Trajectories of depressive and anxiety symptoms from pregnancy to 24-months postpartum during the COVID-19 pandemic
Notice bibliographique
Résumé
Background: As many as 1 in 5 pregnant individuals will develop symptoms consistent with perinatal mood and anxiety disorders (PMADs), making PMADs one of the most common obstetrical complications. The COVID-19 pandemic is a unique stressor which has increased burden on the mental health of pregnant and postpartum individuals. Most studies examining the impact of the pandemic on perinatal mental health have been cross-sectional, while existing longitudinal studies are limited and don’t span beyond 15-months postpartum or have a representative pan-Canadian sample. Examining symptom trajectories would allow for a fuller understanding of the course of depression and anxiety symptoms and tailoring of screening and referral guidelines. Despite being initially high at the beginning of the pandemic, it is unclear if anxiety and depression symptoms have persisted or diminished as the pandemic progressed, and which factors may contribute to trajectories of long-term adverse mental health outcomes. Methods: The current study recruited 9463 pregnant people between 8-35-weeks of pregnancy from the pan-Canadian Pregnancy during the Pandemic (PdP) Cohort. Each participant completed a baseline survey between April 2020 and April 2021, and completed mental health measures at 6-months, 12-months, and 24-months postpartum. Using latent class mixed models, group-based trajectory analysis was used to determine trajectories of anxiety and depression symptoms. Model fit was evaluated using Bayesian and Akaike model criterion. Multinomial logistic regression analysis was conducted to compare trajectory characteristics across groups. Results: A three-class depression symptomology model (moderate-stable 60.9%; elevated-decreasing 26.7%; low-stable 12.4%) and a three-class anxiety model (elevated-increasing 20.2%; elevated-decreasing 65.85%; low-stable 14%) was identified and considered the best fitting model. Common risk factors of depression and anxiety across groups with elevated symptoms include identifying as non-White (odds ratios [ORs] varied from 1.22 to 1.50), low household income (odds ratios [ORs] varied from 1.67 to 2.34), being single (odds ratios [ORs] varied from 1.64 to 2.29), having a history of pre-pregnancy anxiety and/or depression (odds ratios [ORs] varied from 2.53 to 3.06), poor sleep quality (odds ratios [ORs] varied from 1.07 to 1.13), unplanned pregnancy (odds ratios [ORs] varied from 1.40 to 1.82), and elevated baseline anxiety and depression at intake (odds ratios [ORs] varied from 1.27 to 9.84). Common COVID-19 pandemic-related risk factors of depression and anxiety across groups with elevated symptoms include fear their life or their unborn baby’s life was in danger (odds ratios [ORs] varied from 1.01 to 1.02), changes to birth plan due to the pandemic (odds ratios [ORs] varied from 1.82 to 1.88), decreased income due to the pandemic (odds ratios [ORs] varied from 1.44 to 1.58) and feeling more alone than usual (odds ratios [ORs] varied from 1.02 to 1.04).Conclusion: The current study is the first to describe mental health trajectories in a large pan-Canadian sample that began at the beginning of the COVID-19 pandemic. Findings indicate clinically elevated levels of anxiety and depression from pregnancy to the postpartum period, that declined for some groups or persisted throughout the perinatal period. The COVID-19 pandemic was a unique stressor, with consequences ranging far beyond pregnancy. Understanding the depressive and anxiety trajectories of pregnant and postpartum individuals in the context of the pandemic may help to identify individuals who are at greater risk for developing PMADs. These findings could aid in the development of targeted screening and intervention strategies to prevent and mitigate the detrimental lasting impacts perinatal anxiety and depression for birthing individuals and their children
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».