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Journal Article

Citation

Kothari R, Husain Z, Dutta M. J. Interpers. Violence 2022; ePub(ePub): ePub.

Copyright

(Copyright © 2022, SAGE Publishing)

DOI

10.1177/08862605221120898

PMID

36062758

Abstract

Most studies on intimate partner violence (IPV) and its drivers have focused on individual-and household-level characteristics of the victim. Recent studies have acknowledged that it is a community-level phenomenon, using spatial analytical methods to analyze community-level determinants of IPV and its geographic dimensions. Such studies provide mixed evidence on the impact of different factors and need to be supplemented by similar studies-particularly in South Asian countries where IPV is common. The present study examines district-level variations in the incidence of various forms of IPV and identifies its determinants in India, a fast-growing South Asian country with poor gender indicators. The study combines data from the National Family Health Survey, District Level Household Survey, and the decadal Census. It applies spatial analytical methods such as the Global Moran's I, Getis-ord statistic, and Multivariate Local Geary to determine the nature of the spatial distribution of different categories of IPV. Spatial regression models are used to identify the community-level predictors of each category of IPV. The study finds non-random overlapping spatial clusters in the eastern part of India. The study also finds that neighborhoods characterized by low empowerment levels, and with a high child sex ratio, road connectivity, and proportion of socially marginalized groups are more likely to exhibit high levels of all types of IPV-although the impact of these determinants varies across districts. Furthermore, spill-overs in the incidence of IPV between neighboring districts are also observed. The study concludes by recommending the use of localized policies, rather than broad national or state policies, in reducing IPV.


Language: en

Keywords

India; cultural contexts; domestic violence; geographically weighted regression model; spatial statistics

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