Perinatal mental health in low‐ and middle‐income country migrants
Notice bibliographique
Résumé
Perinatal mental health disorders negatively affect the health of the mother, fetus, child and other family members and are now recognised as one of the most common disorders of childbearing. The commonest of these, perinatal depression and anxiety, affects approximately 13% of women in high-income countries (HIC), 15–20% of women in low- and middle-income countries (LMIC), and 42% of migrant women (Collins et al. Arch Womens Ment Health 2011;14:3–11). The world is currently in a migrant crisis with millions of individuals on the move or in emergency camps fleeing conflict, violence, natural disasters or seeking a better life. In fact, the number of international migrants has grown faster than the world's population. Many migrants are vulnerable women who may be pregnant or postpartum and face serious health, economic and social challenges. Unfortunately most research on perinatal mental disorders comes from HIC. Better information is urgently needed on migrant populations, especially from LMIC. In this issue of BJOG, Fellmeth et al. (BJOG 2016;DOI: 10.1111/1471-0528.14184) provide a timely, highly relevant, methodologically strong, systematic review of the literature on migration and perinatal mental health in women originating in LMIC. They analysed 40 studies of nearly 8000 migrant women across four continents and over 11 000 comparison women and found a pooled prevalence of 31% (95% CI 23–40%) for any depressive disorder and 17% (95% CI 12–23%) for major depressive disorder. Although smaller studies have shown elevated rates for anxiety and posttraumatic stress disorder in migrant women from LMIC (Gagnon et al. Soc Sci Med 2013;76:197–207), the current study found insufficient data to assess the burden of anxiety, posttraumatic stress disorder or psychosis in four relevant studies. Overall, migrant new mothers are vulnerable to higher rates of mental health disorders than nonmigrants in the destination country. As in studies of risk factors associated with poor perinatal mental health (in nonmigrant populations), the current review found that a family or personal history of poor mental health and lack of social support were common factors. Our small study of depressed migrant new mothers in Canada found that being separated from family, social isolation, feeling overwhelmed by changes, financial worries, poor knowledge of community services and language difficulties were often problematic. However, negative attitudes of healthcare and social services staff, stigma and fear of being labelled as unfit mothers were vital barriers to seeking care (Ahmad et al. Arch Womens Ment Health 2008;11:295–303). Given that perinatal migrant women, especially from LMIC, are at high risk for mental disorders, healthcare and social-service providers, as well as policy makers, should develop best practices for their care. Most importantly perinatal healthcare providers should be sensitive to the challenges of these women. Supportive inquiries about their coping, wellbeing and mood can assist in case identification and appropriate referrals to social or mental health services. Research on specific psychosocial interventions for this vulnerable population is urgently needed; but meanwhile those found effective in other populations to improve the physical and mental health of mothers and children, should be implemented. Full disclosure of interests available to view online as supporting information. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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 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 | 0,005 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,004 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».