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ORIGINAL RESEARCH article

Front. Public Health
Sec. Injury Prevention and Control
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1491747
This article is part of the Research Topic Geographic Information Systems in Injury Research: Bridging Spatial Science and Public Health View all articles

Study on the Current Situation and Spatial Distribution of Intimate Partner Violence among Chinese Residents

Provisionally accepted
Ruofan Zhang Ruofan Zhang 1*Ge Qu Ge Qu 1*Yuchao Sun Yuchao Sun 1*Jing Feng Jing Feng 1*Zihui Lei Zihui Lei 1*Xinyan Li Xinyan Li 1*Aoqi Shen Aoqi Shen 1*Yibo Wu Yibo Wu 2*Yanli Zuo Yanli Zuo 3*Yong Gan Yong Gan 1*
  • 1 Huazhong University of Science and Technology, Wuhan, China
  • 2 School of Public Health, Health Science Centre, Peking University, Beijing, Beijing Municipality, China
  • 3 Guangxi Medical University, Nanning, Guangxi Zhuang Region, China

The final, formatted version of the article will be published soon.

    Background: Intimate partner violence (IPV), defined as any behavior within an intimate relationship that causes physical, psychological, or sexual harm to those in the relationship, is a significant public health issue worldwide. To analyze the current status and spatial distribution patterns of IPV among residents in China, and identify the nationwide prevalence trends and regions of high severity, so as to provide a scientific basis for the formulation and implementation of government interventions.Methods: A multi-stage sampling approach was employed to conduct a psychological and behavioral survey among 31,449 residents in 148 cities across the nation from June to August 2022. IPV was measured using a self-developed scale that was specifically designed and culturally adapted for the Chinese context, and it was been categorized into psychological violence, physical violence and sexual violence. Geographic information system (GIS) technology and spatial analysis methods was applied. GeoDa 1.18, ArcGIS 10.8 and STATA 17 software were utilized for data analysis.Results: The prevalence rates of IPV among Chinese residents was 45.80%, and the prevalence rates of psychological violence, physical violence and sexual violence was 44.50%, 21.65% and 18.96%, respectively. The standard deviation plot of prevalence rates across provinces revealed that residents in Shanghai consistently had higher rates of all three categories of IPV compared to the national average level. The results of local spatial auto-correlation analysis indicated that there was a high-high clustering pattern of overall prevalence rates of IPV in Jiangxi and Zhejiang provinces, and a high-low clustering pattern was observed in Jilin, Hebei, and Ningxia provinces. The distribution pattern of intimate partner psychological violence prevalence rates showed a similar clustering pattern as the overall IPV. Additionally, there was a low-low clustering pattern of intimate partner physical violence in Anhui province, and a low-low clustering pattern of intimate partner sexual violence was identified in Anhui and Shandong provinces.Conclusion: The prevalence rates of IPV in China was relatively high, especially in Shanghai, and there was a certain degree of spatial distribution difference, which urgently needs to be paid attention to by relevant departments and institutions, especially around Zhejiang and Jiangxi in eastern China.

    Keywords: intimate partner violence, spatial distribution, GIS, spatial autocorrelation, Hotspot analisys

    Received: 05 Sep 2024; Accepted: 28 Jan 2025.

    Copyright: © 2025 Zhang, Qu, Sun, Feng, Lei, Li, Shen, Wu, Zuo and Gan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Ruofan Zhang, Huazhong University of Science and Technology, Wuhan, China
    Ge Qu, Huazhong University of Science and Technology, Wuhan, China
    Yuchao Sun, Huazhong University of Science and Technology, Wuhan, China
    Jing Feng, Huazhong University of Science and Technology, Wuhan, China
    Zihui Lei, Huazhong University of Science and Technology, Wuhan, China
    Xinyan Li, Huazhong University of Science and Technology, Wuhan, China
    Aoqi Shen, Huazhong University of Science and Technology, Wuhan, China
    Yibo Wu, School of Public Health, Health Science Centre, Peking University, Beijing, 100191, Beijing Municipality, China
    Yanli Zuo, Guangxi Medical University, Nanning, 530021, Guangxi Zhuang Region, China
    Yong Gan, Huazhong University of Science and Technology, Wuhan, China

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