In 2023, almost one out of three ever-partnered Turkish women had experienced domestic violence. In comparison, only 12 percent of women living in Switzerland had experienced domestic violence in their lifetime.

Introduction

Domestic Violence Statistics: Domestic violence is a serious and widespread issue, impacting millions of lives across the globe. Unfortunately, women across the world are still going through a tough situation due to such domestic abuse or violence, and still, even today, many women fail to report the incident.

This article includes all effective recent records of domestic violence occurrences in the U.S. and worldwide, types of violence, victim shares by countries, etc. All statistical analyses will help you effectively understand the prevalence and impact of domestic violence on communities. Here's a look at some key statistics that paint a concerning picture.

As of 2024, Timor-Leste had the highest prevalence of domestic violence against women in the Asia-Pacific region, with ** percent of women having experienced physical or sexual violence in a partnership before. In contrast, approximately *** percent of women in Singapore had experienced domestic violence as of 2024.

In 2024, gender-based violence remained a global issue. However, some populations appeared to be more at risk than others. For instance, around *** percent of women with high income aged between 30 and 34 had been subjected to physical or sexual violence in the past year. On the other hand, for women the same age but with low income, the percentage reached ****.

Canada CA: Legislation Exists on Domestic Violence: 1=Yes; 0=No data was reported at 1.000 NA in 2019. This stayed constant from the previous number of 1.000 NA for 2018. Canada CA: Legislation Exists on Domestic Violence: 1=Yes; 0=No data is updated yearly, averaging 1.000 NA from Mar 2010 (Median) to 2019, with 10 observations. The data reached an all-time high of 1.000 NA in 2019 and a record low of 1.000 NA in 2019. Canada CA: Legislation Exists on Domestic Violence: 1=Yes; 0=No data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Canada – Table CA.World Bank.WDI: Governance: Policy and Institutions. Legislation exists on domestic violence is whether there is legislation addressing domestic violence: violence between spouses, within the family or members of the same household, or in interpersonal relationships, including intimate partner violence that is subject to criminal sanctions or provides for protection orders for domestic violence, or the legislation addresses “cruel, inhuman or degrading treatment” or “harassment” that clearly affects physical or mental health, and it is implied that such behavior is considered domestic violence.; ; World Bank: Women, Business and the Law.; ;

The National Intimate Partner and Sexual Violence Survey (NISVS) is an ongoing nationally representative survey that assessed experiences of sexual violence, stalking, and intimate partner violence among adult women and men in the United States and for each individual state. The survey focused exclusively on violence and collected information about: Sexual violence by any perpetrator, including information related to rape, being made to penetrate someone else, sexual coercion, unwanted sexual contact, and non-contact unwanted sexual experiences Stalking, including the use of newer technologies such as text messages, emails, monitoring devices (e.g., cameras and GPS, or global positioning system devices), by perpetrators known and unknown to the victim Physical violence by an intimate partner Psychological aggression by an intimate partner, including information on expressive forms of aggression and coercive control Control of reproductive or sexual health by an intimate partner The NISVS project and data collection was overseen by the Centers for Disease and Prevention (CDC). The overall cost of the NISVS project was shared between the CDC, the Department of Defense (DoD) and the National Institute of Justice (NIJ). ICPSR has multiple versions of NISVS data that you can access by clicking on the links provided below.

A collection of resources on combating domestic violence, including awareness-raising campaigns, support services and trainings in the area of combating domestic violence at a national, EU and International level.

Abstract

Violence against women (VAW), in its many forms and manifestations, and across all settings, is a violation of human rights and fundamental freedoms. Around the world, many women experience violence regardless of age, class, race and ethnicity. Most of this violence is driven by the fact that they are women, and related to gender roles in society. Violence against women is predominately perpetrated by men, and most often by intimate partners. According to most recent global estimates, 35% of women aged 15 years or older globally have experienced physical and/or sexual violence during their lifetime (Devries et al., 2013; WHO, 2013). Intimate partner violence is the leading cause of homicide in women globally (Stockl et al., 2013) and has many other major short- and long-term health consequences (WHO, 2013). The economic and social costs associated with VAW are significant, and global evidence shows that violence consistently undermines development efforts at various levels, affecting physical, human and social capital (WHO, 2005). In Cambodia, the state of research on violence against women points toward widespread experiences of violence across the country (CDHS, 2012; Fulu et al., 21013). Women of all cultures and classes are subjected to many forms of physical, psychological, sexual and economic violence. This includes, but is not limited to intimate partner violence (IPV), rape and sexual assault, sexual harassment, acid violence and trafficking (MoWA, 2008). The Royal Government of Cambodia (RGC) has made a strong commitment to addressing violence against women by introducing a number of legislative and policy reforms including domestic violence legislation and a national action plan. Cambodia has demonstrated its strong commitment to promoting gender equality and ending VAW by ratifying several core international human rights conventions. In addition, there is widespread recognition among Cambodian government leaders that having quality data on the prevalence and health and other consequences of different forms of VAW is essential to increase awareness, inform evidencebased programming and policies, including the NAPVAW, and to monitor progress in the implementations of such interventions. Between 2014-2015, to fill the identified knowledge gaps, the Royal Government of Cambodia with support from the World Health Organization (WHO) and UN Women conducted a national prevalence study using the WHO multicountry study methodology. This methodology was selected because it has been widely used and is known to produce reliable data, that can be used for cross-country comparisons, and it adheres to internationally recognized ethical and safety standards.

Specific Objectives: Among specific objectives, the following deserve special mention:

ESTIMATE THE PREVALENCE AND FREQUENCY of different forms of VAW: physical, sexual, emotional and economic violence against women by intimate partners, as well as sexual and physical violence by perpetrators other than partners (in this document also referred to as ‘nonpartners’) since the age of 15, and sexual violence before the age of 15;

DETERMINE THE ASSOCIATION of physical and/or sexual intimate partner violence with a range of health and other outcomes; IDENTIFY FACTORS that may be associated with either reducing (protective factors) or increasing (risk factors) women’s risk of hysical and/or sexual intimate partner violence; DOCUMENT THE STRATEGIES and services that women use to cope with violence by an intimate partner.

INCREASE NATIONAL CAPACITY and collaboration among researchers and women’s organisations working on domestic violence;

INCREASE AWARENESS about and sensitivity to partner violence among researchers, policymakers and health care providers;

CONTRIBUTE TO THE DEVELOPMENT of a network of people committed to addressing

Geographic coverage

National

Analysis unit

Households Individuals

The data were analysed by WHO using STATA 14. Mean values, frequencies and proportions are presented with exact 95% confidence intervals for binary data. Univariate logistic regression was used and multivariable logistic models were developed to test associations between IPV and different health measures.

Universe

All resident households in Cambodia

Kind of data

Sample survey data [ssd]

Sampling procedure

• The survey sample design was developed by the NIS in the Ministry of Planning. A multi-stage sampling strategy was used based on a sampling frame that took into consideration the 24 provinces in the country delineated into a total of 225 districts for a total of 14,172 "villages" or 28,701 enumeration areas (EAs) in the country. The sample is self-weighted at the household level.

• The results achieved on VAW 2015 sampling design is already completed and describes as follows: a.Two level of survey results will be produces as: first at National level and second sub-national (Urban and Rural) b.Survey methods of VAW 2015 were designed bases on the three- stage stratified cluster sampling. b1. First stage: selected the sample Enumeration area consisting of 200 sample EAs b2. Second stage: selected the sample households consisting of 4,000 households b3. Selected the sample Women consisting of 4,000 eligible women

Mode of data collection

Face-to-face [f2f]

Cleaning operations

The questionnaire was programmed into electronic format using CAPI software, which allowed interviewers to enter the responses to questions directly into the electronic devises that were uploaded on a daily basis. Data entry was therefore not required. The software directly checked internal consistency, range and error checking, and skip patterns of the responses at the point of entering the answers during the interview. The uploaded files were aggregated at a central level and were immediately available for data analysis.

Response rate

Eligible woman response rate: 98% Household response rate: 99.5% Household refused: 0.5%

Sampling error estimates

Sample size calculations: Z (95% Confidence Interval), the value of 1.96 P = 30%. In many countries were data are available, lifetime intimate partner sexual violence often reaches 25-30% and lifetime intimate partner physical violence is 65-70%. In a normal distribution the highest variance for a factor would be at the 50% level (resulting in needing a very large sample) and the lowest variance would be at the extremes (needing the smallest sample). We compromise at 30% which is identical to assuming 70% so the resulting sample size is large, but not unmanageable. DEFF = 2. We have used this value for all the national surveys, to date. E = 0.02291. We calculate the sample size using margin of error 2.291%.

The sample size results are as follow: Confidence Level :1.96 Margin of Error (MOE): 0.02291 Baseline levels of the indicator: 0.3 Design effect (Deff): 2 Sample size (n) - Female: 3,074

United Kingdom UK: Proportion of Women Subjected to Physical and/or Sexual Violence in the Last 12 Months: % of Women Aged 15-49 data was reported at 6.000 % in 2012. United Kingdom UK: Proportion of Women Subjected to Physical and/or Sexual Violence in the Last 12 Months: % of Women Aged 15-49 data is updated yearly, averaging 6.000 % from Dec 2012 (Median) to 2012, with 1 observations. United Kingdom UK: Proportion of Women Subjected to Physical and/or Sexual Violence in the Last 12 Months: % of Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s UK – Table UK.World Bank: Health Statistics. Proportion of women subjected to physical and/or sexual violence in the last 12 months is the percentage of ever partnered women age 15-49 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in the last 12 months.; ; United Nations Statistics Division (UNSD); Weighted Average;

This data base was used for a study that examines the scope and characteristics of male-to-female intimate partner violence in southern rural Chiapas, Mexico, and its association with depression and anxiety symptoms, highlighting the role of partner controlling behaviors.Participants were selected by random sampling. One-hundred and twenty eight women >15 years participated. Data was obtained through an adapted version of the National Survey of the Dynamics of Household Relationships (ENDIREH) intimate partner violence scale, the Patient Health Questionnaire – 9 for depression symptoms and the Generalized Anxiety Disorder – 7 for anxiety symptoms. The study design followed the WHO “Ethic and Safety Recommendations for conducting research on Domestic Violence Against Women”. The protocol received ethical approval from the Institutional Review Board of the Harvard Medical School Office of Human Research Administration and the Chiapas Health Institute.Frequency of physical, sexual and controlling violent events was assessed as follows: never happened, happened once, happened sometimes, happened many times. These categories were provided in the survey and are contingent upon each respondent’s consideration. Severity of IPV (physical and sexual) was categorized as low, moderate or severe. These categories were created through a combination of the frequency of violent events and the severity of events: being kicked, tied-up, choked, attacked with a machete/knife and attacked with a gun where considered severe regardless of frequency; being pushed, pulled by the hair, slapped, hit, or have objects thrown at her where defined as follows: a) low severity when the event(s) occurred once, b) moderate severity when events happened sometimes, and c) high severity when events happened many times. Similarly, being coerced to have sex, or forced to do specific sexual activities while having sex were categorized as follows: a) low severity if it happened once, b) moderate severity if it happened sometimes, and c) severe if it happened many times. In the case of having been forced to have sex through physical force, it was considered a) moderate severity when it happened once, and b) severe when it happened more than once. IPV was labeled as low, moderate or severe based on the physical or sexual violence item that was labeled most severe for each woman.Fourteen control tactics were asked to measure CB: 1) not permitting her to work outside of home; 2) taking away her property, belongings or money; 3) not permitting her to visit her family; 4) not providing with money for basic household needs when he did have; 5) humiliating, shaming or insulting her; 6) falsely accusing her of being unfaithful; 7) frightening her or making her feel afraid of him; 8) locking her in; 9) spying or monitoring her; 10) threatening her with throwing her out of the house; 11) putting the children against her; 12) threatening her with taking the children away from her; 13) threatening her with abandoning her; 14) threatening her with killing her. Partner CB level was categorized as: a) high with more than four control tactics were reported (highest tercile), b) moderate with one to four control tactics were reported, and c) no control when no control tactics reported. High-control IPV (HC-IPV) and moderate-control IPV (MC-IPV) categories were created to reflect Johnson’s suggested categories of Intimate Terrorism and Situational Couple Violence, respectively. IPV was labeled as HC-IPV whenever a) control was high irrespective of the severity of physical or sexual violence, and b) control was moderate and severity of physical or sexual violence was high. IPV was labeled as MC-IPV when a) severity was low, and control was none or moderate, b) when severity was moderate and control none or moderate, and c) when physical or sexual violence was severe and no control tactics were reported.

The global market for domestic abuse safety apps is experiencing robust growth, projected to reach $222 million in 2025 and exhibiting a Compound Annual Growth Rate (CAGR) of 12.1% from 2025 to 2033. This expansion is driven by several key factors. Increasing awareness of domestic violence and its prevalence, coupled with improved access to smartphones and mobile technology, are making these apps increasingly accessible and vital for victims seeking help. Furthermore, the innovative features offered by these apps, such as GPS tracking, silent alerts, and evidence recording capabilities, provide crucial support and a sense of security for individuals in vulnerable situations. The market segmentation reveals a significant demand across both adult and child user demographics, with iOS and Android platforms catering to the diverse technological preferences. The competitive landscape is populated by a range of established and emerging players, each offering unique features and targeting specific user segments. Regional variations in market penetration are expected, with North America and Europe likely leading the adoption rate due to higher levels of technology penetration and social awareness campaigns. However, growth potential exists globally, particularly in developing regions with increasing smartphone adoption and improved internet infrastructure. The continued market expansion is expected to be fuelled by ongoing technological advancements, such as integration with smart home devices and improved AI-powered features for threat detection and response. However, challenges remain, including concerns about data privacy and security, potential for app misuse or malfunction, and the ongoing need for effective public awareness campaigns to increase app adoption among vulnerable populations. Addressing these challenges will be critical to unlocking the full potential of domestic abuse safety apps in providing essential support and promoting safety for victims worldwide. Furthermore, strategic partnerships between app developers, law enforcement agencies, and support organizations will play a vital role in enhancing the effectiveness and accessibility of these life-saving tools.

Portugal PT: Proportion of Women Subjected to Physical and/or Sexual Violence in the Last 12 Months: % of Women Aged 15-49 data was reported at 6.000 % in 2012. Portugal PT: Proportion of Women Subjected to Physical and/or Sexual Violence in the Last 12 Months: % of Women Aged 15-49 data is updated yearly, averaging 6.000 % from Dec 2012 (Median) to 2012, with 1 observations. Portugal PT: Proportion of Women Subjected to Physical and/or Sexual Violence in the Last 12 Months: % of Women Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Portugal – Table PT.World Bank: Health Statistics. Proportion of women subjected to physical and/or sexual violence in the last 12 months is the percentage of ever partnered women age 15-49 who are subjected to physical violence, sexual violence or both by a current or former intimate partner in the last 12 months.; ; United Nations Statistics Division (UNSD); Weighted Average;

In 2022, domestic violence was still a global issue affecting women all around the world. One of the main issues with domestic violence was the acceptance and justification of it. For instance, more than ******************** still considered a husband to be justified in beating his wife if she was to neglect the children or refuse sexual relations.

The Domestic Abuse Safety Apps market has emerged as a vital segment within the broader landscape of personal safety technology. Designed specifically to assist individuals experiencing domestic violence and abuse, these applications function as crucial lifelines, empowering users with immediate access to resources,

Users can access data related to international women’s health as well as data on population and families, education, work, power and decision making, violence against women, poverty, and environment. Background World’s Women Reports are prepared by the Statistics Division of the United Nations Department for Economic and Social Affairs (UNDESA). Reports are produced in five year intervals and began in 1990. A major theme of the reports is comparing women’s situation globally to that of men in a variety of fields. Health data is available related to life expectancy, cause of death, chronic disease, HIV/AIDS, prenatal care, maternal morbidity, reproductive health, contraceptive use, induced abortion, mortality of children under 5, and immunization. User functionality Users can download full text or specific chapter versions of the reports in color and black and white. A limited number of graphs are available for download directly from the website. Topics include obesity and underweight children. Data Notes The report and data tables are available for download in PDF format. The next report is scheduled to be released in 2015. The most recent report was released in 2010.

This data asset contains average scores on pre- and post-training tests conducted before and after PHR trainings. The Protecting Human Rights (PHR) Program works to reduce domestic violence, child marriage and related human rights abuses in 102 unions under eight upazilas of six districts. With support from USAID from March 2011 to March 2017, PHR was implemented by Plan International Bangladesh, the Bangladesh National Women Lawyers’ Association and 11 local NGOs. PHR uses an integrated and broad-based approach that includes advocacy, capacity building, access to justice, services for survivors, and mass awareness and educational projects.

United States US: Legislation Exists on Domestic Violence: 1=Yes; 0=No data was reported at 1.000 NA in 2017. This stayed constant from the previous number of 1.000 NA for 2015. United States US: Legislation Exists on Domestic Violence: 1=Yes; 0=No data is updated yearly, averaging 1.000 NA from Sep 2013 (Median) to 2017, with 3 observations. The data reached an all-time high of 1.000 NA in 2017 and a record low of 1.000 NA in 2017. United States US: Legislation Exists on Domestic Violence: 1=Yes; 0=No data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Policy and Institutions. Legislation exists on domestic violence is whether there is legislation addressing domestic violence: violence between spouses, within the family or members of the same household, or in interpersonal relationships, including intimate partner violence that is subject to criminal sanctions or provides for protection orders for domestic violence, or the legislation addresses “cruel, inhuman or degrading treatment” or “harassment” that clearly affects physical or mental health, and it is implied that such behavior is considered domestic violence.; ; World Bank: Women, Business and the Law.; ;

ABSTRACT OBJECTIVE To identify the prevalence of violence during pregnancy and the association with the socioeconomic, behavioral and clinical characteristics of pregnant women. METHODS Cross-sectional study in a low-risk maternity hospital in the municipality of Cariacica, Espírito Santo. A total of 330 puerperal women were interviewed from August to October 2017. Information on socioeconomic, behavioral, reproductive and clinical characteristics, as well as life experiences, was collected through a questionnaire. To identify the types of violence, the proper World Health Organization instrument was used. Gross bivariate and multivariate analysis was performed and adjusted for Poisson regression with robust variance. RESULTS Prevalence was 16.1% (95%CI 2.5–20.4) for psychological violence, 7.6% (95%CI 5.1–11.0) for physical violence and 2.7% (95%CI 1.4–5.2) for sexual violence. Psychological violence remained associated with age, family income, beginning of sexual life, disease in pregnancy, desire to interrupt pregnancy and number of partners. Physical violence was associated with schooling, beginning of sexual life and disease in pregnancy. Sexual violence remained associated with marital status and desire to interrupt pregnancy (p < 0.05). CONCLUSIONS Psychological violence by an intimate partner was the most prevalent among pregnant women. Women that were younger, had lower income and less schooling, who started their sexual life before the age of 14 and who wished to interrupt pregnancy, experienced violence more frequently during pregnancy.

Family and Domestic violence (FDV) is a global problem with significant social, economic, and health consequences for victims including increased health care costs, mental trauma, and social stigmatization. In Australia, the estimated annual cost of FDV is $22 billion, with one woman being murdered by a current or former partner every week. Despite this, tools that can predict future FDV based on the features of the person of interest (POI) and victim are lacking. The New South Wales Police Force attends thousands of FDV events each year and records details as fixed fields (e.g., demographic information for individuals involved in the event) and as text narratives which describe abuse types, victim injuries, threats, including the mental health status for POIs and victims. This information within the narratives is mostly untapped for research and reporting purposes. After applying a text mining methodology to extract information from 492,393 FDV event narratives (abuse types, victim injuries, mental illness mentions), we linked these characteristics with the respective fixed fields and with actual mental health diagnoses obtained from the NSW Ministry of Health for the same cohort to form a comprehensive FDV dataset. These data were input into five deep learning models (MLP, LSTM, Bi-LSTM, Bi-GRU, BERT) to predict three FDV offense types (“hands-on,” “hands-off,” “Apprehended Domestic Violence Order (ADVO) breach”). The transformer model with BERT embeddings returned the best performance (69.00% accuracy; 66.76% ROC) for “ADVO breach” in a multilabel classification setup while the binary classification setup generated similar results. “Hands-off” offenses proved the hardest offense type to predict (60.72% accuracy; 57.86% ROC using BERT) but showed potential to improve with fine-tuning of binary classification setups. “Hands-on” offenses benefitted least from the contextual information gained through BERT embeddings in which MLP with categorical embeddings outperformed it in three out of four metrics (65.95% accuracy; 78.03% F1-score; 70.00% precision). The encouraging results indicate that future FDV offenses can be predicted using deep learning on a large corpus of police and health data. Incorporating additional data sources will likely increase the performance which can assist those working on FDV and law enforcement to improve outcomes and better manage FDV events.

The number of family violence crimes in Russia reached **** thousand in 2021, falling by nearly one thousand compared to the previous year. The indicator decreased sharply between 2016 and 2017, when the country's laws decriminalized non-aggravated battery and battery within a family that resulted in no serious harm, unless it took place repeatedly. In total, over **** people became victims of domestic violence crimes in Russia in 2021.