Whites' County-Level Racial Bias, COVID-19 Rates, and Racial Inequities in the United States.
Whites' County-Level Racial Bias, COVID-19 Rates, and Racial Inequities in the United States.
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DOI：
10.3390/ijerph17228695
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发表时间：
2020-11-23
影响因子：
--
通讯作者：
Vittinghoff E
中科院分区：
文献类型：
--
作者：
Thomas MD;Michaels EK;Darling-Hammond S;Nguyen TT;Glymour MM;Vittinghoff E
越来越多的证据表明，美国 (US) 2019 年冠状病毒病 (COVID-19) 的结果存在相当大的种族不平等。地区层面的种族偏见与多种不良健康结果有关，但其与 COVID-19 的关联尚未得到探索。结合非西班牙裔白人中隐性和显性反黑人偏见的隐式项目、约翰霍普金斯大学冠状病毒资源中心和《纽约时报》的县级数据，我们使用调整后的线性回归来估计截至 2020 年 7 月 1 日的总体 COVID-19 发病率和死亡率、截至 2020 年 5 月 28 日的黑人和白人发病率，以及平均地区隐性和显性种族偏见的黑人与白人发病率差距。在 2994 个县中，平均 COVID-19 死亡率（标准差）为 1.7/10,000 人 (3.3)，平均累计 COVID-19 发病率为 52.1/10,000 人 (77.2)。较高的种族偏见与较高的总体死亡率相关（每 1 个标准差较高的隐性偏见 b = 0.65/10,000（95% 置信区间：0.39, 0.91）；显性偏见 b = 0.49/10,000（0.27, 0.70））和较高的总体发病率（隐性偏见 b = 8.42/10,000（4.64， 12.20)；显性偏差 b = 8.83/10,000 (5.32, 12.35))。在 957 个拥有特定种族数据的县中，较高的种族偏见预示着较高的白人和黑人发病率，以及较大的黑人与白人发病率差距。白人中的反黑人偏见预示着 COVID-19 的结果会更糟，不平等也会加剧。地区一级的干预措施可以改善健康不平等现象。
Mounting evidence reveals considerable racial inequities in coronavirus disease 2019 (COVID-19) outcomes in the United States (US). Area-level racial bias has been associated with multiple adverse health outcomes, but its association with COVID-19 is yet unexplored. Combining county-level data from Project Implicit on implicit and explicit anti-Black bias among non-Hispanic Whites, Johns Hopkins Coronavirus Resource Center, and The New York Times, we used adjusted linear regressions to estimate overall COVID-19 incidence and mortality rates through 01 July 2020, Black and White incidence rates through 28 May 2020, and Black–White incidence rate gaps on average area-level implicit and explicit racial bias. Across 2994 counties, the average COVID-19 mortality rate (standard deviation) was 1.7/10,000 people (3.3) and average cumulative COVID-19 incidence rate was 52.1/10,000 (77.2). Higher racial bias was associated with higher overall mortality rates (per 1 standard deviation higher implicit bias b = 0.65/10,000 (95% confidence interval: 0.39, 0.91); explicit bias b = 0.49/10,000 (0.27, 0.70)) and higher overall incidence (implicit bias b = 8.42/10,000 (4.64, 12.20); explicit bias b = 8.83/10,000 (5.32, 12.35)). In 957 counties with race-specific data, higher racial bias predicted higher White and Black incidence rates, and larger Black–White incidence rate gaps. Anti-Black bias among Whites predicts worse COVID-19 outcomes and greater inequities. Area-level interventions may ameliorate health inequities.
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影响因子：
2.5
作者：
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作者：
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Calanchini, Jimmy
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Cao, Bin
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DOI：
10.1056/nejmp2023616
发表时间：
2020-09-17
期刊：
The New England journal of medicine
影响因子：
--
作者：
Egede LE;Walker RJ
通讯作者：
Walker RJ