Prevalence and changes of intimate partner violence against women aged 15 to 49 years in 53 low-income and middle-income countries from 2000 to 2021: a secondary analysis of population-based surveys
Notice bibliographique
Résumé
BACKGROUND: In low-income and middle-income countries (LMICs), intimate partner violence poses a substantial barrier to accomplishing target 5.2 of the Sustainable Development Goals: to eliminate all forms of violence against women and girls. Our study aimed to assess the prevalence and changes of intimate partner violence against women in LMICs. We also explored the association between women's empowerment and intimate partner violence. METHODS: In this secondary analysis of population-based surveys, we obtained data from the nationally representative Demographic and Health Surveys conducted in LMICs between 2000 and 2021. We selected countries with available data on the domestic violence module, and women aged 15 to 49 years who currently or formerly had a husband or partner, and who had provided information about intimate partner violence, were included in the analysis. We first estimated the weighted prevalence of intimate partner violence in LMICs with available data, and then we assessed the average annual rate of change using Poisson regression with robust error variance in a subset of countries with at least two surveys. We used multilevel analysis to investigate the association between intimate partner violence and women's empowerment measured at both the country and individual levels. Country-level empowerment was measured by gender inequality index, while individual-level empowerment considered social independence, decision making, and attitude to violence. FINDINGS: A total of 359 479 women aged 15 to 49 years were included from 53 LMICs. 336 811 women from 21 countries with two surveys provided data for assessing the trends of intimate partner violence. The weighted prevalence of any type of intimate partner violence was 37·2% (95% CI 36·6 to 37·8). A significant overall decline in the prevalence of any type of intimate partner violence was observed with an average annual rate of change of -0·2% (95% CI -0·4 to -0·03); however six countries showed significant increasing trends, with average annual rates of change ranging from 1·2% (95% CI 0·7 to 1·7) in Nigeria to 6·6% (5·3 to 7·8) in Sierra Leone. Notably, the prevalence of psychological intimate partner violence has risen (average annual rate of change, 2·3% [95% CI 2·1 to 2·6]), reflected in increased rates across eight countries. Higher levels of country-level women's empowerment were associated with a lower risk of intimate partner violence: women from countries with the highest tertile of gender inequality index had an increased odds of any type of intimate partner violence (odds ratio 1·58 [95% CI 1·12 to 2·23]). Similarly, better individual-level women's empowerment also showed significant associations with a lower risk of intimate partner violence. INTERPRETATION: The prevalence of intimate partner violence remains high, and some countries have shown an increasing trend. The strong relationship between both country-level and individual-level women's empowerment and the prevalence of intimate partner violence suggests that accelerating women's empowerment could be one strategy to further reduce intimate partner violence against women. FUNDING: National Natural Science Foundation; Vanke School of Public Health, Tsinghua University; and Sanming Project of Medicine in Shenzhen.
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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 | 0,004 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| 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 ».