Department of Social Psychology, University of Valencia, Av. Blasco Ibáñez, 21, 46010, Valencia, Spain.
Department of Social Psychology, University of Valencia, Av. Blasco Ibáñez, 21, 46010, Valencia, Spain.
Prev Med. 2021 Jul;148:106550. doi: 10.1016/j.ypmed.2021.106550. Epub 2021 Apr 20.
We conducted a small-area ecological longitudinal study to analyze neighborhood contextual influences on the spatio-temporal variations in intimate partner violence against women (IPVAW) risk in a southern European city over an eight-year period. We used geocoded data of IPVAW cases with associated protection orders (n = 5867) in the city of Valencia, Spain (2011-2018). The city's 552 census block groups were used as the neighborhood units. Neighborhood-level covariates were: income, education, immigrant concentration, residential instability, alcohol outlet density, and criminality. We used a Bayesian autoregressive approach to spatio-temporal disease mapping. Neighborhoods with low levels of income and education and high levels of residential mobility and criminality had higher relative risk of IPVAW. Spatial patterns of high risk of IPVAW persisted over time during the eight-year period analyzed. Areas of stable low risk and with increasing or decreasing risk were also identified. Our findings link neighborhood disadvantage to the existence and persistence over time of spatial inequalities in IPVAW risk, showing that high risk of IPVAW can become chronic in disadvantaged neighborhoods. Our analytic approach provides specific risk estimates at the small-area level that are informative for intervention purposes, and can be useful to assess the effectiveness of prevention efforts in reducing IPVAW.
我们进行了一项小区域生态纵向研究,以分析邻里环境对西班牙南部一城市中女性亲密伴侣暴力(IPVAW)风险的时空变化的影响,该研究持续了八年。我们使用了西班牙巴伦西亚市(2011-2018 年)与保护令相关的 IPVAW 案例的地理编码数据(n=5867)。该城市的 552 个普查街区组被用作邻里单位。邻里层面的协变量包括:收入、教育、移民集中程度、居住不稳定、酒类销售点密度和犯罪率。我们使用贝叶斯自回归方法进行时空疾病制图。收入和教育水平低、居住流动性和犯罪率高的邻里,IPVAW 的相对风险更高。在分析的八年期间,IPVAW 高风险的空间模式持续存在。还确定了稳定的低风险区以及风险增加或降低的区域。我们的研究结果将邻里劣势与 IPVAW 风险的时空不平等的存在和持续联系起来,表明高风险的 IPVAW 在劣势邻里可能会长期存在。我们的分析方法在小区域层面提供了具体的风险估计,这对干预目的很有帮助,并且可以用于评估预防工作在减少 IPVAW 方面的有效性。