The impact of COVID-19 on healthcare coverage and access in racial and ethnic minority populations in the United States.

IF 1 4区 医学 Q4 HEALTH CARE SCIENCES & SERVICES Geospatial Health Pub Date : 2023-12-27 DOI:10.4081/gh.2023.1222
Lauren Freelander, David S Rickless, Corey Anderson, Frank Curriero, Sarah Rockhill, Amir Mirsajedin, Caleb J Colón, Jasmine Lusane, Alexander Vigo-Valentín, David Wong
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Abstract

This study described spatiotemporal changes in health insurance coverage, healthcare access, and reasons for non-insurance among racial/ethnic minority populations in the United States during the COVID-19 pandemic using four national survey datasets. Getis-Ord Gi* statistic and scan statistics were used to analyze geospatial clusters of health insurance coverage by race/ethnicity. Logistic regression was used to estimate odds of reporting inability to access healthcare across two pandemic time periods by race/ethnicity. Racial/ethnic differences in insurance were observed from 2010 through 2019, with the lowest rates being among Hispanic/Latino, African American, American Indian/Alaska Native, and Native Hawaiian/Pacific Islander populations. Pre-pandemic insurance coverage rates were geographically clustered. The percentage of adults citing change in employment status as the reason for non-insurance increased by about 7% after the start of the pandemic, with a small decrease observed among African American adults. Almost half of adults reported reduced healthcare access in June 2020, with 38.7% attributing reduced access to the pandemic; however, by May 2021, the percent of respondents reporting reduced access for any reason and due to the pandemic fell to 26.9% and 12.7%, respectively. In general, racial/ethnic disparities in health insurance coverage and healthcare access worsened during the pandemic. Although coverage and access improved over time, pre-COVID disparities persisted with African American and Hispanic/Latino populations being the most affected by insurance loss and reduced healthcare access. Cost, unemployment, and eligibility drove non-insurance before and during the pandemic.

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COVID-19 对美国少数种族和少数族裔人口医疗保险和就医的影响。
本研究利用四个全国性调查数据集,描述了 COVID-19 大流行期间美国少数种族/族裔人口的健康保险覆盖率、医疗保健获取途径和不投保原因的时空变化。Getis-Ord Gi* 统计法和扫描统计法用于分析按种族/族裔划分的医疗保险覆盖率地理空间群组。逻辑回归用于估算按种族/人种划分的两个大流行时期内报告无法获得医疗保健的几率。从 2010 年到 2019 年,我们观察到了种族/族裔在保险方面的差异,其中西班牙裔/拉丁美洲人、非洲裔美国人、美国印第安人/阿拉斯加原住民和夏威夷原住民/太平洋岛民的保险率最低。大流行前的保险覆盖率呈地域性分布。大流行开始后,以就业状况改变为由不投保的成年人比例增加了约 7%,非裔美国成年人的比例略有下降。在 2020 年 6 月,几乎有一半的成年人报告医疗保健服务减少,其中 38.7% 的人将减少服务的原因归咎于大流行病;然而,到 2021 年 5 月,报告因任何原因和因大流行病而减少服务的受访者百分比分别降至 26.9% 和 12.7%。总体而言,在大流行期间,种族/民族在医疗保险覆盖率和医疗服务获得性方面的差距有所扩大。虽然随着时间的推移,保险覆盖率和获得医疗服务的机会有所改善,但 COVID 前的差距依然存在,非裔美国人和西班牙裔/拉丁美洲人受保险损失和医疗服务减少的影响最大。在大流行之前和期间,成本、失业和资格问题都是导致不投保的原因。
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来源期刊
Geospatial Health
Geospatial Health 医学-公共卫生、环境卫生与职业卫生
CiteScore
2.40
自引率
11.80%
发文量
48
审稿时长
12 months
期刊介绍: The focus of the journal is on all aspects of the application of geographical information systems, remote sensing, global positioning systems, spatial statistics and other geospatial tools in human and veterinary health. The journal publishes two issues per year.
期刊最新文献
Childhood stunting in Indonesia: assessing the performance of Bayesian spatial conditional autoregressive models. A two-stage location model covering COVID-19 sampling, transport and DNA diagnosis: design of a national scheme for infection control. The distribution of cardiovascular diseases in Tanzania: a spatio-temporal investigation. Performance of a negative binomial-GLM in spatial scan statistic: a case study of low-birth weights in Pakistan. Tuberculosis in Aceh Province, Indonesia: a spatial epidemiological study covering the period 2019-2021.
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