Faculty, Staff and Student Publications
Publication Date
2-1-2023
Journal
Cancer Medicine
Abstract
BACKGROUND: In 2021, the U.S. Preventive Services Task Force (USPSTF) updated its recommendation to expand lung cancer screening (LCS) eligibility and mitigate disparities. Although this increased the number of non-White individuals who are eligible for LCS, the update's impact on drivers of disparities is less clear. This analysis focuses on racial disparities among Black individuals because members of this group disproportionately share late-stage lung cancer diagnoses, despite typically having a lower intensity smoking history compared to non-Hispanic White individuals.
METHODS: We used data from the National Health Interview Survey to examine the impact of the 2021 eligibility criteria on racial disparities by factors such as education, poverty, employment history, and insurance status. We also examined preventive care use and reasons for delaying medical care.
RESULTS: When comparing Black individuals and non-Hispanic White individuals, our analyses show significant differences in who would be eligible for LCS: Those who do not have a high school diploma (28.7% vs. 17.0%, p = 0.002), are in poverty (26.2% vs. 14.9%, p < 0.001), and have not worked in the past 12 months (66.5% vs. 53.9%, p = 0.009). Further, our analyses also show that more Black individuals delayed medical care due to not having transportation (11.1% vs. 3.6%, p < 0.001) compared to non-Hispanic White individuals.
CONCLUSIONS: Our results suggest that despite increasing the number of Black individuals who are eligible for LCS, the 2021 USPSTF recommendation highlights ongoing socioeconomic disparities that need to be addressed to ensure equitable access.
Keywords
Humans, Lung Neoplasms, Early Detection of Cancer, Racial Groups, Surveys and Questionnaires, Preventive Health Services, Mass Screening, cancer screening eligibility, disparities, early detection, health services research, lung cancer screening
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Medical Sciences Commons, Oncology Commons
Comments
Associated Data
PMID: 35871312