results of the first europe-wide hbm study · results of the first europe-wide hbm study . ......
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HUMAN BIOMONITORING FOR EUROPE
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Schoeters Greet
Results of the first Europe-wide HBM study
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Outline
• The COPHES-DEMOCOPHES approach
• Calculation of “European exposure values”
• Comparison mothers and children
• Comparison across countries
• Factors which determine exposure
– Personal factors
– Life style factors
– Environmental factors
• Comparison with health based guidance values
• Conclusions
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Feasibility to perform HBM in a coherent and harmonised approach throughout
Europe by means of commonly developed protocols, strategies and scientific tools
ensuring reliable and comparable data.’
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Nov 2009
- Nov 2012
Dec 2010
- Nov 2012
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COPHES partners: 24
EU Member States
and Switserland,
Norway, Croatia
17 Active
DEMOCOPHES
countries: BE, CY,
DE, DK, PL, Ro, SI,
ES, HU, SE, UK, PT,
Cz, SK, LU, IE, CH
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Study population • 120 children (6-11 yrs) and their mothers ( < 45 years) per country
except for Cyprus and Luxembourg (60 mother-child pairs)
• Convenience samples from a rural and urban area selected from lower
and upper end of urbanisation category, not industrial hot spots
– Selection via population register
– Sampling via schools
• Provide hair and urine samples
• Stratification by age and gender
• Information on lifestyle, dietary habits, covariates through personalised
interviews (paper or computerised questionnaires)
• 4 month recruitment period between October 2011 and January 2012
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lead by Umweltbundesambt ,Germany (M. Kolossa –Gehring, K. Becker, G. Schwedler, U..
Fiddicke, M. Seiwert)
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Chemicals
• Mercury: Fish, amalgam fillings
Neurodevelopmental toxicant
• Cadmium: batteries, contaminated soils Nephrotoxicant, reproduction & development
• Phthalates: DEHP, DEP, BiBP, MnBP, MBzP plastics, PVC, food packaging, cosmetics
Endocrine disruptors
• Tobacco smoke Cancer
• Bisphenol A : tinned cans Estrogen activity
hair
urine
urine
urine
urine
H-Hg
U-Cd
U-MEHP
5OH-MEHP
5oxo-MEHP
U-MEP
U-BiBP
U-MnBP
U-MBzP
U-cotinine
U-BPA
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• Centrally organised ICI / EQUAS rounds
• Web-based training
• BPA and TCS: no centrally organised QC/QA
Chemical analysis
lead by Univ of Dusseldorf (J. Angerer, H. Koch, B. Schindler) &
Instituto de Salud Carlos III, Spain (A. Castano , M. Esteban)
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Data management and statistical analysis
• European exposure values: – Geometric means (95% confidence interval) - 90th percentile (95% CI)
– Weighed: all countries contribute equally (except LU, CY)
– Adjusted for a priori defined confounders: age, gender, creatinine,
smoking
• Comparison of countries: – Weighed ANOVA
– Adjusted for confounders
• Exposure determinants
– Multiple mixed regression models: takes into account „clustering‟
8 Lead by VITO: G. Schoeters, E. Den Hond, E. Govarts
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Subject characteristics
Children (n=1844) Mothers (n=1844)
Age, years (median, P25-P75) 8 (7-10) 39 (35-42)
Girls / boys 50.5% / 49.5% -
Frequent fish consumption 24% 26%
Smoking habits 0% smokers 15.3% daily smokers
5.7% occasional smokers
21.7% former smokers
% Environmental Tobacco
