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解决种族和族裔报告中的数据聚合和数据不平等问题,以及对乳腺癌差异的影响。

Addressing Data Aggregation and Data Inequity in Race and Ethnicity Reporting and the Impact on Breast Cancer Disparities.

机构信息

UT Southwestern Medical School, Dallas, TX, USA.

Miami Cancer Institute, Miami, FL, USA.

出版信息

Ann Surg Oncol. 2024 Jan;31(1):42-48. doi: 10.1245/s10434-023-14432-0. Epub 2023 Oct 15.

Abstract

Collecting and reporting data on race and ethnicity is vital to understanding and addressing health disparities in the United States. These health disparities can include increased prevalence and severity of disease, poorer health outcomes, decreased access to healthcare, etc., in disadvantaged populations compared with advantaged groups. Without these data, researchers, administrators, public health practitioners, and policymakers are unable to identify the need for targeted interventions and assistance. When researching or reporting on race and ethnicity, typically broad racial categories are used. These include White or Caucasian, Black or African American, Asian American, Native Hawaiian or Other Pacific Islander, or American Indian and Alaska Native, as well as categories for ethnicity such as Latino or Hispanic or not Latino or Hispanic. These categories, defined by the Office of Management and Budget, are the minimum standards for collecting and reporting race and ethnicity data across federal agencies. Of note, these categories have not been updated since 1997. The lack of accurate and comprehensive data on marginalized racial and ethnic groups limits our understanding of and ability to address health disparities. This has implications for breast cancer outcomes in various populations in this country. In this paper, we examine the impact data inequity and the lack of data equity centered processes have in providing appropriate prevention and intervention efforts and resource allocations.

摘要

收集和报告种族和族裔数据对于了解和解决美国的健康差异至关重要。这些健康差异可能包括疾病的发病率和严重程度增加、健康结果较差、获得医疗保健的机会减少等,在弱势群体中与优势群体相比。如果没有这些数据,研究人员、管理人员、公共卫生从业者和政策制定者就无法确定需要有针对性的干预和援助。在研究或报告种族和族裔时,通常使用广泛的种族类别。这些类别包括白种人或高加索人、非裔美国人、亚裔美国人、夏威夷原住民或其他太平洋岛民,或美洲印第安人和阿拉斯加原住民,以及族裔类别,如拉丁裔或西班牙裔或非拉丁裔或西班牙裔。这些类别由管理和预算办公室定义,是联邦机构收集和报告种族和族裔数据的最低标准。值得注意的是,自 1997 年以来,这些类别一直没有更新。边缘化的种族和族裔群体缺乏准确和全面的数据限制了我们对健康差异的理解和解决能力。这对美国不同人群的乳腺癌结局产生了影响。在本文中,我们研究了数据不平等以及缺乏以数据公平为中心的流程对提供适当的预防和干预措施以及资源分配的影响。

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