Date

5-20-2026

Department

School of Health Sciences

Degree

Doctor of Philosophy in Health Sciences (PhD)

Chair

Chloe Kiara Fields

Keywords

colorectal adenomas, early onset, colorectal cancer, risk stratification, smoking, young adults, epidemiology

Disciplines

Public Health

Abstract

Early-onset colorectal cancer (EOCRC) has increased among adults younger than 50 years, raising concerns regarding risk identification and screening practices in younger populations. This study examined the association between colorectal adenomas and EOCRC among adults aged 20–44 years in the United States and evaluated whether this relationship was influenced by selected demographic and behavioral factors. A cross-sectional analytic design was used to examine medical claims data from the Optum Partner Health database. The study population included 186,790 individuals aged 20–44 years who underwent colonoscopy procedures. Demographic variables included age group, sex, race/ethnicity, and body mass index (BMI). Smoking status was evaluated as a potential confounder. Logistic regression and Firth penalized likelihood models were applied to estimate crude and smoking-adjusted odds ratios (ORs) for EOCRC associated with colorectal adenomas and to assess effect modification using interaction terms. Findings did not demonstrate a statistically significant association between colorectal adenomas and EOCRC. However, these results should be interpreted with caution due to substantial group imbalance and sparse outcome events in the non-adenoma comparison group, which limited statistical power and precision. Adjustment for smoking resulted in minimal change in the effect estimate, indicating no meaningful confounding. Interaction analyses across demographic and clinical subgroups were not statistically significant, although estimates were characterized by wide confidence intervals. Smoking demonstrated a significant association in bivariate analyses but did not materially influence multivariable model results. This study continues to demonstrate the methodological challenges associated with analyzing rare outcomes using electronic medical record data and inform EO-CRC evidence-based prevention and screening strategies.

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Public Health Commons

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