METHODS: Data were collected from 1,770 patients with COVID-19 admitted to an urban academic health medical center in the Chicago, Illinois area from March 2020 to April 2021. Patients were categorized as non-Hispanic White, non-Hispanic Black, NES Hispanic, and English-speaking (ES) Hispanic using NES as a proxy for English language proficiency. Multivariable logistic regression was used to compare the predicted probability for each outcome (i.e., ICU admission, intubation, and in-hospital death) by race/ethnicity.
RESULTS: After adjusting for possible confounders, NES Hispanic patients had the highest predicted probability of ICU admission (p-value < 0.05). Regarding intubation and in-hospital death, NES Hispanic patients had the highest probability, although statistical significance was inconclusive, compared to White, Black, and ES Hispanic patients.
CONCLUSIONS: Race and ethnicity, socioeconomic status, and language have demonstrated disparities in health outcomes. This study provides evidence for heterogeneity within the Hispanic population based on language proficiency that may potentially further contribute to disparities in COVID-19-related health outcomes within marginalized communities.
方法:数据来自芝加哥城市学术健康医疗中心收治的1,770名COVID-19患者,伊利诺伊州地区从2020年3月到2021年4月。患者被归类为非西班牙裔白人,非西班牙裔黑人,NES西班牙裔,和讲英语(ES)的西班牙裔使用NES作为英语语言能力的代理。多变量逻辑回归用于比较每个结果的预测概率(即,入住ICU,插管,和住院死亡)按种族/族裔划分。
结果:在调整了可能的混杂因素后,NES西班牙裔患者入住ICU的预测概率最高(p值<0.05)。关于插管和院内死亡,NES西班牙裔患者的概率最高,尽管统计学意义尚无定论,与白色相比,黑色,和ES西班牙裔患者。
结论:种族和民族,社会经济地位,和语言在健康结果方面表现出差异。这项研究提供了基于语言能力的西班牙裔人群异质性的证据,这可能进一步导致边缘化社区内与COVID-19相关的健康结果的差异。