Association Between Income Inequality and County-Level COVID-19 Cases and Deaths in the US.
Association Between Income Inequality and County-Level COVID-19 Cases and Deaths in the US.
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DOI：
10.1001/jamanetworkopen.2021.8799
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发表时间：
2021-05-03
影响因子：
13.8
通讯作者：
Odden MC
中科院分区：
文献类型：
--
作者：
Tan AX;Hinman JA;Abdel Magid HS;Nelson LM;Odden MC
以基尼系数衡量的县级收入不平等与 COVID-19 病例和死亡之间的关联如何随时间变化？这项生态队列研究发现，研究期间基尼系数与县级 COVID-19 病例和死亡人数呈正相关。收入不平等与 COVID-19 病例和死亡之间的关联随着时间的推移而变化，并且在 2020 年夏季最为强烈。研究结果表明，在 COVID-19 大流行期间，收入不平等较高的地区可能成为减缓 SARS-CoV-2 传播的干预措施的有效目标。社会经济边缘化社区受到 COVID-19 大流行的影响尤为严重。收入不平等可能是 SARS-CoV-2 感染和 COVID-19 死亡的危险因素。评估 2020 年 3 月至 2021 年 2 月双月时间段内县级收入不平等与 COVID-19 病例和死亡之间的关联。这项生态队列研究使用了 2020 年 3 月 1 日至 2021 年 2 月 28 日期间全国 50 个州、波多黎各和哥伦比亚特区 3220 个县的县级 COVID-19 病例和死亡的纵向数据。 2020 年 3 月 1 日至 2021 年 2 月 28 日期间县级每日 COVID-19 病例和死亡数据由马里兰州巴尔的摩约翰霍普金斯大学系统科学与工程中心从 COVID-19 数据存储库中提取。基尼系数是收入分配不平等的衡量标准（以 0 到 1 之间的值表示，其中 0 代表完全平等的地理区域，所有收入均等分享，1 代表完全不平等的社会，所有收入均由 1 个人赚取），其他县级数据主要来自 2014 年至 2018 年美国社区调查的 5 年估计。协变量包括贫困比例中位数、年龄、种族/族裔、每间房间的入住率、城市和农村、教育水平、每 100 万人拥有的医生数量、州和县级口罩使用情况。截至 2021 年 2 月 28 日，每个县平均每 100 万人中记录了 8891 例新冠肺炎 (COVID-19) 病例（四分位数范围，每 100 万人中有 6935-10 666 例病例），每 100 万人中有 156 例死亡（四分位数范围，每 100 万人中有 94-228 例死亡）。 100 000 个人）。县级基尼系数中位数为0.44（四分位距为0.42-0.47）。研究期间，基尼系数与县级 COVID-19 病例 (Spearman ρ = 0.052；P < .001) 和死亡人数 (Spearman ρ = 0.134；P < .001) 呈正相关。这种关联随着时间的推移而变化。基尼系数每增加 0.05 个单位，与调整后的 COVID-19 死亡相对风险相关：2020 年 3 月和 4 月为 1.25（95% CI，1.17-1.33）；2020 年 5 月和 6 月为 1.20（95% CI，1.13-1.28）；7 月和 8 月为 1.46（95% CI，1.37-1.55） 2020年，2020年9月和10月为1.04（95% CI，0.98-1.10），2020年11月和12月为0.76（95% CI，0.72-0.81），2021年1月和2月为1.02（95% CI，0.96-1.07）（P < .001）互动）。调整后的基尼系数与 COVID-19 病例的关联也在 2020 年 7 月和 8 月达到峰值（相对风险，1.28 [95% CI，1.22-1.33]）。这项研究表明，美国各县内的收入不平等与 2020 年夏季 COVID-19 导致的更多病例和死亡有关。COVID-19 大流行凸显了美国因收入不平等而导致的健康结果存在巨大差异。有针对性的干预措施应侧重于收入不平等领域，以拉平曲线并减轻不平等负担。本队列研究以双月时间周期评估了 2020 年 3 月至 2021 年 2 月期间县级收入不平等与 COVID-19 病例和死亡之间的关联。
How does the association between county-level income inequality, measured by the Gini coefficient, and COVID-19 cases and deaths change over time? This ecological cohort study found that there was a positive correlation between Gini coefficients and county-level COVID-19 cases and deaths during the study period. The association between income inequality and COVID-19 cases and deaths varied over time and was strongest in the summer months of 2020. The findings suggest that, during the COVID-19 pandemic, areas of higher income inequality may serve as effective targets for interventions to mitigate the spread of SARS-CoV-2. Socioeconomically marginalized communities have been disproportionately affected by the COVID-19 pandemic. Income inequality may be a risk factor for SARS-CoV-2 infection and death from COVID-19. To evaluate the association between county-level income inequality and COVID-19 cases and deaths from March 2020 through February 2021 in bimonthly time epochs. This ecological cohort study used longitudinal data on county-level COVID-19 cases and deaths from March 1, 2020, through February 28, 2021, in 3220 counties from all 50 states, Puerto Rico, and the District of Columbia. County-level daily COVID-19 case and death data from March 1, 2020, through February 28, 2021, were extracted from the COVID-19 Data Repository by the Center for Systems Science and Engineering at Johns Hopkins University in Baltimore, Maryland. The Gini coefficient, a measure of unequal income distribution (presented as a value between 0 and 1, where 0 represents a perfectly equal geographical region where all income is equally shared and 1 represents a perfectly unequal society where all income is earned by 1 individual), and other county-level data were obtained primarily from the 2014 to 2018 American Community Survey 5-year estimates. Covariates included median proportions of poverty, age, race/ethnicity, crowding given by occupancy per room, urbanicity and rurality, educational level, number of physicians per 100 000 individuals, state, and mask use at the county level. As of February 28, 2021, on average, each county recorded a median of 8891 cases of COVID-19 per 100 000 individuals (interquartile range, 6935-10 666 cases per 100 000 individuals) and 156 deaths per 100 000 individuals (interquartile range, 94-228 deaths per 100 000 individuals). The median county-level Gini coefficient was 0.44 (interquartile range, 0.42-0.47). There was a positive correlation between Gini coefficients and county-level COVID-19 cases (Spearman ρ = 0.052; P < .001) and deaths (Spearman ρ = 0.134; P < .001) during the study period. This association varied over time; each 0.05-unit increase in Gini coefficient was associated with an adjusted relative risk of COVID-19 deaths: 1.25 (95% CI, 1.17-1.33) in March and April 2020, 1.20 (95% CI, 1.13-1.28) in May and June 2020, 1.46 (95% CI, 1.37-1.55) in July and August 2020, 1.04 (95% CI, 0.98-1.10) in September and October 2020, 0.76 (95% CI, 0.72-0.81) in November and December 2020, and 1.02 (95% CI, 0.96-1.07) in January and February 2021 (P < .001 for interaction). The adjusted association of the Gini coefficient with COVID-19 cases also reached a peak in July and August 2020 (relative risk, 1.28 [95% CI, 1.22-1.33]). This study suggests that income inequality within US counties was associated with more cases and deaths due to COVID-19 in the summer months of 2020. The COVID-19 pandemic has highlighted the vast disparities that exist in health outcomes owing to income inequality in the US. Targeted interventions should be focused on areas of income inequality to both flatten the curve and lessen the burden of inequality. This cohort study evaluates the association between county-level income inequality and COVID-19 cases and deaths from March 2020 through February 2021 in bimonthly time epochs.
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发表时间：
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