Socioeconomic and Demographic Determinants of Marital Violence Against Women in Palestine

The study aimed to investigate the demographic, social, and economic factors that affect the prevalence rates of marital violence against Palestinian women. The present study used survey data. The declaration of violence in Palestinian society was made in 2019 by the Palestinian Central Bureau of Statistics. The study sample consisted of 5,114 married women or formerly married women. In addition, the study used the descriptive approach to describe the demographic, social, and economic variables that affect the prevalence of marital violence against women (MVAW). Binary logistic regression was utilized to investigate the determinants of MVAW. The study concluded that young women are more susceptible to all forms of violence. An increase in the number of children in a family is correlated with higher rates of violence, and the women who are living in the Gaza Strip have elevated odds of experiencing MVAW if compared to women living in the West Bank. Women in low-income families are more susceptible to marital violence than women from affluent families. Currently, working women are less vulnerable to MVAW than their non-working counterparts. The study recommends further research and collaboration between government and non-government organizations to prevent the expansion of this problem.

Authors

Institutions

Publication Details

Journal
Journal of Population and Social Studies
Published
2024-08-09
DOI
https://doi.org/10.25133/jpssv332025.017
Citations
3
Primary Topic
Intimate Partner and Family Violence
Type
article
Field-Weighted Citation Impact
1.58
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Socioeconomic and Demographic Determinants of Marital Violence Against Women in Palestine

Mohamed Hammad Morzk, Farouk Tammam Shoaib, Noura Anwar Abdel-Fatah
3 citations
Journal of Population and Social Studies
Intimate Partner and Family Violence
1.58
article

Socioeconomic and Demographic Determinants of Marital Violence Against Women in Palestine

Mohamed Hammad Morzk, Farouk Tammam Shoaib, Noura Anwar Abdel-Fatah
article en
3 citations

Abstract

The study aimed to investigate the demographic, social, and economic factors that affect the prevalence rates of marital violence against Palestinian women. The present study used survey data. The declaration of violence in Palestinian society was made in 2019 by the Palestinian Central Bureau of Statistics. The study sample consisted of 5,114 married women or formerly married women. In addition, the study used the descriptive approach to describe the demographic, social, and economic variables that affect the prevalence of marital violence against women (MVAW). Binary logistic regression was utilized to investigate the determinants of MVAW. The study concluded that young women are more susceptible to all forms of violence. An increase in the number of children in a family is correlated with higher rates of violence, and the women who are living in the Gaza Strip have elevated odds of experiencing MVAW if compared to women living in the West Bank. Women in low-income families are more susceptible to marital violence than women from affluent families. Currently, working women are less vulnerable to MVAW than their non-working counterparts. The study recommends further research and collaboration between government and non-government organizations to prevent the expansion of this problem.

Journal of Population and Social StudiesVol. 33
Cairo University (EG)
Gender equality
Openalex Percentile: Top 16%
Intimate Partner and Family Violence
1.58
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.