European Birth Cohorts - Overview - Some lessons from data pooling Martine Vrijheid

Background  Foetus and infant are especially vulnerable to the effects of environmental contaminants, and that these effects may manifest themselves throughout the lifetime and even over generations. In Europe, there are many pregnancy and birth cohorts currently collecting a wealth of information on environmental exposure and child outcomes. Pregnancy and birth cohort studies have played an important role in studying these effects. Data are often of fragmented nature and there is relatively little coordination to structure and consolidate scattered research.

Aim Coordination of European birth cohort research in the area of environmental exposures. Objectives Inventory of birth cohort data Evaluate exposure, health and exposure-response data Attempt to combine data from various cohorts Make recommendations Methods Inventory questionnaires to cohorts Working Groups – expert evaluation of cohort data Workshops involving all cohorts ENRIECO

Objectives 1.Inventory of data from cohorts and registries 2.Evaluation of existing information 3.Recommendations for research action in key areas of policy concern 4.Recommendations for improved contribution of mother-child cohort research to policy at European level 5.Dissemination Aim To develop a strategy for mother-child cohort research in Europe through the coordination of European cohorts.

Faroes DNBC Co.N.ER INUENDO Duisburg EDEN Generation XXI FLEHS I HUMIS INMA-old REPRO_PL KANC LUKAS PCB cohort INUENDO RHEA Czech Leicester MAS NINFEA GASPII INUENDO GINIplus BAMSE PÉLAGIE MoBa ABCD Generation R KOALA PIAMA LISAplus ALSPAC BiB Size of circle: < 1, , , ,000 INMA-new DARC PARIS ArcRisk-Norway Krákow 37 birth cohorts

B: blood, CB: cord blood, U: urine, P: placenta, BM: breastmilk, S: saliva, H: hair,

Exposures

Exposure Biomarkers

Combining data – ongoing:  POPs & birth outcomes  Smoking, SHS & asthma and allergies  Alcohol consumption & birth outcomes  Socioeconomic inequalities & birth outcomes  Maternal occupation & birth outcomes  Fish consumption & birth outcomes  Maternal complications & asthma and allergies  Obesity – BMI as predictor of body fat  Other EU projects: air pollution, water DBPs, biological agents, etc.

Govarts et al EHP. In Press. Prenatal exposure to polychlorinated biphenyls (PCB) and dichlorodiphenyldichloroethylene (DDE) and fetal growth: a meta-analysis within 12 European birth cohorts. Association of cord serum concentrations of PCB 153 (ng/L) with birth weight (grams

Case studies to evaluate combined data analyses… …using the original raw data from European birth cohorts on allergy / asthma to examine associations between: indoor environmental exposures (a. dampness/mould; b. second hand tobacco smoke) allergies (asthma, allergic rhinitis, eczema) Courtesy: Thomas Keil

Step 1: Willingness to participate Step 2: Assess eligibility of cohorts Step 3: Collect individual participant data Step 4: Harmonise data Step 5: Perform analyses (indiv. cohorts and meta- a.) Courtesy: Thomas Keil

Step 1: Willingness to participate Trust building - Personal contact, if possible - Transparency throughout (propose analysis strategy, discuss analysis plan, agree!, abstracts, publications) - Regular information on progress Courtesy: Thomas Keil

Cohorts in WG 1 (dampness/mould) 1.ALSPAC 2.BAMSE 3.CO.N.ER 4.DARC 5.GINI 6.KOALA 7.Leicester 8.LISA 9.MAS 10. NINFEA 11. PIAMA-NHS Cohorts in WG 2 (smoke+asthma 4-6 y) 1.ALSPAC 2.AMICS 3.BAMSE 4.DARC 5.GINI 6.PIAMA-NHS 7.KOALA 8.Leicester 9. LISA 10. MAS Cohorts in WG 3 (smoke+wheeze 0-2y ) 1. ALSPAC 2. AMICS 3. BAMSE 4. CO.N.ER 5. DARC 6. Generation R 7. GINI INMA A, G, S, V 12. KOALA 13. Leicester 14. LISA 15. MAS 16. NINFEA 17. PIAMA-NHS 18. EDEN 19. RHEA Step 2: Eligibility of Cohorts Courtesy: Thomas Keil

