County socioeconomic status and premature mortality from cancer in the United States

Aleah L Thomas; Rachel J Kulchar; Erica S Stephens; Lee Mason; Sarah S Jackson; Alexandra R Harris; Aldenise P Ewing; Meredith S Shiels; Catherine M Pichardo; Jennifer K McGee-Avila; Wayne R Lawrence

doi:10.1016/j.canep.2025.102747

County socioeconomic status and premature mortality from cancer in the United States

Cancer Epidemiol. 2025 Jan 18:95:102747. doi: 10.1016/j.canep.2025.102747. Online ahead of print.

Affiliations

¹ Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, United States; Weill Cornell Medicine, New York, NY, United States. Electronic address: [email protected].
² Salivary Disorders Unit, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, United States; School of Dentistry, University of California Los Angeles, Los Angeles, CA, United States.
³ Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, United States.
⁴ Division of Epidemiology, College of Public Health, The Ohio State University, Columbus, OH, United States.
⁵ Division of Cancer Control and Population Sciences, NCI, NIH, Rockville, MD, United States.

PMID: 39827619
DOI: 10.1016/j.canep.2025.102747

Abstract

Introduction: There are consistent data demonstrating socioeconomic status (SES) is associated with cancer survivorship among older adults, but research on the relationship between area-level SES and risk of premature mortality from cancer remains not well understood. This study investigated the association between county-level SES and premature mortality from cancer.

Methods: Demographic characteristics and causes of death were ascertained from the national death certificate data for years 2016-2020. Premature cancer death was defined as cancer mortality between ages 25-64. County SES was calculated using the Yost Index and categorized into distribution-based quintiles (1 =lowest SES, 5=highest SES). To calculate the mortality-adjusted rate ratios (aRR) and corresponding 95 % confidence intervals (95 %CI) for the associations between county SES and cancer, we performed multivariable linear mixed models, adjusting for confounders.

Results: A total of 3143 counties were included. The age-adjusted mortality rates of all cancers combined were 107.6, 98.4, 88.6, 81.1, and 66.7 per 100,000 population for the 5 SES quintiles, respectively. Compared with high SES counties, low SES counties had a 58 % greater premature cancer mortality rate (aRR_{quintile 1 vs.}5 =1.58, 95 %CI: 1.55-1.60). Similar associations were observed when stratified by sex, though risk was greatest among men ([aRR_women=1.48, 95 %CI: 1.45-1.52]; [aRR_men=1.66, 95 %CI: 1.62-1.70]). Among leading cancer types, the association was greatest for lung cancer mortality for the lowest SES counties (aRR=2.03; 95 %CI: 1.98-2.08).

Conclusion: Our findings demonstrate that lower SES counties are at greater risk of premature mortality from cancer. Place-based interventions should target the socioeconomic environment across the cancer control continuum.

Keywords: Cancer mortality; Premature mortality; Socioeconomic status.

Published by Elsevier Ltd.