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Applying the exposome concept in birth cohort research: a review of statistical approaches

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dc.contributor.author Santos, Susana
dc.contributor.author Maitre, Léa
dc.contributor.author Warembourg, Charline
dc.contributor.author Agier, Lydiane
dc.contributor.author Richiardi, Lorenzo
dc.contributor.author Basagaña Flores, Xavier
dc.contributor.author Vrijheid, Martine
dc.date.accessioned 2021-02-09T07:04:24Z
dc.date.available 2021-02-09T07:04:24Z
dc.date.issued 2020
dc.identifier.citation Santos S, Maitre L, Warembourg C, Agier L, Richiardi L, Basagaña X, Vrijheid M. Applying the exposome concept in birth cohort research: a review of statistical approaches. Eur J Epidemiol. 2020; 35(3):193-204. DOI: 10.1007/s10654-020-00625-4
dc.identifier.issn 0393-2990
dc.identifier.uri http://hdl.handle.net/10230/46395
dc.description.abstract The exposome represents the totality of life course environmental exposures (including lifestyle and other non-genetic factors), from the prenatal period onwards. This holistic concept of exposure provides a new framework to advance the understanding of complex and multifactorial diseases. Prospective pregnancy and birth cohort studies provide a unique opportunity for exposome research as they are able to capture, from prenatal life onwards, both the external (including lifestyle, chemical, social and wider community-level exposures) and the internal (including inflammation, metabolism, epigenetics, and gut microbiota) domains of the exposome. In this paper, we describe the steps required for applying an exposome approach, describe the main strengths and limitations of different statistical approaches and discuss their challenges, with the aim to provide guidance for methodological choices in the analysis of exposome data in birth cohort studies. An exposome approach implies selecting, pre-processing, describing and analyzing a large set of exposures. Several statistical methods are currently available to assess exposome-health associations, which differ in terms of research question that can be answered, of balance between sensitivity and false discovery proportion, and between computational complexity and simplicity (parsimony). Assessing the association between many exposures and health still raises many exposure assessment issues and statistical challenges. The exposome favors a holistic approach of environmental influences on health, which is likely to allow a more complete understanding of disease etiology.
dc.description.sponsorship This work was supported by the European Union’s Horizon 2020 research and innovation programme under Grant Agreement 733206 (LifeCycle Project) and 874583 (ATHLETE Project).
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Springer
dc.relation.ispartof Eur J Epidemiol. 2020; 35(3):193-204
dc.rights © The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.title Applying the exposome concept in birth cohort research: a review of statistical approaches
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1007/s10654-020-00625-4
dc.subject.keyword Birth cohorts
dc.subject.keyword Environmental epidemiology
dc.subject.keyword Exposome
dc.subject.keyword Life-course epidemiology
dc.subject.keyword Omics
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/733206
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/874583
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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