Cohort description: Measures of early-life behaviour and later psychopathology in the LifeCycle Project - EU Child Cohort Network

Johanna L. Nader, Mònica López-vicente, Jordi Julvez, Monica Guxens, Tim Cadman, Ahmed Elhakeem, Marjo-riitta Järvelin, Nina Rautio, Jouko Miettunen, Hanan El Marroun, Maria Melchior, Barbara Heude, Marie-aline Charles, Tiffany C. Yang, Rosemary R. C. Mceachan, John Wright, Kinga Polanska, Jennie Carson, Ashleigh Lin, Sebastian RauschertRae-chi Huang, Maja Popovic, Lorenzo Richiardi, Eva Corpeleijn, Marloes Cardol, Tuija M. Mikkola, Johan G. Eriksson, Theodosia Salika, Hazel Inskip, Johan Lerbech Vinther, Katrine Strandberg-larsen, Kathrin Gürlich, Veit Grote, Berthold Koletzko, Marina Vafeiadi, Jordi Sunyer, Vincent W. V. Jaddoe, Jennifer R. Harris

Research output: Contribution to journalArticlepeer-review

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Abstract

Background: The EU LifeCycle Project was launched in 2017 to combine, harmonise, and analyse data from more than 250,000 participants across Europe and Australia, involving cohorts participating in the EU-funded LifeCycle Project. The purpose of this cohort description is to provide a detailed overview over the major measures within mental health domains that are available in 17 European and Australian cohorts participating in the LifeCycle Project.

Methods: Data on cognitive, behavioural and psychological development has been collected on participants from birth until adulthood through questionnaire and medical data. We developed an inventory of the available data by mapping individual instruments, domain types, and age groups, providing the basis for statistical harmonization across mental health measures.

Results: The mental health data in LifeCycle contain longitudinal and cross-sectional data for ages 0-18+ years, covering domains across a wide range of behavioural and psychopathology indicators and outcomes (including executive function, depression, ADHD and cognition). These data span a unique combination of qualitative data collected through behavioural/cognitive/mental health questionnaires and examination, as well as data from biological samples and indices in the form of brain imaging (MRI, foetal ultrasound) and DNA methylation data. Harmonized variables on a subset of mental health domains have been developed, providing statistical equivalence of measures required for longitudinal meta-analyses across instruments and cohorts.

Conclusion: Mental health data harmonized through the LifeCycle project can be used to study life course trajectories and exposure-outcome models that examine early life risk factors for mental illness and develop predictive markers for later-life disease.
Original languageEnglish
Pages (from-to)321-331
Number of pages11
JournalJournal of Epidemiology
Volume33
Issue number6
Early online date28 Apr 2022
DOIs
Publication statusPublished - 2023

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