6533b7d8fe1ef96bd126a344

RESEARCH PRODUCT

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

Enrique GraciaMarisol LilaMiriam MarcoSilvia LladosaAntonio López-quílez

subject

Domestic ViolenceHealth Toxicology and Mutagenesisintimate partner violencelcsh:MedicinePoison controlEmigrants and ImmigrantsRisk AssessmentArticleBayes' theoremsocial environmentResidence CharacteristicsBayesian spatial modelingEconometricsHumansWomenCitiesSpatial analysisPhysical disorderlcsh:RPublic Health Environmental and Occupational HealthRegression analysisBayes TheoremdisorderModels TheoreticalRandom effects modelBayesian spatial modeling; crime; disorder; immigration; intimate partner violence; neighborhoods; social environment; social disorganizationGeographySpainDomestic violenceRegression AnalysisneighborhoodsFemalesocial disorganizationCrimeRisk assessmentSocial psychologyimmigration

description

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.

10.3390/ijerph110100866http://europepmc.org/articles/PMC3924479