Examining Spatial Variability in the Association Between Male Partner Alcohol Misuse and Intimate Partner Violence Against Women in Ghana: A GWR Analysis

J Interpers Violence. 2021 Dec;36(23-24):NP12855-NP12874. doi: 10.1177/0886260519900299. Epub 2020 Feb 6.

Abstract

Globally, it is estimated that about 30% of ever-partnered women have experienced some form of intimate partner violence (IPV)-physical assault, sexual assault, or emotional abuse. The prevalence of IPV in sub-Saharan Africa is considerably higher than the global estimate. In Ghana, it is estimated that 24% of women have experienced physical and/or sexual IPV in their lifetime. Studies point to the association between alcohol misuse by intimate male partners and violence against women. However, there has been no consideration for potential spatial variation or heterogeneity in this association. Using estimates from the 2008 Ghana Demographic and Health Survey Data, we employed geographically weighted regression (GWR) analysis to examine spatial variations in the relationship between male partner's alcohol misuse and IPV among women in Ghana. We fitted three models to assess the relationship using a step-wise approach. The first model has alcohol misuse as the only predictor, whereas the second model included other male partner characteristics, such as post-secondary education and employment status. The final introduced female characteristics as additional covariates. The result of the GWR analysis shows that the effect of alcohol misuse on IPV is elevated in the south-western part of Ghana. The findings suggest the potential influence of place-based or contextual factors on the association between alcohol misuse and women's exposure to IPV.

Keywords: Ghana; alcohol misuse; geographically weighted regression; intimate partner violence; women.

MeSH terms

  • Alcoholism* / epidemiology
  • Cross-Sectional Studies
  • Female
  • Ghana / epidemiology
  • Humans
  • Intimate Partner Violence*
  • Male
  • Prevalence
  • Risk Factors
  • Sexual Partners
  • Spatial Regression