MétaCan
Menu
Retour à la cohorte
Enregistrement W4404774543 · doi:10.3389/frph.2024.1508151

Editorial: Opportunities and challenges of human preconception research

2024· editorial· en· W4404774543 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

aboutLe titre ou le résumé porte un signal canadien du lexique géographique.
no affAucune affiliation canadienne : ce travail est invisible pour une base fondée sur la seule affiliation.
Aucune affiliation canadienne. Une base fondée sur la seule affiliation (le devis habituel) n'aurait jamais vu ce travail. C'est l'un des travaux qui justifient l'inversion de la base.

Notice bibliographique

RevueFrontiers in Reproductive Health · 2024
Typeeditorial
Langueen
DomaineMedicine
ThématiqueReproductive Health and Contraception
Établissements canadiensnon disponible
Organismes subventionnairesNational Institute of Environmental Health SciencesNational Institutes of Health
Mots-clésPregnancyFertilityMedicinePopulationDemographyFamily medicineCohortLive birthMiscarriageEnvironmental healthBiology

Résumé

récupéré en direct d'OpenAlex

Preconception studies are notoriously difficult to conduct and pose distinct challenges and limitations. While studies that recruit individuals or couples trying to conceive benefit from having motivated participants, they result in highly selected cohorts, yielding results that may not be generalizable. Pregnancy planners differ from the general population along sociodemographic axes, including age, race/ethnicity, income, and education. 11,12 Studies focused on assessing time to pregnancy, a measure of couple fecundity, restrict to those who are trying to conceive naturally through unprotected heterosexual intercourse, which excludes not only those receiving ovarian stimulation, intrauterine insemination or in vitro fertilization, but also single women and same-sex couples. Conversely, studies focused on data and biospecimen collection to assess preconception exposures in relation to gamete and/or embryo development often recruit from fertility clinics, resulting in a highly selected sample and risking confounding by indication. Preconception analyses are often conducted using retrospective data collected from birth cohort participants, however these results are generalizable only to those successfully able to conceive. Furthermore, when it is time to analyze results, researchers must account for biases of selection, survival, or enhanced surveillance for outcomes related to conception, pregnancy, live birth, and child health.The largest preconception study to date is the ongoing Pregnancy Study Online (PRESTO), a North American web-based preconception cohort study that recruits female-identifying participants age 21-45 years from the United States and Canada who are actively attempting pregnancy through heterosexual intercourse without medical intervention, then encourages them to invite their male partners to enroll, as well. 13 While it aims to examine how the preconception environment influences reproductive outcomes, it has heretofore been limited in its ability to assess health biomarkers or chemical exposures because of the infeasibility of collecting biological samples from participants outside of two metropolitan areas where they had study sites. The researchers recently piloted remote biospecimen collection, in which they asked participants to mail in urine and blood samples, and in this issue compare the in-person and mail-based approaches in terms of the protocol design, the demographics of those who consented to participate in each protocol, and the costs per sample collected. Koenig et al. provide a detailed accounting of their methods and frank discussion of the challenges they encountered that will be immensely helpful to those contemplating remote biospecimen collection in any context, not only preconception research.Another approach to collecting preconception data at scale that has garnered much interest is by leveraging commercial menstrual cycle tracking apps. Jukic et al. report results of a pilot study designed to characterize app users with the goal of understanding the underlying demographics of the population in anticipation of conducting a larger time-to-pregnancy study that will use app-based recruitment. They partnered with Ovia Fertility, a free menstrual cycle tracking app, and sent an email to a random sample of users age ≥18 years in the United States with a link to an online survey that collected demographic data as well as information about their pregnancy status and intention, reproductive and general health history, and height and weight. As with PRESTO, respondents were asked to invite their partners to participate, in this case by answering questions at the end of the survey. In addition to quantifying the potential recruitment yield for their future time-to-pregnancy study, the authors provide valuable information on aspects of user health and behavior that underscore the potential of menstruation cycle tracking apps to study other aspects of preconception and reproductive health.While the preconception period is generally perceived to refer to the months immediately preceding conception, because oocytes are all created prior to birth, exposures that affect oocyte quality and hence fetal and pregnancy health can occur at any time in the female life course prior to pregnancy. Hipwell et al. take such a life course approach in their analysis of stress exposure throughout childhood and adolescence in relation to birth outcomes. Their study is nested within the Pittsburgh Girls Study, an ongoing longitudinal cohort that enrolled girls age 5-8 years and oversampled from low-income neighborhoods. 14 While the original aim of the study was to describe the co-occurrence of the development of behavior and mental health problems in girls, annual assessments over more than 20 years have provided an opportunity to examine a host of other outcomes, including pregnancy outcomes among those who have gone on to have children of their own. The repurposing of a pediatric cohort to provide preconception data for the next generation is an innovative approach that allows for investigation of a far broader range of exposures at multiple potentially critical periods of reproductive development that may be as relevant as-if not more so than-the months immediately preceding conception.Discovering associations of preconception health with pregnancy and child outcomes is all very interesting from an epidemiologic point of view, but the fundamental purpose of epidemiologic research is to improve public health, so it is important that findings be disseminated to those who might directly benefit from them. How best to do so is the focus of Daly et al., who interviewed twenty women in the West of England about their receptivity to various methods for delivering preconception health advice and approaches to potential interventions. The themes that emerged around accessibility, discretion, and trustworthiness, as well as opinions as to desirable-and undesirable-content are relevant to clinicians, health educators, and anyone planning a campaign to improve preconception health.Collectively, the studies in this special issue highlight the growing interest in preconception health research and posit some innovative options for study design, participant recruitment, and data collection, as well as communication of results to the target population. Despite the challenges of preconception research, there are many opportunities to understand and influence human health. These include the examination of biological mechanisms underlying reproductive development and gamete production, genetic and epigenetic factors that influence fecundity and fetal programming, as well as interactions between social and environmental exposures during critical life stages that affect reproductive health across the life course, and potentially across generations. Finally, while preconception studies have occasionally involved male partners, few have followed maternal-paternalchild triads longitudinally. The associations of male preconception health not only with semen quality, but also with pregnancy and offspring outcomes is an area ripe for future research.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,010
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,050
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0100,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,003
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,143
Tête enseignante GPT0,424
Écart entre enseignants0,281 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle