Key Takeaways
- IPV causes $8.3 billion in medical costs annually in US
- Victims lose 8 million workdays per year due to DV in US
- 37% of DV victims suffer physical injury requiring medical attention
- Only 34% of victims report to police
- DV arrests increased 68% from 1994-2008 due to mandatory policies
- Batterer intervention programs reduce recidivism by 33%
- 80% of male perpetrators have prior criminal records
- Alcohol abuse is a factor in 40-60% of domestic violence cases
- 25% of perpetrators have witnessed DV in their childhood
- In the United States, approximately 10 million people experience domestic violence annually
- Globally, 1 in 3 women (about 736 million) have experienced physical and/or sexual intimate partner violence or non-partner sexual violence in their lifetime
- 41% of women worldwide have experienced some form of intimate partner violence
- In the US, Black women experience IPV at 35% lifetime rate vs 29% white women
- 44% of lesbian women and 61% of bisexual women report IPV vs 35% heterosexual women
- Transgender individuals experience IPV at rates 2.5 times higher than cisgender
Domestic violence drives major health and economic harm, costing billions annually and increasing depression, suicide risk, and child exposure.
Related reading
Consequences and Impacts
Consequences and Impacts Interpretation
More related reading
Interventions and Responses
Interventions and Responses Interpretation
More related reading
Perpetrator Characteristics
Perpetrator Characteristics Interpretation
More related reading
Prevalence and Incidence
Prevalence and Incidence Interpretation
More related reading
Victim Demographics
Victim Demographics Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Lukas Bauer. (2026, February 13). Domestic.Violence Statistics. Gitnux. https://gitnux.org/domestic-violence-statistics
Lukas Bauer. "Domestic.Violence Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/domestic-violence-statistics.
Lukas Bauer. 2026. "Domestic.Violence Statistics." Gitnux. https://gitnux.org/domestic-violence-statistics.
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