Scoping review of climate drivers on maternal health: current evidence and clinical implications
Notice bibliographique
Résumé
Objective: To systematically review the literature on associations between climate drivers and health outcomes among pregnant people. This review fills a gap by synthesizing evidence for a clinician audience. Data Sources: Systematic scoping review of articles published in PubMed and clinicaltrials.gov from January 2010 through December 2023. Study Eligibility Criteria: Empirical studies published in English-language peer-reviewed journals, assessing associations between select climate drivers and adverse maternal and birth outcomes. The review included studies examining heat, storms, sea level rise, flooding, drought, wildfires, and other climate-related factors. Health outcomes included preterm birth, low birthweight, small for gestational age, gestational diabetes, pre-eclampsia/eclampsia, miscarriage/stillbirth and maternal mortality. Study Appraisal and Synthesis Methods: The scoping review protocol was registered with the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY202410004, January 3, 2024) and conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). Data were extracted by 2 authors; quality and risk of bias was assessed independently. Results: =158) met inclusion criteria. The majority of studies (146/158; 92.4%) documented statistically significant and clinically meaningful associations between climate drivers and adverse perinatal health outcomes, including risk of preterm birth, low birthweight, and stillbirth as well as preeclampsia, gestational diabetes, miscarriage, and maternal death. Among the most durable findings: extreme heat exposure in early and late pregnancy were associated with increased risk of preterm birth and stillbirth. Driven in part by large (often population-based) studies and objective outcomes from surveillance data or medical record reviews, studies in this scoping review were evaluated as high quality (scoring 7-9 on the Newcastle-Ottawa Scale). Risk of bias was generally low. Conclusions: Climate drivers are consistently associated with adverse health outcomes for pregnant people. Continuing education for clinicians, and clinician-patient communications should be expanded to address risks of climate change and extreme weather exposure, especially risks of extreme heat in late-pregnancy. Results from this review should inform multilevel interventions to address adverse health effects of climate during pregnancy as well as practice advisories, protocols, checklists, and clinical guidelines in obstetrics.
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.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».