使用隐性变量方法开发城市层面结构性种族主义的复合,多维测量方法
Michael Siegel1, Madeline Rieders2, Hannah Rieders2
1Department of Public Health and Community Medicine, Tufts University School of Medicine, 636 Harrison Avenue, Boston, MA, 02111, USA. Mike.Siegel@tufts.edu.
Journal of racial and ethnic health disparities
|June 29, 2023
概括
一项新的城市层面的结构性种族主义衡量结果显示,美国各地存在显著的差异. 较高的结构性种族主义与枪支杀人率的种族差异增加有关,突出了其对公共卫生的影响.
科学领域:
- 公共卫生 公共卫生
- 社会学 社会学 社会学
- 城市研究 城市研究
背景情况:
- 结构性种族主义与种族健康差异有关.
- 现有的措施不能全面捕捉城市层面的结构性种族主义.
- 城市层面的政策和机构对结构性种族主义有很大的影响.
研究的目的:
- 开发和验证一个新的,多维度的结构性种族主义在美国城市层面的测量.
- 评估结构性种族主义与种族健康差异之间的关系,特别是枪支杀人率.
主要方法:
- 确认因素分析用于在776个美国城市建模结构性种族主义.
- 该模型包含了五个维度的指标:隔离,监禁,教育,就业和经济地位.
- 为了代表城市层面的结构性种族主义,生成了因数得分,并检查了它们与枪支杀人差异的相关性.
主要成果:
- 在城市之间观察到结构性种族主义和枪支杀人种族差异的深刻差异.
- 结构性种族主义是枪支杀人事件中种族差异的重要预测因素.
- 结构性种族主义得分增加1个标准偏差与枪支杀人率比率增加1.2倍有关.
结论:
- 开发的措施为量化城市层面的结构性种族主义提供了一个新的工具.
- 研究人员可以利用这一措施来调查结构性种族主义对种族健康差异的影响.
- 调查结果强调了解决城市层面的结构因素以减少健康不平等的重要性.
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