Improving racial data equity among minority groups in South Carolina using COVID-19 as an example: application of principal components analysis.

ABSTRACT:

Background

Data inequity occurs when racial and ethnic groups are aggregated during data collection or reporting despite their differences. To demonstrate racial data equity importance, we re-analyzed South Carolina's (SC) census data and COVID-19 case-rate and death-rate distributions according to age, sex, and new combined single and multiracial categories.

Methods

The new combined single and multiracial categories included individuals who identified as a single race alone (such as American Indian or Alaska Native, AI-AN) with those who identified as more than one race (such as AI-AN and White) regardless of Hispanic or Latino heritage. We compared those distributions to the single race categories using the American Community Survey 2018-2022 and COVID-19 case and death su

SUBMITTER: Rubaiya F 

PROVIDER: S-EPMC12512368 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature