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首页> 外文期刊>International Journal of Environmental Research and Public Health >Exploring Neighborhood Influences on Small-Area Variations in Intimate Partner Violence Risk: A Bayesian Random-Effects Modeling Approach
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Exploring Neighborhood Influences on Small-Area Variations in Intimate Partner Violence Risk: A Bayesian Random-Effects Modeling Approach

机译：探索对亲密伴侣暴力风险中小范围变异的邻里影响：贝叶斯随机效应建模方法

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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.
机译：本文使用针对女性的亲密伴侣暴力案（IPVAW）的空间数据来研究邻里水平对瓦伦西亚（西班牙）市警察局中IPVAW风险的小区域变化的影响。为了分析IPVAW风险的区域变化及其与邻域级别的解释变量的关联，我们使用贝叶斯空间随机效应建模方法以及疾病映射方法来表示每个区域的风险概率。分析表明，IPVAW病例在移民集中度高，公共秩序和犯罪率高，身体疾病多的地区更可能发生。结果还显示了一个空间成分，表明可归因于空间结构随机效应的剩余可变性。贝叶斯空间建模为识别IPVAW高风险和低风险区域提供了新的视角，并为设计更全面的预防和干预策略提供了新途径。

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