Dataset Information

Socioeconomic Factors Associated With Reports of Domestic Violence in Large Brazilian Cities.

ABSTRACT: Background: Domestic violence is a traumatic experience that can lead to physical consequences, mental disorders and financial damage. Over 18 cases per 100,000 inhabitants were reported in Brazil between 2013 and 2014. The ministry of health poses a mandatory notification of all cases of domestic violence, which is essential, bearing in mind its systemic relation to various social issues and the extensive regional differences and high socioeconomic inequalities present in Brazil. Aim: To analyze the characteristics of the notification rates of domestic violence and investigate the correlation of these with health and socioeconomic characteristics of large Brazilian cities. Methods: Retrospective data on notifications of domestic violence was collected from the National Information System for Notifiable Diseases for Brazil, 2017. Dependent variables were collected from the Brazilian Institute of Geography and Statistics and Ministry of Citizenship. Inclusion criteria were: cities larger than 100.000 habitants and that had at least 20 reports, totaling 68.313 reports in 259 cities. These were stratified by age, race and sex of victim, type of violence used, violence perpetrator, place of occurrence and means of aggression. Proportional number of notified cases was calculated for each city to expose different characteristics of reports. A multiple linear regression model was used to investigate the correlation between report rates and different socioeconomic and health variables. Results: The analysis showed a high proportion of repeated violence, use of body strength and over 50% were perpetrated by a partner or boyfriend. Report rates were higher for women, black individuals and children under four, highlighting subgroups of the population that were more vulnerable. Indeed, these groups were correlated differently with socioeconomic variables. Poverty, assessed as Bolsa Família investment, was correlated with domestic violence report rates across vulnerable groups. Conclusion: The study showed that black women and children are more vulnerable to domestic violence, highlighting deleterious effects of patriarchy and structural racism within Brazilian society. Altogether, we suggest that reducing poverty, patriarchy and structural racism could lead to fewer cases of domestic violence.

SUBMITTER: Pereira MUL

PROVIDER: S-EPMC7884961 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Socioeconomic Factors Associated With Reports of Domestic Violence in Large Brazilian Cities.

Pereira Marina Uchoa Lopes MUL Gaspar Renato Simões RS

Frontiers in public health 20210201

<b>Background:</b> Domestic violence is a traumatic experience that can lead to physical consequences, mental disorders and financial damage. Over 18 cases per 100,000 inhabitants were reported in Brazil between 2013 and 2014. The ministry of health poses a mandatory notification of all cases of domestic violence, which is essential, bearing in mind its systemic relation to various social issues and the extensive regional differences and high socioeconomic inequalities present in Brazil. <b>Aim: ...[more]

PMID: 33604324

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Project description:BackgroundDomestic violence and abuse (DVA) is common and damaging to health. UK national guidance advocates a multi-agency response to DVA, and domestic homicide reviews consistently recommend improved information-sharing between agencies. Identification of patients experiencing DVA in general practice may come from external information shared with the practice, such as police incident reports and multi-agency risk assessment conference (MARAC) reports. The aim of this study was to explore the views of general practitioners (GPs) and the police about sharing reports about DVA with GPs.MethodsQualitative semi-structured interviews were conducted with GPs, police staff and a partnership manager. Participants were located across England and Wales. Thematic analysis was undertaken.ResultsInterviews were conducted with 23 GPs, six police staff and one former partnership manager. Experiences of information-sharing with GPs about DVA varied. Participants described the relevance and value of external reports to GPs to help address the health consequences of DVA and safeguard patients. They balanced competing priorities when managing this information in the electronic medical record, namely visibility to GPs versus the risk of unintended disclosure to patients. GPs also spoke of the judgements they made about exploring DVA with patients based on external reports, which varied between abusive and non-abusive adults and children. Some felt constrained by short general practice consultations. Some police and GPs reflected on a loss of control when information about DVA was shared between agencies, and the risk of unintended consequences. Both police and GPs highlighted the importance of clear information and a shared understanding about responsibility for action.ConclusionGPs regarded external reports about DVA as relevant to their role, but safely recording this information in the electronic medical record and using it to support patients required complex judgements. Both GPs and police staff emphasised the importance of clarity of information and responsibility for action when information was shared between agencies about patients affected by DVA.

Project description:BACKGROUND:The police attend numerous domestic violence events each year, recording details of these events as both structured (coded) data and unstructured free-text narratives. Abuse types (including physical, psychological, emotional, and financial) conducted by persons of interest (POIs) along with any injuries sustained by victims are typically recorded in long descriptive narratives. OBJECTIVE:We aimed to determine if an automated text mining method could identify abuse types and any injuries sustained by domestic violence victims in narratives contained in a large police dataset from the New South Wales Police Force. METHODS:We used a training set of 200 recorded domestic violence events to design a knowledge-driven approach based on syntactical patterns in the text and then applied this approach to a large set of police reports. RESULTS:Testing our approach on an evaluation set of 100 domestic violence events provided precision values of 90.2% and 85.0% for abuse type and victim injuries, respectively. In a set of 492,393 domestic violence reports, we found 71.32% (351,178) of events with mentions of the abuse type(s) and more than one-third (177,117 events; 35.97%) contained victim injuries. "Emotional/verbal abuse" (33.46%; 117,488) was the most common abuse type, followed by "punching" (86,322 events; 24.58%) and "property damage" (22.27%; 78,203 events). "Bruising" was the most common form of injury sustained (51,455 events; 29.03%), with "cut/abrasion" (28.93%; 51,284 events) and "red marks/signs" (23.71%; 42,038 events) ranking second and third, respectively. CONCLUSIONS:The results suggest that text mining can automatically extract information from police-recorded domestic violence events that can support further public health research into domestic violence, such as examining the relationship of abuse types with victim injuries and of gender and abuse types with risk escalation for victims of domestic violence. Potential also exists for this extracted information to be linked to information on the mental health status.

Dataset Information

Socioeconomic Factors Associated With Reports of Domestic Violence in Large Brazilian Cities.

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Socioeconomic Factors Associated With Reports of Domestic Violence in Large Brazilian Cities.

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