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European Birth Cohorts Overview Some lessons from data pooling

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.

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European Birth Cohorts Overview Some lessons from data pooling

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  1. European Birth Cohorts • Overview • Somelessonsfrom data pooling Martine Vrijheid

  2. 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. Pregnancy and birth cohort studies have played an important role in studying these effects. In Europe, there are many pregnancy and birth cohorts currently collecting a wealth of information on environmental exposure and child outcomes. Data are often of fragmented nature and there is relatively little coordination to structure and consolidate scattered research.

  3. ENRIECO • 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

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

  5. ArcRisk-Norway Faroes MoBa • LUKAS Size of circle: < 1,000 1-5,000 5-20,000 100,000 INUENDO HUMIS BAMSE DNBC BiB ABCD Generation R KOALA PIAMA • KANC DARC • INUENDO • REPRO_PL Duisburg MAS Leicester • Krákow FLEHS I INUENDO • Czech LISAplus ALSPAC • PCB cohort GINIplus PARIS EDEN PÉLAGIE Co.N.ER NINFEA INMA-new GASPII INMA-old Generation XXI RHEA 37 birth cohorts

  6. www.birthcohortsenrieco.net

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

  8. Exposures

  9. ExposureBiomarkers

  10. www.birthcohorts.net

  11. 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.

  12. Govarts et al. 2011. 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

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

  14. 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

  15. 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

  16. Cohorts in WG 1 • (dampness/mould) • ALSPAC • BAMSE • CO.N.ER • DARC • GINI • KOALA • Leicester • LISA • MAS • NINFEA • PIAMA-NHS • Cohorts in WG 2 • (smoke+asthma 4-6y) • ALSPAC • AMICS • BAMSE • DARC • GINI • PIAMA-NHS • KOALA • Leicester • LISA • MAS • Cohorts in WG 3 • (smoke+wheeze 0-2y) • ALSPAC • AMICS • BAMSE • CO.N.ER • DARC • Generation R • GINI • 8.-11. 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

  17. 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

  18. 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

  19. % % cohort ES (95% CI) ES (95% CI) Weight Weight AMICS-M 1.48 (0.71, 3.08) 1.48 (0.71, 3.08) 6.65 6.65 BAMSE 1.50 (1.16, 1.94) 1.50 (1.16, 1.94) 53.93 53.93 DARC 1.55 (0.56, 4.29) 1.55 (0.56, 4.29) 3.44 3.44 LISA 1.67 (0.90, 3.10) 1.67 (0.90, 3.10) 9.32 9.32 MAS 2.83 (1.29, 6.19) 2.83 (1.29, 6.19) 5.82 5.82 PIAMA 1.10 (0.73, 1.66) 1.10 (0.73, 1.66) 20.83 20.83 Overall (I-squared = 0.0%, p = 0.444) 1.47 (1.22, 1.78) 1.47 (1.22, 1.78) 100.00 100.00 NOTE: Weights are from random effects analysis .162 1 1 6.19 Step 5: Data Analyses Prenatal second hand smoke exposure and asthma age 4-6 years Adjusted for sex, parental asthma, parental education, birth weight and older siblings. Courtesy: Thomas Keil

  20. 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 asingle data collection and harmonization process. • Complex data questions solved by telephone contacts with most cohorts in a fast and uncomplicated way. Courtesy: Thomas Keil

  21. 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

  22. Lessons • More than 35 birth cohorts in Europe, studying more than 350 000 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.

  23. 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.

  24. 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: www.enrieco.org Inventory: www.birthcohortsenrieco.net

  25. 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 www.chicosproject.eu

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