Smoke
Home: 17%
Elsewhere: 42%
Home: 11%
Elsewhere: 56%
Educational level (family) Primary: 9.0%; Secondary: 32.9%; Tertiary: 58.1%
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European exposure values:
Average exposure: geometric mean and 95%CI
P90 and 95%CI
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Average EU exposure values: GM (95% CI)
Children Mothers
Mercury in hair µg/g 0.145 (0.139 – 0.151) 0.225 (0.216 – 0.234)
U-Cotinine µg/L 0.797 (0.759 – 0.837) 2.751 (2.406 – 3.145)
U-Cadmium µg/L 0.071 (0.069 – 0.074) 0.219 (0.211 – 0.228)
U-DEHP metabolites µg/L 47.6 (46.0-49.3) 29.2 (28.1-30.3)
U-MnBP µg/L 34.8 (33.5-36.2) 23.9 (23.0-24.9)
U-MBzP µg/L 7.1 (6.8-7.5) 4.5 (4.3-4.7)
U-MEP µg/L 34.4 (32.8-36.0) 48.2 (45.6-51.0)
U-MiBP µg/L 45.4 (43.6-47.3) 30.1 (28.9-31.4)
U-Bisphenol A µg/L 1.97 (1.81 – 2.15) 1.78 (1.62 – 1.94)
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Children Mothers
Mercury in hair µg/g 0.145 (0.139 – 0.151) 0.225 (0.216 – 0.234)
U-Cotinine µg/L 0.797 (0.759 – 0.837) 2.751 (2.406 – 3.145)
U-Cadmium µg/L 0.071 (0.069 – 0.074) 0.219 (0.211 – 0.228)
U-DEHP metabolites µg/L 47.6 (46.0-49.3) 29.2 (28.1-30.3)
U-MnBP µg/L 34.8 (33.5-36.2) 23.9 (23.0-24.9)
U-MBzP µg/L 7.1 (6.8-7.5) 4.5 (4.3-4.7)
U-MEP µg/L 34.4 (32.8-36.0) 48.2 (45.6-51.0)
U-MiBP µg/L 45.4 (43.6-47.3) 30.1 (28.9-31.4)
U-Bisphenol A µg/L 1.97 (1.81 – 2.15) 1.78 (1.62 – 1.94)
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High correlation between mothers and children
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0
20
40
60
80
100
0 20 40 60
sum
DEH
P m
etab
olit
es in
uri
ne (µ
g/L)
, c
hild
ren
sum DEHP metabolites in urine (µg/L), mothers
DEHP metabolites in urine - correlation between children and mothers
0
20
40
60
80
100
0 20 40 60
Mn
BP
in u
rin
e (µ
g/L)
, ch
ildre
n
MnBP in urine (µg/L), mothers
MnBP in urine - correlation between children and mothers
0
5
10
15
20
25
0 5 10 15
MB
zP in
uri
ne
(µg/
L), c
hild
ren
MBzP in urine (µg/L), mothers
MBzP in urine - correlation between children and mothers
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Biomarker values show a large variability in the population
Children Mothers
Biomarker Unit P90 P90/P10 P90 P90/P10
Mercury in hair µg/g 0.8 (0.7-0.9) 27 1.2 (1.1- 1.3) 25
U-Cotinine µg/L 4.9 (3.9-6.2) 26 1182 (974-1433) 4884
U-Cadmium µg/L 0.22 (0.21-0.23) 6 0.62 (0.58-0.66) 6
U-DEHP metab. µg/L 137 (126-150) 8 91 (84-100) 10
U-MnBP µg/L 95 (87- 104) 8 66 (61-72) 8
U-MBzP µg/L 28 (25-31) 12 17.7 (16.1-19.5) 13
U-MEP µg/L 159 (138-183) 18 252 (221-287) 26,4
U-MiBP µg/L 131 (117-147) 8 88 (81-96) 8
U-Bisphenol A µg/L 7.4 (6.2-8.7) 12 6.6 (5.6-7.7) 15 13
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Spain
Portugal East –European
countries
Countries differ in their exposure profiles
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Mercury in hair: comparison within Europe
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0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0
Hungary RomaniaGermany
Slovak RepublicPoland
United KingdomSwitzerland
Czech RepublicIreland
ALLSweden
SloveniaBelgium
LuxembourgDenmark
CyprusPortugal
Spain
Mercury in hair (µg/g), adjusted for age
Mercury in hair - mothers
p<0.001
p<0.001
p<0.001
p<0.001
p<0.001
p<0.001
p<0.001
p=0.09
p<0.001
p=0.06
p<0.001
p<0.001
p<0.001
p<0.001
p<0.001
p<0.001
p<0.001
* NHANES 1999-2000; 16-49 yr. women; N=1736:GM (95% CI) = 0.20 (0.16-0.24) µg Hg/g hair
* Health-based guideline (JECFA): 2.5 µg Hg/ g hair
0 20 40 60 80 100
Hungary
Germany
Poland
Switzerland
Romania
Slovak Republic
Ireland
Czech Republic
Slovenia
Luxembourg
Sweden
United Kingdom
Belgium
Denmark
Cyprus
Spain
Portugal
% children eating fish several times/week
