不平等的指标:探索区域层面的结构性种族主义操作化的复杂性
Joëlle Atere-Roberts1,2, Paul L Delamater2,3, Whitney R Robinson4
1Department of Epidemiology, University of North Carolina Chapel Hill, NC, USA.
SSM - population health
|August 30, 2024
概括
本研究评估了区域一级的指标来衡量结构性种族主义和健康差异. 它强调了它们在研究中的潜力和局限性,为准确的空间分析提供了方法论见解.
科学领域:
- 公共卫生 公共卫生
- 社会流行病学 社会流行病学
- 地理信息系统 (GIS) 是指地理信息系统.
背景情况:
- 结构性种族主义对人口健康状况产生重大影响.
- 区域级指标经常用于量化卫生研究中的结构性种族主义.
- 了解这些指标的实用性和局限性对于准确的研究至关重要.
研究的目的:
- 检查结构性种族主义和健康研究中使用的两种常见类型的区域级指标.
- 通过choropleth地图来评估这些指标的空间模式.
- 提供方法论考虑,并讨论使用这些指标作为结构性种族主义的代理人的前景和局限性.
主要方法:
- 利用合唱地图可视化和分析区域级指标的空间分布.
- 比较和对比了两种不同类型的区域级指标.
- 审查了关于在健康研究中应用区域级指标的现有文献.
主要成果:
- 确定了检查的区域级指标的独特空间模式.
- 展示了 choropleth 映射用于评估指标空间性的潜力.
- 突出了指标如何代表潜在的结构性种族主义的变化.
结论:
- 区域级指标为结构性种族主义提供了有价值的见解,但需要仔细考虑方法.
- 合乐图是可视化这些指标的空间模式的有效工具.
- 研究人员必须承认在卫生研究中使用区域级指标作为结构性种族主义的代理时的前景和局限性.
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