7.3 Smolders

16/10/2013

Interpreting biomarker data from the COPHES‐DEMOCOPHES twin projects:

Using lifestyle and environmental data to understand biomarker differences among countries

HUMAN BIOMONITORING FOR EUROPEa harmonised approach

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» In short:» COPHES: FP7‐project, coordinated by BiPRO GmbH (Germany)» DEMOCOPHES: LIFE+ cofunding together with participating countries,

coordinated by FPS (Belgium)» Primary aims:

» 1. Feasibility study

» 2. Capacity building


‘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.’

‘With great efforts and success, (DEMO)COPHES established an analytical quality assurance scheme (Interlaboratory comparison & External Quality Assessment Schemes) that:

a) enabled identification, training and selection of analytically competent laboratories for the HBM measurements throughout Europe and,

b) guaranteed the reliability and comparability of data throughout Europe and the world

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» In short:» Study details:

» Selected biomarkers: Cd, cotinine, certain phthalates (urine), Hg (hair)

» Study population: 120 mother‐ child pairs per country (CY & LU: n = 60)

» In total, 1844 urine and hair samples were collected» Convenience samples from a rural and urban area» Additionally, BPA was measured in 6 countries


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» Data collection for interpretation purposes:


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Hypotheses tested using aggregate datasetsTested for…

Cd Hg CotinineAre differences in environmental concentrations able to explain differences inbiomarker values (national level)

Air X XFood (for Hg specifically aquatic food products) X XSoil X X

Is anti‐smoking legislation and banning of smoking in public places related tobiomarker values of non‐smokers? X X

Are regional emission data useful to improve the interpretation of biomarkervalues? X X

» Interpreting biomarker data:

» No specific hypotheses were tested for phthalates


Research question: are differences in environmental concentrations or lifestyle variables able to explain differences in biomarker values among the

17 countries participating in the DEMOCOPHES field study?

Hypotheses tested using aggregate datasetsTested for…

Cd Hg CotinineAre differences in environmental concentrations able to explain differences inbiomarker values (national level)

Air X XFood (for Hg specifically aquatic food products) X XSoil X X

Is anti‐smoking legislation and banning of smoking in public places related tobiomarker values of non‐smokers? X X

Are regional emission data useful to improve the interpretation of biomarkervalues? X X

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» Cadmium» Hypothesis: Are differences in environmental concentrations able to

explain differences in urinary Cd (national level) – Air emissions» Data source: Centre on Emission Inventories and Projections (CEIP)


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» Cadmium» Hypothesis: Are differences in environmental concentrations able to

explain differences in urinary Cd (national level) – Air emissions» Data source: Centre on Emission Inventories and Projections database» Biomarker data: Geometric mean (GM) urinary Cd in Mothers


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» Cadmium» Hypothesis: Are differences in dietary lifestyle factors able to explain

differences in urinary Cd – Uptake through food» Data source: European Food Safety Authority (EFSA)

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differences in urinary Cd – Uptake through food» Data source: European Food Safety Authority (EFSA)

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differences in urinary Cd – Uptake through food» Data source: European Food Safety Authority (EFSA)» Biomarker data: Mothers (high exposure scenario*) * Sum of P95 for cereals and vegetables +

mean exposure for whole population

Spearman’s r=0.71 n=8; p=0.058

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» Mercury» Hypothesis: Are differences in dietary lifestyle factors able to explain

differences in Hg in hair – Uptake through fish consumption» Data source: Food and Agriculture Organization (FAO)

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» Mercury» Hypothesis: Are differences in dietary lifestyle factors able to explain

differences in Hg in hair – Uptake through fish consumption» Data source: FAO data – Consumption of marine organisms» Biomarker data: Children and mothers

Spearman’s r=0.75 n=17; p<0.001

Spearman’s r=0.80 n=17; p<0.001

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» Cotinine» Hypothesis: Is anti‐smoking legislation and banning of smoking in

public places related to biomarker values of non‐smokers?» Data source: Smokefree Partnership database and DG Sanco

The countries in green follow both the letterand spirit of the Article 8 guidelines of the WHOFramework Convention on Tobacco Control1. The smoke-free law is strong;2. The smoke-free law is strongly enforced.There is negligible smoking in workplaces, barsand restaurants.

The countries in orange only offer limitedprotection. Many places are smoke free butdoes not give 100% protection against theharmful effects of second-hand smoke due tothe exemptions allowed. In some countries, thelaw is strong, but it is poorly enforced.

The countries in red have weak or unenforcedlaws. Workers are not protected

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» Cotinine» Hypothesis: Is anti‐smoking legislation and banning of smoking in

public places related to biomarker values of non‐smokers?» Data source: Smokefree Partnership database and DG Sanco» Biomarker data: Children and mothers

K-W p=0.039K-W p=0.033*

*

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» CONCLUSIONS» The COPHES/DEMOCOPHES twin projects were succesful in collecting

comparable biomarker data across 17 countries in Europe!

» Although interpretation was not the key goal of the projects, someinteresting findings:

» Cd: marginal significance with air emissions and food quality (onlymothers, reflecting long‐term integration of urinary Cd)

» Hg: clear relationship between both qualitative and quantitativefish consumption

» Cotinine: Countries with a strict anti smoking legislation show lower levels of ETS‐related biomarkers


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» CONCLUSIONS (continued)» (Sub)National datasets: difficult to find representative and comparable

regional data» No data for all DEMOCOPHES countries» Differences in data quality/quantity» Result: limited power of analyses

» Some limitations to use aggregate data:» Problem of spatial scale: How relevant are national emission data?» Study populations not country‐representative (convenience sample)» Harmonized food quality/quantity data difficult to find» Future: more harmonised datasets (EU‐Menu, INSPIRE,…)


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» Take home message…


Harmonised HBM across Europe…

YES WE CAN !!!

Interpretation of biomarker data…

YES WE COULD !!!

Need for continued harmonisation…

YES WE SHOULD !!!

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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

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)


AustriaUmweltbundesamt GmbH

BelgiumVITO

SwitzerlandFederal Office of Public

Health

CyprusSGL

Larnaca Hospital

Czech RepublicNIPH

GermanyUBA

HungaryNIEH

DenmarkUCHP

United KingdomHPA

EstoniaNIHD

SpainISCIII

FinlandTHL

FranceInVS

GreeceNHRF

CroatiaIMROH

IrelandHSEItalyISS

LithuaniaVDU

LuxembourgCRP-GL

Laboratoire National de Santé

the NetherlandsEHSIRIVM

NorwayNIPH-NOPolandNIOM

PortugalAIDFL / IMP

RomaniaEHC

SloveniaJSI

SlovakiaUVZ SR

KUL

SwedenKI-IMM

JRCCEFICHEAL

FPSCoordinator

DEMOCOPHES

DGUVBiPRO

Coordinator COPHES

Luxembourg:Laboratoire Nationale de Santé

(THL)

Cyprus:Larnaca Hospital

Portugal:Institute of Preventive Medicine, Lisbon Faculty of Medicine

(AIDFM / IMP)

Belgium:FPS Health, Food chain safety and environment

Coordinator DEMOCOPHES

Belgium:Katholieke Universiteit Leuven

(KUL)

Health & Medicine

7.3 Smolders