Sea fish consumption
P
9
0
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Mercury in hair: effect of fish consumption
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0.206 0.135 0.311 0.2180.00
0.20
0.40
0.60
0.80
1.00
> 1/monthsn=246
≤ 1/monthsn=1561
> 1/monthsn=298
≤ 1/monthsn=1515
Me
rcu
ry i
n h
air
(µ
g/g
)
Mercury in hair -relation with fresh water fish consumption
CHILDREN MOTHERS
p<0.001 p<0.001
0.566 0.111 0.780 0.1820.00
0.20
0.40
0.60
0.80
1.00
> 1/weekn=283
≤ 1/weekn=1549
> 1/weekn=294
≤ 1/weekn=1541
Mer
cury
in h
air
(µg/
g)
Mercury in hair -relation with sea fish consumption
CHILDREN MOTHERS
p<0.001 p<0.001
Levels increase
Children: age, consumption of sea fish, shell fish, sea food
products, fresh water fish, educational level of the family
Mothers: age, consumption of sea fish, shell fish, fresh
water fish, educational level of the family
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Determinants of exposure to mercury in children:
multiple regression model
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Parameters Strata Estimate (95%CI) for
change (multiplicative factor)
p-value
overal
l p-value
Number of observations in model: n=1798
Gender
boys 0.96 (0.89 – 1.05) 0.37 0.37 girls 1.00 -
Age 5-8 years 1.08 (1.00 – 1.17) 0.06 0.06 9-11 years 1.00 -
Consumption of sea fish Several times per week 1.46 (1.26 – 1.69) <0.001 <0.001 Once per week or less 1.00
Consumption of shellfish Several times per week 1.56 (1.35 – 1.79) <0.001 <0.001 Once per week or less 1.00
Consumption of fresh water fish
Several times per week 1.23 (1.08 – 1.39) <0.001 <0.001 Once per week or less 1.00
Educational level of the familiy
primary 0.81 (0.69 – 0.96) 0.01 <0.001 secondary 0.81 (0.74 – 0.90) <0.001 tertiary 1.00 -
Area of residence Urban 1.35 (1.23 – 1.47) <0.001 <0.001 Rural 1.00
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Not all Europeans are equal
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0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
Sweden
Luxembourg
Denmark
Spain
ALL
Belgium
Slovenia
BPA in urine (µg/L), adjusted for creatinine, age and gender
Bisphenol A in urine - children
Overall p-value: p=0.04
p=0.008
p=0.56
p=0.72
p=0.78
p=0.17
p=0.02
0 10 20 30 40 50 60 70 80 90 100
Cyprus Luxembourg
Switzerland
Belgium
United Kingdom
Germany
Denmark
Slovenia
Portugal Sweden
ALL
Hungary
Ireland
Czech Republic
Spain
Romania
Poland
Slovac Republic
sum DEHP metabolites in urine (µg/L), adj. for creatinine, age, gender
sum DEHP metabolites in urine - children
p<0.001
p<0.001
p<0.001
p<0.001
p<0.001
p<0.001
p=0.001
p=0.54
p=0.21
p=0.004
p=0.009
p<0.001
p=0.96
p<0.001
p<0.001
p<0.001
p<0.001
0 5 10 15 20 25 30
Cyprus
Romania
United Kingdom
Switzerland
Luxembourg
Ireland
Germany
Hungary
ALL
Slovac Republic
Denmark
Slovenia
Portugal
Belgium
Czech Republic
Poland
Spain
Sweden
MBzP in urine (µg/L), adjusted for creatinine, age and gender
MBzP in urine - children
p<0.001
p<0.001
p<0.001
p<0.001
p=0.002
p=0.004
p=0.10
p=0.55
p=0.71
p=0.55
p=0.41
p=0.04
p=0.61
p=0.01
p<0.001
p=0.03
p<0.001
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Environmental factors Trend
p<0,05
Biomarker / matrix Studypopulation
Ice cream consumption U-DEHP metabolites children
U-MnBP mothers
U-MBzP mothers and children
Gum consumption U-DEHP metabolites children
U-MEP mothers
PVC in floors/ walls U-MnBP children
U-MBzP/MiBP mothers and children
Renovation of house U-MiBP mothers
Use of personal care
products
MEP mothers and children
U-MiBP children
Consumption of canned
food
U-BPA mothers
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Environmental factors Trend
p<0,05
Biomarker / matrix Studypopulation
