Prevalence of female genital mutilation and associated factors among women and girls in Africa: a systematic review and meta-analysis
Notice bibliographique
Résumé
Abstract Background Female genital mutilation (FGM) has zero health benefits. It can lead to short- and long-term risks and complications, including physical, sexual, and mental health and well-being of girls and women. It is a worldwide public health issue with more than 80% prevalence in Africa. It is a global imperative to strengthen work for the elimination, and the United Nations Sustainable Development Goal (SDG) strives to eliminate FGM and monitor the progress made. However, one of a challenge in tracking progress is establishing baseline prevalence data within regions and countries. Therefore, this review aimed to pool the prevalence of FGM in Africa and identify the promoting factors among women and girls. Methods This review was conducted according to the PRISMA checklist guideline. Both published and unpublished studies conducted from 2012 onwards were eligible. Studies written in non-English languages were excluded. To retrieve relevant studies; PubMed/Medline, Google Scholar, Science Direct, African Journals Online databases, and African Index Medicus (AIM) were searched using a combination of searching terms. The Newcastle-Ottawa Assessment Scale (NOS) tool was used to assess the quality of each included study. The Cochran’s Q chi-square and I2 statistical tests were used to evaluate the heterogeneity of the included studies. The Funnel plot and Egger's regression test (p value < 0.05) were used to evaluate meh publication bias. We used STATA for analysis and the overall and subgroup pooled effect size was estimated using the random effect model with DerSimonian and Laired pooled effect method. The overall prevalence of FGM and the adjusted odds ratio (AOR) with 95%CI (confidence interval) for contributing factors were calculated and presented using a forest plot. Result This study included 155 primary studies conducted on the prevalence and/or factors associated with FGM in Africa. The pooled prevalence of FGM was 56.4% (95%CI 49.7–63.6). The primary factors promoting the practice of FGM were family history of circumcision (AOR = 13.71, 95%CI 9.11−20.62), being a Muslim religion follower (AOR = 3.51, 95%CI 2.61−4.71), poor wealth index (AOR = 1.38, 95%CI1.27−1.51), higher age (AOR = 2.95, 95%CI 2.49−3.38), not attending formal education (AOR = 3.28, 95%CI 2.62−4.12), and rural residency (AOR = 2.27, 95%CI 1.84−2.80). Conclusion The prevalence of FGM in Africa was found to be high. This study also observed a variation in FGM prevalence across regions and countries and a slight temporal decline over the study period. As the global community enters the final decade dedicated to eliminating FGM, there remains much to be done to achieve the elimination goal.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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) | 0,019 | 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 ».