Exploring Neighborhood Influences on Small-Area Variations in Intimate Partner Violence Risk: A Bayesian Random-Effects Modeling Approach

International Journal of Environmental Research and Public Health

Enrique Gracia¹  Antonio López-Quílez²  Miriam Marco¹  Silvia Lladosa² 

[1] Department of Social Psychology, University of Valencia, Valencia 46010, Spain; E-Mails:;Department of Statistics and Operations Research, University of Valencia, Burjassot 46100, Spain; E-Mails:

关键词: Bayesian spatial modeling;    crime;    disorder;    immigration;    intimate partner violence;    neighborhoods;    social environment;    social disorganization;   

DOI  :  10.3390/ijerph110100866

来源: mdpi

【 摘 要 】

This paper uses spatial data of cases of intimate partner violence against women (IPVAW) to examine neighborhood-level influences on small-area variations in IPVAW risk in a police district of the city of Valencia (Spain). To analyze area variations in IPVAW risk and its association with neighborhood-level explanatory variables we use a Bayesian spatial random-effects modeling approach, as well as disease mapping methods to represent risk probabilities in each area. Analyses show that IPVAW cases are more likely in areas of high immigrant concentration, high public disorder and crime, and high physical disorder. Results also show a spatial component indicating remaining variability attributable to spatially structured random effects. Bayesian spatial modeling offers a new perspective to identify IPVAW high and low risk areas, and provides a new avenue for the design of better-informed prevention and intervention strategies.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.