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人口普查区并非邻里社区:解决研究中历史上的红线政策对当代健康结果影响时存在的空间错位问题。

Census Tracts Are Not Neighborhoods: Addressing Spatial Misalignment in Studies Examining the Impact of Historical Redlining on Present-day Health Outcomes.

机构信息

From the Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA.

出版信息

Epidemiology. 2023 Nov 1;34(6):817-826. doi: 10.1097/EDE.0000000000001646. Epub 2023 Sep 26.

Abstract

BACKGROUND

Research examining the effects of historical redlining on present-day health outcomes is often complicated by the misalignment of contemporary census boundaries with the neighborhood boundaries drawn by the US Home Owners' Loan Corporation (HOLC) in the 1930s. Previous studies have used different approaches to assign historical HOLC grades to contemporary geographies, but how well they capture redlining exposure is unknown.

METHODS

Our analysis included 7711 residences identified in the Multiple Listing Service database in Atlanta, Georgia (2017-2022). We evaluated the classification of HOLC grade assignment (A, B, C, D, or ungraded) when assigning exposure under four area-level approaches (centroid, majority land area, weighted score, and highest HOLC) compared with using complete address data (gold standard). We additionally compared approaches across three 2020 census geographies (tract, block group, and block).

RESULTS

When comparing the use of census tracts to complete address data, sensitivity was highest for the weighted score approach, which correctly identified 77% of residences in truly A-D graded neighborhoods as compared with the majority land area (44%), centroid (54%), and highest HOLC (59%) approaches. Regarding specificity, the majority land area approach best-classified residences in truly ungraded neighborhoods (93%) as compared with the weighted score (65%), centroid (81%), and highest HOLC (54%) approaches. Classification improved regardless of approach when using census block compared with the census tract.

CONCLUSIONS

Misclassification of historical redlining exposure is inevitable when using contemporary census geographies rather than complete address data. This study provides a framework for assessing spatial misalignment and selecting an approach for classification.

摘要

背景

研究历史上的红线划定对当今健康结果的影响通常很复杂,因为当代人口普查边界与美国房主贷款公司(HOLC)在 20 世纪 30 年代绘制的社区边界不一致。以前的研究使用了不同的方法将历史 HOLC 等级分配给当代地理区域,但它们对红线暴露的捕捉程度尚不清楚。

方法

我们的分析包括佐治亚州亚特兰大市多重上市服务数据库中确定的 7711 处住宅(2017-2022 年)。我们评估了在四种区域级别方法(质心、多数土地面积、加权得分和最高 HOLC)下分配暴露程度时的 HOLC 等级分配(A、B、C、D 或未分级)的分类,与使用完整地址数据(黄金标准)相比。我们还比较了三种 2020 年人口普查地理区域(普查地段、街区组和街区)的方法。

结果

当将普查地段与完整地址数据进行比较时,加权得分方法的敏感性最高,与多数土地面积(44%)、质心(54%)和最高 HOLC(59%)方法相比,正确识别出真正 A-D 级社区中的 77%的住宅。关于特异性,与加权得分(65%)、质心(81%)和最高 HOLC(54%)方法相比,多数土地面积方法最好地分类了真正未分级社区中的住宅(93%)。无论使用哪种方法,与普查地段相比,使用普查区块都能提高分类精度。

结论

当使用当代人口普查地理区域而不是完整地址数据时,历史红线暴露的分类错误是不可避免的。本研究提供了评估空间不一致性和选择分类方法的框架。

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