We have not considered the proportion of use of bottled or fil-
tered water, which, in some countries, may be substantial and
account for exposure misclassification through the ingestion route
(Wright et al. 2006), nor the exposure to DBPs through inhalation
and dermal exposure during household cleaning activities
(Charisiadis et al. 2014), showering or bathing, or in swimming
pools (Villanueva et al. 2007), which contributes to increased
THM exposure because the available data set of Costet et al.
2011 did not include this information for all studies. Although
models are adjusted for the main risk factors of bladder cancer,
the potential for residual confounding cannot be ruled out.
The biggest challenge has been the collection of representa-
tive THM data at the national level in the 28 EU countries for a
comparable recent period. In particular, the data for Romania are
a limitation, and the estimated PAF and attributable cases for
Romania were markedly reduced when using the EU mean in
place of the original estimate. In addition, using the EU mean for
all countries with <50%coverage (Greece, Italy, Romania, and
the United Kingdom) resulted in a net decrease in the overall
PAF and attributable case estimates. Potential exposure
misclassification may result from reliance on monitoring data
covering 75% of the population that may lead both to over- or
underestimation of the THM average. For some countries, a vari-
able proportion of the noncovered population may use private
wells with low THM levels. For example, in the Czech Republic,
94% of the population is served by public water supply systems,
but we had THM data only for 74%. Similarly in Greece, for
large cities including Thessaloniki and Larisa, THM data were
not available. However, we do not have this type of information
for all the countries, and we cannot generalize and anticipate the
impact on the EU population-weighted THM estimate.
The reporting situation differs widely among countries.
According to the European Council (EC) Drinking Water
Directive, countries are obliged to report the drinking water qual-
ity to the public and the EC in a 3-year report. However, only the
number of THM analyses and percentage of noncompliant meas-
urements are presented and not the actual monitoring or even de-
scriptive data (EC 1998). Only some countries maintain a
centralized electronic database of THM measurements and only
Ireland (U.S. EPA 2015) and Denmark (GEUS) have this data-
base publicly available. Denmark provides information only for
chloroform since it is the only DBP regularly measured. Danish
drinking water is not chlorinated, but chloroform has been found
in groundwater and can either originate from anthropogenic pol-
lution or be of natural origin, i.e., from forest soil (Hunkeler et al.,
2012). Open data are available for some countries in a decentral-
ized way, which forced us to do an extensive internet search of
municipality and water utility websites (e.g., Italy, Greece),
including manual data extraction from published individual labo-
ratory reports (e.g., Luxemburg).
Not all municipalities or water utilities report their water qual-
ity analysis results, and among the ones that do, only a subset
includes THMs values. For example, for Italy, we checked rele-
vant websites covering 54% of the Italian population, and, of
these, only 35% included THM information. It is therefore impor-
tant for these countries to set up centralized electronic databases
to monitor drinking water quality and for these databases to be
publicly available, both to the EC and also to the public and sci-
entific community. This is also in line with the proposal for the
new EC directive (EC 2018) on the quality of water intended for
human consumption that requires the establishment of centralized
databases and better publicity of the results of water quality anal-
yses. However, in the new directive, there is no provision to
lower the maximum permissible limit for THMs of 100 lg=Lor
to include information on the actual monitoring results in these
databases, although it proposes to regulate additional DBPs such
as HAAs, chlorite, and chlorate.
Another source of heterogeneity in THM levels is the diver-
sity of monitoring sampling sites (e.g., treatment plant, distribu-
tion network, and consumers’taps). This is relevant since THM
levels may differ, i.e., levels may increase with residence time in
the distribution network and distance to the tap, presence of addi-
tional chlorination, distribution network maintenance, etc.
(Charisiadis et al. 2015). Only 12 of 26 countries report THM
measurements collected at consumers’taps only. The rest report
measurements from specimens collected in a variety of places
(water treatment plants, water tanks, distribution network, and
taps), and annual averages may not accurately reflect levels at the
consumers’taps. Routine monitoring is less frequent in small
water supplies, sometimes only once per year, and may not reflect
the annual average exposure. However, it involves a relatively
small amount of population, and this potential source of error
would be minor in the overall estimates. Furthermore, for some
countries, we could not calculate the population-weighted aver-
age due to lack of appropriate data and used the nonweighted one
Environmental Health Perspectives 017001-11 128(1) January 2020
in the estimation of the EU mean. The weighted average may be
different from the nonweighted average, depending on the size of
the population served by each water distribution system and its
respective THM levels.
