A Multi-site Investigation of Social Determinants of Health and SARS-CoV-2 Testing and Vaccination Outcomes among Diverse US Latinx Adults

7.项目总结 拉丁裔在美国构成了一个庞大且不断增长的人口，但在研究中通常代表不足 样本，仅限于其他种族或族裔群体的统计比较。1.获取大量、 公共卫生研究中不同的拉丁裔样本导致将拉丁裔视为一个整体，尽管已知 以及重要的群体内差异。1-5这些情况导致了量身定制的疾病 预防和控制战略1，并允许健康不平等现象持续存在，例如 在新冠肺炎大流行之前和整个过程中，拉丁裔与非拉丁裔白人相比所经历的 12，14，甚至所有其他种族-民族-性别群体。13，92 Yearby的修订后的社会健康决定因素(SDOH) 框架解释说，结构性歧视(如种族主义、种族中心主义和性别歧视)是根本原因 经济、医疗保健、教育、社会和环境分配不公的原因 人群中的SDOH，这最终导致不成比例的疾病负担。19个人持有 多重身份(例如，民族、种族、原籍国、性别、年龄、语言)，与结构 不同方式的歧视，22-24，但这些身份如何与SDOH和SARS-CoV-2检测和 拉丁裔人的疫苗接种结果尚不清楚。本提案利用Latinx身份识别参与者 数据(N=31,372)，来自10个有目的、地理位置不同的快速诊断 服务不足人群(RADx-UP)项目，以克服先前研究中的限制。具体地说，使用 目标1的池化第1层通用数据元素，我们将确定经济、 关于SARS-CoV-2检测的医疗保健获取、教育和环境SDOH(例如，参与 测试、测试通道)和疫苗接种(例如，接种状况、未接种/未接种的原因)结果 在对拉美裔美国成年人进行的大规模、稳健的个人数据元分析中。使用相同的第1层数据 目标2，我们将调查目标1模式如何随种族、原籍国、性别、年龄和语言的变化而变化。 最后，对于目标3，我们将使用第2级数据并采用比例等值数据协调技术来 审查其他与身份相关的主持人(例如，移民身份)、SDOH(例如，种族歧视、 粮食不安全)，以及更有力的检测和疫苗接种结果措施，以推进目标1和目标2 模型；并评估研究结果在多大程度上适用于全国拉丁裔人口。学习 这些发现将推进设计精确的、文化上量身定做的预防所需的经验知识基础 以及拉丁裔内部的控制战略，以减少新冠肺炎及其他地区的健康不平等现象。

7. Project Summary Latinxs comprise a large and growing population in the US, but are typically underrepresented in study samples, limiting statistical comparisons to only other racial or ethnic groups.1 Inadequate access to large, diverse samples of Latinxs in public health research has led to treating Latinxs as a monolith, despite known and important within-group differences.1–5 These conditions have led to inadequately tailored disease prevention and control strategies1 and allowed for the persistence of health inequities such as those experienced among Latinxs before and throughout the COVID-19 pandemic compared to non-Latinx Whites8– 12,14 and even to all other racial-ethnic-sex groups.13,92 Yearby's revised Social Determinants of Health (SDOH) Framework explains that structural discrimination (e.g., racism, ethnocentrism, and sexism) is the underlying cause of the inequitable distributions of economic, healthcare access, educational, social, and environmental SDOH across populations, which ultimately results in disproportionate disease burden.19 Individuals hold multiple identities (e.g., ethnic, racial, country of origin, gender, age, language) that interact with structural discrimination in distinct ways,22–24 but how these identities interact with SDOH and SARS-CoV-2 testing and vaccination outcomes within Latinxs is unknown. The present proposal harnesses Latinx-identifying participant data (N = 31,372) from 10 purposively selected, geographically diverse Rapid Acceleration of Diagnostics for Underserved Populations (RADx-UP) projects to overcome the limitations in prior research. Specifically, using pooled Tier 1 common data elements for Aim 1, we will identify the relative importance of economic, healthcare access, educational, and environmental SDOH on SARS-CoV-2 testing (e.g., engagement in testing, testing access) and vaccination (e.g., vaccination status, reasons to/to not get vaccinated) outcomes within a large, robust individual person data meta-analysis of Latinx US adults. Using the same Tier 1 data for Aim 2, we will investigate how the Aim 1 model varies by race, country of origin, gender, age, and language. Finally, for Aim 3, we will use Tier 2 data and employ scale equating data harmonization techniques to examine additional identity-related moderators (e.g., immigration status), SDOH (e.g., racial discrimination, food insecurity), and more robust measures of testing and vaccination outcomes that advance the Aim 1 and 2 models; and evaluate the degree to which the findings generalize to the national Latinx population. Study findings will advance the empirical knowledge base necessary to design precise, culturally tailored prevention and control strategies within Latinxs to reduce health inequities in COVID-19 and beyond.