Lower level of education of
family
Mercury in hair mothers and children
U-cotinine children and non-
smoking mothers
U-cadmium mothers
U-DEHP metabolites mother
U-MnBP children
U-MiBP mothers
U-MEP children
U-BPA children
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Cotinine in urine: ETS exposure
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7,027 1,595 0,574 2,117 0,6480
1
2
3
4
5
6
7
8
9
ETS daily
n=175
ETS less than
dailyn=128
ETS never
n=1513
ETS
n=158
no ETS
n=1259
Co
tin
ine
in
uri
ne
(µ
g/g
cre
ati
nin
e)
Cotinine in urine - relation with ETS at home
CHILDREN MOTHERS
p<0.001p<0.001
non-smoking mothers
1,163 0,588 0,847 0,6240,0
0,5
1,0
1,5
2,0
ETS n=768
no ETSn=1048
ETSn=811
no ETS n=611
Co
tin
ine
in
uri
ne
(µ
g/g
cre
ati
nin
e)
Cotinine in urine - relation with ETS elsewhere
CHILDREN MOTHERS
p=0.11p<0.001
non-smoking mothers only
Levels increase
Children: urinary creatinine, age,ETS at home, ETS elsewhere, ETS last
24 hrs, educational level of the family
Non smoking mothers: ETS at home,ETS during last 24hrs, educational level
of the family
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Cotinine in urine: distribution within EU
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0.0 0.5 1.0 1.5 2.0 2.5 3.0
Sweden
Germany
Luxembourg
Switzerland
Slovenia
Belgium
Denmark
United Kingdom
Ireland
ALL
Cyprus
Slovac Republic
Portugal
Spain
Poland
Czech Republic
Hungary
Roemenia
Cotinine in urine (µg/L), adjusted for creatinine, age and gender
Cotinine in urine - results in children
p<0.001
p<0.001
p<0.001
p<0.001
p<0.001
p=0.01
p=0.04
p=0.71
p=0.049
p=0.002
p=0.001
p<0.001
p=0.21
p<0.001
p<0.001
p<0.001
p<0.001
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Exposure to second hand smoke and legislation
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Environmental determinants of exposure
Mercury and fish consumption
Cotinine and exposure to tobacco smoke
Cadmium and tobacco smoke
Pthtalates and personal care products, use of PVC in floors/walls,
ice cream, gum
Bisphenol A and consumption of canned foods
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Exposure vs. health-based guidance values
• German HBM commission: HBM I & HBM II values
• Biomonitoring Equivalents (BE)
= concentration of a chemical, consistent with existing health-
based guidance values e.g. TDI
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<HBM I no adverse health effects expected
>HBM I & <HBM II adverse health effects can not be excluded with
sufficient certainty
>HBM II adverse health effects expected
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Mercury in hair: health-based guidance values
2.3 µg/g hair
JECFA/WHO
5 µg/g hair
HBMI
Total N HBM I
>5 µg Hg/g hair
Provisional threshold
value JECFA/WHO:
>2.3 µg Hg/g hair
Children 1836 5 (0.3%) 25 (1.4%)
Mothers 1839 6 (0.3%) 62 (3.4%)
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Conclusions • Biomarker values showed a large variability in the population and between
the countries
• Exposure of the general population in EU is well below the current health
based guidance values, very few participants had values which were higher
that the health based guidance values.
• The biomarker levels in children were highly correlated with the levels in
their mother, especially for mercury and cotinine, which may indicate a
common environmental factor that influences the biomarker level.
• The information reported by the participants on their environment and life
style allowed to identify factors that influence the biomarker levels and
hence indicate a leverage for intervention
27 Environmental research , 141, August 2015
Environ Health Perspect. 2015 Mar;123(3):255-63. doi: 10.1289/ehp.1408616.
