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

Author

Listed:
  • Enrique Gracia

    (Department of Social Psychology, University of Valencia, Valencia 46010, Spain)

  • Antonio López-Quílez

    (Department of Statistics and Operations Research, University of Valencia, Burjassot 46100, Spain)

  • Miriam Marco

    (Department of Social Psychology, University of Valencia, Valencia 46010, Spain)

  • Silvia Lladosa

    (Department of Statistics and Operations Research, University of Valencia, Burjassot 46100, Spain)

  • Marisol Lila

    (Department of Social Psychology, University of Valencia, Valencia 46010, Spain)

Abstract

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.

Suggested Citation

  • Enrique Gracia & Antonio López-Quílez & Miriam Marco & Silvia Lladosa & Marisol Lila, 2014. "Exploring Neighborhood Influences on Small-Area Variations in Intimate Partner Violence Risk: A Bayesian Random-Effects Modeling Approach," IJERPH, MDPI, vol. 11(1), pages 1-17, January.
  • Handle: RePEc:gam:jijerp:v:11:y:2014:i:1:p:866-882:d:32038
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    References listed on IDEAS

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    1. Li, Q. & Kirby, R.S. & Sigler, R.T. & Hwang, S.-S. & LaGory, M.E. & Goldenberg, R.L., 2010. "A multilevel analysis of individual, household, and neighborhood correlates of intimate partner violence among low-income pregnant women in Jefferson County, Alabama," American Journal of Public Health, American Public Health Association, vol. 100(3), pages 531-539.
    2. O'Campo, P. & Gielen, A.C. & Faden, R.R. & Xue, X. & Kass, N. & Wang, M.-C., 1995. "Violence by male partners against women during the childbearing year: A contextual analysis," American Journal of Public Health, American Public Health Association, vol. 85(8), pages 1092-1097.
    3. J. Law, 2009. "Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology by LAWSON, A. B," Biometrics, The International Biometric Society, vol. 65(2), pages 661-662, June.
    4. Jane Law & Matthew Quick, 2013. "Exploring links between juvenile offenders and social disorganization at a large map scale: a Bayesian spatial modeling approach," Journal of Geographical Systems, Springer, vol. 15(1), pages 89-113, January.
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    Cited by:

    1. Ángel Romero-Martínez & Marisol Lila & Manuela Martínez & Vicente Pedrón-Rico & Luis Moya-Albiol, 2016. "Improvements in Empathy and Cognitive Flexibility after Court-Mandated Intervention Program in Intimate Partner Violence Perpetrators: The Role of Alcohol Abuse," IJERPH, MDPI, vol. 13(4), pages 1-13, March.
    2. Miriam Marco & Antonio López-Quílez & David Conesa & Enrique Gracia & Marisol Lila, 2017. "Spatio-Temporal Analysis of Suicide-Related Emergency Calls," IJERPH, MDPI, vol. 14(7), pages 1-13, July.
    3. Chao Song & Yaqian He & Yanchen Bo & Jinfeng Wang & Zhoupeng Ren & Huibin Yang, 2018. "Risk Assessment and Mapping of Hand, Foot, and Mouth Disease at the County Level in Mainland China Using Spatiotemporal Zero-Inflated Bayesian Hierarchical Models," IJERPH, MDPI, vol. 15(7), pages 1-16, July.

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