Conclusion
The current average THMs levels in drinking water in all EU
countries were below the European regulatory limits, although
maximum levels showed exceedance in nine countries. Assuming
a causal association, our results suggest that current THM expo-
sures in the European Union may lead to a considerable number
of bladder cancer cases that could be avoided by optimizing
water treatment, disinfection, and distribution, among other
measures, without compromising the microbiological quality of
drinking water. The main efforts in reduction of THM levels
should be made in countries with the highest proportion of
exceedance and highest average THM levels.
Acknowledgments
This work was funded by the EU Seventh Framework
Programme EXPOsOMICS Project (grant agreement no. 308610),
Human Genetics Foundation agreement 17-080 ISG, and CIBER
Epidemiología y Salud Pública (CIBERESP). ISGlobal is a
member of the Centres de Recerca de Catalunya (CERCA)
Programme, Generalitat de Catalunya. We would like to thank
the members of the European Programme for Intervention
Epidemiology Training (EPIET) Alumni Network (EAN) for
their assistance in identifying appropriate national focal
points in specific countries. We would also like to thank the
people from the national and local authorities and universities
for the provision of THM data: Sofie Dewaele (Leefmilieu
Brussel-BIM/Bruxelles Environnement–IBGE Afd. Inspectie en
verontreinigde bodems, Dpt. Geïntegreerde controles, Brussels,
Belgium), Steven Vanderwaeren (Team Watervoorziening-en
gebruik, Vlaamse Milieumaatschappij, Afdeling Operationeel
Waterbeheer, Brussels, Belgium), Jurica Štiglić(Croatian
National Institute of Public Health, Zagreb, Croatia), Outi
Zacheus (National Institute for Health and Welfare, Kuopio,
Finland), Carmelo Massimo Maida (University of Palermo,
Italy), Anna Norata (Agenzia di Tutela della Salute Citta’
Metropolitana Milano, Italy), Marco Chiesa (Agenzia di Tutela
della Salute della Val Padana-Sede Territoriale di Mantova,
Italy), Vincenzo Clasadonte (Agenzia di Tutela della Salute della
Val Padana-Sede Territoriale Cremona, Italy), Emilia Guberti
(Local Health Authority, Bologna, Italy), Cinzia Govoni (Local
Health Authority, Ferrara, Italy), Paolo Pagliai (Local Health
Authority Romagna, Italy), Daniela de Vita (Local Health
Authority, Reggio Emilia, Italy), Danila Tortorici (Regional
Health and Social Agency, Emilia Romagna, Italy), Marco
Schintu (University of Cagliari, Italy), Paolo Montuori
(University of Napoli Federico II, Italy), Audrius Dedele
(Department of Environmental Sciences, Faculty of Natural
Sciences, Vytautas Magnus University, Kaunas, Lithuania),
Stefan Cachia (Water Services Corporation, Malta), Roel C.H.
Vermuelen (Institute of Risk Assessment Sciences, Utrecht
University, Utrecht, the Netherlands), the Chief Sanitary
Inspectorate (Poland), Luís Simas (Water Quality Department,
Entidade Reguladora, Dos Serviços De Águas e Resíduos,
Lisboa, Portugal), and Christina Forslund (Food Control
Department, National Food Agency, Uppsala, Sweden). Finally,
we would like to thank Charles F. Lynch (University of Iowa,
USA), Sylvaine Cordier (Université de Rennes, Inserm,
Ecole
des hautes études en santé Publique (EHESP), Rennes, France),
Will D. King (Queen’s University, Kingston, Ontario, Canada),
and Kenneth P. Cantor (National Cancer Institute, National
Institutes of Health, Bethesda, USA) for allowing us to use the
dose–exposure data from their study. We are grateful to
Xavier Basagaña (ISGlobal) for statistical assistance.
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