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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.<\/jats:p>","DOI":"10.1007\/s10654-020-00625-4","type":"journal-article","created":{"date-parts":[[2020,3,27]],"date-time":"2020-03-27T08:02:51Z","timestamp":1585296171000},"page":"193-204","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":77,"title":["Applying the exposome concept in birth cohort research: a review of statistical approaches"],"prefix":"10.1007","volume":"35","author":[{"given":"Susana","family":"Santos","sequence":"first","affiliation":[]},{"given":"L\u00e9a","family":"Maitre","sequence":"additional","affiliation":[]},{"given":"Charline","family":"Warembourg","sequence":"additional","affiliation":[]},{"given":"Lydiane","family":"Agier","sequence":"additional","affiliation":[]},{"given":"Lorenzo","family":"Richiardi","sequence":"additional","affiliation":[]},{"given":"Xavier","family":"Basaga\u00f1a","sequence":"additional","affiliation":[]},{"given":"Martine","family":"Vrijheid","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,3,27]]},"reference":[{"key":"625_CR1","doi-asserted-by":"crossref","first-page":"1659","DOI":"10.1016\/S0140-6736(16)31679-8","volume":"388","author":"GBD 2015 Risk Factors Collaborators","year":"2016","unstructured":"GBD 2015 Risk Factors Collaborators. 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