IDEAS home Printed from https://ideas.repec.org/a/eee/socmed/v380y2025ics0277953625005726.html

Neighborhoods can be sexist too: Hostile sexism and risk of intimate partner violence across city neighborhoods

Author

Listed:
  • Gracia, Enrique
  • López-Quílez, Antonio
  • Marco, Miriam
  • Escobar-Hernández, Pablo
  • Lila, Marisol

Abstract

Hostile sexism reflects prejudices and hostile attitudes toward women that may justify and facilitate intimate partner violence (IPV). The present study aimed to measure and map hostile sexism attitudes at the neighborhood level, and analyzed whether neighborhood-level hostile sexism was associated with the risk of IPV across city neighborhoods (Valencia, Spain). We used geocoded data on IPV cases (N = 2,060) aggregated at the census block group level (N = 552). Informed by a social disorganization theoretical framework, neighborhood-level covariates included administrative data on sociodemographic and contextual characteristics (i.e., income, immigrant concentration, residential instability, and social disorder and crime), and survey data on hostile sexism (N = 8,165). We conducted a small-area ecological study using Bayesian spatial modeling and disease mapping methods. Results showed the spatial clustering of neighborhood-level hostile sexism (i.e., these attitudes were not distributed equally across neighborhoods, but showed a distinctive geographical pattern), and that neighborhoods with higher levels of hostile sexism had higher relative risks of IPV, once other neighborhood-level characteristics were accounted for. This study showed that the unequal distribution of neighborhood-level hostile sexism compounded with other neighborhood characteristics (i.e., low income, high immigrant concentration, and high levels of social disorder and criminality) to explain important spatial inequalities in IPV risk across city neighborhoods. Neighborhood-level prevention efforts should consider including strategies to reduce gender biased social norms, prejudices, and hostile attitudes toward women that create a social climate that helps to justify, tolerate, and facilitate IPV.

