Factors Affecting Domestic Violence among Married Women in Zambia

Kusanthan, Thankian; Mwaba, Sidney O. C.; Menon, J. Anitha

doi:10.9734/bjesbs/2016/20140

Cited by 18 publications

(18 citation statements)

References 20 publications

(24 reference statements)

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“…Another study conducted on Demographic Health Survey in Ghana shows a relatively lower prevalence of domestic violence where 33.6% of women experience it at some point in their life (5). This result is comparable with a study conducted on the Zambian Demographic Health Survey where 43% of women experienced domestic violence (6).…”

Section: Introductionsupporting

confidence: 85%

Spatial Distribution and Predictors of Domestic Violence Among Women Aged 15-49 in Ethiopia: Analysis of EDHS 2016 Dataset.

Seid

Yilma

Alemu

2020

Preprint

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Introduction: Violence against women particularly that is commited by an intimate partner is becoming a social and public health problem across the world. Studies from different countries shows that the spatial variation in distribution of domestic violence was commonly attributed by neighborhood level predictors. Despite the importance of spatial techniques, studies that employ it in Ethiopia are limited. Therefore, the aim of this study is to determine the spatial distribution and predictors of domestic violence among women aged 15-49 in Ethiopia by using EDHS 2016 dataset. Methods: Secondary data from EDHS 2016 was used to determine the spatial distribution of domestic violence in Ethiopia. Spatial auto-correlation statistics (both Global and Local Moran’s I) was used to assess the spatial distribution of domestic violence cases in Ethiopia. Spatial locations of significant clusters were identified by using Kuldorff’s Sat Scan version 9.4 software. Finally, binary logistic regression and generalized linear mixed model were fitted to identify predictors of domestic violence. Result: The study found that spatial clustering of domestic violence cases in Ethiopia with Moran’s I value of 0.26, Z score of 8.26, and P-value < 0.01. The Sat Scan analysis find out 24 significant locations of domestic violence clusters. Among this, 10 are primary clusters with RR 2.18, LLR of 39.55, and P-value < 0.01. The output from regression analysis identifies low economic status, husband/partner alcohol use, witnessing family violence as a child, marital controlling behaviors, and community acceptance of wife-beating as significant predictors of domestic violence.Conclusion and Recommendation: There is spatial clustering of d domestic violence cases in Ethiopia. Areas with a high burden of the problem should get priority for intervention. Comprehensive and collaborative action should be taken by involving stakeholders at different levels. Specific activities may include Organizing media on awareness creation and continuous education on how to maintain a stable relationship between couples and employing long term and intensive effort for transforming culture and social norms that encourage violence against woman are among the major ones.

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Section: Introductionsupporting

confidence: 85%

Spatial Distribution and Predictors of Domestic Violence Among Women Aged 15-49 in Ethiopia: Analysis of EDHS 2016 Dataset.

Seid

Yilma

Alemu

2020

Preprint

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“…However, the relationship between physical violence and marital duration is culture sensitive. For example, Kusanthan et al (2016) found the opposite result among Zambian women, where the prevalence of physical violence increased with increased marital duration. Non-users of contraceptives were found to be less exposed to physical violence compared with current users.…”

Section: Discussionmentioning

confidence: 93%

Women’s Empowerment and Intimate Partner Violence in Bangladesh: Investigating the Complex Relationship

Sanawar¹,

Islam

Majumder

et al. 2018

J. Biosoc. Sci.

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The aim of this study was to assess whether women's empowerment ensures reduced intimate partner violence (IPV). The differential relationship between women's empowerment and IPV among married women in Bangladesh was investigated using 2007 Demographic and Health Survey data. Logistic regression models were used to assess whether women's empowerment had any influence on their likelihood of experiencing IPV while controlling for other covariates. The analyses revealed that older cohorts of women, who were more empowered, were more vulnerable to physical violence than less-empowered, younger women. The likelihood of being affected by physical violence among less-empowered, childless women was greater than that of more-empowered women with only male children. Less-empowered, uneducated women were more likely to experience physical violence than more-empowered, primary-educated women. Less-empowered women who had been married for less than 5 years were more likely to suffer from physical violence than more-empowered women who had been married for more than 19 years. The likelihood of experiencing sexual violence was not found to have any significant association with women's empowerment. The findings suggest that although women's empowerment in Bangladesh is gradually improving, some sub-groups of empowered women are still susceptible to IPV.

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“…According to the empirical findings obtained in the study; (i) the risk of facing physical, sexual and both physical and sexual violence by the participants who lived in the Eastern region of the country was higher than those who lived in other regions; (ii) the probability of facing physical violence in women between 43-59 years of age was higher than those of other age groups; (iii) the rate of women who received no education in terms of facing violence was higher than those from other educational levels; (iv) the probability of facing violence by women whose spouses were graduated from secondary schools was higher than those whose spouses were from other educational levels; (v) the probability of facing violence by women whose spouses worked at industrial sector was lower than the women whose spouses worked at other sectors; (vi) the increase in the frequency of alcohol use and gambling of the husband increased the probability of facing physical and sexual violence of women; (vii) the probability of facing physical, sexual and both physical and sexual violence was higher in women who think that their spouses were cheating them; (viii) the probability of facing physical and sexual violence against women who were relatives with their spouses was higher than women who were not relatives with their husbands; (ix) the probability of facing physical and sexual violence for women whose husbands did not receive any education was higher than women whose husbands were from other educational levels. Ksuthan, Mwaba and Menon (2016) conducted a study for Zambia and analyzed the factors that affected domestic violence with the Logistic Regression Model. The sampling of the study included 7146 ever married women.…”

Section: Literature Reviewmentioning

confidence: 99%

An Analysis on Domestic Violence against Women in Turkey: Multinomial Logit Model

Kızılgöl¹,

Ipek²

2018

berj

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Factors Affecting Domestic Violence among Married Women in Zambia

Cited by 18 publications

References 20 publications

Spatial Distribution and Predictors of Domestic Violence Among Women Aged 15-49 in Ethiopia: Analysis of EDHS 2016 Dataset.

Spatial Distribution and Predictors of Domestic Violence Among Women Aged 15-49 in Ethiopia: Analysis of EDHS 2016 Dataset.

Women’s Empowerment and Intimate Partner Violence in Bangladesh: Investigating the Complex Relationship

An Analysis on Domestic Violence against Women in Turkey: Multinomial Logit Model

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