Importance: COVID-19 racial disparities have gained significant attention yet little is known about how age distributions obscure racial-ethnic disparities in COVID-19 case fatality ratios (CFR).

Objective: We filled this gap by assessing relevant data availability and quality across states, and in states with available data, investigating how racial-ethnic disparities in CFR changed after age adjustment.

Design/setting/participants/exposure: We conducted a landscape analysis as of July 1st, 2020 and developed a grading system to assess COVID-19 case and death data by age and race in 50 states and DC. In states where age- and race-specific data were available, we applied direct age standardization to compare CFR across race-ethnicities. We developed an online dashboard to automatically and continuously update our results.

Main Outcome And Measure: Our main outcome was CFR (deaths per 100 confirmed cases). We examined CFR by age and race-ethnicities.

Results: We found substantial variations in disaggregating and reporting case and death data across states. Only three states, California, Illinois and Ohio, had sufficient age- and race-ethnicity-disaggregation to allow the investigation of racial-ethnic disparities in CFR while controlling for age. In total, we analyzed 391,991confirmed cases and 17,612 confirmed deaths. The crude CFRs varied from, e.g. 7.35% among Non-Hispanic (NH) White population to 1.39% among Hispanic population in Ohio. After age standardization, racial-ethnic differences in CFR narrowed, e.g. from 5.28% among NH White population to 3.79% among NH Asian population in Ohio, or an over one-fold difference. In addition, the ranking of race-ethnic-specific CFRs changed after age standardization. NH White population had the leading crude CFRs whereas NH Black and NH Asian population had the leading and second leading age-adjusted CFRs respectively in two of the three states. Hispanic population's age-adjusted CFR were substantially higher than the crude. Sensitivity analysis did not change these results qualitatively.

Conclusions And Relevance: The availability and quality of age- and race-ethnic-specific COVID-19 case and death data varied greatly across states. Age distributions in confirmed cases obscured racial-ethnic disparities in COVID-19 CFR. Age standardization narrows racial-ethnic disparities and changes ranking. Public COVID-19 data availability, quality, and harmonization need improvement to address racial disparities in this pandemic.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7536886PMC
http://dx.doi.org/10.1101/2020.10.01.20205377DOI Listing

Publication Analysis

Top Keywords

racial-ethnic disparities
24
age standardization
20
age
12
age distributions
12
covid-19 case
12
availability quality
12
case death
12
death data
12
white population
12
case fatality
8

Similar Publications

Background: Black women and other minorities have higher age adjusted incidence risk for cervical and endometrial cancer than White women. However, the extent of racial and ethnic disparities in clinical trial enrollment among studies performed mainly in North America and Europe for gynecologic malignancy is unknown.

Objective: This study analyzed enrollment rates by race/ethnicity in trials that led to Food and Drug Administration (FDA) approvals for gynecological cancers from 2010 to 2024.

View Article and Find Full Text PDF

Background/objectives: Urinary fluoride (UF) is the most well-established biomarker for fluoride exposure, and understanding its distribution can inform risk assessment for potential adverse systemic health effects. To our knowledge, this study is the first to report distributions of UF among youth according to sociodemographic factors in a nationally representative United States (US) sample.

Methods: The study included 1191 children aged 6-11 years and 1217 adolescents aged 12-19 years from the National Health and Nutrition Examination Survey (NHANES) 2015-2016.

View Article and Find Full Text PDF

Diet Quality, Metabolic Syndrome, and Nativity Status: Elucidating Metabolic Advantage and Disadvantage Among Non-US-Native and US-Native Populations Using NHANES Data (2013-2018).

Nutrients

January 2025

Office of Minority Health and Health Disparities Research, Georgetown Lombardi Comprehensive Cancer Center, Georgetown University, 1010 New Jersey Ave. SE, Washington, DC 20003, USA.

Background/objectives: Nutrient-poor diet quality is a major driver of the global burden of metabolic syndrome (MetS). The US ranks among the lowest in diet quality and has the highest rate of immigration, which may present unique challenges for non-US-native populations who experience changes in access to health-promoting resources. This study examined associations among MetS, nativity status, diet quality, and interaction effects of race-ethnicity among Hispanic, Asian, Black, and White US-native and non-US-native adults.

View Article and Find Full Text PDF

Layperson cardiopulmonary resuscitation (CPR) and automated external defibrillator (AED) use are vital for improving survival rates after out-of-hospital cardiac arrest (OHCA), yet their application varies by community demographics. We evaluated the concerns and factors influencing willingness to perform CPR and use AEDs among laypersons in high-risk, low-resource communities. From April 2022 to March 2024, laypersons in Northern Manhattan's Community District 12 completed surveys assessing their attitudes toward CPR and AED use before attending Hands-Only CPR training.

View Article and Find Full Text PDF

Background: Chordoma is a rare bone cancer with limited treatment options. Clinical trials are crucial for developing effective therapies, but their success depends on including diverse patient populations. The objective of this study was to systematically evaluate the reporting of racial, ethnic, and socioeconomic diversity in United States clinical trials exploring treatment for chordoma.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!