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<title lang=en>Epidemiologic tools to study the influence of environmental factors on fecundity and pregnancy-related outcomes.</title>
<creator>Slama, Rémy</creator>
<creator>Ballester, Ferran</creator>
<creator>Casas, Maribel</creator>
<creator>Cordier, Sylvaine</creator>
<creator>Eggesbø, Merete</creator>
<creator>Iniguez, Carmen</creator>
<creator>Nieuwenhuijsen, Mark</creator>
<creator>Philippat, Claire</creator>
<creator>Rey, Sylvie</creator>
<creator>Vandentorren, Stéphanie</creator>
<creator>Vrijheid, Martine</creator>
<contributor>Equipe avenir "Environmental Epidemiology Applied to Fecundity and Reproduction" ; Université Joseph Fourier - Grenoble 1 (UJF) - Institut National de la Santé et de la Recherche Médicale (INSERM)</contributor>
<contributor>Chercheur Indépendant</contributor>
<contributor>Epidemiologia Ambiental ; Centre for Research in Environmental Epidemiology (CREAL) - Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP) of Pamplona - Institut Hospital del Mar d'Investigacions Mèdiques (IMIM)</contributor>
<contributor>Institut de recherche, santé, environnement et travail [Rennes] (Irset) ; Université d'Angers (UA) - Université des Antilles et de la Guyane (UAG) - Université de Rennes 1 (UR1) - École des Hautes Études en Santé Publique [EHESP] (EHESP) - Institut National de la Santé et de la Recherche Médicale (INSERM) - Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )</contributor>
<contributor>Division of Epidemiology ; Norwegian Institute of Public Health</contributor>
<contributor>Institut de Veille Sanitaire (INVS) ; Institut de Veille Sanitaire (INVS)</contributor>
<description>International audience</description>
<source>ISSN: 0193-936X</source>
<source>EISSN: 1478-6729</source>
<source>Epidemiologic Reviews</source>
<publisher>Oxford University Press (OUP)</publisher>
<identifier>hal-01002724</identifier>
<identifier>https://hal-univ-rennes1.archives-ouvertes.fr/hal-01002724</identifier>
<source>https://hal-univ-rennes1.archives-ouvertes.fr/hal-01002724</source>
<source>Epidemiologic Reviews, Oxford University Press (OUP), 2014, 36 (1), pp.148-64. 〈10.1093/epirev/mxt011〉</source>
<identifier>DOI : 10.1093/epirev/mxt011</identifier>
<relation>info:eu-repo/semantics/altIdentifier/doi/10.1093/epirev/mxt011</relation>
<identifier>PUBMED : 24363355</identifier>
<relation>info:eu-repo/semantics/altIdentifier/pmid/24363355</relation>
<language>en</language>
<subject lang=en>birth weight</subject>
<subject lang=en>cohort studies</subject>
<subject lang=en>congenital abnormalities</subject>
<subject lang=en>environment</subject>
<subject lang=en>fecundity</subject>
<subject lang=en>fetal membranes</subject>
<subject lang=en>premature rupture</subject>
<subject lang=en>pregnancy</subject>
<subject lang=en>preterm birth</subject>
<subject>[SDV.BDLR] Life Sciences [q-bio]/Reproductive Biology</subject>
<type>info:eu-repo/semantics/article</type>
<type>Journal articles</type>
<description lang=en>Adverse pregnancy outcomes entail a large health burden for the mother and offspring; a part of it might be avoided by better understanding the role of environmental factors in their etiology. Our aims were to review the assessment tools to characterize fecundity troubles and pregnancy-related outcomes in human populations and their sensitivity to environmental factors. For each outcome, we reviewed the possible study designs, main sources of bias, and their suggested cures. In terms of study design, for most pregnancy outcomes, cohorts with recruitment early during or even before pregnancy allow efficient characterization of pregnancy-related events, time-varying confounders, and in utero exposures that may impact birth outcomes and child health. Studies on congenital anomalies require specific designs, assessment of anomalies in medical pregnancy terminations, and, for congenital anomalies diagnosed postnatally, follow-up during several months after birth. Statistical analyses should take into account environmental exposures during the relevant time windows; survival models are an appropriate approach for fecundity, fetal loss, and gestational duration/preterm delivery. Analysis of gestational duration could distinguish pregnancies according to delivery induction (and possibly pregnancy-related conditions). In conclusion, careful design and analysis are required to better characterize environmental effects on human reproduction.</description>
<date>2014</date>
</dc>
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