Step 3: Delays in data collection process because of Variables not send in correct order Labels did not often include the whole translated questions Half of the variables were wrongly or not translated at all Plausibility checks showed categories were sometimes wrong (eg non-smokers with 10 cig/day) Courtesy: Thomas Keil

Step 4: Data Harmonization Homogeneous data only for some outcome variables (ISAAC questions were often modified) Very heterogeneous data for: - Main exposures (mould/dampness, smoking) - Potential confounders (breast feeding, smoking, educational level etc) - Variation in time points of exposure and follow-up assessment Courtesy: Thomas Keil

Adjusted for sex, parental asthma, parental education, birth weight and older siblings. Prenatal second hand smoke exposure and asthma age 4-6 years Step 5: Data Analyses Courtesy: Thomas Keil

What went well? Kick-Off Meeting successful to establish personal contacts and interest in case studies. Key responsibility for coordination and communication concentrated in one institution; with a single data collection and harmonization process. Complex data questions solved by telephone contacts with most cohorts in a fast and uncomplicated way. Courtesy: Thomas Keil

What were the challenges? -Time and effort for data management were underestimated -Heterogeneity of outcome data -Heterogeneity of exposure data -Frequent meetings and personal contacts essential Compromises for outcome and exposure variables result in loss of information in harmonized datasets. Courtesy: Thomas Keil

Lessons  More than 35 birth cohorts in Europe, studying more than mother-child pairs  Data and methods are fragmented  Combining information is possible and scientifically beneficial  Combining data from existing cohorts requires careful consideration of the aims, protocols, data, ethical issues, analyses and management  it is time and labour intensive.

Future??  Flexible and long-term platform/network/infrastructure  for combined studies  for exchange of methods/expertise  Flexible to inclusion of new cohorts  Expansion to countries outside Europe This will only be possible with continued support for coordination.

Collaborators Project PI: Mark Nieuwenhuijsen (CREAL) Postdoc: Maribel Casas (CREAL) WP leaders: Martine Vrijheid, Ulrike Gehring, Remy Slama, Joachim Heinreich, Thomas Keil, Manolis Kogevinas Cohort representatives: Anna Bergström, Amanda Carmichael, Sylvaine Cordier, Merete Eggesbø, Esben Eller, Maria P Fantini, Marieta F Fernández, Ana Fernández-Somoano, Regina Grazuleviciene, Cynthia Hohmann, Anne M Karvonen, Gudrun Koppen, Ursula Krämer, Claudia E Kuehni, Per Magnus, Renata Majewska, Anne Marie Nybo Andersen, Evridiki Patelarou, Maria Skaalum Petersen, Frank H Pierik, Kinga Polanska, Daniela Porta, Lorenzo Richiardi, Ana Cristina Santos, Radim J Sram, Carel Thijs, Christina Tischer, Gunnar Toft, Tomáš Trnovec, Stephanie Vandentorren, Tanja GM Vrijkotte, Michael Wilhelm, John Wright The full evaluation reports are publically available through the ENRIECO website: Inventory:

Project PI:- Martine Vrijheid Partners: ALSPAC cohort (Bristol, UK)- Debbie Lawlor, Particia Lucas Danish National Birth Cohort - Anne-Marie Nybo Andersen Generation R cohort (Netherlands)- Vincent Jaddoe, Hein Raat, Johan de Jongste, Liesbeth Duijts INMA cohort (Spain)- Jordi Sunyer, Mark Nieuwenhuijsen MoBa cohort (Norway)- Camilla Stoltenberg, Per Magnus NINFEA cohort (Turin)- Franco Merletti, Lorenz Richiardi RHEA cohort (Crete)- Manolis Kogevinas, Leda Chatzi