Violence against African migrant women living in Turin: clinical and forensic evaluation.
Paola CastagnaRossana RicciardelliFederica PiazzaGrazia MattutinoBeatrice PattarinoAntonella CanaveseSarah GinoPublished in: International journal of legal medicine (2018)
The phenomenon of migration is often related to violence and exploitation. Data collection in conflict-affected countries is hard and complicated by the lack of literature, especially on the health of migrant female victims of violence. The aim of our study has been to realise a clinical and forensic evaluation on African female migrant's global health through their admissions to the Rape Centre "Soccorso Violenza Sessuale" at Sant'Anna Hospital in Turin. In our sample, we considered several aspects such as place where the violence occurred, number and the identity of the perpetrators, use of physical restraint instruments and/or substances, kidnapping, prostitution under duress, abuses, pregnancies and outcomes, injuries and complained symptoms, female genital mutilation, and sexually transmitted diseases. The sample consisted of 143 women, of which 136 were victims of violence. In 72.8% of the episodes, the perpetrator of violence was an unknown subject. Of the women, 58.8% reported being abused in Libya, 92.6% were victims of sexual violence, and 30.2% became pregnant after sexual abuse. The physical examination of the sample showed that 34.6% of women had at least a scar and that 12.5% reported a female genital mutilation. This is the first database on health of African female migrants in Turin area collecting data on migration, violence, and physical and psychological effects of abuse.
Keyphrases
- mental health
- intimate partner violence
- polycystic ovary syndrome
- pregnancy outcomes
- healthcare
- public health
- global health
- physical activity
- type diabetes
- breast cancer risk
- pregnant women
- insulin resistance
- electronic health record
- adipose tissue
- health information
- metabolic syndrome
- depressive symptoms
- risk assessment
- big data
- skeletal muscle
- adverse drug
- acute care
- artificial intelligence