Suggested Citation

  • Gracia, Enrique & López-Quílez, Antonio & Marco, Miriam & Escobar-Hernández, Pablo & Lila, Marisol, 2025. "Neighborhoods can be sexist too: Hostile sexism and risk of intimate partner violence across city neighborhoods," Social Science & Medicine, Elsevier, vol. 380(C).
  • Handle: RePEc:eee:socmed:v:380:y:2025:i:c:s0277953625005726
    DOI: 10.1016/j.socscimed.2025.118241
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0277953625005726
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.socscimed.2025.118241?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Seema Vyas & Lori Heise, 2016. "How do area-level socioeconomic status and gender norms affect partner violence against women? Evidence from Tanzania," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 61(8), pages 971-980, November.
    2. Anke Hoeffler, 2017. "What are the costs of violence?," Politics, Philosophy & Economics, , vol. 16(4), pages 422-445, November.
    3. Clark, Cari Jo & Ferguson, Gemma & Shrestha, Binita & Shrestha, Prabin Nanicha & Oakes, J. Michael & Gupta, Jhumka & McGhee, Susi & Cheong, Yuk Fai & Yount, Kathryn M., 2018. "Social norms and women's risk of intimate partner violence in Nepal," Social Science & Medicine, Elsevier, vol. 202(C), pages 162-169.
    4. Haining, Robert & Law, Jane & Griffith, Daniel, 2009. "Modelling small area counts in the presence of overdispersion and spatial autocorrelation," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2923-2937, June.
    5. Heise, Lori & Kotsadam, Andreas, 2015. "Cross-national and multilevel correlates of partner violence: an analysis of data from population-based surveys," MPRA Paper 123379, University Library of Munich, Germany.
    6. Julian Besag & Jeremy York & Annie Mollié, 1991. "Bayesian image restoration, with two applications in spatial statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(1), pages 1-20, March.
    7. VanderEnde, Kristin E. & Yount, Kathryn M. & Dynes, Michelle M. & Sibley, Lynn M., 2012. "Community-level correlates of intimate partner violence against women globally: A systematic review," Social Science & Medicine, Elsevier, vol. 75(7), pages 1143-1155.
    8. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
    9. United Nations UN, 2015. "Transforming our World: the 2030 Agenda for Sustainable Development," Working Papers id:7559, eSocialSciences.
    10. Enrique Gracia & Antonio López-Quílez & Miriam Marco & Marisol Lila, 2018. "Neighborhood characteristics and violence behind closed doors: The spatial overlap of child maltreatment and intimate partner violence," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-13, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Carmen Aina & Lavinia Parisi & Matteo Picchio, 2025. "Burning Rage: How Heat Shapes Gender-Based Violence," Working Papers 499, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lan Hu & Yongwan Chun & Daniel A. Griffith, 2020. "Uncovering a positive and negative spatial autocorrelation mixture pattern: a spatial analysis of breast cancer incidences in Broward County, Florida, 2000–2010," Journal of Geographical Systems, Springer, vol. 22(3), pages 291-308, July.
    2. Chien-Chou Chen & Guo-Jun Lo & Ta-Chien Chan, 2022. "Spatial Analysis on Supply and Demand of Adult Surgical Masks in Taipei Metropolitan Areas in the Early Phase of the COVID-19 Pandemic," IJERPH, MDPI, vol. 19(11), pages 1-12, May.
    3. Miriam Marco & Enrique Gracia & Antonio López-Quílez & Marisol Lila, 2021. "The Spatial Overlap of Police Calls Reporting Street-Level and Behind-Closed-Doors Crime: A Bayesian Modeling Approach," IJERPH, MDPI, vol. 18(10), pages 1-14, May.
    4. Daqian Liu & Wei Song & Chunliang Xiu & Jun Xu, 2021. "Understanding the Spatiotemporal Pattern of Crimes in Changchun, China: A Bayesian Modeling Approach," Sustainability, MDPI, vol. 13(19), pages 1-15, September.
    5. Cerqua, Augusto & Giannantoni, Costanza & Letta, Marco & Pinto, Gabriele, 2026. "Femicides, anti-violence centers, and policy targeting," European Economic Review, Elsevier, vol. 183(C).
    6. Shreosi Sanyal & Thierry Rochereau & Cara Nichole Maesano & Laure Com-Ruelle & Isabella Annesi-Maesano, 2018. "Long-Term Effect of Outdoor Air Pollution on Mortality and Morbidity: A 12-Year Follow-Up Study for Metropolitan France," IJERPH, MDPI, vol. 15(11), pages 1-8, November.
    7. Mayer Alvo & Jingrui Mu, 2023. "COVID-19 Data Analysis Using Bayesian Models and Nonparametric Geostatistical Models," Mathematics, MDPI, vol. 11(6), pages 1-13, March.
    8. Vanessa Santos-Sánchez & Juan Antonio Córdoba-Doña & Javier García-Pérez & Antonio Escolar-Pujolar & Lucia Pozzi & Rebeca Ramis, 2020. "Cancer Mortality and Deprivation in the Proximity of Polluting Industrial Facilities in an Industrial Region of Spain," IJERPH, MDPI, vol. 17(6), pages 1-15, March.
    9. Massimo Bilancia & Giacomo Demarinis, 2014. "Bayesian scanning of spatial disease rates with integrated nested Laplace approximation (INLA)," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(1), pages 71-94, March.
    10. Douglas R. M. Azevedo & Marcos O. Prates & Dipankar Bandyopadhyay, 2021. "MSPOCK: Alleviating Spatial Confounding in Multivariate Disease Mapping Models," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(3), pages 464-491, September.
    11. Bondo, Kristin J. & Rosenberry, Christopher S. & Stainbrook, David & Walter, W. David, 2024. "Comparing risk of chronic wasting disease occurrence using Bayesian hierarchical spatial models and different surveillance types," Ecological Modelling, Elsevier, vol. 493(C).
    12. Jonathan Wakefield & Taylor Okonek & Jon Pedersen, 2020. "Small Area Estimation for Disease Prevalence Mapping," International Statistical Review, International Statistical Institute, vol. 88(2), pages 398-418, August.
    13. Julien Riou & Anthony Hauser & Anna Fesser & Christian L. Althaus & Matthias Egger & Garyfallos Konstantinoudis, 2023. "Direct and indirect effects of the COVID-19 pandemic on mortality in Switzerland," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    14. Isabel Martínez-Pérez & Verónica González-Iglesias & Valentín Rodríguez Suárez & Ana Fernández-Somoano, 2021. "Spatial Distribution of Hospitalizations for Ischemic Heart Diseases in the Central Region of Asturias, Spain," IJERPH, MDPI, vol. 18(23), pages 1-10, November.
    15. Johnson, Blair T. & Sisti, Anthony & Bernstein, Mary & Chen, Kun & Hennessy, Emily A. & Acabchuk, Rebecca L. & Matos, Michaela, 2021. "Community-level factors and incidence of gun violence in the United States, 2014–2017," Social Science & Medicine, Elsevier, vol. 280(C).
    16. Maike Tahden & Juliane Manitz & Klaus Baumgardt & Gerhard Fell & Thomas Kneib & Guido Hegasy, 2016. "Epidemiological and Ecological Characterization of the EHEC O104:H4 Outbreak in Hamburg, Germany, 2011," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-19, October.
    17. Márcio Poletti Laurini, 2017. "A spatial error model with continuous random effects and an application to growth convergence," Journal of Geographical Systems, Springer, vol. 19(4), pages 371-398, October.
    18. Radka Jersakova & James Lomax & James Hetherington & Brieuc Lehmann & George Nicholson & Mark Briers & Chris Holmes, 2022. "Bayesian imputation of COVID‐19 positive test counts for nowcasting under reporting lag," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(4), pages 834-860, August.
    19. Exaverio Chireshe & Retius Chifurira & Knowledge Chinhamu & Jesca Mercy Batidzirai & Ayesha B. M. Kharsany, 2025. "Spatial Analysis of HIV Determinants Among Females Aged 15–34 in KwaZulu Natal, South Africa: A Bayesian Spatial Logistic Regression Model," IJERPH, MDPI, vol. 22(3), pages 1-25, March.
    20. repec:osf:osfxxx:39ke6_v1 is not listed on IDEAS
    21. Birgit Schrödle & Leonhard Held, 2011. "A primer on disease mapping and ecological regression using $${\texttt{INLA}}$$," Computational Statistics, Springer, vol. 26(2), pages 241-258, June.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:socmed:v:380:y:2025:i:c:s0277953625005726. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/315/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.