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Conclusion: EU wide human biomonitoring at the cross cutting of
environment, life style and health:
a new joint venture for a healthier Europe
• Man made chemicals are prevalent in the general population but we
need comparable data ( cfr US NHANES) than can be linked to
environment and life style in the EU
• EU wide human biomonitoring : evaluates policy measures and sets
new priorities , to protect all citizens alike
• Solid human biomonitoring data are needed to quantify linkage to
health outcomes
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Thanks
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• Protocol development : L. Casteleyn (KUL, Be)
• Recruitment and sampling: M. Kolossa –Gehring ( UBA, De)
• Sample processing and QA: J. Angerer (RUB, De), A. Castano ( ISCIII, Es)
• Data analysis and interpretation: G. Schoeters, E. Den Hond (VITO, Be)
• Communication: O. Sepai ( PHE, UK)
• Training; L. Bloemen (EHSI, Nl) , M. Horvat (JSI, Sv)
• HBM and related research: L.E. Knudsen (UCPH, Dk)
• HBM and policy: A. Joas (BIPRO, De)
• Coordination: R. Joas (BIPRO, DE)
COPHES was funded by the European Commission (FP7 grant agreement 244237)
DEMOCOPHES was funded by LIFE+ ( grant agreement LIFE09ENV/BE/000410)
Coordinated by P. Biot & D. Aerts (FPS, Be)
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United Kingdom:
Health Protection Agency
(HPA)
Ireland:
Health Service Executive
(HSE) The Netherlands:
Environmental Health Sciences International
(EHSI)
The Netherlands:
National Institute of Public Health and the Environment
(RIVM)
Spain:
Instituto de Salud Carlos III
(ISCIII)
Italy:
Istituto Superiore di Sanità
(ISS)
Germany:
BiPRO GmbH Coordinator COPHES
Belgium:
FPS Health, Food chain safety and environment
Katholieke universiteit Leuven Coordinator DEMOCOPHES
Denmark:
University of Copenhagen
(UCHP)
Estonia:
National Institute for Health Development
(NIHD)
Belgium:
Flemish Institute for technological Research
(VITO)
Belgium:
Joint Research Centre
(JRC)
Belgium:
CEFIC
Belgium:
Health and Environment Alliance
(HEAL)
Switzerland:
Federal Office of Public Health
Germany:
Umweltbundesamt
(UBA)
Germany:
Deutsche Gesetzliche Unfallversicherung
(DGUV)
Austria:
Umweltbundesamt GmbH
Czech Republic:
National Institute of Public Health
(NIPH) Hungary:
National Institute of Environmental Health
(NIEH)
France:
Institut de Veille Sanitaire
(InVS) Croatia:
Institute for Medical Research and Occupational Health
(IMROH)
Lithuania:
Nvytautas Magnus University
(VDU)
Luxembourg:
Centre de Recherche Public – Gabriel Lippmann
(CRP-GL)
Finland:
National Institute for Health and Welfare
(THL) Sweden:
Karolinska Institutet
(KI-IMM)
Norway:
National Institute of Public Health Norway
(NIPH-NO)
Poland:
Nofer Institute of Occupational Medicine
(NIOM)
Romania:
Environmental Health Center
(EHC)
Slovenia:
Jozef Stefan Institute
(JSI)
Slovakia:
Public Health Authority of the Slovak Republic
(UVZ SR)
Greece:
National Hellenic Research Foundation
(NHRF) Cyprus:
Ministry of Health - State General Laboratory
(SGL)
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Austria
Umweltbundesamt GmbH
Belgium
VITO
Switzerland
Federal Office of Public
Health
Cyprus
SGL
Larnaca Hospital
Czech Republic
NIPH
Germany
UBA
Hungary
NIEH
Denmark
UCHP
United Kingdom
HPA
Estonia
NIHD
Spain
ISCIII
Finland
THL
France
InVS
Greece
NHRF
Croatia
IMROH
Ireland
HSE
Italy
ISS
Lithuania
VDU
Luxembourg
CRP-GL
Laboratoire National de Santé
the Netherlands
EHSI
RIVM
Norway
NIPH-NO
Poland
NIOM
Portugal
AIDFL / IMP
Romania
EHC
Slovenia
JSI
Slovakia
UVZ SR
Sweden
KI-IMM
JRC
CEFIC
HEAL
FPS & KUL
Coordinator
DEMOCOPHES
DGUV
BiPRO
Coordinator COPHES
Luxembourg:
Laboratoire Nationale de Santé
(THL)
Cyprus:
Larnaca Hospital
Portugal:
Institute of Preventive Medicine, Lisbon Faculty of Medicine
(AIDFM / IMP)